build(deps-dev): bump pandas-stubs from 2.3.2.250827 to 2.3.2.250926

Bumps [pandas-stubs](https://github.com/pandas-dev/pandas-stubs) from 2.3.2.250827 to 2.3.2.250926.
- [Changelog](https://github.com/pandas-dev/pandas-stubs/blob/main/docs/release_procedure.md)
- [Commits](https://github.com/pandas-dev/pandas-stubs/compare/v2.3.2.250827...v2.3.2.250926)

---
updated-dependencies:
- dependency-name: pandas-stubs
  dependency-version: 2.3.2.250926
  dependency-type: direct:development
  update-type: version-update:semver-patch
...

Signed-off-by: dependabot[bot] <support@github.com>

.github/workflows/docker-build.yml

@@ -7,13 +7,11 @@ on:
   push:
     branches:
       - 'main'
-      - 'feature/config-overhaul'
     tags:
       - 'v*'
   pull_request:
     branches:
-      - 'main'
+      - '**'
-      - 'feature/config-overhaul'
 
 env:
   DOCKERHUB_REPO: akkudoktor/eos
@@ -197,6 +195,7 @@ jobs:
             type=ref,event=pr
             type=semver,pattern={{version}}
             type=semver,pattern={{major}}.{{minor}}
+            type=raw,value=latest,enable={{is_default_branch}}
           labels: |
             org.opencontainers.image.licenses=${{ env.EOS_LICENSE }}
           annotations: |

.github/workflows/stale.yml

@@ -0,0 +1,35 @@
+name: "Close stale pull requests/issues"
+on:
+  schedule:
+  - cron: "16 00 * * *"
+
+permissions:
+  contents: read
+
+jobs:
+  stale:
+    name: Find Stale issues and PRs
+    runs-on: ubuntu-22.04
+    if: github.repository == 'Akkudoktor-EOS/EOS'
+    permissions:
+      pull-requests: write # to comment on stale pull requests
+      issues: write        # to comment on stale issues
+
+    steps:
+    - uses: actions/stale@5bef64f19d7facfb25b37b414482c7164d639639 # v9.1.0
+      with:
+        stale-pr-message: 'This pull request has been marked as stale because it has been open (more
+          than) 90 days with no activity. Remove the stale label or add a comment saying that you
+          would like to have the label removed otherwise this pull request will automatically be
+          closed in 30 days. Note, that you can always re-open a closed pull request at any time.'
+        stale-issue-message: 'This issue has been marked as stale because it has been open (more
+          than) 90 days with no activity. Remove the stale label or add a comment saying that you
+          would like to have the label removed otherwise this issue will automatically be closed in
+          30 days. Note, that you can always re-open a closed issue at any time.'
+        days-before-stale: 90
+        days-before-close: 30
+        stale-issue-label: 'stale'
+        stale-pr-label: 'stale'
+        exempt-pr-labels: 'in progress'
+        exempt-issue-labels: 'feature request, enhancement'
+        operations-per-run: 400

.gitignore

@@ -179,7 +179,7 @@ cython_debug/
 #  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
 #  and can be added to the global gitignore or merged into this file.  For a more nuclear
 #  option (not recommended) you can uncomment the following to ignore the entire idea folder.
-#.idea/
+.idea/
 
 # General
 .DS_Store

.gitlint

@@ -0,0 +1,35 @@
+[general]
+# verbosity should be a value between 1 and 3, the commandline -v flags take precedence over this
+verbosity = 3
+
+regex-style-search=true
+
+# Ignore rules, reference them by id or name (comma-separated)
+ignore=title-trailing-punctuation, T3
+
+# Enable specific community contributed rules
+contrib=contrib-title-conventional-commits,CC1
+
+# Set the extra-path where gitlint will search for user defined rules
+extra-path=scripts/gitlint
+
+[title-max-length]
+line-length=80
+
+[title-min-length]
+min-length=5
+
+[ignore-by-title]
+# Match commit titles starting with "Release"
+regex=^Release(.*)
+ignore=title-max-length,body-min-length
+
+[ignore-by-body]
+# Match commits message bodies that have a line that contains 'release'
+regex=(.*)release(.*)
+ignore=all
+
+[ignore-by-author-name]
+# Match commits by author name (e.g. ignore dependabot commits)
+regex=dependabot
+ignore=all

.pre-commit-config.yaml

@@ -12,12 +12,12 @@ repos:
       - id: check-merge-conflict
         exclude: '\.rst$'  # Exclude .rst files
   - repo: https://github.com/PyCQA/isort
-    rev: 5.13.2
+    rev: 6.0.0
     hooks:
       - id: isort
         name: isort
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.6.8
+    rev: v0.9.6
     hooks:
       # Run the linter and fix simple issues automatically
       - id: ruff
@@ -25,7 +25,7 @@ repos:
       # Run the formatter.
       - id: ruff-format
   - repo: https://github.com/pre-commit/mirrors-mypy
-    rev: 'v1.13.0'
+    rev: 'v1.15.0'
     hooks:
       - id: mypy
         additional_dependencies:
@@ -33,3 +33,16 @@ repos:
           - "pandas-stubs==2.2.3.241009"
           - "numpy==2.1.3"
         pass_filenames: false
+  - repo: https://github.com/jackdewinter/pymarkdown
+    rev: v0.9.29
+    hooks:
+      - id: pymarkdown
+        files: ^docs/
+        exclude: ^docs/_generated
+        args:
+          - --config=docs/pymarkdown.json
+          - scan
+  - repo: https://github.com/jorisroovers/gitlint
+    rev:  v0.19.1
+    hooks:
+      - id: gitlint

CONTRIBUTING.md

@@ -6,7 +6,7 @@ The `EOS` project is in early development, therefore we encourage contribution i
 
 ## Documentation
 
-Latest development documentation can be found at [Akkudoktor-EOS](https://akkudoktor-eos.readthedocs.io/en/main/).
+Latest development documentation can be found at [Akkudoktor-EOS](https://akkudoktor-eos.readthedocs.io/en/latest/).
 
 ## Bug Reports
 
@@ -21,8 +21,8 @@ There are just too many possibilities and the project would drown in tickets oth
 ## Code Contributions
 
 We welcome code contributions and bug fixes via [Pull Requests](https://github.com/Akkudoktor-EOS/EOS/pulls).
-To make collaboration easier, we require pull requests to pass code style and unit tests.
+To make collaboration easier, we require pull requests to pass code style, unit tests, and commit
-
+message style checks.
 
 ### Setup development environment
 
@@ -33,6 +33,7 @@ See also [README.md](README.md).
 python -m venv .venv
 source .venv/bin/activate
 pip install -r requirements-dev.txt
+pip install -e .
 ```
 
 Install make to get access to helpful shortcuts (documentation generation, manual formatting, etc.).
@@ -59,6 +60,7 @@ To run formatting automatically before every commit:
 
 ```bash
 pre-commit install
+pre-commit install --hook-type commit-msg
 ```
 
 Or run them manually:
@@ -74,3 +76,8 @@ Use `pytest` to run tests locally:
 ```bash
 python -m pytest -vs --cov src --cov-report term-missing tests/
 ```
+
+### Commit message style
+
+Our commit message checks use [`gitlint`](https://github.com/jorisroovers/gitlint). The checks
+enforce the [`Conventional Commits`](https://www.conventionalcommits.org) commit message style.

Dockerfile

@@ -1,3 +1,4 @@
+# syntax=docker/dockerfile:1.7
 ARG PYTHON_VERSION=3.12.7
 FROM python:${PYTHON_VERSION}-slim
 
@@ -9,6 +10,9 @@ ENV EOS_CACHE_DIR="${EOS_DIR}/cache"
 ENV EOS_OUTPUT_DIR="${EOS_DIR}/output"
 ENV EOS_CONFIG_DIR="${EOS_DIR}/config"
 
+# Overwrite when starting the container in a production environment
+ENV EOS_SERVER__EOSDASH_SESSKEY=s3cr3t
+
 WORKDIR ${EOS_DIR}
 
 RUN adduser --system --group --no-create-home eos \
@@ -31,6 +35,19 @@ RUN mkdir -p src && pip install -e .
 
 COPY src src
 
+# Create minimal default configuration for Docker to fix EOSDash accessibility (#629)
+# This ensures EOSDash binds to 0.0.0.0 instead of 127.0.0.1 in containers
+RUN echo '{\n\
+  "server": {\n\
+    "host": "0.0.0.0",\n\
+    "port": 8503,\n\
+    "startup_eosdash": true,\n\
+    "eosdash_host": "0.0.0.0",\n\
+    "eosdash_port": 8504\n\
+  }\n\
+}' > "${EOS_CONFIG_DIR}/EOS.config.json" \
+    && chown eos:eos "${EOS_CONFIG_DIR}/EOS.config.json"
+
 USER eos
 ENTRYPOINT []
 

Makefile

@@ -1,5 +1,5 @@
 # Define the targets
-.PHONY: help venv pip install dist test test-full docker-run docker-build docs read-docs clean format mypy run run-dev
+.PHONY: help venv pip install dist test test-full docker-run docker-build docs read-docs clean format gitlint mypy run run-dev
 
 # Default target
 all: help
@@ -11,16 +11,22 @@ help:
 	@echo "  pip          - Install dependencies from requirements.txt."
 	@echo "  pip-dev      - Install dependencies from requirements-dev.txt."
 	@echo "  format       - Format source code."
+	@echo "  gitlint      - Lint last commit message."
 	@echo "  mypy         - Run mypy."
 	@echo "  install      - Install EOS in editable form (development mode) into virtual environment."
 	@echo "  docker-run   - Run entire setup on docker"
 	@echo "  docker-build - Rebuild docker image"
 	@echo "  docs         - Generate HTML documentation (in build/docs/html/)."
 	@echo "  read-docs    - Read HTML documentation in your browser."
-	@echo "  gen-docs     - Generate openapi.json and docs/_generated/*.""
+	@echo "  gen-docs     - Generate openapi.json and docs/_generated/*."
-	@echo "  clean-docs   - Remove generated documentation.""
+	@echo "  clean-docs   - Remove generated documentation."
-	@echo "  run          - Run EOS production server in the virtual environment."
+	@echo "  run          - Run EOS production server in virtual environment."
-	@echo "  run-dev      - Run EOS development server in the virtual environment (automatically reloads)."
+	@echo "  run-dev      - Run EOS development server in virtual environment (automatically reloads)."
+	@echo "  run-dash     - Run EOSdash production server in virtual environment."
+	@echo "  run-dash-dev - Run EOSdash development server in virtual environment (automatically reloads)."
+	@echo "  test         - Run tests."
+	@echo "  test-full    - Run tests with full optimization."
+	@echo "  test-ci      - Run tests as CI does. No user config file allowed."
 	@echo "  dist         - Create distribution (in dist/)."
 	@echo "  clean        - Remove generated documentation, distribution and virtual environment."
 
@@ -70,6 +76,11 @@ read-docs: docs
 	@echo "Read the documentation in your browser"
 	.venv/bin/python -m webbrowser build/docs/html/index.html
 
+# Clean Python bytecode
+clean-bytecode:
+	find . -type d -name "__pycache__" -exec rm -r {} +
+	find . -type f -name "*.pyc" -delete
+
 # Clean target to remove generated documentation and documentation artefacts
 clean-docs:
 	@echo "Searching and deleting all '_autosum' directories in docs..."
@@ -85,11 +96,19 @@ clean: clean-docs
 
 run:
 	@echo "Starting EOS production server, please wait..."
-	.venv/bin/python src/akkudoktoreos/server/eos.py
+	.venv/bin/python -m akkudoktoreos.server.eos
 
 run-dev:
 	@echo "Starting EOS development server, please wait..."
-	.venv/bin/python src/akkudoktoreos/server/eos.py --host localhost --port 8503 --reload true
+	.venv/bin/python -m akkudoktoreos.server.eos --host localhost --port 8503 --reload true
+
+run-dash:
+	@echo "Starting EOSdash production server, please wait..."
+	.venv/bin/python -m akkudoktoreos.server.eosdash
+
+run-dash-dev:
+	@echo "Starting EOSdash development server, please wait..."
+	.venv/bin/python -m akkudoktoreos.server.eosdash --host localhost --port 8504 --reload true
 
 # Target to setup tests.
 test-setup: pip-dev
@@ -100,6 +119,11 @@ test:
 	@echo "Running tests..."
 	.venv/bin/pytest -vs --cov src --cov-report term-missing
 
+# Target to run tests as done by CI on Github.
+test-ci:
+	@echo "Running tests as CI..."
+	.venv/bin/pytest --full-run --check-config-side-effect -vs --cov src --cov-report term-missing
+
 # Target to run all tests.
 test-full:
 	@echo "Running all tests..."
@@ -109,6 +133,10 @@ test-full:
 format:
 	.venv/bin/pre-commit run --all-files
 
+# Target to trigger gitlint using pre-commit for the last commit message
+gitlint:
+	.venv/bin/pre-commit run gitlint --hook-stage commit-msg --commit-msg-filename .git/COMMIT_EDITMSG
+
 # Target to format code.
 mypy:
 	.venv/bin/mypy

README.md

@@ -8,9 +8,19 @@ Documentation can be found at [Akkudoktor-EOS](https://akkudoktor-eos.readthedoc
 
 See [CONTRIBUTING.md](CONTRIBUTING.md).
 
+## System requirements
+
+- Python >= 3.11, < 3.13
+- Architecture: amd64, aarch64 (armv8)
+- OS: Linux, Windows, macOS
+
+Note: For Python 3.13 some dependencies (e.g. [Pendulum](https://github.com/python-pendulum/Pendulum)) are not yet available on https://pypi.org and have to be manually compiled (a recent [Rust](https://www.rust-lang.org/tools/install) installation is required).
+
+Other architectures (e.g. armv6, armv7) are unsupported for now, because a multitude of dependencies are not available on https://piwheels.org and have to be built manually (a recent Rust installation and [GCC](https://gcc.gnu.org/) are required, Python 3.11 is recommended).
+
 ## Installation
 
-The project requires Python 3.10 or newer. Official docker images can be found at [akkudoktor/eos](https://hub.docker.com/r/akkudoktor/eos).
+The project requires Python 3.11 or newer. Docker images (amd64/aarch64) can be found at [akkudoktor/eos](https://hub.docker.com/r/akkudoktor/eos).
 
 Following sections describe how to locally start the EOS server on `http://localhost:8503`.
 
@@ -23,16 +33,19 @@ Linux:
 ```bash
 python -m venv .venv
 .venv/bin/pip install -r requirements.txt
+.venv/bin/pip install -e .
 ```
 
 Windows:
 
 ```cmd
 python -m venv .venv
+.venv\Scripts\Activate
 .venv\Scripts\pip install -r requirements.txt
+.venv\Scripts\pip install -e .
 ```
 
-Finally, start the EOS server:
+Finally, start the EOS server to access it at `http://localhost:8503` (API docs at `http://localhost:8503/docs`):
 
 Linux:
 
@@ -48,6 +61,8 @@ Windows:
 
 ### Docker
 
+Start EOS with following command to access it at `http://localhost:8503` (API docs at `http://localhost:8503/docs`):
+
 ```bash
 docker compose up
 ```

docker-compose.yaml

@@ -21,5 +21,25 @@ services:
       - EOS_ELECPRICE__PROVIDER=ElecPriceAkkudoktor
       - EOS_ELECPRICE__CHARGES_KWH=0.21
     ports:
-      - "${EOS_SERVER__PORT}:${EOS_SERVER__PORT}"
+      # Configure what ports to expose on host
-      - "${EOS_SERVER__EOSDASH_PORT}:${EOS_SERVER__EOSDASH_PORT}"
+      - "${EOS_SERVER__PORT}:8503"
+      - "${EOS_SERVER__EOSDASH_PORT}:8504"
+
+    # Volume mount configuration (optional)
+    # IMPORTANT: When mounting local directories, the default config won't be available.
+    # You must create an EOS.config.json file in your local config directory with:
+    # {
+    #   "server": {
+    #     "host": "0.0.0.0",        # Required for Docker container accessibility
+    #     "port": 8503,
+    #     "startup_eosdash": true,
+    #     "eosdash_host": "0.0.0.0", # Required for Docker container accessibility
+    #     "eosdash_port": 8504
+    #   }
+    # }
+    #
+    # Example volume mounts (uncomment to use):
+    # volumes:
+    #   - ./config:/opt/eos/config     # Mount local config directory
+    #   - ./cache:/opt/eos/cache       # Mount local cache directory
+    #   - ./output:/opt/eos/output     # Mount local output directory

docs/_generated/config.md

@@ -15,10 +15,6 @@ Properties:
     timezone (Optional[str]): Computed time zone string based on the specified latitude
         and longitude.
 
-Validators:
-    validate_latitude (float): Ensures `latitude` is within the range -90 to 90.
-    validate_longitude (float): Ensures `longitude` is within the range -180 to 180.
-
 :::{table} general
 :widths: 10 20 10 5 5 30
 :align: left
@@ -27,12 +23,10 @@ Validators:
 | ---- | -------------------- | ---- | --------- | ------- | ----------- |
 | data_folder_path | `EOS_GENERAL__DATA_FOLDER_PATH` | `Optional[pathlib.Path]` | `rw` | `None` | Path to EOS data directory. |
 | data_output_subpath | `EOS_GENERAL__DATA_OUTPUT_SUBPATH` | `Optional[pathlib.Path]` | `rw` | `output` | Sub-path for the EOS output data directory. |
-| data_cache_subpath | `EOS_GENERAL__DATA_CACHE_SUBPATH` | `Optional[pathlib.Path]` | `rw` | `cache` | Sub-path for the EOS cache data directory. |
 | latitude | `EOS_GENERAL__LATITUDE` | `Optional[float]` | `rw` | `52.52` | Latitude in decimal degrees, between -90 and 90, north is positive (ISO 19115) (°) |
 | longitude | `EOS_GENERAL__LONGITUDE` | `Optional[float]` | `rw` | `13.405` | Longitude in decimal degrees, within -180 to 180 (°) |
 | timezone | | `Optional[str]` | `ro` | `N/A` | Compute timezone based on latitude and longitude. |
 | data_output_path | | `Optional[pathlib.Path]` | `ro` | `N/A` | Compute data_output_path based on data_folder_path. |
-| data_cache_path | | `Optional[pathlib.Path]` | `ro` | `N/A` | Compute data_cache_path based on data_folder_path. |
 | config_folder_path | | `Optional[pathlib.Path]` | `ro` | `N/A` | Path to EOS configuration directory. |
 | config_file_path | | `Optional[pathlib.Path]` | `ro` | `N/A` | Path to EOS configuration file. |
 :::
@@ -46,7 +40,6 @@ Validators:
        "general": {
            "data_folder_path": null,
            "data_output_subpath": "output",
-           "data_cache_subpath": "cache",
            "latitude": 52.52,
            "longitude": 13.405
        }
@@ -62,18 +55,66 @@ Validators:
        "general": {
            "data_folder_path": null,
            "data_output_subpath": "output",
-           "data_cache_subpath": "cache",
            "latitude": 52.52,
            "longitude": 13.405,
            "timezone": "Europe/Berlin",
            "data_output_path": null,
-           "data_cache_path": null,
            "config_folder_path": "/home/user/.config/net.akkudoktoreos.net",
            "config_file_path": "/home/user/.config/net.akkudoktoreos.net/EOS.config.json"
        }
    }
 ```
 
+## Cache Configuration
+
+:::{table} cache
+:widths: 10 20 10 5 5 30
+:align: left
+
+| Name | Environment Variable | Type | Read-Only | Default | Description |
+| ---- | -------------------- | ---- | --------- | ------- | ----------- |
+| subpath | `EOS_CACHE__SUBPATH` | `Optional[pathlib.Path]` | `rw` | `cache` | Sub-path for the EOS cache data directory. |
+| cleanup_interval | `EOS_CACHE__CLEANUP_INTERVAL` | `float` | `rw` | `300` | Intervall in seconds for EOS file cache cleanup. |
+:::
+
+### Example Input/Output
+
+```{eval-rst}
+.. code-block:: json
+
+   {
+       "cache": {
+           "subpath": "cache",
+           "cleanup_interval": 300.0
+       }
+   }
+```
+
+## Energy Management Configuration
+
+:::{table} ems
+:widths: 10 20 10 5 5 30
+:align: left
+
+| Name | Environment Variable | Type | Read-Only | Default | Description |
+| ---- | -------------------- | ---- | --------- | ------- | ----------- |
+| startup_delay | `EOS_EMS__STARTUP_DELAY` | `float` | `rw` | `5` | Startup delay in seconds for EOS energy management runs. |
+| interval | `EOS_EMS__INTERVAL` | `Optional[float]` | `rw` | `None` | Intervall in seconds between EOS energy management runs. |
+:::
+
+### Example Input/Output
+
+```{eval-rst}
+.. code-block:: json
+
+   {
+       "ems": {
+           "startup_delay": 5.0,
+           "interval": 300.0
+       }
+   }
+```
+
 ## Logging Configuration
 
 :::{table} logging
@@ -82,8 +123,10 @@ Validators:
 
 | Name | Environment Variable | Type | Read-Only | Default | Description |
 | ---- | -------------------- | ---- | --------- | ------- | ----------- |
-| level | `EOS_LOGGING__LEVEL` | `Optional[str]` | `rw` | `None` | EOS default logging level. |
+| level | `EOS_LOGGING__LEVEL` | `Optional[str]` | `rw` | `None` | This is deprecated. Use console_level and file_level instead. |
-| root_level | | `str` | `ro` | `N/A` | Root logger logging level. |
+| console_level | `EOS_LOGGING__CONSOLE_LEVEL` | `Optional[str]` | `rw` | `None` | Logging level when logging to console. |
+| file_level | `EOS_LOGGING__FILE_LEVEL` | `Optional[str]` | `rw` | `None` | Logging level when logging to file. |
+| file_path | | `Optional[pathlib.Path]` | `ro` | `N/A` | Computed log file path based on data output path. |
 :::
 
 ### Example Input
@@ -93,7 +136,9 @@ Validators:
 
    {
        "logging": {
-           "level": "INFO"
+           "level": null,
+           "console_level": "TRACE",
+           "file_level": "TRACE"
        }
    }
 ```
@@ -105,8 +150,10 @@ Validators:
 
    {
        "logging": {
-           "level": "INFO",
+           "level": null,
-           "root_level": "INFO"
+           "console_level": "TRACE",
+           "file_level": "TRACE",
+           "file_path": "/home/user/.local/share/net.akkudoktoreos.net/output/eos.log"
        }
    }
 ```
@@ -377,6 +424,7 @@ Validators:
 | ---- | -------------------- | ---- | --------- | ------- | ----------- |
 | provider | `EOS_ELECPRICE__PROVIDER` | `Optional[str]` | `rw` | `None` | Electricity price provider id of provider to be used. |
 | charges_kwh | `EOS_ELECPRICE__CHARGES_KWH` | `Optional[float]` | `rw` | `None` | Electricity price charges (€/kWh). |
+| vat_rate | `EOS_ELECPRICE__VAT_RATE` | `Optional[float]` | `rw` | `1.19` | VAT rate factor applied to electricity price when charges are used. |
 | provider_settings | `EOS_ELECPRICE__PROVIDER_SETTINGS` | `Optional[akkudoktoreos.prediction.elecpriceimport.ElecPriceImportCommonSettings]` | `rw` | `None` | Provider settings |
 :::
 
@@ -389,6 +437,7 @@ Validators:
        "elecprice": {
            "provider": "ElecPriceAkkudoktor",
            "charges_kwh": 0.21,
+           "vat_rate": 1.19,
            "provider_settings": null
        }
    }
@@ -430,7 +479,7 @@ Validators:
 | Name | Environment Variable | Type | Read-Only | Default | Description |
 | ---- | -------------------- | ---- | --------- | ------- | ----------- |
 | provider | `EOS_LOAD__PROVIDER` | `Optional[str]` | `rw` | `None` | Load provider id of provider to be used. |
-| provider_settings | `EOS_LOAD__PROVIDER_SETTINGS` | `Union[akkudoktoreos.prediction.loadakkudoktor.LoadAkkudoktorCommonSettings, akkudoktoreos.prediction.loadimport.LoadImportCommonSettings, NoneType]` | `rw` | `None` | Provider settings |
+| provider_settings | `EOS_LOAD__PROVIDER_SETTINGS` | `Union[akkudoktoreos.prediction.loadakkudoktor.LoadAkkudoktorCommonSettings, akkudoktoreos.prediction.loadvrm.LoadVrmCommonSettings, akkudoktoreos.prediction.loadimport.LoadImportCommonSettings, NoneType]` | `rw` | `None` | Provider settings |
 :::
 
 ### Example Input/Output
@@ -473,6 +522,33 @@ Validators:
    }
 ```
 
+### Common settings for VRM API
+
+:::{table} load::provider_settings
+:widths: 10 10 5 5 30
+:align: left
+
+| Name | Type | Read-Only | Default | Description |
+| ---- | ---- | --------- | ------- | ----------- |
+| load_vrm_token | `str` | `rw` | `your-token` | Token for Connecting VRM API |
+| load_vrm_idsite | `int` | `rw` | `12345` | VRM-Installation-ID |
+:::
+
+#### Example Input/Output
+
+```{eval-rst}
+.. code-block:: json
+
+   {
+       "load": {
+           "provider_settings": {
+               "load_vrm_token": "your-token",
+               "load_vrm_idsite": 12345
+           }
+       }
+   }
+```
+
 ### Common settings for load data import from file
 
 :::{table} load::provider_settings
@@ -507,8 +583,9 @@ Validators:
 | Name | Environment Variable | Type | Read-Only | Default | Description |
 | ---- | -------------------- | ---- | --------- | ------- | ----------- |
 | provider | `EOS_PVFORECAST__PROVIDER` | `Optional[str]` | `rw` | `None` | PVForecast provider id of provider to be used. |
+| provider_settings | `EOS_PVFORECAST__PROVIDER_SETTINGS` | `Union[akkudoktoreos.prediction.pvforecastimport.PVForecastImportCommonSettings, akkudoktoreos.prediction.pvforecastvrm.PVforecastVrmCommonSettings, NoneType]` | `rw` | `None` | Provider settings |
 | planes | `EOS_PVFORECAST__PLANES` | `Optional[list[akkudoktoreos.prediction.pvforecast.PVForecastPlaneSetting]]` | `rw` | `None` | Plane configuration. |
-| provider_settings | `EOS_PVFORECAST__PROVIDER_SETTINGS` | `Optional[akkudoktoreos.prediction.pvforecastimport.PVForecastImportCommonSettings]` | `rw` | `None` | Provider settings |
+| max_planes | `EOS_PVFORECAST__MAX_PLANES` | `Optional[int]` | `rw` | `0` | Maximum number of planes that can be set |
 | planes_peakpower | | `List[float]` | `ro` | `N/A` | Compute a list of the peak power per active planes. |
 | planes_azimuth | | `List[float]` | `ro` | `N/A` | Compute a list of the azimuths per active planes. |
 | planes_tilt | | `List[float]` | `ro` | `N/A` | Compute a list of the tilts per active planes. |
@@ -524,10 +601,11 @@ Validators:
    {
        "pvforecast": {
            "provider": "PVForecastAkkudoktor",
+           "provider_settings": null,
            "planes": [
                {
                    "surface_tilt": 10.0,
-                   "surface_azimuth": 10.0,
+                   "surface_azimuth": 180.0,
                    "userhorizon": [
                        10.0,
                        20.0,
@@ -549,7 +627,7 @@ Validators:
                },
                {
                    "surface_tilt": 20.0,
-                   "surface_azimuth": 20.0,
+                   "surface_azimuth": 90.0,
                    "userhorizon": [
                        5.0,
                        15.0,
@@ -570,7 +648,7 @@ Validators:
                    "strings_per_inverter": 2
                }
            ],
-           "provider_settings": null
+           "max_planes": 0
        }
    }
 ```
@@ -583,10 +661,11 @@ Validators:
    {
        "pvforecast": {
            "provider": "PVForecastAkkudoktor",
+           "provider_settings": null,
            "planes": [
                {
                    "surface_tilt": 10.0,
-                   "surface_azimuth": 10.0,
+                   "surface_azimuth": 180.0,
                    "userhorizon": [
                        10.0,
                        20.0,
@@ -608,7 +687,7 @@ Validators:
                },
                {
                    "surface_tilt": 20.0,
-                   "surface_azimuth": 20.0,
+                   "surface_azimuth": 90.0,
                    "userhorizon": [
                        5.0,
                        15.0,
@@ -629,14 +708,14 @@ Validators:
                    "strings_per_inverter": 2
                }
            ],
-           "provider_settings": null,
+           "max_planes": 0,
            "planes_peakpower": [
                5.0,
                3.5
            ],
            "planes_azimuth": [
-               10.0,
+               180.0,
-               20.0
+               90.0
            ],
            "planes_tilt": [
                10.0,
@@ -662,6 +741,116 @@ Validators:
    }
 ```
 
+### PV Forecast Plane Configuration
+
+:::{table} pvforecast::planes::list
+:widths: 10 10 5 5 30
+:align: left
+
+| Name | Type | Read-Only | Default | Description |
+| ---- | ---- | --------- | ------- | ----------- |
+| surface_tilt | `Optional[float]` | `rw` | `30.0` | Tilt angle from horizontal plane. Ignored for two-axis tracking. |
+| surface_azimuth | `Optional[float]` | `rw` | `180.0` | Orientation (azimuth angle) of the (fixed) plane. Clockwise from north (north=0, east=90, south=180, west=270). |
+| userhorizon | `Optional[List[float]]` | `rw` | `None` | Elevation of horizon in degrees, at equally spaced azimuth clockwise from north. |
+| peakpower | `Optional[float]` | `rw` | `None` | Nominal power of PV system in kW. |
+| pvtechchoice | `Optional[str]` | `rw` | `crystSi` | PV technology. One of 'crystSi', 'CIS', 'CdTe', 'Unknown'. |
+| mountingplace | `Optional[str]` | `rw` | `free` | Type of mounting for PV system. Options are 'free' for free-standing and 'building' for building-integrated. |
+| loss | `Optional[float]` | `rw` | `14.0` | Sum of PV system losses in percent |
+| trackingtype | `Optional[int]` | `rw` | `None` | Type of suntracking. 0=fixed, 1=single horizontal axis aligned north-south, 2=two-axis tracking, 3=vertical axis tracking, 4=single horizontal axis aligned east-west, 5=single inclined axis aligned north-south. |
+| optimal_surface_tilt | `Optional[bool]` | `rw` | `False` | Calculate the optimum tilt angle. Ignored for two-axis tracking. |
+| optimalangles | `Optional[bool]` | `rw` | `False` | Calculate the optimum tilt and azimuth angles. Ignored for two-axis tracking. |
+| albedo | `Optional[float]` | `rw` | `None` | Proportion of the light hitting the ground that it reflects back. |
+| module_model | `Optional[str]` | `rw` | `None` | Model of the PV modules of this plane. |
+| inverter_model | `Optional[str]` | `rw` | `None` | Model of the inverter of this plane. |
+| inverter_paco | `Optional[int]` | `rw` | `None` | AC power rating of the inverter [W]. |
+| modules_per_string | `Optional[int]` | `rw` | `None` | Number of the PV modules of the strings of this plane. |
+| strings_per_inverter | `Optional[int]` | `rw` | `None` | Number of the strings of the inverter of this plane. |
+:::
+
+#### Example Input/Output
+
+```{eval-rst}
+.. code-block:: json
+
+   {
+       "pvforecast": {
+           "planes": [
+               {
+                   "surface_tilt": 10.0,
+                   "surface_azimuth": 180.0,
+                   "userhorizon": [
+                       10.0,
+                       20.0,
+                       30.0
+                   ],
+                   "peakpower": 5.0,
+                   "pvtechchoice": "crystSi",
+                   "mountingplace": "free",
+                   "loss": 14.0,
+                   "trackingtype": 0,
+                   "optimal_surface_tilt": false,
+                   "optimalangles": false,
+                   "albedo": null,
+                   "module_model": null,
+                   "inverter_model": null,
+                   "inverter_paco": 6000,
+                   "modules_per_string": 20,
+                   "strings_per_inverter": 2
+               },
+               {
+                   "surface_tilt": 20.0,
+                   "surface_azimuth": 90.0,
+                   "userhorizon": [
+                       5.0,
+                       15.0,
+                       25.0
+                   ],
+                   "peakpower": 3.5,
+                   "pvtechchoice": "crystSi",
+                   "mountingplace": "free",
+                   "loss": 14.0,
+                   "trackingtype": 1,
+                   "optimal_surface_tilt": false,
+                   "optimalangles": false,
+                   "albedo": null,
+                   "module_model": null,
+                   "inverter_model": null,
+                   "inverter_paco": 4000,
+                   "modules_per_string": 20,
+                   "strings_per_inverter": 2
+               }
+           ]
+       }
+   }
+```
+
+### Common settings for VRM API
+
+:::{table} pvforecast::provider_settings
+:widths: 10 10 5 5 30
+:align: left
+
+| Name | Type | Read-Only | Default | Description |
+| ---- | ---- | --------- | ------- | ----------- |
+| pvforecast_vrm_token | `str` | `rw` | `your-token` | Token for Connecting VRM API |
+| pvforecast_vrm_idsite | `int` | `rw` | `12345` | VRM-Installation-ID |
+:::
+
+#### Example Input/Output
+
+```{eval-rst}
+.. code-block:: json
+
+   {
+       "pvforecast": {
+           "provider_settings": {
+               "pvforecast_vrm_token": "your-token",
+               "pvforecast_vrm_idsite": 12345
+           }
+       }
+   }
+```
+
 ### Common settings for pvforecast data import from file or JSON string
 
 :::{table} pvforecast::provider_settings
@@ -689,89 +878,6 @@ Validators:
    }
 ```
 
-### PV Forecast Plane Configuration
-
-:::{table} pvforecast::planes::list
-:widths: 10 10 5 5 30
-:align: left
-
-| Name | Type | Read-Only | Default | Description |
-| ---- | ---- | --------- | ------- | ----------- |
-| surface_tilt | `Optional[float]` | `rw` | `None` | Tilt angle from horizontal plane. Ignored for two-axis tracking. |
-| surface_azimuth | `Optional[float]` | `rw` | `None` | Orientation (azimuth angle) of the (fixed) plane. Clockwise from north (north=0, east=90, south=180, west=270). |
-| userhorizon | `Optional[List[float]]` | `rw` | `None` | Elevation of horizon in degrees, at equally spaced azimuth clockwise from north. |
-| peakpower | `Optional[float]` | `rw` | `None` | Nominal power of PV system in kW. |
-| pvtechchoice | `Optional[str]` | `rw` | `crystSi` | PV technology. One of 'crystSi', 'CIS', 'CdTe', 'Unknown'. |
-| mountingplace | `Optional[str]` | `rw` | `free` | Type of mounting for PV system. Options are 'free' for free-standing and 'building' for building-integrated. |
-| loss | `Optional[float]` | `rw` | `14.0` | Sum of PV system losses in percent |
-| trackingtype | `Optional[int]` | `rw` | `None` | Type of suntracking. 0=fixed, 1=single horizontal axis aligned north-south, 2=two-axis tracking, 3=vertical axis tracking, 4=single horizontal axis aligned east-west, 5=single inclined axis aligned north-south. |
-| optimal_surface_tilt | `Optional[bool]` | `rw` | `False` | Calculate the optimum tilt angle. Ignored for two-axis tracking. |
-| optimalangles | `Optional[bool]` | `rw` | `False` | Calculate the optimum tilt and azimuth angles. Ignored for two-axis tracking. |
-| albedo | `Optional[float]` | `rw` | `None` | Proportion of the light hitting the ground that it reflects back. |
-| module_model | `Optional[str]` | `rw` | `None` | Model of the PV modules of this plane. |
-| inverter_model | `Optional[str]` | `rw` | `None` | Model of the inverter of this plane. |
-| inverter_paco | `Optional[int]` | `rw` | `None` | AC power rating of the inverter. [W] |
-| modules_per_string | `Optional[int]` | `rw` | `None` | Number of the PV modules of the strings of this plane. |
-| strings_per_inverter | `Optional[int]` | `rw` | `None` | Number of the strings of the inverter of this plane. |
-:::
-
-#### Example Input/Output
-
-```{eval-rst}
-.. code-block:: json
-
-   {
-       "pvforecast": {
-           "planes": [
-               {
-                   "surface_tilt": 10.0,
-                   "surface_azimuth": 10.0,
-                   "userhorizon": [
-                       10.0,
-                       20.0,
-                       30.0
-                   ],
-                   "peakpower": 5.0,
-                   "pvtechchoice": "crystSi",
-                   "mountingplace": "free",
-                   "loss": 14.0,
-                   "trackingtype": 0,
-                   "optimal_surface_tilt": false,
-                   "optimalangles": false,
-                   "albedo": null,
-                   "module_model": null,
-                   "inverter_model": null,
-                   "inverter_paco": 6000,
-                   "modules_per_string": 20,
-                   "strings_per_inverter": 2
-               },
-               {
-                   "surface_tilt": 20.0,
-                   "surface_azimuth": 20.0,
-                   "userhorizon": [
-                       5.0,
-                       15.0,
-                       25.0
-                   ],
-                   "peakpower": 3.5,
-                   "pvtechchoice": "crystSi",
-                   "mountingplace": "free",
-                   "loss": 14.0,
-                   "trackingtype": 1,
-                   "optimal_surface_tilt": false,
-                   "optimalangles": false,
-                   "albedo": null,
-                   "module_model": null,
-                   "inverter_model": null,
-                   "inverter_paco": 4000,
-                   "modules_per_string": 20,
-                   "strings_per_inverter": 2
-               }
-           ]
-       }
-   }
-```
-
 ## Weather Forecast Configuration
 
 :::{table} weather
@@ -826,20 +932,17 @@ Validators:
 
 ## Server Configuration
 
-Attributes:
-    To be added
-
 :::{table} server
 :widths: 10 20 10 5 5 30
 :align: left
 
 | Name | Environment Variable | Type | Read-Only | Default | Description |
 | ---- | -------------------- | ---- | --------- | ------- | ----------- |
-| host | `EOS_SERVER__HOST` | `Optional[pydantic.networks.IPvAnyAddress]` | `rw` | `0.0.0.0` | EOS server IP address. |
+| host | `EOS_SERVER__HOST` | `Optional[pydantic.networks.IPvAnyAddress]` | `rw` | `127.0.0.1` | EOS server IP address. |
 | port | `EOS_SERVER__PORT` | `Optional[int]` | `rw` | `8503` | EOS server IP port number. |
 | verbose | `EOS_SERVER__VERBOSE` | `Optional[bool]` | `rw` | `False` | Enable debug output |
 | startup_eosdash | `EOS_SERVER__STARTUP_EOSDASH` | `Optional[bool]` | `rw` | `True` | EOS server to start EOSdash server. |
-| eosdash_host | `EOS_SERVER__EOSDASH_HOST` | `Optional[pydantic.networks.IPvAnyAddress]` | `rw` | `0.0.0.0` | EOSdash server IP address. |
+| eosdash_host | `EOS_SERVER__EOSDASH_HOST` | `Optional[pydantic.networks.IPvAnyAddress]` | `rw` | `127.0.0.1` | EOSdash server IP address. |
 | eosdash_port | `EOS_SERVER__EOSDASH_PORT` | `Optional[int]` | `rw` | `8504` | EOSdash server IP port number. |
 :::
 
@@ -850,11 +953,11 @@ Attributes:
 
    {
        "server": {
-           "host": "0.0.0.0",
+           "host": "127.0.0.1",
            "port": 8503,
            "verbose": false,
            "startup_eosdash": true,
-           "eosdash_host": "0.0.0.0",
+           "eosdash_host": "127.0.0.1",
            "eosdash_port": 8504
        }
    }
@@ -889,12 +992,21 @@ Attributes:
        "general": {
            "data_folder_path": null,
            "data_output_subpath": "output",
-           "data_cache_subpath": "cache",
            "latitude": 52.52,
            "longitude": 13.405
        },
+       "cache": {
+           "subpath": "cache",
+           "cleanup_interval": 300.0
+       },
+       "ems": {
+           "startup_delay": 5.0,
+           "interval": 300.0
+       },
        "logging": {
-           "level": "INFO"
+           "level": null,
+           "console_level": "TRACE",
+           "file_level": "TRACE"
        },
        "devices": {
            "batteries": [
@@ -940,6 +1052,7 @@ Attributes:
        "elecprice": {
            "provider": "ElecPriceAkkudoktor",
            "charges_kwh": 0.21,
+           "vat_rate": 1.19,
            "provider_settings": null
        },
        "load": {
@@ -948,10 +1061,11 @@ Attributes:
        },
        "pvforecast": {
            "provider": "PVForecastAkkudoktor",
+           "provider_settings": null,
            "planes": [
                {
                    "surface_tilt": 10.0,
-                   "surface_azimuth": 10.0,
+                   "surface_azimuth": 180.0,
                    "userhorizon": [
                        10.0,
                        20.0,
@@ -973,7 +1087,7 @@ Attributes:
                },
                {
                    "surface_tilt": 20.0,
-                   "surface_azimuth": 20.0,
+                   "surface_azimuth": 90.0,
                    "userhorizon": [
                        5.0,
                        15.0,
@@ -994,18 +1108,18 @@ Attributes:
                    "strings_per_inverter": 2
                }
            ],
-           "provider_settings": null
+           "max_planes": 0
        },
        "weather": {
            "provider": "WeatherImport",
            "provider_settings": null
        },
        "server": {
-           "host": "0.0.0.0",
+           "host": "127.0.0.1",
            "port": 8503,
            "verbose": false,
            "startup_eosdash": true,
-           "eosdash_host": "0.0.0.0",
+           "eosdash_host": "127.0.0.1",
            "eosdash_port": 8504
        },
        "utils": {}

docs/_generated/openapi.md

@@ -166,6 +166,127 @@ Note:
 
 ---
 
+## GET /v1/admin/cache
+
+**Links**: [local](http://localhost:8503/docs#/default/fastapi_admin_cache_get_v1_admin_cache_get), [eos](https://petstore3.swagger.io/?url=https://raw.githubusercontent.com/Akkudoktor-EOS/EOS/refs/heads/main/openapi.json#/default/fastapi_admin_cache_get_v1_admin_cache_get)
+
+Fastapi Admin Cache Get
+
+```
+Current cache management data.
+
+Returns:
+    data (dict): The management data.
+```
+
+**Responses**:
+
+- **200**: Successful Response
+
+---
+
+## POST /v1/admin/cache/clear
+
+**Links**: [local](http://localhost:8503/docs#/default/fastapi_admin_cache_clear_post_v1_admin_cache_clear_post), [eos](https://petstore3.swagger.io/?url=https://raw.githubusercontent.com/Akkudoktor-EOS/EOS/refs/heads/main/openapi.json#/default/fastapi_admin_cache_clear_post_v1_admin_cache_clear_post)
+
+Fastapi Admin Cache Clear Post
+
+```
+Clear the cache from expired data.
+
+Deletes expired cache files.
+
+Args:
+    clear_all (Optional[bool]): Delete all cached files. Default is False.
+
+Returns:
+    data (dict): The management data after cleanup.
+```
+
+**Parameters**:
+
+- `clear_all` (query, optional): No description provided.
+
+**Responses**:
+
+- **200**: Successful Response
+
+- **422**: Validation Error
+
+---
+
+## POST /v1/admin/cache/load
+
+**Links**: [local](http://localhost:8503/docs#/default/fastapi_admin_cache_load_post_v1_admin_cache_load_post), [eos](https://petstore3.swagger.io/?url=https://raw.githubusercontent.com/Akkudoktor-EOS/EOS/refs/heads/main/openapi.json#/default/fastapi_admin_cache_load_post_v1_admin_cache_load_post)
+
+Fastapi Admin Cache Load Post
+
+```
+Load cache management data.
+
+Returns:
+    data (dict): The management data that was loaded.
+```
+
+**Responses**:
+
+- **200**: Successful Response
+
+---
+
+## POST /v1/admin/cache/save
+
+**Links**: [local](http://localhost:8503/docs#/default/fastapi_admin_cache_save_post_v1_admin_cache_save_post), [eos](https://petstore3.swagger.io/?url=https://raw.githubusercontent.com/Akkudoktor-EOS/EOS/refs/heads/main/openapi.json#/default/fastapi_admin_cache_save_post_v1_admin_cache_save_post)
+
+Fastapi Admin Cache Save Post
+
+```
+Save the current cache management data.
+
+Returns:
+    data (dict): The management data that was saved.
+```
+
+**Responses**:
+
+- **200**: Successful Response
+
+---
+
+## POST /v1/admin/server/restart
+
+**Links**: [local](http://localhost:8503/docs#/default/fastapi_admin_server_restart_post_v1_admin_server_restart_post), [eos](https://petstore3.swagger.io/?url=https://raw.githubusercontent.com/Akkudoktor-EOS/EOS/refs/heads/main/openapi.json#/default/fastapi_admin_server_restart_post_v1_admin_server_restart_post)
+
+Fastapi Admin Server Restart Post
+
+```
+Restart the server.
+
+Restart EOS properly by starting a new instance before exiting the old one.
+```
+
+**Responses**:
+
+- **200**: Successful Response
+
+---
+
+## POST /v1/admin/server/shutdown
+
+**Links**: [local](http://localhost:8503/docs#/default/fastapi_admin_server_shutdown_post_v1_admin_server_shutdown_post), [eos](https://petstore3.swagger.io/?url=https://raw.githubusercontent.com/Akkudoktor-EOS/EOS/refs/heads/main/openapi.json#/default/fastapi_admin_server_shutdown_post_v1_admin_server_shutdown_post)
+
+Fastapi Admin Server Shutdown Post
+
+```
+Shutdown the server.
+```
+
+**Responses**:
+
+- **200**: Successful Response
+
+---
+
 ## GET /v1/config
 
 **Links**: [local](http://localhost:8503/docs#/default/fastapi_config_get_v1_config_get), [eos](https://petstore3.swagger.io/?url=https://raw.githubusercontent.com/Akkudoktor-EOS/EOS/refs/heads/main/openapi.json#/default/fastapi_config_get_v1_config_get)
@@ -238,11 +359,11 @@ Returns:
 
 ---
 
-## PUT /v1/config/reset
+## POST /v1/config/reset
 
-**Links**: [local](http://localhost:8503/docs#/default/fastapi_config_update_post_v1_config_reset_put), [eos](https://petstore3.swagger.io/?url=https://raw.githubusercontent.com/Akkudoktor-EOS/EOS/refs/heads/main/openapi.json#/default/fastapi_config_update_post_v1_config_reset_put)
+**Links**: [local](http://localhost:8503/docs#/default/fastapi_config_reset_post_v1_config_reset_post), [eos](https://petstore3.swagger.io/?url=https://raw.githubusercontent.com/Akkudoktor-EOS/EOS/refs/heads/main/openapi.json#/default/fastapi_config_reset_post_v1_config_reset_post)
 
-Fastapi Config Update Post
+Fastapi Config Reset Post
 
 ```
 Reset the configuration to the EOS configuration file.
@@ -257,6 +378,141 @@ Returns:
 
 ---
 
+## GET /v1/config/{path}
+
+**Links**: [local](http://localhost:8503/docs#/default/fastapi_config_get_key_v1_config__path__get), [eos](https://petstore3.swagger.io/?url=https://raw.githubusercontent.com/Akkudoktor-EOS/EOS/refs/heads/main/openapi.json#/default/fastapi_config_get_key_v1_config__path__get)
+
+Fastapi Config Get Key
+
+```
+Get the value of a nested key or index in the config model.
+
+Args:
+    path (str): The nested path to the key (e.g., "general/latitude" or "optimize/nested_list/0").
+
+Returns:
+    value (Any): The value of the selected nested key.
+```
+
+**Parameters**:
+
+- `path` (path, required): The nested path to the configuration key (e.g., general/latitude).
+
+**Responses**:
+
+- **200**: Successful Response
+
+- **422**: Validation Error
+
+---
+
+## PUT /v1/config/{path}
+
+**Links**: [local](http://localhost:8503/docs#/default/fastapi_config_put_key_v1_config__path__put), [eos](https://petstore3.swagger.io/?url=https://raw.githubusercontent.com/Akkudoktor-EOS/EOS/refs/heads/main/openapi.json#/default/fastapi_config_put_key_v1_config__path__put)
+
+Fastapi Config Put Key
+
+```
+Update a nested key or index in the config model.
+
+Args:
+    path (str): The nested path to the key (e.g., "general/latitude" or "optimize/nested_list/0").
+    value (Any): The new value to assign to the key or index at path.
+
+Returns:
+    configuration (ConfigEOS): The current configuration after the update.
+```
+
+**Parameters**:
+
+- `path` (path, required): The nested path to the configuration key (e.g., general/latitude).
+
+**Request Body**:
+
+- `application/json`: {
+  "anyOf": [
+    {},
+    {
+      "type": "null"
+    }
+  ],
+  "description": "The value to assign to the specified configuration path (can be None).",
+  "title": "Value"
+}
+
+**Responses**:
+
+- **200**: Successful Response
+
+- **422**: Validation Error
+
+---
+
+## GET /v1/health
+
+**Links**: [local](http://localhost:8503/docs#/default/fastapi_health_get_v1_health_get), [eos](https://petstore3.swagger.io/?url=https://raw.githubusercontent.com/Akkudoktor-EOS/EOS/refs/heads/main/openapi.json#/default/fastapi_health_get_v1_health_get)
+
+Fastapi Health Get
+
+```
+Health check endpoint to verify that the EOS server is alive.
+```
+
+**Responses**:
+
+- **200**: Successful Response
+
+---
+
+## GET /v1/logging/log
+
+**Links**: [local](http://localhost:8503/docs#/default/fastapi_logging_get_log_v1_logging_log_get), [eos](https://petstore3.swagger.io/?url=https://raw.githubusercontent.com/Akkudoktor-EOS/EOS/refs/heads/main/openapi.json#/default/fastapi_logging_get_log_v1_logging_log_get)
+
+Fastapi Logging Get Log
+
+```
+Get structured log entries from the EOS log file.
+
+Filters and returns log entries based on the specified query parameters. The log
+file is expected to contain newline-delimited JSON entries.
+
+Args:
+    limit (int): Maximum number of entries to return.
+    level (Optional[str]): Filter logs by severity level (e.g., DEBUG, INFO).
+    contains (Optional[str]): Return only logs that include this string in the message.
+    regex (Optional[str]): Return logs that match this regular expression in the message.
+    from_time (Optional[str]): ISO 8601 timestamp to filter logs not older than this.
+    to_time (Optional[str]): ISO 8601 timestamp to filter logs not newer than this.
+    tail (bool): If True, fetch the most recent log entries (like `tail`).
+
+Returns:
+    JSONResponse: A JSON list of log entries.
+```
+
+**Parameters**:
+
+- `limit` (query, optional): Maximum number of log entries to return.
+
+- `level` (query, optional): Filter by log level (e.g., INFO, ERROR).
+
+- `contains` (query, optional): Filter logs containing this substring.
+
+- `regex` (query, optional): Filter logs by matching regex in message.
+
+- `from_time` (query, optional): Start time (ISO format) for filtering logs.
+
+- `to_time` (query, optional): End time (ISO format) for filtering logs.
+
+- `tail` (query, optional): If True, returns the most recent lines (tail mode).
+
+**Responses**:
+
+- **200**: Successful Response
+
+- **422**: Validation Error
+
+---
+
 ## PUT /v1/measurement/data
 
 **Links**: [local](http://localhost:8503/docs#/default/fastapi_measurement_data_put_v1_measurement_data_put), [eos](https://petstore3.swagger.io/?url=https://raw.githubusercontent.com/Akkudoktor-EOS/EOS/refs/heads/main/openapi.json#/default/fastapi_measurement_data_put_v1_measurement_data_put)
@@ -473,6 +729,93 @@ Merge the measurement of given key and value into EOS measurements at given date
 
 ---
 
+## GET /v1/prediction/dataframe
+
+**Links**: [local](http://localhost:8503/docs#/default/fastapi_prediction_dataframe_get_v1_prediction_dataframe_get), [eos](https://petstore3.swagger.io/?url=https://raw.githubusercontent.com/Akkudoktor-EOS/EOS/refs/heads/main/openapi.json#/default/fastapi_prediction_dataframe_get_v1_prediction_dataframe_get)
+
+Fastapi Prediction Dataframe Get
+
+```
+Get prediction for given key within given date range as series.
+
+Args:
+    key (str): Prediction key
+    start_datetime (Optional[str]): Starting datetime (inclusive).
+        Defaults to start datetime of latest prediction.
+    end_datetime (Optional[str]: Ending datetime (exclusive).
+
+Defaults to end datetime of latest prediction.
+```
+
+**Parameters**:
+
+- `keys` (query, required): Prediction keys.
+
+- `start_datetime` (query, optional): Starting datetime (inclusive).
+
+- `end_datetime` (query, optional): Ending datetime (exclusive).
+
+- `interval` (query, optional): Time duration for each interval. Defaults to 1 hour.
+
+**Responses**:
+
+- **200**: Successful Response
+
+- **422**: Validation Error
+
+---
+
+## PUT /v1/prediction/import/{provider_id}
+
+**Links**: [local](http://localhost:8503/docs#/default/fastapi_prediction_import_provider_v1_prediction_import__provider_id__put), [eos](https://petstore3.swagger.io/?url=https://raw.githubusercontent.com/Akkudoktor-EOS/EOS/refs/heads/main/openapi.json#/default/fastapi_prediction_import_provider_v1_prediction_import__provider_id__put)
+
+Fastapi Prediction Import Provider
+
+```
+Import prediction for given provider ID.
+
+Args:
+    provider_id: ID of provider to update.
+    data: Prediction data.
+    force_enable: Update data even if provider is disabled.
+        Defaults to False.
+```
+
+**Parameters**:
+
+- `provider_id` (path, required): Provider ID.
+
+- `force_enable` (query, optional): No description provided.
+
+**Request Body**:
+
+- `application/json`: {
+  "anyOf": [
+    {
+      "$ref": "#/components/schemas/PydanticDateTimeDataFrame"
+    },
+    {
+      "$ref": "#/components/schemas/PydanticDateTimeData"
+    },
+    {
+      "type": "object",
+      "additionalProperties": true
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "title": "Data"
+}
+
+**Responses**:
+
+- **200**: Successful Response
+
+- **422**: Validation Error
+
+---
+
 ## GET /v1/prediction/keys
 
 **Links**: [local](http://localhost:8503/docs#/default/fastapi_prediction_keys_get_v1_prediction_keys_get), [eos](https://petstore3.swagger.io/?url=https://raw.githubusercontent.com/Akkudoktor-EOS/EOS/refs/heads/main/openapi.json#/default/fastapi_prediction_keys_get_v1_prediction_keys_get)
@@ -516,7 +859,7 @@ Args:
 
 - `end_datetime` (query, optional): Ending datetime (exclusive).
 
-- `interval` (query, optional): Time duration for each interval.
+- `interval` (query, optional): Time duration for each interval. Defaults to 1 hour.
 
 **Responses**:
 

docs/akkudoktoreos/about.md

@@ -1,9 +0,0 @@
-% SPDX-License-Identifier: Apache-2.0
-
-# About Akkudoktor EOS
-
-The Energy System Simulation and Optimization System (EOS) provides a comprehensive solution for
-simulating and optimizing an energy system based on renewable energy sources. With a focus on
-photovoltaic (PV) systems, battery storage (batteries), load management (consumer requirements),
-heat pumps, electric vehicles, and consideration of electricity price data, this system enables
-forecasting and optimization of energy flow and costs over a specified period.

docs/akkudoktoreos/architecture.md

@@ -20,17 +20,22 @@ EOS Architecture
 
 ### Configuration
 
-The configuration controls all aspects of EOS: optimization, prediction, measurement, and energy management.
+The configuration controls all aspects of EOS: optimization, prediction, measurement, and energy
+management.
 
 ### Energy Management
 
-Energy management is the overall process to provide planning data for scheduling the different devices in your system in an optimal way. Energy management cares for the update of predictions and the optimization of the planning based on the simulated behavior of the devices. The planning is on the hour. Sub-hour energy management is left
+Energy management is the overall process to provide planning data for scheduling the different
+devices in your system in an optimal way. Energy management cares for the update of predictions and
+the optimization of the planning based on the simulated behavior of the devices. The planning is on
+the hour.
 
 ### Optimization
 
 ### Device Simulations
 
-Device simulations simulate devices' behavior based on internal logic and predicted data. They provide the data needed for optimization.
+Device simulations simulate devices' behavior based on internal logic and predicted data. They
+provide the data needed for optimization.
 
 ### Predictions
 
@@ -38,7 +43,8 @@ Predictions provide predicted future data to be used by the optimization.
 
 ### Measurements
 
-Measurements are utilized to refine predictions using real data from your system, thereby enhancing accuracy.
+Measurements are utilized to refine predictions using real data from your system, thereby enhancing
+accuracy.
 
 ### EOS Server
 

docs/akkudoktoreos/configuration.md

@@ -31,10 +31,10 @@ Use endpoint `POST /v1/config/reset` to reset the configuration to the values in
 
 The configuration sources and their priorities are as follows:
 
-1. **Runtime Config Updates**: Provided during runtime by the REST interface
+1. `Settings`: Provided during runtime by the REST interface
-2. **Environment Variables**: Defined at startup of the REST server and during runtime
+2. `Environment Variables`: Defined at startup of the REST server and during runtime
-3. **EOS Configuration File**: Read at startup of the REST server and on request
+3. `EOS Configuration File`: Read at startup of the REST server and on request
-4. **Default Values**
+4. `Default Values`
 
 ### Runtime Config Updates
 

docs/akkudoktoreos/integration.md

@@ -1,4 +1,5 @@
 % SPDX-License-Identifier: Apache-2.0
+(integration-page)=
 
 # Integration
 
@@ -17,18 +18,24 @@ APIs, and online services in creative and practical ways.
 
 Andreas Schmitz uses [Node-RED](https://nodered.org/) as part of his home automation setup.
 
-### Resources
+### Node-Red Resources
 
-- [Installation Guide (German)](https://meintechblog.de/2024/09/05/andreas-schmitz-joerg-installiert-mein-energieoptimierungssystem/) — A detailed guide on integrating an early version of EOS with
+- [Installation Guide (German)](https://www.youtube.com/playlist?list=PL8_vk9A-s7zLD865Oou6y3EeQLlNtu-Hn)
-  `Node-RED`.
+  \— A detailed guide on integrating EOS with `Node-RED`.
 
 ## Home Assistant
 
 [Home Assistant](https://www.home-assistant.io/) is an open-source home automation platform that
 emphasizes local control and user privacy.
 
-### Resources
+(duetting-solution)=
+
+### Home Assistant Resources
 
 - Duetting's [EOS Home Assistant Addon](https://github.com/Duetting/ha_eos_addon) — Additional
-  details can be found in this
+  details can be found in this [discussion thread](https://github.com/Akkudoktor-EOS/EOS/discussions/294).
-  [discussion thread](https://github.com/Akkudoktor-EOS/EOS/discussions/294).
+
+## EOS Connect
+
+[EOS connect](https://github.com/ohAnd/EOS_connect) uses `EOS` for energy management and optimization,
+and connects to smart home platforms to monitor, forecast, and control energy flows.

docs/akkudoktoreos/introduction.md

@@ -0,0 +1,180 @@
+% SPDX-License-Identifier: Apache-2.0
+
+# Introduction
+
+The Energy System Simulation and Optimization System (EOS) provides a comprehensive
+solution for simulating and optimizing an energy system based on renewable energy
+sources. With a focus on photovoltaic (PV) systems, battery storage (batteries), load
+management (consumer requirements), heat pumps, electric vehicles, and consideration of
+electricity price data, this system enables forecasting and optimization of energy flow
+and costs over a specified period.
+
+After successfully installing a PV system with or without battery storage, most owners
+first priority is often to charge the electric car with surplus energy in order to use
+the electricity generated by the PV system cost-effectively for electromobility.
+
+After initial experiences, the desire to include battery storage and dynamic electricity
+prices in the solution soon arises. The market already offers various commercial and
+non-commercial solutions for this, such as the popular open source hardware and software
+solutions evcc or openWB.
+
+Some solutions take into account the current values ​​of the system such as PV power
+output, battery storage charge level or the current electricity price to decide whether
+to charge the electric car with PV surplus or from the grid (e.g. openWB), some use
+historical consumption values ​​and PV forecast data for their calculations, but leave out
+the current electricity prices and charging the battery storage from the power grid
+(Predbat). Others are specialiced on working in combination with a specific smart home
+solution (e.g. emhass). Still others focus on certain consumers, such as the electric car,
+or are currently working on integrating the forecast values ​​(evcc). And some are commercial
+devices that require an electrician to install them and expect a certain ecosystem
+(e.g. Sunny Home Manager).
+
+The Akkudoktor EOS
+
+- takes into account historical, current and forecast data such as consumption values, PV
+  forecast data, electricity price forecast, battery storage and electric car charge levels
+- the simulation also takes into account the possibility of charging the battery storage
+  from the grid at low electricity prices
+- is not limited to certain consumers, but includes electric cars, heat pumps or more
+  powerful consumers such as tumble dryers
+- is independent of a specific smart home solution and can also be integrated into
+  self-developed solutions if desired
+- is a free and independent open source software solution
+
+![Introdution](../_static/introduction/introduction.png)
+
+The challenge is to charge (electric car) or start the consumers (washing machine, dryer)
+at the right time and to do so as cost-efficiently as possible. If PV yield forecast,
+battery storage and dynamic electricity price forecasts are included in the calculation,
+the possibilities increase, but unfortunately so does the complexity.
+
+The Akkudoktor EOS addresses this challenge by simulating energy flows in the household
+based on target values, forecast data and current operating data over a 48-hour
+observation period, running through a large number of different scenarios and finally
+providing a cost-optimized plan for the current day controlling the relevant consumers.
+
+## Prerequisites
+
+- Technical requirements
+- Input data
+
+### Technical requirements
+
+- reasonably fast computer on which EOS is installed
+- controllable energy system consisting of photovoltaic system, solar battery storage,
+  energy intensive consumers that must provide the appropriate interfaces
+- integration solution for integrating the energy system and EOS
+
+### Input Data
+
+![Overview](../_static/introduction/overview.png)
+
+The EOS requires various types of data for the simulation:
+
+Forecast data
+
+- PV yield forecast
+- Expected household consumption
+- Electricity price forecast
+- Forecast temperature trend (if heatpump is used)
+
+Basic data and current operating data
+
+- Current charge level of the battery storage
+- Value of electricity in the battery storage
+- Current charge level of the electric car
+- Energy consumption and running time of dishwasher, washing machine and tumble dryer
+
+Target values
+
+- Charge level the electric car should reach in the next few hours
+- Consumers to run in the next few hours
+
+There are various service providers available for PV forecasting that calculate forecast
+data for a PV system based on the various influencing factors, such as system size,
+orientation, location, time of year and weather conditions. EOS also offers a
+[PV forecasting service](#prediction-page) which can be used. This service uses
+public data in the background.
+
+For the forecast of household consumption EOS provides a standard load curve for an
+average day based on annual household consumption that you can fetch via API. This data
+was compiled based on data from several households and provides an initial usable basis.
+Alternatively your own collected historical data could be used to reflect your personal
+consumption behaviour.
+
+## Simulation Results
+
+Based on the input data, the EOS uses a genetic algorithm to create a cost-optimized
+schedule for the coming hours from numerous simulations of the overall system.
+
+The plan created contains for each of the coming hours
+
+- Control information
+  - whether and with what power the battery storage should be charged from the grid
+  - when the battery storage should be charged via the PV system
+  - whether discharging the battery storage is permitted or not
+  - when and with what power the electric car should be charged
+  - when a household appliance should be activated
+- Energy history information
+  - Total load of the house
+  - Grid consumption
+  - Feed-in
+  - Load of the planned household appliances
+  - Charge level of the battery storage
+  - Charge level of the electric car
+  - Active losses
+- Cost information
+  - Revenue per hour (when fed into the grid)
+  - Total costs per hour (when drawn from the grid)
+  - Overall balance (revenue-costs)
+  - Cost development
+
+If required, the simulation result can also be created and downloaded in graphical
+form as a PDF from EOS.
+
+## Integration
+
+The Akkudoktor EOS can be integrated into a wide variety of systems with a variety
+of components.
+
+![Integration](../_static/introduction/integration.png)
+
+However, the components are not integrated by the EOS itself, but must be integrated by
+the user using an integration solution and currently requires some effort and technical
+know-how.
+
+Any [integration](#integration-page) solution that can act as an intermediary between the
+components and the REST API of EOS can be used. One possible solution that enables the
+integration of components and EOS is Node-RED. Another solution could be Home Assistant
+usings its built in features.
+
+Access to the data and functions of the components can be done in a variety of ways.
+Node-RED offers a large number of types of nodes that allow access via the protocols
+commonly used in this area, such as Modbus or MQTT. Access to any existing databases,
+such as InfluxDB or PostgreSQL, is also possible via nodes provided by Node-RED.
+
+It becomes easier if a smart home solution like Home Assistant, openHAB or ioBroker or
+solutions such as evcc or openWB are already in use. In this case, these smart home
+solutions already take over the technical integration and communication with the components
+at a technical level and Node-RED offers nodes for accessing these solutions, so that the
+corresponding sources can be easily integrated into a flow.
+
+In Home Assistant you could use an automation to prepare the input payload for EOS and
+then use the RESTful integration to call EOS. Based on this concept there is already a
+Home Assistant add-on created by [Duetting](#duetting-solution).
+
+The plan created by EOS must also be executed via the chosen integration solution,
+with the respective devices receiving their instructions according to the plan.
+
+## Limitations
+
+The plan calculated by EOS is cost-optimized due to the genetic algorithm used, but not
+necessarily cost-optimal, since genetic algorithms do not always find the global optimum,
+but usually find good local optima very quickly in a large solution space.
+
+## Links
+
+- [German Videos explaining the basic concept and installation process of EOS (YouTube)](https://www.youtube.com/playlist?list=PL8_vk9A-s7zLD865Oou6y3EeQLlNtu-Hn)
+- [German Forum of Akkudoktor EOS](https://akkudoktor.net/c/der-akkudoktor/eos)
+- [Akkudoktor-EOS GitHub Repository](https://github.com/Akkudoktor-EOS/EOS)
+- [Latest EOS Documentation](https://akkudoktor-eos.readthedocs.io/en/latest/)

docs/akkudoktoreos/logging.md

@@ -0,0 +1,75 @@
+% SPDX-License-Identifier: Apache-2.0
+(logging-page)=
+
+# Logging
+
+EOS automatically records important events and messages to help you understand what’s happening and
+to troubleshoot problems.
+
+## How Logging Works
+
+- By default, logs are shown in your terminal (console).
+- You can also save logs to a file for later review.
+- Log files are rotated automatically to avoid becoming too large.
+
+## Controlling Log Details
+
+### 1. Command-Line Option
+
+Set the amount of log detail shown on the console by using `--log-level` when starting EOS.
+
+Example:
+
+```{eval-rst}
+.. tabs::
+
+  .. tab:: Windows
+
+     .. code-block:: powershell
+
+        .venv\Scripts\python src/akkudoktoreos/server/eos.py --log-level DEBUG
+
+  .. tab:: Linux
+
+     .. code-block:: bash
+
+        .venv/bin/python src/akkudoktoreos/server/eos.py --log-level DEBUG
+
+```
+
+Common levels:
+
+- DEBUG (most detail)
+- INFO (default)
+- WARNING
+- ERROR
+- CRITICAL (least detail)
+
+### 2. Configuration File
+
+You can also set logging options in your EOS configuration file (EOS.config.json).
+
+```Json
+{
+  "logging": {
+    "console_level": "INFO",
+    "file_level": "DEBUG"
+  }
+}
+```
+
+### 3. Environment Variable
+
+You can also control the log level by setting the `EOS_LOGGING__CONSOLE_LEVEL` and the
+`EOS_LOGGING__FILE_LEVEL` environment variables.
+
+```bash
+  EOS_LOGGING__CONSOLE_LEVEL="INFO"
+  EOS_LOGGING__FILE_LEVEL="DEBUG"
+```
+
+## File Logging
+
+If the `file_level` configuration is set, log records are written to a rotating log file. The log
+file is in the data output directory and named `eos.log`. You may directly read the file or use
+the `/v1/logging/log` endpoint to access the file log.

docs/akkudoktoreos/measurement.md

@@ -5,9 +5,9 @@
 Measurements are utilized to refine predictions using real data from your system, thereby enhancing
 accuracy.
 
-- **Household Load Measurement**
+- Household Load Measurement
-- **Grid Export Measurement**
+- Grid Export Measurement
-- **Grid Import Measurement**
+- Grid Import Measurement
 
 ## Storing Measurements
 

docs/akkudoktoreos/optimization.md

@@ -2,7 +2,207 @@
 
 # Optimization
 
-:::{admonition} Todo
+## Introduction
-:class: note
+
-Describe optimization.
+The `POST /optimize` API endpoint optimizes your energy management system based on various inputs
-:::
+including electricity prices, battery storage capacity, PV forecast, and temperature data.
+
+## Input Payload
+
+### Sample Request
+
+```json
+{
+    "ems": {
+        "preis_euro_pro_wh_akku": 0.0007,
+        "einspeiseverguetung_euro_pro_wh": 0.00007,
+        "gesamtlast": [500, 500, ..., 500, 500],
+        "pv_prognose_wh": [300, 0, 0, ..., 2160, 1840],
+        "strompreis_euro_pro_wh": [0.0003784, 0.0003868, ..., 0.00034102, 0.00033709]
+    },
+    "pv_akku": {
+        "device_id": "battery1",
+        "capacity_wh": 12000,
+        "charging_efficiency": 0.92,
+        "discharging_efficiency": 0.92,
+        "max_charge_power_w": 5700,
+        "initial_soc_percentage": 66,
+        "min_soc_percentage": 5,
+        "max_soc_percentage": 100
+    },
+    "inverter": {
+        "device_id": "inverter1",
+        "max_power_wh": 15500
+        "battery_id": "battery1",
+    },
+    "eauto": {
+        "device_id": "auto1",
+        "capacity_wh": 64000,
+        "charging_efficiency": 0.88,
+        "discharging_efficiency": 0.88,
+        "max_charge_power_w": 11040,
+        "initial_soc_percentage": 98,
+        "min_soc_percentage": 60,
+        "max_soc_percentage": 100
+    },
+    "temperature_forecast": [18.3, 18, ..., 20.16, 19.84],
+    "start_solution": null
+}
+```
+
+## Input Parameters
+
+### Energy Management System (EMS)
+
+#### Battery Cost (`preis_euro_pro_wh_akku`)
+
+- Unit: €/Wh
+- Purpose: Represents the residual value of energy stored in the battery
+- Impact: Lower values encourage battery depletion, higher values preserve charge at the end of the simulation.
+
+#### Feed-in Tariff (`einspeiseverguetung_euro_pro_wh`)
+
+- Unit: €/Wh
+- Purpose: Compensation received for feeding excess energy back to the grid
+
+#### Total Load Forecast (`gesamtlast`)
+
+- Unit: W
+- Time Range: 48 hours (00:00 today to 23:00 tomorrow)
+- Format: Array of hourly values
+- Note: Exclude optimizable loads (EV charging, battery charging, etc.)
+
+##### Data Sources
+
+1. Standard Load Profile: `GET /v1/prediction/list?key=load_mean` for a standard load profile based
+   on your yearly consumption.
+2. Adjusted Load Profile: `GET /v1/prediction/list?key=load_mean_adjusted` for a combination of a
+   standard load profile based on your yearly consumption incl. data from last 48h.
+
+#### PV Generation Forecast (`pv_prognose_wh`)
+
+- Unit: W
+- Time Range: 48 hours (00:00 today to 23:00 tomorrow)
+- Format: Array of hourly values
+- Data Source: `GET /v1/prediction/series?key=pvforecast_ac_power`
+
+#### Electricity Price Forecast (`strompreis_euro_pro_wh`)
+
+- Unit: €/Wh
+- Time Range: 48 hours (00:00 today to 23:00 tomorrow)
+- Format: Array of hourly values
+- Data Source: `GET /v1/prediction/list?key=elecprice_marketprice_wh`
+
+Verify prices against your local tariffs.
+
+### Battery Storage System
+
+#### Configuration
+
+- `device_id`: ID of battery
+- `capacity_wh`: Total battery capacity in Wh
+- `charging_efficiency`: Charging efficiency (0-1)
+- `discharging_efficiency`: Discharging efficiency (0-1)
+- `max_charge_power_w`: Maximum charging power in W
+
+#### State of Charge (SoC)
+
+- `initial_soc_percentage`: Current battery level (%)
+- `min_soc_percentage`: Minimum allowed SoC (%)
+- `max_soc_percentage`: Maximum allowed SoC (%)
+
+### Inverter
+
+- `device_id`: ID of inverter
+- `max_power_wh`: Maximum inverter power in Wh
+- `battery_id`: ID of battery
+
+### Electric Vehicle (EV)
+
+- `device_id`: ID of electric vehicle
+- `capacity_wh`: Battery capacity in Wh
+- `charging_efficiency`: Charging efficiency (0-1)
+- `discharging_efficiency`: Discharging efficiency (0-1)
+- `max_charge_power_w`: Maximum charging power in W
+- `initial_soc_percentage`: Current charge level (%)
+- `min_soc_percentage`: Minimum allowed SoC (%)
+- `max_soc_percentage`: Maximum allowed SoC (%)
+
+### Temperature Forecast
+
+- Unit: °C
+- Time Range: 48 hours (00:00 today to 23:00 tomorrow)
+- Format: Array of hourly values
+- Data Source: `GET /v1/prediction/list?key=weather_temp_air`
+
+## Output Format
+
+### Sample Response
+
+```json
+{
+    "ac_charge": [0.625, 0, ..., 0.75, 0],
+    "dc_charge": [1, 1, ..., 1, 1],
+    "discharge_allowed": [0, 0, 1, ..., 0, 0],
+    "eautocharge_hours_float": [0.625, 0, ..., 0.75, 0],
+    "result": {
+        "Last_Wh_pro_Stunde": [...],
+        "EAuto_SoC_pro_Stunde": [...],
+        "Einnahmen_Euro_pro_Stunde": [...],
+        "Gesamt_Verluste": 1514.96,
+        "Gesamtbilanz_Euro": 2.51,
+        "Gesamteinnahmen_Euro": 2.88,
+        "Gesamtkosten_Euro": 5.39,
+        "akku_soc_pro_stunde": [...]
+    }
+}
+```
+
+### Output Parameters
+
+#### Battery Control
+
+- `ac_charge`: Grid charging schedule (0-1)
+- `dc_charge`: DC charging schedule (0-1)
+- `discharge_allowed`: Discharge permission (0 or 1)
+
+0 (no charge)
+1 (charge with full load)
+
+`ac_charge` multiplied by the maximum charge power of the battery results in the planned charging power.
+
+#### EV Charging
+
+- `eautocharge_hours_float`: EV charging schedule (0-1)
+
+#### Results
+
+The `result` object contains detailed information about the optimization outcome.
+The length of the array is between 25 and 48 and starts at the current hour and ends at 23:00 tomorrow.
+
+- `Last_Wh_pro_Stunde`: Array of hourly load values in Wh
+  - Shows the total energy consumption per hour
+  - Includes household load, battery charging/discharging, and EV charging
+
+- `EAuto_SoC_pro_Stunde`: Array of hourly EV state of charge values (%)
+  - Shows the projected EV battery level throughout the optimization period
+
+- `Einnahmen_Euro_pro_Stunde`: Array of hourly revenue values in Euro
+
+- `Gesamt_Verluste`: Total energy losses in Wh
+
+- `Gesamtbilanz_Euro`: Overall financial balance in Euro
+
+- `Gesamteinnahmen_Euro`: Total revenue in Euro
+
+- `Gesamtkosten_Euro`: Total costs in Euro
+
+- `akku_soc_pro_stunde`: Array of hourly battery state of charge values (%)
+
+## Timeframe overview
+
+```{figure} ../_static/optimization_timeframes.png
+:alt: Timeframe Overview
+
+Timeframe Overview
+```

docs/akkudoktoreos/prediction.md

@@ -1,14 +1,15 @@
 % SPDX-License-Identifier: Apache-2.0
+(prediction-page)=
 
 # Predictions
 
 Predictions, along with simulations and measurements, form the foundation upon which energy
 optimization is executed. In EOS, a standard set of predictions is managed, including:
 
-- **Household Load Prediction**
+- Household Load Prediction
-- **Electricity Price Prediction**
+- Electricity Price Prediction
-- **PV Power Prediction**
+- PV Power Prediction
-- **Weather Prediction**
+- Weather Prediction
 
 ## Storing Predictions
 
@@ -60,13 +61,15 @@ A dictionary with the following structure:
 #### 2. DateTimeDataFrame
 
 A JSON string created from a [pandas](https://pandas.pydata.org/docs/index.html) dataframe with a
-`DatetimeIndex`. Use [pandas.DataFrame.to_json(orient="index")](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.to_json.html#pandas.DataFrame.to_json).
+`DatetimeIndex`. Use
+[pandas.DataFrame.to_json(orient="index")](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.to_json.html#pandas.DataFrame.to_json).
 The column name of the data must be the same as the names of the `prediction key`s.
 
 #### 3. DateTimeSeries
 
 A JSON string created from a [pandas](https://pandas.pydata.org/docs/index.html) series with a
-`DatetimeIndex`. Use [pandas.Series.to_json(orient="index")](https://pandas.pydata.org/docs/reference/api/pandas.Series.to_json.html#pandas.Series.to_json).
+`DatetimeIndex`. Use
+[pandas.Series.to_json(orient="index")](https://pandas.pydata.org/docs/reference/api/pandas.Series.to_json.html#pandas.Series.to_json).
 
 ## Adjusted Predictions
 
@@ -116,9 +119,11 @@ Configuration options:
   - `provider`: Electricity price provider id of provider to be used.
 
     - `ElecPriceAkkudoktor`: Retrieves from Akkudoktor.net.
+    - `ElecPriceEnergyCharts`: Retrieves from Energy-Charts.info.
     - `ElecPriceImport`: Imports from a file or JSON string.
 
   - `charges_kwh`: Electricity price charges (€/kWh).
+  - `vat_rate`: VAT rate factor applied to electricity price when charges are used (default: 1.19).
   - `provider_settings.import_file_path`: Path to the file to import electricity price forecast data from.
   - `provider_settings.import_json`: JSON string, dictionary of electricity price forecast value lists.
 
@@ -130,6 +135,24 @@ prices by extrapolating historical price data combined with the most recent actu
 from Akkudoktor.net. Electricity price charges given in the `charges_kwh` configuration
 option are added.
 
+### ElecPriceEnergyCharts Provider
+
+The `ElecPriceEnergyCharts` provider retrieves day-ahead electricity market prices from
+[Energy-Charts.info](https://www.Energy-Charts.info). It supports both short-term and extended forecasting by combining
+real-time market data with historical price trends.
+
+- For the next 24 hours, market prices are fetched directly from Energy-Charts.info.
+- For periods beyond 24 hours, prices are estimated using extrapolation based on historical data and the latest
+  available market values.
+
+Charges and VAT
+
+- If `charges_kwh` configuration option is greater than 0, the electricity price is calculated as:
+  `(market price + charges_kwh) * vat_rate` where `vat_rate` is configurable (default: 1.19 for 19% VAT).
+- If `charges_kwh` is set to 0, the electricity price is simply: `market_price` (no VAT applied).
+
+**Note:** For the most accurate forecasts, it is recommended to set the `historic_hours` parameter to 840.
+
 ### ElecPriceImport Provider
 
 The `ElecPriceImport` provider is designed to import electricity prices from a file or a JSON
@@ -141,9 +164,12 @@ The prediction key for the electricity price forecast data is:
 - `elecprice_marketprice_wh`: Electricity market price per Wh (€/Wh).
 
 The electricity proce forecast data must be provided in one of the formats described in
-<project:#prediction-import-providers>. The data source must be given in the
+<project:#prediction-import-providers>. The data source can be given in the
 `import_file_path` or `import_json` configuration option.
 
+The data may additionally or solely be provided by the
+**PUT** `/v1/prediction/import/ElecPriceImport` endpoint.
+
 ## Load Prediction
 
 Prediction keys:
@@ -159,6 +185,7 @@ Configuration options:
   - `provider`: Load provider id of provider to be used.
 
     - `LoadAkkudoktor`: Retrieves from local database.
+    - `LoadVrm`: Retrieves data from the VRM API by Victron Energy.
     - `LoadImport`: Imports from a file or JSON string.
 
   - `provider_settings.loadakkudoktor_year_energy`: Yearly energy consumption (kWh).
@@ -171,6 +198,27 @@ The `LoadAkkudoktor` provider retrieves generic load data from a local database
 align with the annual energy consumption specified in the `loadakkudoktor_year_energy` configuration
 option.
 
+### LoadVrm Provider
+
+The `LoadVrm` provider retrieves load forecast data from the VRM API by Victron Energy.
+To receive forecasts, the system data must be configured under Dynamic ESS in the VRM portal.
+To query the forecasts, an API token is required, which can also be created in the VRM portal under Preferences.
+This token must be stored in the EOS configuration along with the VRM-Installations-ID.
+
+```python
+    {
+        "load": {
+            "provider": "LoadVrm",
+            "provider_settings": {
+                "load_vrm_token": "dummy-token",
+                "load_vrm_idsite": 12345
+    }
+```
+
+The prediction keys for the load forecast data are:
+
+- `load_mean`: Predicted load mean value (W).
+
 ### LoadImport Provider
 
 The `LoadImport` provider is designed to import load forecast data from a file or a JSON
@@ -184,9 +232,12 @@ The prediction keys for the load forecast data are:
 - `load_mean_adjusted`: Predicted load mean value adjusted by load measurement (W).
 
 The load forecast data must be provided in one of the formats described in
-<project:#prediction-import-providers>. The data source must be given in the `loadimport_file_path`
+<project:#prediction-import-providers>. The data source can be given in the `loadimport_file_path`
 or `loadimport_json` configuration option.
 
+The data may additionally or solely be provided by the
+**PUT** `/v1/prediction/import/LoadImport` endpoint.
+
 ## PV Power Prediction
 
 Prediction keys:
@@ -206,16 +257,25 @@ Configuration options:
   - `provider`: PVForecast provider id of provider to be used.
 
     - `PVForecastAkkudoktor`: Retrieves from Akkudoktor.net.
+    - `PVForecastVrm`: Retrieves data from the VRM API by Victron Energy.
     - `PVForecastImport`: Imports from a file or JSON string.
 
   - `planes[].surface_tilt`: Tilt angle from horizontal plane. Ignored for two-axis tracking.
-  - `planes[].surface_azimuth`: Orientation (azimuth angle) of the (fixed) plane. Clockwise from north (north=0, east=90, south=180, west=270).
+  - `planes[].surface_azimuth`: Orientation (azimuth angle) of the (fixed) plane.
+                                Clockwise from north (north=0, east=90, south=180, west=270).
   - `planes[].userhorizon`: Elevation of horizon in degrees, at equally spaced azimuth clockwise from north.
   - `planes[].peakpower`: Nominal power of PV system in kW.
   - `planes[].pvtechchoice`: PV technology. One of 'crystSi', 'CIS', 'CdTe', 'Unknown'.
-  - `planes[].mountingplace`: Type of mounting for PV system. Options are 'free' for free-standing and 'building' for building-integrated.
+  - `planes[].mountingplace`: Type of mounting for PV system.
+                              Options are 'free' for free-standing and 'building' for building-integrated.
   - `planes[].loss`: Sum of PV system losses in percent
-  - `planes[].trackingtype`: Type of suntracking. 0=fixed, 1=single horizontal axis aligned north-south, 2=two-axis tracking, 3=vertical axis tracking, 4=single horizontal axis aligned east-west, 5=single inclined axis aligned north-south.
+  - `planes[].trackingtype`: Type of suntracking.
+                             0=fixed,
+                             1=single horizontal axis aligned north-south,
+                             2=two-axis tracking,
+                             3=vertical axis tracking,
+                             4=single horizontal axis aligned east-west,
+                             5=single inclined axis aligned north-south.
   - `planes[].optimal_surface_tilt`: Calculate the optimum tilt angle. Ignored for two-axis tracking.
   - `planes[].optimalangles`: Calculate the optimum tilt and azimuth angles. Ignored for two-axis tracking.
   - `planes[].albedo`: Proportion of the light hitting the ground that it reflects back.
@@ -227,39 +287,73 @@ Configuration options:
   - `provider_settings.import_file_path`: Path to the file to import PV forecast data from.
   - `provider_settings.import_json`: JSON string, dictionary of PV forecast value lists.
 
-------
+---
 
-Some of the planes configuration options directly follow the [PVGIS](https://joint-research-centre.ec.europa.eu/photovoltaic-geographical-information-system-pvgis/getting-started-pvgis/pvgis-user-manual_en) nomenclature.
+Detailed definitions taken from
-
+[PVGIS](https://joint-research-centre.ec.europa.eu/photovoltaic-geographical-information-system-pvgis/getting-started-pvgis/pvgis-user-manual_en).
-Detailed definitions taken from **PVGIS**:
 
 - `pvtechchoice`
 
-The performance of PV modules depends on the temperature and on the solar irradiance, but the exact dependence varies between different types of PV modules. At the moment we can estimate the losses due to temperature and irradiance effects for the following types of modules: crystalline silicon cells; thin film modules made from CIS or CIGS and thin film modules made from Cadmium Telluride (CdTe).
+The performance of PV modules depends on the temperature and on the solar irradiance, but the exact
+dependence varies between different types of PV modules. At the moment we can estimate the losses
+due to temperature and irradiance effects for the following types of modules: crystalline silicon
+cells; thin film modules made from CIS or CIGS and thin film modules made from Cadmium Telluride
+(CdTe).
 
-For other technologies (especially various amorphous technologies), this correction cannot be calculated here. If you choose one of the first three options here the calculation of performance will take into account the temperature dependence of the performance of the chosen technology. If you choose the other option (other/unknown), the calculation will assume a loss of 8% of power due to temperature effects (a generic value which has found to be reasonable for temperate climates).
+For other technologies (especially various amorphous technologies), this correction cannot be
+calculated here. If you choose one of the first three options here the calculation of performance
+will take into account the temperature dependence of the performance of the chosen technology. If
+you choose the other option (other/unknown), the calculation will assume a loss of 8% of power due
+to temperature effects (a generic value which has found to be reasonable for temperate climates).
 
-PV power output also depends on the spectrum of the solar radiation. PVGIS can calculate how the variations of the spectrum of sunlight affects the overall energy production from a PV system. At the moment this calculation can be done for crystalline silicon and CdTe modules. Note that this calculation is not yet available when using the NSRDB solar radiation database.
+PV power output also depends on the spectrum of the solar radiation. PVGIS can calculate how the
+variations of the spectrum of sunlight affects the overall energy production from a PV system. At
+the moment this calculation can be done for crystalline silicon and CdTe modules. Note that this
+calculation is not yet available when using the NSRDB solar radiation database.
 
 - `peakpower`
 
-This is the power that the manufacturer declares that the PV array can produce under standard test conditions (STC), which are a constant 1000W of solar irradiation per square meter in the plane of the array, at an array temperature of 25°C. The peak power should be entered in kilowatt-peak (kWp). If you do not know the declared peak power of your modules but instead know the area of the modules and the declared conversion efficiency (in percent), you can calculate the peak power as power = area * efficiency / 100.
+This is the power that the manufacturer declares that the PV array can produce under standard test
+conditions (STC), which are a constant 1000W of solar irradiation per square meter in the plane of
+the array, at an array temperature of 25°C. The peak power should be entered in kilowatt-peak (kWp).
+If you do not know the declared peak power of your modules but instead know the area of the modules
+and the declared conversion efficiency (in percent), you can calculate the peak power as
+power = area \* efficiency / 100.
 
-Bifacial modules: PVGIS doesn't make specific calculations for bifacial modules at present. Users who wish to explore the possible benefits of this technology can input the power value for Bifacial Nameplate Irradiance. This can also be can also be estimated from the front side peak power P_STC value and the bifaciality factor, φ (if reported in the module data sheet) as: P_BNPI  = P_STC * (1 + φ * 0.135). NB this bifacial approach  is not appropriate for BAPV or BIPV installations or for modules mounting on a N-S axis i.e. facing E-W.
+Bifacial modules: PVGIS doesn't make specific calculations for bifacial modules at present. Users
+who wish to explore the possible benefits of this technology can input the power value for Bifacial
+Nameplate Irradiance. This can also be can also be estimated from the front side peak power P_STC
+value and the bifaciality factor, φ (if reported in the module data sheet) as:
+P_BNPI = P_STC \* (1 + φ \* 0.135). NB this bifacial approach is not appropriate for BAPV or BIPV
+installations or for modules mounting on a N-S axis i.e. facing E-W.
 
 - `loss`
 
-The estimated system losses are all the losses in the system, which cause the power actually delivered to the electricity grid to be lower than the power produced by the PV modules. There are several causes for this loss, such as losses in cables, power inverters, dirt (sometimes snow) on the modules and so on. Over the years the modules also tend to lose a bit of their power, so the average yearly output over the lifetime of the system will be a few percent lower than the output in the first years.
+The estimated system losses are all the losses in the system, which cause the power actually
+delivered to the electricity grid to be lower than the power produced by the PV modules. There are
+several causes for this loss, such as losses in cables, power inverters, dirt (sometimes snow) on
+the modules and so on. Over the years the modules also tend to lose a bit of their power, so the
+average yearly output over the lifetime of the system will be a few percent lower than the output
+in the first years.
 
-We have given a default value of 14% for the overall losses. If you have a good idea that your value will be different (maybe due to a really high-efficiency inverter) you may reduce this value a little.
+We have given a default value of 14% for the overall losses. If you have a good idea that your value
+will be different (maybe due to a really high-efficiency inverter) you may reduce this value a little.
 
 - `mountingplace`
 
-For fixed (non-tracking) systems, the way the modules are mounted will have an influence on the temperature of the module, which in turn affects the efficiency. Experiments have shown that if the movement of air behind the modules is restricted, the modules can get considerably hotter (up to 15°C at 1000W/m2 of sunlight).
+For fixed (non-tracking) systems, the way the modules are mounted will have an influence on the
+temperature of the module, which in turn affects the efficiency. Experiments have shown that if the
+movement of air behind the modules is restricted, the modules can get considerably hotter
+(up to 15°C at 1000W/m2 of sunlight).
 
-In PVGIS there are two possibilities: free-standing, meaning that the modules are mounted on a rack with air flowing freely behind the modules; and building- integrated, which means that the modules are completely built into the structure of the wall or roof of a building, with no air movement behind the modules.
+In PVGIS there are two possibilities: free-standing, meaning that the modules are mounted on a rack
+with air flowing freely behind the modules; and building- integrated, which means that the modules
+are completely built into the structure of the wall or roof of a building, with no air movement
+behind the modules.
 
-Some types of mounting are in between these two extremes, for instance if the modules are mounted on a roof with curved roof tiles, allowing air to move behind the modules. In such cases, the performance will be somewhere between the results of the two calculations that are possible here.
+Some types of mounting are in between these two extremes, for instance if the modules are mounted on
+a roof with curved roof tiles, allowing air to move behind the modules. In such cases, the
+performance will be somewhere between the results of the two calculations that are possible here.
 
 - `userhorizon`
 
@@ -271,9 +365,10 @@ represent equal angular distance around the horizon. For instance, if you have 3
 point is due north, the next is 10 degrees east of north, and so on, until the last point, 10
 degrees west of north.
 
-------
+---
 
-Most of the planes configuration options are in line with the [PVLib](https://pvlib-python.readthedocs.io/en/stable/_modules/pvlib/iotools/pvgis.html) definition for PVGIS data.
+Most of the configuration options are in line with the
+[PVLib](https://pvlib-python.readthedocs.io/en/stable/_modules/pvlib/iotools/pvgis.html) definition for PVGIS data.
 
 Detailed definitions from **PVLib** for PVGIS data.
 
@@ -286,7 +381,7 @@ Tilt angle from horizontal plane.
 Orientation (azimuth angle) of the (fixed) plane. Clockwise from north (north=0, east=90, south=180,
 west=270). This is offset 180 degrees from the convention used by PVGIS.
 
-------
+---
 
 ### PVForecastAkkudoktor Provider
 
@@ -301,7 +396,8 @@ The following prediction configuration options of the PV system must be set:
 For each plane of the PV system the following configuration options must be set:
 
 - `pvforecast.planes[].surface_tilt`: Tilt angle from horizontal plane. Ignored for two-axis tracking.
-- `pvforecast.planes[].surface_azimuth`: Orientation (azimuth angle) of the (fixed) plane. Clockwise from north (north=0, east=90, south=180, west=270).
+- `pvforecast.planes[].surface_azimuth`: Orientation (azimuth angle) of the (fixed) plane.
+                                         Clockwise from north (north=0, east=90, south=180, west=270).
 - `pvforecast.planes[].userhorizon`: Elevation of horizon in degrees, at equally spaced azimuth clockwise from north.
 - `pvforecast.planes[].inverter_paco`: AC power rating of the inverter. [W]
 - `pvforecast.planes[].peakpower`: Nominal power of PV system in kW.
@@ -322,34 +418,56 @@ Example:
         "surface_azimuth": -10,
         "surface_tilt": 7,
         "userhorizon": [20, 27, 22, 20],
-        "inverter_paco": 10000,
+        "inverter_paco": 10000
       },
       {
         "peakpower": 4.8,
         "surface_azimuth": -90,
         "surface_tilt": 7,
         "userhorizon": [30, 30, 30, 50],
-        "inverter_paco": 10000,
+        "inverter_paco": 10000
       },
       {
         "peakpower": 1.4,
         "surface_azimuth": -40,
         "surface_tilt": 60,
         "userhorizon": [60, 30, 0, 30],
-        "inverter_paco": 2000,
+        "inverter_paco": 2000
       },
       {
         "peakpower": 1.6,
         "surface_azimuth": 5,
         "surface_tilt": 45,
         "userhorizon": [45, 25, 30, 60],
-        "inverter_paco": 1400,
+        "inverter_paco": 1400
       }
     ]
   }
 }
 ```
 
+### PVForecastVrm Provider
+
+The `PVForecastVrm` provider retrieves pv power forecast data from the VRM API by Victron Energy.
+To receive forecasts, the system data must be configured under Dynamic ESS in the VRM portal.
+To query the forecasts, an API token is required, which can also be created in the VRM portal under Preferences.
+This token must be stored in the EOS configuration along with the VRM-Installations-ID.
+
+```python
+    {
+        "pvforecast": {
+            "provider": "PVForecastVrm",
+            "provider_settings": {
+                "pvforecast_vrm_token": "dummy-token",
+                "pvforecast_vrm_idsite": 12345
+            }
+    }
+```
+
+The prediction keys for the PV forecast data are:
+
+- `pvforecast_dc_power`: Total DC power (W).
+
 ### PVForecastImport Provider
 
 The `PVForecastImport` provider is designed to import PV forecast data from a file or a JSON
@@ -358,13 +476,16 @@ becomes available.
 
 The prediction keys for the PV forecast data are:
 
-- `pvforecast_ac_power`: Total DC power (W).
+- `pvforecast_ac_power`: Total AC power (W).
-- `pvforecast_dc_power`: Total AC power (W).
+- `pvforecast_dc_power`: Total DC power (W).
 
 The PV forecast data must be provided in one of the formats described in
-<project:#prediction-import-providers>. The data source must be given in the
+<project:#prediction-import-providers>. The data source can be given in the
 `import_file_path` or `import_json` configuration option.
 
+The data may additionally or solely be provided by the
+**PUT** `/v1/prediction/import/PVForecastImport` endpoint.
+
 ## Weather Prediction
 
 Prediction keys:
@@ -398,8 +519,8 @@ Configuration options:
 
   - `provider`: Load provider id of provider to be used.
 
-    - `BrightSky`: Retrieves from https://api.brightsky.dev.
+    - `BrightSky`: Retrieves from [BrightSky](https://api.brightsky.dev).
-    - `ClearOutside`: Retrieves from https://clearoutside.com/forecast.
+    - `ClearOutside`: Retrieves from [ClearOutside](https://clearoutside.com/forecast).
     - `LoadImport`: Imports from a file or JSON string.
 
   - `provider_settings.import_file_path`: Path to the file to import weatherforecast data from.
@@ -460,7 +581,7 @@ The `WeatherImport` provider is designed to import weather forecast data from a
 string. An external entity should update the file or JSON string whenever new prediction data
 becomes available.
 
-The prediction keys for the PV forecast data are:
+The prediction keys for the weather forecast data are:
 
 - `weather_dew_point`: Dew Point (°C)
 - `weather_dhi`: Diffuse Horizontal Irradiance (W/m2)
@@ -486,5 +607,8 @@ The prediction keys for the PV forecast data are:
 - `weather_wind_speed`: Wind Speed (kmph)
 
 The PV forecast data must be provided in one of the formats described in
-<project:#prediction-import-providers>. The data source must be given in the
+<project:#prediction-import-providers>. The data source can be given in the
 `import_file_path` or `import_json` configuration option.
+
+The data may additionally or solely be provided by the
+**PUT** `/v1/prediction/import/WeatherImport` endpoint.

docs/develop/getting_started.md

@@ -19,6 +19,7 @@ Install the dependencies in a virtual environment:
 
         python -m venv .venv
         .venv\Scripts\pip install -r requirements.txt
+        .venv\Scripts\pip install -e .
 
   .. tab:: Linux
 
@@ -26,6 +27,7 @@ Install the dependencies in a virtual environment:
 
         python -m venv .venv
         .venv/bin/pip install -r requirements.txt
+        .venv/bin/pip install -e .
 
 ```
 
@@ -73,37 +75,53 @@ This project uses the `EOS.config.json` file to manage configuration settings.
 
 ### Default Configuration
 
-A default configuration file `default.config.json` is provided. This file contains all the necessary configuration keys with their default values.
+A default configuration file `default.config.json` is provided. This file contains all the necessary
+configuration keys with their default values.
 
 ### Custom Configuration
 
 Users can specify a custom configuration directory by setting the environment variable `EOS_DIR`.
 
-- If the directory specified by `EOS_DIR` contains an existing `EOS.config.json` file, the application will use this configuration file.
+- If the directory specified by `EOS_DIR` contains an existing `EOS.config.json` file, the
-- If the `EOS.config.json` file does not exist in the specified directory, the `default.config.json` file will be copied to the directory as `EOS.config.json`.
+  application will use this configuration file.
+- If the `EOS.config.json` file does not exist in the specified directory, the `default.config.json`
+  file will be copied to the directory as `EOS.config.json`.
 
 ### Configuration Updates
 
-If the configuration keys in the `EOS.config.json` file are missing or different from those in `default.config.json`, they will be automatically updated to match the default settings, ensuring that all required keys are present.
+If the configuration keys in the `EOS.config.json` file are missing or different from those in
+`default.config.json`, they will be automatically updated to match the default settings, ensuring
+that all required keys are present.
 
 ## Classes and Functionalities
 
-This project uses various classes to simulate and optimize the components of an energy system. Each class represents a specific aspect of the system, as described below:
+This project uses various classes to simulate and optimize the components of an energy system. Each
+class represents a specific aspect of the system, as described below:
 
-- `Battery`: Simulates a battery storage system, including capacity, state of charge, and now charge and discharge losses.
+- `Battery`: Simulates a battery storage system, including capacity, state of charge, and now
+             charge and discharge losses.
 
-- `PVForecast`: Provides forecast data for photovoltaic generation, based on weather data and historical generation data.
+- `PVForecast`: Provides forecast data for photovoltaic generation, based on weather data and
+                historical generation data.
 
-- `Load`: Models the load requirements of a household or business, enabling the prediction of future energy demand.
+- `Load`: Models the load requirements of a household or business, enabling the prediction of future
+          energy demand.
 
-- `Heatpump`: Simulates a heat pump, including its energy consumption and efficiency under various operating conditions.
+- `Heatpump`: Simulates a heat pump, including its energy consumption and efficiency under various
+              operating conditions.
 
-- `Strompreis`: Provides information on electricity prices, enabling optimization of energy consumption and generation based on tariff information.
+- `Strompreis`: Provides information on electricity prices, enabling optimization of energy
+                consumption and generation based on tariff information.
 
-- `EMS`: The Energy Management System (EMS) coordinates the interaction between the various components, performs optimization, and simulates the operation of the entire energy system.
+- `EMS`: The Energy Management System (EMS) coordinates the interaction between the various
+         components, performs optimization, and simulates the operation of the entire energy system.
 
-These classes work together to enable a detailed simulation and optimization of the energy system. For each class, specific parameters and settings can be adjusted to test different scenarios and strategies.
+These classes work together to enable a detailed simulation and optimization of the energy system.
+For each class, specific parameters and settings can be adjusted to test different scenarios and
+strategies.
 
 ### Customization and Extension
 
-Each class is designed to be easily customized and extended to integrate additional functions or improvements. For example, new methods can be added for more accurate modeling of PV system or battery behavior. Developers are invited to modify and extend the system according to their needs.
+Each class is designed to be easily customized and extended to integrate additional functions or
+improvements. For example, new methods can be added for more accurate modeling of PV system or
+battery behavior. Developers are invited to modify and extend the system according to their needs.

docs/index.md

@@ -8,23 +8,45 @@
 
 ```{toctree}
 :maxdepth: 2
-:caption: 'Contents:'
+:caption: Overview
+
+akkudoktoreos/introduction.md
+
+```
+
+```{toctree}
+:maxdepth: 2
+:caption: Tutorials
 
-welcome.md
-akkudoktoreos/about.md
 develop/getting_started.md
+
+```
+
+```{toctree}
+:maxdepth: 2
+:caption: How-To Guides
+
 develop/CONTRIBUTING.md
+
+```
+
+```{toctree}
+:maxdepth: 2
+:caption: Reference
+
 akkudoktoreos/architecture.md
 akkudoktoreos/configuration.md
 akkudoktoreos/optimization.md
 akkudoktoreos/prediction.md
 akkudoktoreos/measurement.md
 akkudoktoreos/integration.md
+akkudoktoreos/logging.md
 akkudoktoreos/serverapi.md
 akkudoktoreos/api.rst
+
 ```
 
-# Indices and tables
+## Indices and tables
 
 - {ref}`genindex`
 - {ref}`modindex`

docs/pymarkdown.json

@@ -0,0 +1,20 @@
+{
+    "plugins": {
+        "md007": {
+            "enabled": true,
+            "code_block_line_length" : 160
+        },
+        "md013": {
+            "enabled": true,
+            "line_length" : 120
+        },
+        "md041": {
+            "enabled": false
+        }
+    },
+    "extensions": {
+        "front-matter" : {
+            "enabled" : true
+        }
+    }
+}

docs/welcome.md

@@ -1,12 +1,12 @@
 % SPDX-License-Identifier: Apache-2.0
 
-# Welcome to the EOS documentation!
+# Welcome to the EOS documentation
 
 This documentation is continuously written. It is edited via text files in the
 [Markdown/ Markedly Structured Text](https://myst-parser.readthedocs.io/en/latest/index.html)
 markup language and then compiled into a static website/ offline document using the open source tool
-[Sphinx](https://www.sphinx-doc.org) and will someday land on
+[Sphinx](https://www.sphinx-doc.org) and is available on
-[Read the Docs](https://akkudoktoreos.readthedocs.io/en/latest/index.html).
+[Read the Docs](https://akkudoktor-eos.readthedocs.io/en/latest/).
 
 You can contribute to EOS's documentation by opening
 [GitHub issues](https://github.com/Akkudoktor-EOS/EOS/issues)

pyproject.toml

@@ -7,7 +7,7 @@ authors = [
 description = "This project provides a comprehensive solution for simulating and optimizing an energy system based on renewable energy sources. With a focus on photovoltaic (PV) systems, battery storage (batteries), load management (consumer requirements), heat pumps, electric vehicles, and consideration of electricity price data, this system enables forecasting and optimization of energy flow and costs over a specified period."
 readme = "README.md"
 license = {file = "LICENSE"}
-requires-python = ">=3.10"
+requires-python = ">=3.11"
 classifiers = [
     "Development Status :: 3 - Alpha",
     "Programming Language :: Python :: 3",
@@ -43,12 +43,18 @@ profile = "black"
 
 [tool.ruff]
 line-length = 100
+exclude = [
+    "tests",
+    "scripts",
+]
+output-format = "full"
 
 [tool.ruff.lint]
 select = [
     "F",      # Enable all `Pyflakes` rules.
     "D",      # Enable all `pydocstyle` rules, limiting to those that adhere to the
               # Google convention via `convention = "google"`, below.
+    "S",      # Enable all `flake8-bandit` rules.
 ]
 ignore = [
    # Prevent errors due to ruff false positives

requirements-dev.txt

@@ -1,14 +1,15 @@
 -r requirements.txt
-gitpython==3.1.44
+gitlint==0.19.1
-linkify-it-py==2.0.3
+GitPython==3.1.45
-myst-parser==4.0.0
+myst-parser==4.0.1
-sphinx==8.1.3
+sphinx==8.2.3
 sphinx_rtd_theme==3.0.2
 sphinx-tabs==3.4.7
-pytest==8.3.4
+pymarkdownlnt==0.9.32
-pytest-cov==6.0.0
+pytest==8.4.2
+pytest-cov==7.0.0
 pytest-xprocess==1.0.2
 pre-commit
-mypy==1.13.0
+mypy==1.18.2
-types-requests==2.32.0.20241016
+types-requests==2.32.4.20250913
-pandas-stubs==2.2.3.241126
+pandas-stubs==2.3.2.250926

requirements.txt

@@ -1,17 +1,25 @@
-numpy==2.2.2
+cachebox==5.0.2
-numpydantic==1.6.7
+numpy==2.3.3
-matplotlib==3.10.0
+numpydantic==1.6.11
-fastapi[standard]==0.115.7
+matplotlib==3.10.6
-python-fasthtml==0.12.0
+fastapi[standard]==0.115.14
-uvicorn==0.34.0
+python-fasthtml==0.12.29
-scikit-learn==1.6.1
+MonsterUI==1.0.29
-timezonefinder==6.5.8
+markdown-it-py==3.0.0
-deap==1.4.2
+mdit-py-plugins==0.5.0
-requests==2.32.3
+bokeh==3.8.0
-pandas==2.2.3
+uvicorn==0.36.0
-pendulum==3.0.0
+scikit-learn==1.7.2
-platformdirs==4.3.6
+timezonefinder==7.0.2
-pvlib==0.11.2
+deap==1.4.3
-pydantic==2.10.6
+requests==2.32.5
-statsmodels==0.14.4
+pandas==2.3.2
-pydantic-settings==2.7.0
+pendulum==3.1.0
+platformdirs==4.4.0
+psutil==7.1.0
+pvlib==0.13.1
+pydantic==2.11.9
+statsmodels==0.14.5
+pydantic-settings==2.11.0
+linkify-it-py==2.0.3
+loguru==0.7.3

scripts/extract_markdown.py

@@ -150,7 +150,7 @@ def main():
 
     try:
         if args.input_file:
-            with open(args.input_file, "r", encoding="utf8") as f:
+            with open(args.input_file, "r", encoding="utf-8", newline=None) as f:
                 content = f.read()
         elif args.input:
             content = args.input
@@ -164,7 +164,7 @@ def main():
         )
         if args.output_file:
             # Write to file
-            with open(args.output_file, "w", encoding="utf8") as f:
+            with open(args.output_file, "w", encoding="utf-8", newline="\n") as f:
                 f.write(extracted_content)
         else:
             # Write to std output

scripts/generate_config_md.py

@@ -3,22 +3,21 @@
 
 import argparse
 import json
+import os
+import re
 import sys
 import textwrap
 from pathlib import Path
 from typing import Any, Union
 
+from loguru import logger
 from pydantic.fields import ComputedFieldInfo, FieldInfo
 from pydantic_core import PydanticUndefined
 
 from akkudoktoreos.config.config import ConfigEOS, GeneralSettings, get_config
-from akkudoktoreos.core.logging import get_logger
 from akkudoktoreos.core.pydantic import PydanticBaseModel
 from akkudoktoreos.utils.docs import get_model_structure_from_examples
 
-logger = get_logger(__name__)
-
-
 documented_types: set[PydanticBaseModel] = set()
 undocumented_types: dict[PydanticBaseModel, tuple[str, list[str]]] = dict()
 
@@ -86,7 +85,7 @@ def get_default_value(field_info: Union[FieldInfo, ComputedFieldInfo], regular_f
 
 
 def get_type_name(field_type: type) -> str:
-    type_name = str(field_type).replace("typing.", "")
+    type_name = str(field_type).replace("typing.", "").replace("pathlib._local", "pathlib")
     if type_name.startswith("<class"):
         type_name = field_type.__name__
     return type_name
@@ -144,6 +143,7 @@ def generate_config_table_md(
         field_type = field_info.annotation if regular_field else field_info.return_type
         default_value = get_default_value(field_info, regular_field)
         description = field_info.description if field_info.description else "-"
+        deprecated = field_info.deprecated if field_info.deprecated else None
         read_only = "rw" if regular_field else "ro"
         type_name = get_type_name(field_type)
 
@@ -153,6 +153,11 @@ def generate_config_table_md(
                 env_entry = f"| `{prefix}{config_name}` "
             else:
                 env_entry = "| "
+        if deprecated:
+            if isinstance(deprecated, bool):
+                description = "Deprecated!"
+            else:
+                description = deprecated
         table += f"| {field_name} {env_entry}| `{type_name}` | `{read_only}` | `{default_value}` | {description} |\n"
 
         inner_types: dict[PydanticBaseModel, tuple[str, list[str]]] = dict()
@@ -258,7 +263,7 @@ def generate_config_md(config_eos: ConfigEOS) -> str:
     markdown = "# Configuration Table\n\n"
 
     # Generate tables for each top level config
-    for field_name, field_info in config_eos.model_fields.items():
+    for field_name, field_info in config_eos.__class__.model_fields.items():
         field_type = field_info.annotation
         markdown += generate_config_table_md(
             field_type, [field_name], f"EOS_{field_name.upper()}__", True
@@ -278,6 +283,13 @@ def generate_config_md(config_eos: ConfigEOS) -> str:
     markdown = markdown.rstrip("\n")
     markdown += "\n"
 
+    # Assure log path does not leak to documentation
+    markdown = re.sub(
+        r'(?<=["\'])/[^"\']*/output/eos\.log(?=["\'])',
+        '/home/user/.local/share/net.akkudoktoreos.net/output/eos.log',
+        markdown
+    )
+
     return markdown
 
 
@@ -296,9 +308,11 @@ def main():
 
     try:
         config_md = generate_config_md(config_eos)
+        if os.name == "nt":
+            config_md = config_md.replace("\\\\", "/")
         if args.output_file:
             # Write to file
-            with open(args.output_file, "w", encoding="utf8") as f:
+            with open(args.output_file, "w", encoding="utf-8", newline="\n") as f:
                 f.write(config_md)
         else:
             # Write to std output

scripts/generate_openapi.py

@@ -16,6 +16,7 @@ Example:
 
 import argparse
 import json
+import os
 import sys
 
 from fastapi.openapi.utils import get_openapi
@@ -41,6 +42,9 @@ def generate_openapi() -> dict:
     general = openapi_spec["components"]["schemas"]["ConfigEOS"]["properties"]["general"]["default"]
     general["config_file_path"] = "/home/user/.config/net.akkudoktoreos.net/EOS.config.json"
     general["config_folder_path"] = "/home/user/.config/net.akkudoktoreos.net"
+    # Fix file path for logging settings to not show local/test file path
+    logging = openapi_spec["components"]["schemas"]["ConfigEOS"]["properties"]["logging"]["default"]
+    logging["file_path"] = "/home/user/.local/share/net.akkudoktoreos.net/output/eos.log"
 
     return openapi_spec
 
@@ -59,7 +63,7 @@ def main():
         openapi_spec_str = json.dumps(openapi_spec, indent=2)
         if args.output_file:
             # Write to file
-            with open(args.output_file, "w", encoding="utf8") as f:
+            with open(args.output_file, "w", encoding="utf-8", newline="\n") as f:
                 f.write(openapi_spec_str)
         else:
             # Write to std output

scripts/generate_openapi_md.py

@@ -3,6 +3,7 @@
 
 import argparse
 import json
+import os
 import sys
 
 import git
@@ -284,9 +285,11 @@ def main():
 
     try:
         openapi_md = generate_openapi_md()
+        if os.name == "nt":
+            openapi_md = openapi_md.replace("127.0.0.1", "127.0.0.1")
         if args.output_file:
             # Write to file
-            with open(args.output_file, "w", encoding="utf8") as f:
+            with open(args.output_file, "w", encoding="utf-8", newline="\n") as f:
                 f.write(openapi_md)
         else:
             # Write to std output

scripts/gitlint/eos_commit_rules.py

@@ -0,0 +1 @@
+# Placeholder for gitlint user rules (see https://jorisroovers.com/gitlint/latest/rules/user_defined_rules/).

single_test_optimization.py

@@ -12,15 +12,12 @@ import numpy as np
 
 from akkudoktoreos.config.config import get_config
 from akkudoktoreos.core.ems import get_ems
-from akkudoktoreos.core.logging import get_logger
 from akkudoktoreos.optimization.genetic import (
     OptimizationParameters,
     optimization_problem,
 )
 from akkudoktoreos.prediction.prediction import get_prediction
 
-get_logger(__name__, logging_level="DEBUG")
-
 
 def prepare_optimization_real_parameters() -> OptimizationParameters:
     """Prepare and return optimization parameters with real world data.

single_test_prediction.py

@@ -121,30 +121,40 @@ def run_prediction(provider_id: str, verbose: bool = False) -> str:
     # Initialize the oprediction
     config_eos = get_config()
     prediction_eos = get_prediction()
-    if verbose:
-        print(f"\nProvider ID: {provider_id}")
     if provider_id in ("PVForecastAkkudoktor",):
         settings = config_pvforecast()
-        settings["pvforecast"]["provider"] = provider_id
+        forecast = "pvforecast"
     elif provider_id in ("BrightSky", "ClearOutside"):
         settings = config_weather()
-        settings["weather"]["provider"] = provider_id
+        forecast = "weather"
     elif provider_id in ("ElecPriceAkkudoktor",):
         settings = config_elecprice()
-        settings["elecprice"]["provider"] = provider_id
+        forecast = "elecprice"
     elif provider_id in ("LoadAkkudoktor",):
         settings = config_elecprice()
+        forecast = "load"
         settings["load"]["loadakkudoktor_year_energy"] = 1000
-        settings["load"]["provider"] = provider_id
     else:
         raise ValueError(f"Unknown provider '{provider_id}'.")
+    settings[forecast]["provider"] = provider_id
     config_eos.merge_settings_from_dict(settings)
 
+    provider = prediction_eos.provider_by_id(provider_id)
+
     prediction_eos.update_data()
 
     # Return result of prediction
-    provider = prediction_eos.provider_by_id(provider_id)
     if verbose:
+        print(f"\nProvider ID: {provider.provider_id()}")
+        print("----------")
+        print("\nSettings\n----------")
+        print(settings)
+        print("\nProvider\n----------")
+        print(f"elecprice.provider: {config_eos.elecprice.provider}")
+        print(f"load.provider: {config_eos.load.provider}")
+        print(f"pvforecast.provider: {config_eos.pvforecast.provider}")
+        print(f"weather.provider: {config_eos.weather.provider}")
+        print(f"enabled: {provider.enabled()}")
         for key in provider.record_keys:
             print(f"\n{key}\n----------")
             print(f"Array: {provider.key_to_array(key)}")

src/akkudoktoreos/config/config.py

@@ -14,6 +14,7 @@ import shutil
 from pathlib import Path
 from typing import Any, ClassVar, Optional, Type
 
+from loguru import logger
 from platformdirs import user_config_dir, user_data_dir
 from pydantic import Field, computed_field
 from pydantic_settings import (
@@ -22,15 +23,15 @@ from pydantic_settings import (
     PydanticBaseSettingsSource,
     SettingsConfigDict,
 )
-from pydantic_settings.sources import ConfigFileSourceMixin
 
 # settings
 from akkudoktoreos.config.configabc import SettingsBaseModel
+from akkudoktoreos.core.cachesettings import CacheCommonSettings
 from akkudoktoreos.core.coreabc import SingletonMixin
 from akkudoktoreos.core.decorators import classproperty
-from akkudoktoreos.core.logging import get_logger
+from akkudoktoreos.core.emsettings import EnergyManagementCommonSettings
 from akkudoktoreos.core.logsettings import LoggingCommonSettings
-from akkudoktoreos.core.pydantic import merge_models
+from akkudoktoreos.core.pydantic import PydanticModelNestedValueMixin, merge_models
 from akkudoktoreos.devices.settings import DevicesCommonSettings
 from akkudoktoreos.measurement.measurement import MeasurementCommonSettings
 from akkudoktoreos.optimization.optimization import OptimizationCommonSettings
@@ -43,8 +44,6 @@ from akkudoktoreos.server.server import ServerCommonSettings
 from akkudoktoreos.utils.datetimeutil import to_timezone
 from akkudoktoreos.utils.utils import UtilsCommonSettings
 
-logger = get_logger(__name__)
-
 
 def get_absolute_path(
     basepath: Optional[Path | str], subpath: Optional[Path | str]
@@ -79,10 +78,6 @@ class GeneralSettings(SettingsBaseModel):
     Properties:
         timezone (Optional[str]): Computed time zone string based on the specified latitude
             and longitude.
-
-    Validators:
-        validate_latitude (float): Ensures `latitude` is within the range -90 to 90.
-        validate_longitude (float): Ensures `longitude` is within the range -180 to 180.
     """
 
     _config_folder_path: ClassVar[Optional[Path]] = None
@@ -96,10 +91,6 @@ class GeneralSettings(SettingsBaseModel):
         default="output", description="Sub-path for the EOS output data directory."
     )
 
-    data_cache_subpath: Optional[Path] = Field(
-        default="cache", description="Sub-path for the EOS cache data directory."
-    )
-
     latitude: Optional[float] = Field(
         default=52.52,
         ge=-90.0,
@@ -128,12 +119,6 @@ class GeneralSettings(SettingsBaseModel):
         """Compute data_output_path based on data_folder_path."""
         return get_absolute_path(self.data_folder_path, self.data_output_subpath)
 
-    @computed_field  # type: ignore[prop-decorator]
-    @property
-    def data_cache_path(self) -> Optional[Path]:
-        """Compute data_cache_path based on data_folder_path."""
-        return get_absolute_path(self.data_folder_path, self.data_cache_subpath)
-
     @computed_field  # type: ignore[prop-decorator]
     @property
     def config_folder_path(self) -> Optional[Path]:
@@ -147,27 +132,74 @@ class GeneralSettings(SettingsBaseModel):
         return self._config_file_path
 
 
-class SettingsEOS(BaseSettings):
+class SettingsEOS(BaseSettings, PydanticModelNestedValueMixin):
     """Settings for all EOS.
 
     Used by updating the configuration with specific settings only.
     """
 
-    general: Optional[GeneralSettings] = None
+    general: Optional[GeneralSettings] = Field(
-    logging: Optional[LoggingCommonSettings] = None
+        default=None,
-    devices: Optional[DevicesCommonSettings] = None
+        description="General Settings",
-    measurement: Optional[MeasurementCommonSettings] = None
+    )
-    optimization: Optional[OptimizationCommonSettings] = None
+    cache: Optional[CacheCommonSettings] = Field(
-    prediction: Optional[PredictionCommonSettings] = None
+        default=None,
-    elecprice: Optional[ElecPriceCommonSettings] = None
+        description="Cache Settings",
-    load: Optional[LoadCommonSettings] = None
+    )
-    pvforecast: Optional[PVForecastCommonSettings] = None
+    ems: Optional[EnergyManagementCommonSettings] = Field(
-    weather: Optional[WeatherCommonSettings] = None
+        default=None,
-    server: Optional[ServerCommonSettings] = None
+        description="Energy Management Settings",
-    utils: Optional[UtilsCommonSettings] = None
+    )
+    logging: Optional[LoggingCommonSettings] = Field(
+        default=None,
+        description="Logging Settings",
+    )
+    devices: Optional[DevicesCommonSettings] = Field(
+        default=None,
+        description="Devices Settings",
+    )
+    measurement: Optional[MeasurementCommonSettings] = Field(
+        default=None,
+        description="Measurement Settings",
+    )
+    optimization: Optional[OptimizationCommonSettings] = Field(
+        default=None,
+        description="Optimization Settings",
+    )
+    prediction: Optional[PredictionCommonSettings] = Field(
+        default=None,
+        description="Prediction Settings",
+    )
+    elecprice: Optional[ElecPriceCommonSettings] = Field(
+        default=None,
+        description="Electricity Price Settings",
+    )
+    load: Optional[LoadCommonSettings] = Field(
+        default=None,
+        description="Load Settings",
+    )
+    pvforecast: Optional[PVForecastCommonSettings] = Field(
+        default=None,
+        description="PV Forecast Settings",
+    )
+    weather: Optional[WeatherCommonSettings] = Field(
+        default=None,
+        description="Weather Settings",
+    )
+    server: Optional[ServerCommonSettings] = Field(
+        default=None,
+        description="Server Settings",
+    )
+    utils: Optional[UtilsCommonSettings] = Field(
+        default=None,
+        description="Utilities Settings",
+    )
 
     model_config = SettingsConfigDict(
-        env_nested_delimiter="__", nested_model_default_partial_update=True, env_prefix="EOS_"
+        env_nested_delimiter="__",
+        nested_model_default_partial_update=True,
+        env_prefix="EOS_",
+        ignored_types=(classproperty,),
     )
 
 
@@ -178,6 +210,8 @@ class SettingsEOSDefaults(SettingsEOS):
     """
 
     general: GeneralSettings = GeneralSettings()
+    cache: CacheCommonSettings = CacheCommonSettings()
+    ems: EnergyManagementCommonSettings = EnergyManagementCommonSettings()
     logging: LoggingCommonSettings = LoggingCommonSettings()
     devices: DevicesCommonSettings = DevicesCommonSettings()
     measurement: MeasurementCommonSettings = MeasurementCommonSettings()
@@ -243,6 +277,16 @@ class ConfigEOS(SingletonMixin, SettingsEOSDefaults):
     ENCODING: ClassVar[str] = "UTF-8"
     CONFIG_FILE_NAME: ClassVar[str] = "EOS.config.json"
 
+    def __hash__(self) -> int:
+        # ConfigEOS is a singleton
+        return hash("config_eos")
+
+    def __eq__(self, other: Any) -> bool:
+        if not isinstance(other, ConfigEOS):
+            return False
+        # ConfigEOS is a singleton
+        return True
+
     @classmethod
     def settings_customise_sources(
         cls,
@@ -281,7 +325,13 @@ class ConfigEOS(SingletonMixin, SettingsEOSDefaults):
             - This method logs a warning if the default configuration file cannot be copied.
             - It ensures that a fallback to the default configuration file is always possible.
         """
-        file_settings: Optional[ConfigFileSourceMixin] = None
+        setting_sources = [
+            init_settings,
+            env_settings,
+            dotenv_settings,
+        ]
+
+        file_settings: Optional[JsonConfigSettingsSource] = None
         config_file, exists = cls._get_config_file_path()
         config_dir = config_file.parent
         if not exists:
@@ -292,28 +342,27 @@ class ConfigEOS(SingletonMixin, SettingsEOSDefaults):
                 logger.warning(f"Could not copy default config: {exc}. Using default config...")
                 config_file = cls.config_default_file_path
                 config_dir = config_file.parent
+        try:
             file_settings = JsonConfigSettingsSource(settings_cls, json_file=config_file)
+            setting_sources.append(file_settings)
+        except Exception as e:
+            logger.error(
+                f"Error reading config file '{config_file}' (falling back to default config): {e}"
+            )
         default_settings = JsonConfigSettingsSource(
             settings_cls, json_file=cls.config_default_file_path
         )
         GeneralSettings._config_folder_path = config_dir
         GeneralSettings._config_file_path = config_file
 
-        return (
+        setting_sources.append(default_settings)
-            init_settings,
+        return tuple(setting_sources)
-            env_settings,
-            dotenv_settings,
-            file_settings,
-            default_settings,
-        )
 
-    @classmethod
     @classproperty
     def config_default_file_path(cls) -> Path:
         """Compute the default config file path."""
         return cls.package_root_path.joinpath("data/default.config.json")
 
-    @classmethod
     @classproperty
     def package_root_path(cls) -> Path:
         """Compute the package root path."""
@@ -327,13 +376,24 @@ class ConfigEOS(SingletonMixin, SettingsEOSDefaults):
         """
         if hasattr(self, "_initialized"):
             return
-        super().__init__(*args, **kwargs)
+        self._setup(self, *args, **kwargs)
-        self._create_initial_config_file()
-        self._update_data_folder_path()
 
     def _setup(self, *args: Any, **kwargs: Any) -> None:
         """Re-initialize global settings."""
+        # Check for config file content/ version type
+        config_file, exists = self._get_config_file_path()
+        if exists:
+            with config_file.open("r", encoding="utf-8", newline=None) as f_config:
+                config_txt = f_config.read()
+                if '"directories": {' in config_txt or '"server_eos_host": ' in config_txt:
+                    error_msg = f"Configuration file '{config_file}' is outdated. Please remove or update  manually."
+                    logger.error(error_msg)
+                    raise ValueError(error_msg)
+        # Assure settings base knows EOS configuration
+        SettingsBaseModel.config = self
+        # (Re-)load settings
         SettingsEOSDefaults.__init__(self, *args, **kwargs)
+        # Init config file and data folder pathes
         self._create_initial_config_file()
         self._update_data_folder_path()
 
@@ -347,7 +407,9 @@ class ConfigEOS(SingletonMixin, SettingsEOSDefaults):
             ValueError: If the `settings` is not a `SettingsEOS` instance.
         """
         if not isinstance(settings, SettingsEOS):
-            raise ValueError(f"Settings must be an instance of SettingsEOS: '{settings}'.")
+            error_msg = f"Settings must be an instance of SettingsEOS: '{settings}'."
+            logger.error(error_msg)
+            raise ValueError(error_msg)
 
         self.merge_settings_from_dict(settings.model_dump(exclude_none=True, exclude_unset=True))
 
@@ -383,7 +445,7 @@ class ConfigEOS(SingletonMixin, SettingsEOSDefaults):
         if self.general.config_file_path and not self.general.config_file_path.exists():
             self.general.config_file_path.parent.mkdir(parents=True, exist_ok=True)
             try:
-                with open(self.general.config_file_path, "w") as f:
+                with self.general.config_file_path.open("w", encoding="utf-8", newline="\n") as f:
                     f.write(self.model_dump_json(indent=4))
             except Exception as e:
                 logger.error(
@@ -424,10 +486,10 @@ class ConfigEOS(SingletonMixin, SettingsEOSDefaults):
 
     @classmethod
     def _get_config_file_path(cls) -> tuple[Path, bool]:
-        """Finds the a valid configuration file or returns the desired path for a new config file.
+        """Find a valid configuration file or return the desired path for a new config file.
 
         Returns:
-            tuple[Path, bool]: The path to the configuration directory and if there is already a config file there
+            tuple[Path, bool]: The path to the configuration file and if there is already a config file there
         """
         config_dirs = []
         env_base_dir = os.getenv(cls.EOS_DIR)
@@ -436,7 +498,7 @@ class ConfigEOS(SingletonMixin, SettingsEOSDefaults):
         logger.debug(f"Environment config dir: '{env_dir}'")
         if env_dir is not None:
             config_dirs.append(env_dir.resolve())
-        config_dirs.append(Path(user_config_dir(cls.APP_NAME)))
+        config_dirs.append(Path(user_config_dir(cls.APP_NAME, cls.APP_AUTHOR)))
         config_dirs.append(Path.cwd())
         for cdir in config_dirs:
             cfile = cdir.joinpath(cls.CONFIG_FILE_NAME)
@@ -455,8 +517,8 @@ class ConfigEOS(SingletonMixin, SettingsEOSDefaults):
         """
         if not self.general.config_file_path:
             raise ValueError("Configuration file path unknown.")
-        with self.general.config_file_path.open("w", encoding=self.ENCODING) as f_out:
+        with self.general.config_file_path.open("w", encoding="utf-8", newline="\n") as f_out:
-            json_str = super().model_dump_json()
+            json_str = super().model_dump_json(indent=4)
             f_out.write(json_str)
 
     def update(self) -> None:

src/akkudoktoreos/config/configabc.py

@@ -1,9 +1,12 @@
 """Abstract and base classes for configuration."""
 
+from typing import Any, ClassVar
+
 from akkudoktoreos.core.pydantic import PydanticBaseModel
 
 
 class SettingsBaseModel(PydanticBaseModel):
     """Base model class for all settings configurations."""
 
-    pass
+    # EOS configuration - set by ConfigEOS
+    config: ClassVar[Any] = None

src/akkudoktoreos/core/cache.py

@@ -1,32 +1,14 @@
-"""Class for in-memory managing of cache files.
+"""In-memory and file caching.
 
-The `CacheFileStore` class is a singleton-based, thread-safe key-value store for managing
+Decorators and classes for caching results of computations,
-temporary file objects, allowing the creation, retrieval, and management of cache files.
+both in memory (using an LRU cache) and in temporary files. It also includes
-
+mechanisms for managing cache file expiration and retrieval.
-Classes:
---------
-- CacheFileStore: A thread-safe, singleton class for in-memory managing of file-like cache objects.
-- CacheFileStoreMeta: Metaclass for enforcing the singleton behavior in `CacheFileStore`.
-
-Example usage:
---------------
-    # CacheFileStore usage
-    >>> cache_store = CacheFileStore()
-    >>> cache_store.create('example_key')
-    >>> cache_file = cache_store.get('example_key')
-    >>> cache_file.write('Some data')
-    >>> cache_file.seek(0)
-    >>> print(cache_file.read())  # Output: 'Some data'
-
-Notes:
-------
-- Cache files are automatically associated with the current date unless specified.
 """
 
-from __future__ import annotations
+import functools
-
 import hashlib
 import inspect
+import json
 import os
 import pickle
 import tempfile
@@ -35,8 +17,8 @@ from typing import (
     IO,
     Any,
     Callable,
+    ClassVar,
     Dict,
-    Generic,
     List,
     Literal,
     Optional,
@@ -44,29 +26,223 @@ from typing import (
     TypeVar,
 )
 
+import cachebox
+from loguru import logger
 from pendulum import DateTime, Duration
-from pydantic import BaseModel, ConfigDict, Field
+from pydantic import Field
 
-from akkudoktoreos.core.coreabc import ConfigMixin
+from akkudoktoreos.core.coreabc import ConfigMixin, SingletonMixin
-from akkudoktoreos.core.logging import get_logger
+from akkudoktoreos.core.pydantic import PydanticBaseModel
 from akkudoktoreos.utils.datetimeutil import compare_datetimes, to_datetime, to_duration
 
-logger = get_logger(__name__)
+# ---------------------------------
+# In-Memory Caching Functionality
+# ---------------------------------
+
+# Define a type variable for methods and functions
+TCallable = TypeVar("TCallable", bound=Callable[..., Any])
 
 
-T = TypeVar("T")
+def cache_until_update_store_callback(event: int, key: Any, value: Any) -> None:
+    """Calback function for CacheUntilUpdateStore."""
+    CacheUntilUpdateStore.last_event = event
+    CacheUntilUpdateStore.last_key = key
+    CacheUntilUpdateStore.last_value = value
+    if event == cachebox.EVENT_MISS:
+        CacheUntilUpdateStore.miss_count += 1
+    elif event == cachebox.EVENT_HIT:
+        CacheUntilUpdateStore.hit_count += 1
+    else:
+        # unreachable code
+        raise NotImplementedError
+
+
+class CacheUntilUpdateStore(SingletonMixin):
+    """Singleton-based in-memory LRU (Least Recently Used) cache.
+
+    This cache is shared across the application to store results of decorated
+    methods or functions until the next EMS (Energy Management System) update.
+
+    The cache uses an LRU eviction strategy, storing up to 100 items, with the oldest
+    items being evicted once the cache reaches its capacity.
+    """
+
+    cache: ClassVar[cachebox.LRUCache] = cachebox.LRUCache(maxsize=100, iterable=None, capacity=100)
+    last_event: ClassVar[Optional[int]] = None
+    last_key: ClassVar[Any] = None
+    last_value: ClassVar[Any] = None
+    hit_count: ClassVar[int] = 0
+    miss_count: ClassVar[int] = 0
+
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
+        """Initializes the `CacheUntilUpdateStore` instance with default parameters.
+
+        The cache uses an LRU eviction strategy with a maximum size of 100 items.
+        This cache is a singleton, meaning only one instance will exist throughout
+        the application lifecycle.
+
+        Example:
+            >>> cache = CacheUntilUpdateStore()
+        """
+        if hasattr(self, "_initialized"):
+            return
+        super().__init__(*args, **kwargs)
+
+    def __getattr__(self, name: str) -> Any:
+        """Propagates method calls to the cache object.
+
+        This method allows you to call methods on the underlying cache object,
+        and it will delegate the call to the cache's corresponding method.
+
+        Args:
+            name (str): The name of the method being called.
+
+        Returns:
+            Callable: A method bound to the cache object.
+
+        Raises:
+            AttributeError: If the cache object does not have the requested method.
+
+        Example:
+            >>> result = cache.get("key")
+        """
+        # This will return a method of the target cache, or raise an AttributeError
+        target_attr = getattr(self.cache, name)
+        if callable(target_attr):
+            return target_attr
+        else:
+            return target_attr
+
+    def __getitem__(self, key: Any) -> Any:
+        """Retrieves an item from the cache by its key.
+
+        Args:
+            key (Any): The key used for subscripting to retrieve an item.
+
+        Returns:
+            Any: The value corresponding to the key in the cache.
+
+        Raises:
+            KeyError: If the key does not exist in the cache.
+
+        Example:
+            >>> value = cache["user_data"]
+        """
+        return CacheUntilUpdateStore.cache[key]
+
+    def __setitem__(self, key: Any, value: Any) -> None:
+        """Stores an item in the cache.
+
+        Args:
+            key (Any): The key used to store the item in the cache.
+            value (Any): The value to store.
+
+        Example:
+            >>> cache["user_data"] = {"name": "Alice", "age": 30}
+        """
+        CacheUntilUpdateStore.cache[key] = value
+
+    def __len__(self) -> int:
+        """Returns the number of items in the cache."""
+        return len(CacheUntilUpdateStore.cache)
+
+    def __repr__(self) -> str:
+        """Provides a string representation of the CacheUntilUpdateStore object."""
+        return repr(CacheUntilUpdateStore.cache)
+
+    def clear(self) -> None:
+        """Clears the cache, removing all stored items.
+
+        This method propagates the `clear` method call to the underlying cache object,
+        ensuring that the cache is emptied when necessary (e.g., at the end of the energy
+        management system run).
+
+        Example:
+            >>> cache.clear()
+        """
+        if hasattr(self.cache, "clear") and callable(getattr(self.cache, "clear")):
+            CacheUntilUpdateStore.cache.clear()
+            CacheUntilUpdateStore.last_event = None
+            CacheUntilUpdateStore.last_key = None
+            CacheUntilUpdateStore.last_value = None
+            CacheUntilUpdateStore.miss_count = 0
+            CacheUntilUpdateStore.hit_count = 0
+        else:
+            raise AttributeError(f"'{self.cache.__class__.__name__}' object has no method 'clear'")
+
+
+def cachemethod_until_update(method: TCallable) -> TCallable:
+    """Decorator for in memory caching the result of an instance method.
+
+    This decorator caches the method's result in `CacheUntilUpdateStore`, ensuring
+    that subsequent calls with the same arguments return the cached result until the
+    next EMS update cycle.
+
+    Args:
+        method (Callable): The instance method to be decorated.
+
+    Returns:
+        Callable: The wrapped method with caching functionality.
+
+    Example:
+        >>> class MyClass:
+        >>>     @cachemethod_until_update
+        >>>     def expensive_method(self, param: str) -> str:
+        >>>         # Perform expensive computation
+        >>>         return f"Computed {param}"
+    """
+
+    @cachebox.cachedmethod(
+        cache=CacheUntilUpdateStore().cache, callback=cache_until_update_store_callback
+    )
+    @functools.wraps(method)
+    def wrapper(self: Any, *args: Any, **kwargs: Any) -> Any:
+        result = method(self, *args, **kwargs)
+        return result
+
+    return wrapper
+
+
+def cache_until_update(func: TCallable) -> TCallable:
+    """Decorator for in memory caching the result of a standalone function.
+
+    This decorator caches the function's result in `CacheUntilUpdateStore`, ensuring
+    that subsequent calls with the same arguments return the cached result until the
+    next EMS update cycle.
+
+    Args:
+        func (Callable): The function to be decorated.
+
+    Returns:
+        Callable: The wrapped function with caching functionality.
+
+    Example:
+        >>> @cache_until_next_update
+        >>> def expensive_function(param: str) -> str:
+        >>>     # Perform expensive computation
+        >>>     return f"Computed {param}"
+    """
+
+    @cachebox.cached(
+        cache=CacheUntilUpdateStore().cache, callback=cache_until_update_store_callback
+    )
+    @functools.wraps(func)
+    def wrapper(*args: Any, **kwargs: Any) -> Any:
+        result = func(*args, **kwargs)
+        return result
+
+    return wrapper
+
+
+# ---------------------------------
+# Cache File Management
+# ---------------------------------
+
 Param = ParamSpec("Param")
 RetType = TypeVar("RetType")
 
 
-class CacheFileRecord(BaseModel):
+class CacheFileRecord(PydanticBaseModel):
-    # Enable custom serialization globally in config
-    model_config = ConfigDict(
-        arbitrary_types_allowed=True,
-        use_enum_values=True,
-        validate_assignment=True,
-    )
-
     cache_file: Any = Field(..., description="File descriptor of the cache file.")
     until_datetime: DateTime = Field(..., description="Datetime until the cache file is valid.")
     ttl_duration: Optional[Duration] = Field(
@@ -74,24 +250,7 @@ class CacheFileRecord(BaseModel):
     )
 
 
-class CacheFileStoreMeta(type, Generic[T]):
+class CacheFileStore(ConfigMixin, SingletonMixin):
-    """A thread-safe implementation of CacheFileStore."""
-
-    _instances: dict[CacheFileStoreMeta[T], T] = {}
-
-    _lock: threading.Lock = threading.Lock()
-    """Lock object to synchronize threads on first access to CacheFileStore."""
-
-    def __call__(cls) -> T:
-        """Return CacheFileStore instance."""
-        with cls._lock:
-            if cls not in cls._instances:
-                instance = super().__call__()
-                cls._instances[cls] = instance
-        return cls._instances[cls]
-
-
-class CacheFileStore(ConfigMixin, metaclass=CacheFileStoreMeta):
     """A key-value store that manages file-like tempfile objects to be used as cache files.
 
     Cache files are associated with a date. If no date is specified, the cache files are
@@ -105,7 +264,7 @@ class CacheFileStore(ConfigMixin, metaclass=CacheFileStoreMeta):
         store (dict): A dictionary that holds the in-memory cache file objects
                       with their associated keys and dates.
 
-    Example usage:
+    Example:
         >>> cache_store = CacheFileStore()
         >>> cache_store.create('example_file')
         >>> cache_file = cache_store.get('example_file')
@@ -114,14 +273,18 @@ class CacheFileStore(ConfigMixin, metaclass=CacheFileStoreMeta):
         >>> print(cache_file.read())  # Output: 'Some data'
     """
 
-    def __init__(self) -> None:
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
         """Initializes the CacheFileStore instance.
 
         This constructor sets up an empty key-value store (a dictionary) where each key
         corresponds to a cache file that is associated with a given key and an optional date.
         """
+        if hasattr(self, "_initialized"):
+            return
         self._store: Dict[str, CacheFileRecord] = {}
-        self._store_lock = threading.Lock()
+        self._store_lock = threading.RLock()
+        self._store_file = self.config.cache.path().joinpath("cachefilestore.json")
+        super().__init__(*args, **kwargs)
 
     def _until_datetime_by_options(
         self,
@@ -329,9 +492,9 @@ class CacheFileStore(ConfigMixin, metaclass=CacheFileStoreMeta):
                 # File already available
                 cache_file_obj = cache_item.cache_file
             else:
-                self.config.general.data_cache_path.mkdir(parents=True, exist_ok=True)
+                self.config.cache.path().mkdir(parents=True, exist_ok=True)
                 cache_file_obj = tempfile.NamedTemporaryFile(
-                    mode=mode, delete=delete, suffix=suffix, dir=self.config.general.data_cache_path
+                    mode=mode, delete=delete, suffix=suffix, dir=self.config.cache.path()
                 )
                 self._store[cache_file_key] = CacheFileRecord(
                     cache_file=cache_file_obj,
@@ -502,7 +665,7 @@ class CacheFileStore(ConfigMixin, metaclass=CacheFileStoreMeta):
 
     def clear(
         self,
-        clear_all: bool = False,
+        clear_all: Optional[bool] = None,
         before_datetime: Optional[Any] = None,
     ) -> None:
         """Deletes all cache files or those expiring before `before_datetime`.
@@ -516,8 +679,6 @@ class CacheFileStore(ConfigMixin, metaclass=CacheFileStoreMeta):
         Raises:
             OSError: If there's an error during file deletion.
         """
-        delete_keys = []  # List of keys to delete, prevent deleting when traversing the store
-
         # Some weired logic to prevent calling to_datetime on clear_all.
         # Clear_all may be set on __del__. At this time some info for to_datetime will
         # not be available anymore.
@@ -528,6 +689,8 @@ class CacheFileStore(ConfigMixin, metaclass=CacheFileStoreMeta):
                 before_datetime = to_datetime(before_datetime)
 
         with self._store_lock:  # Synchronize access to _store
+            delete_keys = []  # List of keys to delete, prevent deleting when traversing the store
+
             for cache_file_key, cache_item in self._store.items():
                 # Some weired logic to prevent calling to_datetime on clear_all.
                 # Clear_all may be set on __del__. At this time some info for to_datetime will
@@ -566,6 +729,89 @@ class CacheFileStore(ConfigMixin, metaclass=CacheFileStoreMeta):
             for delete_key in delete_keys:
                 del self._store[delete_key]
 
+    def current_store(self) -> dict:
+        """Current state of the store.
+
+        Returns:
+            data (dict): current cache management data.
+        """
+        with self._store_lock:
+            store_current = {}
+            for key, record in self._store.items():
+                ttl_duration = record.ttl_duration
+                if ttl_duration:
+                    ttl_duration = ttl_duration.total_seconds()
+                store_current[key] = {
+                    # Convert file-like objects to file paths for serialization
+                    "cache_file": self._get_file_path(record.cache_file),
+                    "mode": record.cache_file.mode,
+                    "until_datetime": to_datetime(record.until_datetime, as_string=True),
+                    "ttl_duration": ttl_duration,
+                }
+            return store_current
+
+    def save_store(self) -> dict:
+        """Saves the current state of the store to a file.
+
+        Returns:
+            data (dict): cache management data that was saved.
+        """
+        with self._store_lock:
+            self._store_file.parent.mkdir(parents=True, exist_ok=True)
+            store_to_save = self.current_store()
+            with self._store_file.open("w", encoding="utf-8", newline="\n") as f:
+                try:
+                    json.dump(store_to_save, f, indent=4)
+                except Exception as e:
+                    logger.error(f"Error saving cache file store: {e}")
+            return store_to_save
+
+    def load_store(self) -> dict:
+        """Loads the state of the store from a file.
+
+        Returns:
+            data (dict): cache management data that was loaded.
+        """
+        with self._store_lock:
+            store_loaded = {}
+            if self._store_file.exists():
+                with self._store_file.open("r", encoding="utf-8", newline=None) as f:
+                    try:
+                        store_to_load = json.load(f)
+                    except Exception as e:
+                        logger.error(
+                            f"Error loading cache file store: {e}\n"
+                            + f"Deleting the store file {self._store_file}."
+                        )
+                        self._store_file.unlink()
+                        return {}
+                    for key, record in store_to_load.items():
+                        if record is None:
+                            continue
+                        if key in self._store.keys():
+                            # Already available - do not overwrite by record from file
+                            continue
+                        try:
+                            cache_file_obj = open(
+                                record["cache_file"], "rb+" if "b" in record["mode"] else "r+"
+                            )
+                        except Exception as e:
+                            cache_file_record = record["cache_file"]
+                            logger.warning(f"Can not open cache file '{cache_file_record}': {e}")
+                            continue
+                        ttl_duration = record["ttl_duration"]
+                        if ttl_duration:
+                            ttl_duration = to_duration(float(record["ttl_duration"]))
+                        self._store[key] = CacheFileRecord(
+                            cache_file=cache_file_obj,
+                            until_datetime=record["until_datetime"],
+                            ttl_duration=ttl_duration,
+                        )
+                        cache_file_obj.seek(0)
+                        # Remember newly loaded
+                        store_loaded[key] = record
+            return store_loaded
+
 
 def cache_in_file(
     ignore_params: List[str] = [],
@@ -707,7 +953,7 @@ def cache_in_file(
                     logger.debug("Used cache file for function: " + func.__name__)
                     cache_file.seek(0)
                     if "b" in mode:
-                        result = pickle.load(cache_file)
+                        result = pickle.load(cache_file)  # noqa: S301
                     else:
                         result = cache_file.read()
                 except Exception as e:

src/akkudoktoreos/core/cachesettings.py

@@ -0,0 +1,32 @@
+"""Settings for caching.
+
+Kept in an extra module to avoid cyclic dependencies on package import.
+"""
+
+from pathlib import Path
+from typing import Optional
+
+from pydantic import Field
+
+from akkudoktoreos.config.configabc import SettingsBaseModel
+
+
+class CacheCommonSettings(SettingsBaseModel):
+    """Cache Configuration."""
+
+    subpath: Optional[Path] = Field(
+        default="cache", description="Sub-path for the EOS cache data directory."
+    )
+
+    cleanup_interval: float = Field(
+        default=5 * 60, description="Intervall in seconds for EOS file cache cleanup."
+    )
+
+    # Do not make this a pydantic computed field. The pydantic model must be fully initialized
+    # to have access to config.general, which may not be the case if it is a computed field.
+    def path(self) -> Optional[Path]:
+        """Compute cache path based on general.data_folder_path."""
+        data_cache_path = self.config.general.data_folder_path
+        if data_cache_path is None or self.subpath is None:
+            return None
+        return data_cache_path.joinpath(self.subpath)

src/akkudoktoreos/core/coreabc.py

@@ -13,13 +13,10 @@ Classes:
 import threading
 from typing import Any, ClassVar, Dict, Optional, Type
 
+from loguru import logger
 from pendulum import DateTime
 from pydantic import computed_field
 
-from akkudoktoreos.core.logging import get_logger
-
-logger = get_logger(__name__)
-
 config_eos: Any = None
 measurement_eos: Any = None
 prediction_eos: Any = None
@@ -265,10 +262,12 @@ class SingletonMixin:
         class MySingletonModel(SingletonMixin, PydanticBaseModel):
             name: str
 
-            # implement __init__ to avoid re-initialization of parent class PydanticBaseModel:
+            # implement __init__ to avoid re-initialization of parent classes:
             def __init__(self, *args: Any, **kwargs: Any) -> None:
                 if hasattr(self, "_initialized"):
                     return
+                # Your initialisation here
+                ...
                 super().__init__(*args, **kwargs)
 
         instance1 = MySingletonModel(name="Instance 1")

src/akkudoktoreos/core/dataabc.py

@@ -19,6 +19,7 @@ from typing import Any, Dict, Iterator, List, Optional, Tuple, Type, Union, over
 import numpy as np
 import pandas as pd
 import pendulum
+from loguru import logger
 from numpydantic import NDArray, Shape
 from pendulum import DateTime, Duration
 from pydantic import (
@@ -31,7 +32,6 @@ from pydantic import (
 )
 
 from akkudoktoreos.core.coreabc import ConfigMixin, SingletonMixin, StartMixin
-from akkudoktoreos.core.logging import get_logger
 from akkudoktoreos.core.pydantic import (
     PydanticBaseModel,
     PydanticDateTimeData,
@@ -39,8 +39,6 @@ from akkudoktoreos.core.pydantic import (
 )
 from akkudoktoreos.utils.datetimeutil import compare_datetimes, to_datetime, to_duration
 
-logger = get_logger(__name__)
-
 
 class DataBase(ConfigMixin, StartMixin, PydanticBaseModel):
     """Base class for handling generic data.
@@ -811,7 +809,8 @@ class DataSequence(DataBase, MutableSequence):
         dates, values = self.key_to_lists(
             key=key, start_datetime=start_datetime, end_datetime=end_datetime, dropna=dropna
         )
-        return pd.Series(data=values, index=pd.DatetimeIndex(dates), name=key)
+        series = pd.Series(data=values, index=pd.DatetimeIndex(dates), name=key)
+        return series
 
     def key_from_series(self, key: str, series: pd.Series) -> None:
         """Update the DataSequence from a Pandas Series.
@@ -953,6 +952,44 @@ class DataSequence(DataBase, MutableSequence):
         array = resampled.values
         return array
 
+    def to_dataframe(
+        self,
+        start_datetime: Optional[DateTime] = None,
+        end_datetime: Optional[DateTime] = None,
+    ) -> pd.DataFrame:
+        """Converts the sequence of DataRecord instances into a Pandas DataFrame.
+
+        Args:
+            start_datetime (Optional[datetime]): The lower bound for filtering (inclusive).
+                Defaults to the earliest possible datetime if None.
+            end_datetime (Optional[datetime]): The upper bound for filtering (exclusive).
+                Defaults to the latest possible datetime if None.
+
+        Returns:
+            pd.DataFrame: A DataFrame containing the filtered data from all records.
+        """
+        if not self.records:
+            return pd.DataFrame()  # Return empty DataFrame if no records exist
+
+        # Use filter_by_datetime to get filtered records
+        filtered_records = self.filter_by_datetime(start_datetime, end_datetime)
+
+        # Convert filtered records to a dictionary list
+        data = [record.model_dump() for record in filtered_records]
+
+        # Convert to DataFrame
+        df = pd.DataFrame(data)
+        if df.empty:
+            return df
+
+        # Ensure `date_time` column exists and use it for the index
+        if not "date_time" in df.columns:
+            error_msg = f"Cannot create dataframe: no `date_time` column in `{df}`."
+            logger.error(error_msg)
+            raise TypeError(error_msg)
+        df.index = pd.DatetimeIndex(df["date_time"])
+        return df
+
     def sort_by_datetime(self, reverse: bool = False) -> None:
         """Sort the DataRecords in the sequence by their date_time attribute.
 
@@ -1465,7 +1502,7 @@ class DataImportMixin:
                 error_msg += f"Field: {field}\nError: {message}\nType: {error_type}\n"
             logger.debug(f"PydanticDateTimeDataFrame import: {error_msg}")
 
-        # Try dictionary with special keys start_datetime and intervall
+        # Try dictionary with special keys start_datetime and interval
         try:
             import_data = PydanticDateTimeData.model_validate_json(json_str)
             self.import_from_dict(import_data.to_dict())
@@ -1525,7 +1562,7 @@ class DataImportMixin:
             and `key_prefix = "load"`, only the "load_mean" key will be processed even though
             both keys are in the record.
         """
-        with import_file_path.open("r") as import_file:
+        with import_file_path.open("r", encoding="utf-8", newline=None) as import_file:
             import_str = import_file.read()
         self.import_from_json(
             import_str, key_prefix=key_prefix, start_datetime=start_datetime, interval=interval
@@ -1807,6 +1844,88 @@ class DataContainer(SingletonMixin, DataBase, MutableMapping):
 
         return array
 
+    def keys_to_dataframe(
+        self,
+        keys: list[str],
+        start_datetime: Optional[DateTime] = None,
+        end_datetime: Optional[DateTime] = None,
+        interval: Optional[Any] = None,  # Duration assumed
+        fill_method: Optional[str] = None,
+    ) -> pd.DataFrame:
+        """Retrieve a dataframe indexed by fixed time intervals for specified keys from the data in each DataProvider.
+
+        Generates a pandas DataFrame using the NumPy arrays for each specified key, ensuring a common time index..
+
+        Args:
+            keys (list[str]): A list of field names to retrieve.
+            start_datetime (datetime, optional): Start date for filtering records (inclusive).
+            end_datetime (datetime, optional): End date for filtering records (exclusive).
+            interval (duration, optional): The fixed time interval. Defaults to 1 hour.
+            fill_method (str, optional): Method to handle missing values during resampling.
+                - 'linear': Linearly interpolate missing values (for numeric data only).
+                - 'ffill': Forward fill missing values.
+                - 'bfill': Backward fill missing values.
+                - 'none': Defaults to 'linear' for numeric values, otherwise 'ffill'.
+
+        Returns:
+            pd.DataFrame: A DataFrame where each column represents a key's array with a common time index.
+
+        Raises:
+            KeyError: If no valid data is found for any of the requested keys.
+            ValueError: If any retrieved array has a different time index than the first one.
+        """
+        # Ensure datetime objects are normalized
+        start_datetime = to_datetime(start_datetime, to_maxtime=False) if start_datetime else None
+        end_datetime = to_datetime(end_datetime, to_maxtime=False) if end_datetime else None
+        if interval is None:
+            interval = to_duration("1 hour")
+        if start_datetime is None:
+            # Take earliest datetime of all providers that are enabled
+            for provider in self.enabled_providers:
+                if start_datetime is None:
+                    start_datetime = provider.min_datetime
+                elif (
+                    provider.min_datetime
+                    and compare_datetimes(provider.min_datetime, start_datetime).lt
+                ):
+                    start_datetime = provider.min_datetime
+        if end_datetime is None:
+            # Take latest datetime of all providers that are enabled
+            for provider in self.enabled_providers:
+                if end_datetime is None:
+                    end_datetime = provider.max_datetime
+                elif (
+                    provider.max_datetime
+                    and compare_datetimes(provider.max_datetime, end_datetime).gt
+                ):
+                    end_datetime = provider.min_datetime
+            if end_datetime:
+                end_datetime.add(seconds=1)
+
+        # Create a DatetimeIndex based on start, end, and interval
+        reference_index = pd.date_range(
+            start=start_datetime, end=end_datetime, freq=interval, inclusive="left"
+        )
+
+        data = {}
+        for key in keys:
+            try:
+                array = self.key_to_array(key, start_datetime, end_datetime, interval, fill_method)
+
+                if len(array) != len(reference_index):
+                    raise ValueError(
+                        f"Array length mismatch for key '{key}' (expected {len(reference_index)}, got {len(array)})"
+                    )
+
+                data[key] = array
+            except KeyError as e:
+                raise KeyError(f"Failed to retrieve data for key '{key}': {e}")
+
+        if not data:
+            raise KeyError(f"No valid data found for the requested keys {keys}.")
+
+        return pd.DataFrame(data, index=reference_index)
+
     def provider_by_id(self, provider_id: str) -> DataProvider:
         """Retrieves a data provider by its unique identifier.
 

src/akkudoktoreos/core/decorators.py

@@ -1,17 +1,15 @@
+from collections.abc import Callable
 from typing import Any, Optional
 
-from akkudoktoreos.core.logging import get_logger
 
-logger = get_logger(__name__)
+class classproperty:
-
-
-class classproperty(property):
     """A decorator to define a read-only property at the class level.
 
-    This class extends the built-in `property` to allow a method to be accessed
+    This class replaces the built-in `property` which is no longer available in
-    as a property on the class itself, rather than an instance. This is useful
+    combination with @classmethod since Python 3.13 to allow a method to be
-    when you want a property-like syntax for methods that depend on the class
+    accessed as a property on the class itself, rather than an instance. This
-    rather than any instance of the class.
+    is useful when you want a property-like syntax for methods that depend on
+    the class rather than any instance of the class.
 
     Example:
         class MyClass:
@@ -28,15 +26,19 @@ class classproperty(property):
                  decorated method on the class.
 
     Parameters:
-        fget (Callable[[type], Any]): A method that takes the class as an
+        fget (Callable[[Any], Any]): A method that takes the class as an
                                       argument and returns a value.
 
     Raises:
-        AssertionError: If `fget` is not defined when `__get__` is called.
+        RuntimeError: If `fget` is not defined when `__get__` is called.
     """
 
+    def __init__(self, fget: Callable[[Any], Any]) -> None:
+        self.fget = fget
+
     def __get__(self, _: Any, owner_cls: Optional[type[Any]] = None) -> Any:
         if owner_cls is None:
             return self
-        assert self.fget is not None
+        if self.fget is None:
+            raise RuntimeError("'fget' not defined when `__get__` is called")
         return self.fget(owner_cls)

src/akkudoktoreos/core/ems.py

@@ -1,24 +1,24 @@
+import traceback
 from typing import Any, ClassVar, Optional
 
 import numpy as np
+from loguru import logger
 from numpydantic import NDArray, Shape
 from pendulum import DateTime
 from pydantic import ConfigDict, Field, computed_field, field_validator, model_validator
 from typing_extensions import Self
 
+from akkudoktoreos.core.cache import CacheUntilUpdateStore
 from akkudoktoreos.core.coreabc import ConfigMixin, PredictionMixin, SingletonMixin
-from akkudoktoreos.core.logging import get_logger
 from akkudoktoreos.core.pydantic import ParametersBaseModel, PydanticBaseModel
 from akkudoktoreos.devices.battery import Battery
 from akkudoktoreos.devices.generic import HomeAppliance
 from akkudoktoreos.devices.inverter import Inverter
-from akkudoktoreos.utils.datetimeutil import to_datetime
+from akkudoktoreos.utils.datetimeutil import compare_datetimes, to_datetime
 from akkudoktoreos.utils.utils import NumpyEncoder
 
-logger = get_logger(__name__)
 
-
+class EnergyManagementParameters(ParametersBaseModel):
-class EnergieManagementSystemParameters(ParametersBaseModel):
     pv_prognose_wh: list[float] = Field(
         description="An array of floats representing the forecasted photovoltaic output in watts for different time intervals."
     )
@@ -107,7 +107,7 @@ class SimulationResult(ParametersBaseModel):
         return NumpyEncoder.convert_numpy(field)[0]
 
 
-class EnergieManagementSystem(SingletonMixin, ConfigMixin, PredictionMixin, PydanticBaseModel):
+class EnergyManagement(SingletonMixin, ConfigMixin, PredictionMixin, PydanticBaseModel):
     # Disable validation on assignment to speed up simulation runs.
     model_config = ConfigDict(
         validate_assignment=False,
@@ -116,16 +116,33 @@ class EnergieManagementSystem(SingletonMixin, ConfigMixin, PredictionMixin, Pyda
     # Start datetime.
     _start_datetime: ClassVar[Optional[DateTime]] = None
 
+    # last run datetime. Used by energy management task
+    _last_datetime: ClassVar[Optional[DateTime]] = None
+
     @computed_field  # type: ignore[prop-decorator]
     @property
     def start_datetime(self) -> DateTime:
         """The starting datetime of the current or latest energy management."""
-        if EnergieManagementSystem._start_datetime is None:
+        if EnergyManagement._start_datetime is None:
-            EnergieManagementSystem.set_start_datetime()
+            EnergyManagement.set_start_datetime()
-        return EnergieManagementSystem._start_datetime
+        return EnergyManagement._start_datetime
 
     @classmethod
     def set_start_datetime(cls, start_datetime: Optional[DateTime] = None) -> DateTime:
+        """Set the start datetime for the next energy management cycle.
+
+        If no datetime is provided, the current datetime is used.
+
+        The start datetime is always rounded down to the nearest hour
+        (i.e., setting minutes, seconds, and microseconds to zero).
+
+        Args:
+            start_datetime (Optional[DateTime]): The datetime to set as the start.
+                If None, the current datetime is used.
+
+        Returns:
+            DateTime: The adjusted start datetime.
+        """
         if start_datetime is None:
             start_datetime = to_datetime()
         cls._start_datetime = start_datetime.set(minute=0, second=0, microsecond=0)
@@ -176,7 +193,7 @@ class EnergieManagementSystem(SingletonMixin, ConfigMixin, PredictionMixin, Pyda
 
     def set_parameters(
         self,
-        parameters: EnergieManagementSystemParameters,
+        parameters: EnergyManagementParameters,
         ev: Optional[Battery] = None,
         home_appliance: Optional[HomeAppliance] = None,
         inverter: Optional[Inverter] = None,
@@ -243,8 +260,9 @@ class EnergieManagementSystem(SingletonMixin, ConfigMixin, PredictionMixin, Pyda
             is mostly relevant to prediction providers.
             force_update (bool, optional): If True, forces to update the data even if still cached.
         """
+        # Throw away any cached results of the last run.
+        CacheUntilUpdateStore().clear()
         self.set_start_hour(start_hour=start_hour)
-        self.config.update()
 
         # Check for run definitions
         if self.start_datetime is None:
@@ -255,14 +273,75 @@ class EnergieManagementSystem(SingletonMixin, ConfigMixin, PredictionMixin, Pyda
             error_msg = "Prediction hours unknown."
             logger.error(error_msg)
             raise ValueError(error_msg)
-        if self.config.prediction.optimisation_hours is None:
+        if self.config.optimization.hours is None:
-            error_msg = "Optimisation hours unknown."
+            error_msg = "Optimization hours unknown."
             logger.error(error_msg)
             raise ValueError(error_msg)
 
         self.prediction.update_data(force_enable=force_enable, force_update=force_update)
         # TODO: Create optimisation problem that calls into devices.update_data() for simulations.
 
+        logger.info("Energy management run (crippled version - prediction update only)")
+
+    def manage_energy(self) -> None:
+        """Repeating task for managing energy.
+
+        This task should be executed by the server regularly (e.g., every 10 seconds)
+        to ensure proper energy management. Configuration changes to the energy management interval
+        will only take effect if this task is executed.
+
+        - Initializes and runs the energy management for the first time if it has never been run
+          before.
+        - If the energy management interval is not configured or invalid (NaN), the task will not
+          trigger any repeated energy management runs.
+        - Compares the current time with the last run time and runs the energy management if the
+          interval has elapsed.
+        - Logs any exceptions that occur during the initialization or execution of the energy
+          management.
+
+        Note: The task maintains the interval even if some intervals are missed.
+        """
+        current_datetime = to_datetime()
+        interval = self.config.ems.interval  # interval maybe changed in between
+
+        if EnergyManagement._last_datetime is None:
+            # Never run before
+            try:
+                # Remember energy run datetime.
+                EnergyManagement._last_datetime = current_datetime
+                # Try to run a first energy management. May fail due to config incomplete.
+                self.run()
+            except Exception as e:
+                trace = "".join(traceback.TracebackException.from_exception(e).format())
+                message = f"EOS init: {e}\n{trace}"
+                logger.error(message)
+            return
+
+        if interval is None or interval == float("nan"):
+            # No Repetition
+            return
+
+        if (
+            compare_datetimes(current_datetime, EnergyManagement._last_datetime).time_diff
+            < interval
+        ):
+            # Wait for next run
+            return
+
+        try:
+            self.run()
+        except Exception as e:
+            trace = "".join(traceback.TracebackException.from_exception(e).format())
+            message = f"EOS run: {e}\n{trace}"
+            logger.error(message)
+
+        # Remember the energy management run - keep on interval even if we missed some intervals
+        while (
+            compare_datetimes(current_datetime, EnergyManagement._last_datetime).time_diff
+            >= interval
+        ):
+            EnergyManagement._last_datetime = EnergyManagement._last_datetime.add(seconds=interval)
+
     def set_start_hour(self, start_hour: Optional[int] = None) -> None:
         """Sets start datetime to given hour.
 
@@ -315,7 +394,8 @@ class EnergieManagementSystem(SingletonMixin, ConfigMixin, PredictionMixin, Pyda
 
         # Fetch objects
         battery = self.battery
-        assert battery  # to please mypy
+        if battery is None:
+            raise ValueError(f"battery not set: {battery}")
         ev = self.ev
         home_appliance = self.home_appliance
         inverter = self.inverter
@@ -440,9 +520,9 @@ class EnergieManagementSystem(SingletonMixin, ConfigMixin, PredictionMixin, Pyda
 
 
 # Initialize the Energy Management System, it is a singleton.
-ems = EnergieManagementSystem()
+ems = EnergyManagement()
 
 
-def get_ems() -> EnergieManagementSystem:
+def get_ems() -> EnergyManagement:
     """Gets the EOS Energy Management System."""
     return ems

src/akkudoktoreos/core/emsettings.py

@@ -0,0 +1,26 @@
+"""Settings for energy management.
+
+Kept in an extra module to avoid cyclic dependencies on package import.
+"""
+
+from typing import Optional
+
+from pydantic import Field
+
+from akkudoktoreos.config.configabc import SettingsBaseModel
+
+
+class EnergyManagementCommonSettings(SettingsBaseModel):
+    """Energy Management Configuration."""
+
+    startup_delay: float = Field(
+        default=5,
+        ge=1,
+        description="Startup delay in seconds for EOS energy management runs.",
+    )
+
+    interval: Optional[float] = Field(
+        default=None,
+        description="Intervall in seconds between EOS energy management runs.",
+        examples=["300"],
+    )

src/akkudoktoreos/core/logabc.py

@@ -1,20 +1,3 @@
 """Abstract and base classes for logging."""
 
-import logging
+LOGGING_LEVELS: list[str] = ["TRACE", "DEBUG", "INFO", "WARNING", "ERROR", "CRITICAL"]
-
-
-def logging_str_to_level(level_str: str) -> int:
-    """Convert log level string to logging level."""
-    if level_str == "DEBUG":
-        level = logging.DEBUG
-    elif level_str == "INFO":
-        level = logging.INFO
-    elif level_str == "WARNING":
-        level = logging.WARNING
-    elif level_str == "CRITICAL":
-        level = logging.CRITICAL
-    elif level_str == "ERROR":
-        level = logging.ERROR
-    else:
-        raise ValueError(f"Unknown loggin level: {level_str}")
-    return level

src/akkudoktoreos/core/logging.py

@@ -1,91 +1,241 @@
-"""Utility functions for handling logging tasks.
+"""Utility for configuring Loguru loggers."""
-
-Functions:
-----------
-- get_logger: Creates and configures a logger with console and optional rotating file logging.
-
-Example usage:
---------------
-    # Logger setup
-    >>> logger = get_logger(__name__, log_file="app.log", logging_level="DEBUG")
-    >>> logger.info("Logging initialized.")
-
-Notes:
-------
-- The logger supports rotating log files to prevent excessive log file size.
-"""
 
+import json
 import logging as pylogging
 import os
-from logging.handlers import RotatingFileHandler
+import re
-from typing import Optional
+import sys
+from pathlib import Path
+from types import FrameType
+from typing import Any, List, Optional
 
-from akkudoktoreos.core.logabc import logging_str_to_level
+import pendulum
+from loguru import logger
+
+from akkudoktoreos.core.logabc import LOGGING_LEVELS
 
 
-def get_logger(
+class InterceptHandler(pylogging.Handler):
-    name: str,
+    """A logging handler that redirects standard Python logging messages to Loguru.
-    log_file: Optional[str] = None,
-    logging_level: Optional[str] = None,
-    max_bytes: int = 5000000,
-    backup_count: int = 5,
-) -> pylogging.Logger:
-    """Creates and configures a logger with a given name.
 
-    The logger supports logging to both the console and an optional log file. File logging is
+    This handler ensures consistency between the `logging` module and Loguru by intercepting
-    handled by a rotating file handler to prevent excessive log file size.
+    logs sent to the standard logging system and re-emitting them through Loguru with proper
+    formatting and context (including exception info and call depth).
+
+    Attributes:
+        loglevel_mapping (dict): Mapping from standard logging levels to Loguru level names.
+    """
+
+    loglevel_mapping: dict[int, str] = {
+        50: "CRITICAL",
+        40: "ERROR",
+        30: "WARNING",
+        20: "INFO",
+        10: "DEBUG",
+        5: "TRACE",
+        0: "NOTSET",
+    }
+
+    def emit(self, record: pylogging.LogRecord) -> None:
+        """Emits a logging record by forwarding it to Loguru with preserved metadata.
 
         Args:
-        name (str): The name of the logger, typically `__name__` from the calling module.
+            record (logging.LogRecord): A record object containing log message and metadata.
-        log_file (Optional[str]): Path to the log file for file logging. If None, no file logging is done.
+        """
-        logging_level (Optional[str]): Logging level (e.g., "INFO", "DEBUG"). Defaults to "INFO".
+        try:
-        max_bytes (int): Maximum size in bytes for log file before rotation. Defaults to 5 MB.
+            level = logger.level(record.levelname).name
-        backup_count (int): Number of backup log files to keep. Defaults to 5.
+        except AttributeError:
+            level = self.loglevel_mapping.get(record.levelno, "INFO")
+
+        frame: Optional[FrameType] = pylogging.currentframe()
+        depth: int = 2
+        while frame and frame.f_code.co_filename == pylogging.__file__:
+            frame = frame.f_back
+            depth += 1
+
+        log = logger.bind(request_id="app")
+        log.opt(depth=depth, exception=record.exc_info).log(level, record.getMessage())
+
+
+console_handler_id = None
+file_handler_id = None
+
+
+def track_logging_config(config_eos: Any, path: str, old_value: Any, value: Any) -> None:
+    """Track logging config changes."""
+    global console_handler_id, file_handler_id
+
+    if not path.startswith("logging"):
+        raise ValueError(f"Logging shall not track '{path}'")
+
+    if not config_eos.logging.console_level:
+        # No value given - check environment value - may also be None
+        config_eos.logging.console_level = os.getenv("EOS_LOGGING__LEVEL")
+    if not config_eos.logging.file_level:
+        # No value given - check environment value - may also be None
+        config_eos.logging.file_level = os.getenv("EOS_LOGGING__LEVEL")
+
+    # Remove handlers
+    if console_handler_id:
+        try:
+            logger.remove(console_handler_id)
+        except Exception as e:
+            logger.debug("Exception on logger.remove: {}", e, exc_info=True)
+        console_handler_id = None
+    if file_handler_id:
+        try:
+            logger.remove(file_handler_id)
+        except Exception as e:
+            logger.debug("Exception on logger.remove: {}", e, exc_info=True)
+        file_handler_id = None
+
+    # Create handlers with new configuration
+    # Always add console handler
+    if config_eos.logging.console_level not in LOGGING_LEVELS:
+        logger.error(
+            f"Invalid console log level '{config_eos.logging.console_level} - forced to INFO'."
+        )
+        config_eos.logging.console_level = "INFO"
+
+    console_handler_id = logger.add(
+        sys.stderr,
+        enqueue=True,
+        backtrace=True,
+        level=config_eos.logging.console_level,
+        # format=_console_format
+    )
+
+    # Add file handler
+    if config_eos.logging.file_level and config_eos.logging.file_path:
+        if config_eos.logging.file_level not in LOGGING_LEVELS:
+            logger.error(
+                f"Invalid file log level '{config_eos.logging.console_level}' - forced to INFO."
+            )
+            config_eos.logging.file_level = "INFO"
+
+        file_handler_id = logger.add(
+            sink=config_eos.logging.file_path,
+            rotation="100 MB",
+            retention="3 days",
+            enqueue=True,
+            backtrace=True,
+            level=config_eos.logging.file_level,
+            serialize=True,  # JSON dict formatting
+            # format=_file_format
+        )
+
+    # Redirect standard logging to Loguru
+    pylogging.basicConfig(handlers=[InterceptHandler()], level=0)
+    # Redirect uvicorn and fastapi logging to Loguru
+    pylogging.getLogger("uvicorn.access").handlers = [InterceptHandler()]
+    for pylogger_name in ["uvicorn", "uvicorn.error", "fastapi"]:
+        pylogger = pylogging.getLogger(pylogger_name)
+        pylogger.handlers = [InterceptHandler()]
+        pylogger.propagate = False
+
+    logger.info(
+        f"Logger reconfigured - console: {config_eos.logging.console_level}, file: {config_eos.logging.file_level}."
+    )
+
+
+def read_file_log(
+    log_path: Path,
+    limit: int = 100,
+    level: Optional[str] = None,
+    contains: Optional[str] = None,
+    regex: Optional[str] = None,
+    from_time: Optional[str] = None,
+    to_time: Optional[str] = None,
+    tail: bool = False,
+) -> List[dict]:
+    """Read and filter structured log entries from a JSON-formatted log file.
+
+    Args:
+        log_path (Path): Path to the JSON-formatted log file.
+        limit (int, optional): Maximum number of log entries to return. Defaults to 100.
+        level (Optional[str], optional): Filter logs by log level (e.g., "INFO", "ERROR"). Defaults to None.
+        contains (Optional[str], optional): Filter logs that contain this substring in their message. Case-insensitive. Defaults to None.
+        regex (Optional[str], optional): Filter logs whose message matches this regular expression. Defaults to None.
+        from_time (Optional[str], optional): ISO 8601 datetime string to filter logs not earlier than this time. Defaults to None.
+        to_time (Optional[str], optional): ISO 8601 datetime string to filter logs not later than this time. Defaults to None.
+        tail (bool, optional): If True, read the last lines of the file (like `tail -n`). Defaults to False.
 
     Returns:
-        logging.Logger: Configured logger instance.
+        List[dict]: A list of filtered log entries as dictionaries.
 
-    Example:
+    Raises:
-        logger = get_logger(__name__, log_file="app.log", logging_level="DEBUG")
+        FileNotFoundError: If the log file does not exist.
-        logger.info("Application started")
+        ValueError: If the datetime strings are invalid or improperly formatted.
+        Exception: For other unforeseen I/O or parsing errors.
     """
-    # Create a logger with the specified name
+    if not log_path.exists():
-    logger = pylogging.getLogger(name)
+        raise FileNotFoundError("Log file not found")
-    logger.propagate = True
-    if logging_level is not None:
-        level = logging_str_to_level(logging_level)
-        logger.setLevel(level)
 
-    # The log message format
+    try:
-    formatter = pylogging.Formatter("%(asctime)s - %(name)s - %(levelname)s - %(message)s")
+        from_dt = pendulum.parse(from_time) if from_time else None
+        to_dt = pendulum.parse(to_time) if to_time else None
+    except Exception as e:
+        raise ValueError(f"Invalid date/time format: {e}")
 
-    # Prevent loggers from being added multiple times
+    regex_pattern = re.compile(regex) if regex else None
-    # There may already be a logger from pytest
-    if not logger.handlers:
-        # Create a console handler with a standard output stream
-        console_handler = pylogging.StreamHandler()
-        if logging_level is not None:
-            console_handler.setLevel(level)
-        console_handler.setFormatter(formatter)
 
-        # Add the console handler to the logger
+    def matches_filters(log: dict) -> bool:
-        logger.addHandler(console_handler)
+        if level and log.get("level", {}).get("name") != level.upper():
+            return False
+        if contains and contains.lower() not in log.get("message", "").lower():
+            return False
+        if regex_pattern and not regex_pattern.search(log.get("message", "")):
+            return False
+        if from_dt or to_dt:
+            try:
+                log_time = pendulum.parse(log["time"])
+            except Exception:
+                return False
+            if from_dt and log_time < from_dt:
+                return False
+            if to_dt and log_time > to_dt:
+                return False
+        return True
 
-    if log_file and len(logger.handlers) < 2:  # We assume a console logger to be the first logger
+    matched_logs = []
-        # If a log file path is specified, create a rotating file handler
+    lines: list[str] = []
 
-        # Ensure the log directory exists
+    if tail:
-        log_dir = os.path.dirname(log_file)
+        with log_path.open("rb") as f:
-        if log_dir and not os.path.exists(log_dir):
+            f.seek(0, 2)
-            os.makedirs(log_dir)
+            end = f.tell()
+            buffer = bytearray()
+            pointer = end
 
-        # Create a rotating file handler
+            while pointer > 0 and len(lines) < limit * 5:
-        file_handler = RotatingFileHandler(log_file, maxBytes=max_bytes, backupCount=backup_count)
+                pointer -= 1
-        if logging_level is not None:
+                f.seek(pointer)
-            file_handler.setLevel(level)
+                byte = f.read(1)
-        file_handler.setFormatter(formatter)
+                if byte == b"\n":
+                    if buffer:
+                        line = buffer[::-1].decode("utf-8", errors="ignore")
+                        lines.append(line)
+                        buffer.clear()
+                else:
+                    buffer.append(byte[0])
+            if buffer:
+                line = buffer[::-1].decode("utf-8", errors="ignore")
+                lines.append(line)
+        lines = lines[::-1]
+    else:
+        with log_path.open("r", encoding="utf-8", newline=None) as f_txt:
+            lines = f_txt.readlines()
 
-        # Add the file handler to the logger
+    for line in lines:
-        logger.addHandler(file_handler)
+        if not line.strip():
+            continue
+        try:
+            log = json.loads(line)
+        except json.JSONDecodeError:
+            continue
+        if matches_filters(log):
+            matched_logs.append(log)
+            if len(matched_logs) >= limit:
+                break
 
-    return logger
+    return matched_logs

src/akkudoktoreos/core/logsettings.py

@@ -3,13 +3,13 @@
 Kept in an extra module to avoid cyclic dependencies on package import.
 """
 
-import logging
+from pathlib import Path
 from typing import Optional
 
 from pydantic import Field, computed_field, field_validator
 
 from akkudoktoreos.config.configabc import SettingsBaseModel
-from akkudoktoreos.core.logabc import logging_str_to_level
+from akkudoktoreos.core.logabc import LOGGING_LEVELS
 
 
 class LoggingCommonSettings(SettingsBaseModel):
@@ -17,27 +17,47 @@ class LoggingCommonSettings(SettingsBaseModel):
 
     level: Optional[str] = Field(
         default=None,
-        description="EOS default logging level.",
+        deprecated="This is deprecated. Use console_level and file_level instead.",
-        examples=["INFO", "DEBUG", "WARNING", "ERROR", "CRITICAL"],
     )
 
-    # Validators
+    console_level: Optional[str] = Field(
-    @field_validator("level", mode="after")
+        default=None,
-    @classmethod
+        description="Logging level when logging to console.",
-    def set_default_logging_level(cls, value: Optional[str]) -> Optional[str]:
+        examples=LOGGING_LEVELS,
-        if isinstance(value, str) and value.upper() == "NONE":
+    )
-            value = None
+
-        if value is None:
+    file_level: Optional[str] = Field(
-            return None
+        default=None,
-        level = logging_str_to_level(value)
+        description="Logging level when logging to file.",
-        logging.getLogger().setLevel(level)
+        examples=LOGGING_LEVELS,
-        return value
+    )
 
-    # Computed fields
     @computed_field  # type: ignore[prop-decorator]
     @property
-    def root_level(self) -> str:
+    def file_path(self) -> Optional[Path]:
-        """Root logger logging level."""
+        """Computed log file path based on data output path."""
-        level = logging.getLogger().getEffectiveLevel()
+        try:
-        level_name = logging.getLevelName(level)
+            path = SettingsBaseModel.config.general.data_output_path / "eos.log"
-        return level_name
+        except:
+            # Config may not be fully set up
+            path = None
+        return path
+
+    # Validators
+    @field_validator("console_level", "file_level", mode="after")
+    @classmethod
+    def validate_level(cls, value: Optional[str]) -> Optional[str]:
+        """Validate logging level string."""
+        if value is None:
+            # Nothing to set
+            return None
+        if isinstance(value, str):
+            level = value.upper()
+            if level == "NONE":
+                return None
+            if level not in LOGGING_LEVELS:
+                raise ValueError(f"Logging level {value} not supported")
+            value = level
+        else:
+            raise TypeError(f"Invalid {type(value)} of logging level {value}")
+        return value

src/akkudoktoreos/core/pydantic.py

@@ -12,20 +12,35 @@ Key Features:
   pandas DataFrames and Series with datetime indexes.
 """
 
+import inspect
 import json
 import re
+import uuid
+import weakref
 from copy import deepcopy
-from typing import Any, Dict, List, Optional, Type, Union
+from typing import (
+    Any,
+    Callable,
+    Dict,
+    List,
+    Optional,
+    Type,
+    Union,
+    get_args,
+    get_origin,
+)
 from zoneinfo import ZoneInfo
 
 import pandas as pd
 import pendulum
+from loguru import logger
 from pandas.api.types import is_datetime64_any_dtype
 from pydantic import (
     AwareDatetime,
     BaseModel,
     ConfigDict,
     Field,
+    PrivateAttr,
     RootModel,
     TypeAdapter,
     ValidationError,
@@ -35,6 +50,10 @@ from pydantic import (
 
 from akkudoktoreos.utils.datetimeutil import to_datetime, to_duration
 
+# Global weakref dictionary to hold external state per model instance
+# Used as a workaround for PrivateAttr not working in e.g. Mixin Classes
+_model_private_state: "weakref.WeakKeyDictionary[Union[PydanticBaseModel, PydanticModelNestedValueMixin], Dict[str, Any]]" = weakref.WeakKeyDictionary()
+
 
 def merge_models(source: BaseModel, update_dict: dict[str, Any]) -> dict[str, Any]:
     def deep_update(source_dict: dict[str, Any], update_dict: dict[str, Any]) -> dict[str, Any]:
@@ -82,11 +101,538 @@ class PydanticTypeAdapterDateTime(TypeAdapter[pendulum.DateTime]):
         return bool(re.match(iso8601_pattern, value))
 
 
-class PydanticBaseModel(BaseModel):
+class PydanticModelNestedValueMixin:
-    """Base model class with automatic serialization and deserialization of `pendulum.DateTime` fields.
+    """A mixin providing methods to get, set and track nested values within a Pydantic model.
 
-    This model serializes pendulum.DateTime objects to ISO 8601 strings and
+    The methods use a '/'-separated path to denote the nested values.
-    deserializes ISO 8601 strings to pendulum.DateTime objects.
+    Supports handling `Optional`, `List`, and `Dict` types, ensuring correct initialization of
+    missing attributes.
+
+
+    Example:
+        class Address(PydanticBaseModel):
+            city: str
+
+        class User(PydanticBaseModel):
+            name: str
+            address: Address
+
+        def on_city_change(old, new, path):
+            print(f"{path}: {old} -> {new}")
+
+        user = User(name="Alice", address=Address(city="NY"))
+        user.track_nested_value("address/city", on_city_change)
+        user.set_nested_value("address/city", "LA")  # triggers callback
+
+    """
+
+    def track_nested_value(self, path: str, callback: Callable[[Any, str, Any, Any], None]) -> None:
+        """Register a callback for a specific path (or subtree).
+
+        Callback triggers if set path is equal or deeper.
+
+        Args:
+            path (str): '/'-separated path to track.
+            callback (callable): Function called as callback(model_instance, set_path, old_value, new_value).
+        """
+        try:
+            self._validate_path_structure(path)
+            pass
+        except:
+            raise ValueError(f"Path '{path}' is invalid")
+        path = path.strip("/")
+        # Use private data workaround
+        # Should be:
+        #  _nested_value_callbacks: dict[str, list[Callable[[str, Any, Any], None]]]
+        #   = PrivateAttr(default_factory=dict)
+        nested_value_callbacks = get_private_attr(self, "nested_value_callbacks", dict())
+        if path not in nested_value_callbacks:
+            nested_value_callbacks[path] = []
+        nested_value_callbacks[path].append(callback)
+        set_private_attr(self, "nested_value_callbacks", nested_value_callbacks)
+
+        logger.debug("Nested value callbacks {}", nested_value_callbacks)
+
+    def _validate_path_structure(self, path: str) -> None:
+        """Validate that a '/'-separated path is structurally valid for this model.
+
+        Checks that each segment of the path corresponds to a field or index in the model's type structure,
+        without requiring that all intermediate values are currently initialized. This method is intended
+        to ensure that the path could be valid for nested access or assignment, according to the model's
+        class definition.
+
+        Args:
+            path (str): The '/'-separated attribute/index path to validate (e.g., "address/city" or "items/0/value").
+
+        Raises:
+            ValueError: If any segment of the path does not correspond to a valid field in the model,
+                or an invalid transition is made (such as an attribute on a non-model).
+
+        Example:
+            class Address(PydanticBaseModel):
+                city: str
+
+            class User(PydanticBaseModel):
+                name: str
+                address: Address
+
+            user = User(name="Alice", address=Address(city="NY"))
+            user._validate_path_structure("address/city")  # OK
+            user._validate_path_structure("address/zipcode")  # Raises ValueError
+        """
+        path_elements = path.strip("/").split("/")
+        # The model we are currently working on
+        model: Any = self
+        # The model we get the type information from. It is a pydantic BaseModel
+        parent: BaseModel = model
+        # The field that provides type information for the current key
+        # Fields may have nested types that translates to a sequence of keys, not just one
+        # - my_field: Optional[list[OtherModel]] -> e.g. "myfield/0" for index 0
+        #   parent_key = ["myfield",] ... ["myfield", "0"]
+        #   parent_key_types = [list, OtherModel]
+        parent_key: list[str] = []
+        parent_key_types: list = []
+
+        for i, key in enumerate(path_elements):
+            is_final_key = i == len(path_elements) - 1
+            # Add current key to parent key to enable nested type tracking
+            parent_key.append(key)
+
+            # Get next value
+            next_value = None
+            if isinstance(model, BaseModel):
+                # Track parent and key for possible assignment later
+                parent = model
+                parent_key = [
+                    key,
+                ]
+                parent_key_types = self._get_key_types(model.__class__, key)
+
+                # If this is the final key, set the value
+                if is_final_key:
+                    return
+
+                # Attempt to access the next attribute, handling None values
+                next_value = getattr(model, key, None)
+
+                # Handle missing values (initialize dict/list/model if necessary)
+                if next_value is None:
+                    next_type = parent_key_types[len(parent_key) - 1]
+                    next_value = self._initialize_value(next_type)
+
+            elif isinstance(model, list):
+                # Handle lists
+                try:
+                    idx = int(key)
+                except Exception as e:
+                    raise IndexError(
+                        f"Invalid list index '{key}' at '{path}': key = '{key}'; parent = '{parent}', parent_key = '{parent_key}'; model = '{model}'; {e}"
+                    )
+
+                # Get next type from parent key type information
+                next_type = parent_key_types[len(parent_key) - 1]
+
+                if len(model) > idx:
+                    next_value = model[idx]
+                else:
+                    return
+
+                if is_final_key:
+                    return
+
+            elif isinstance(model, dict):
+                # Handle dictionaries (auto-create missing keys)
+
+                # Get next type from parent key type information
+                next_type = parent_key_types[len(parent_key) - 1]
+
+                if is_final_key:
+                    return
+
+                if key not in model:
+                    return
+                else:
+                    next_value = model[key]
+
+            else:
+                raise KeyError(f"Key '{key}' not found in model.")
+
+            # Move deeper
+            model = next_value
+
+    def get_nested_value(self, path: str) -> Any:
+        """Retrieve a nested value from the model using a '/'-separated path.
+
+        Supports accessing nested attributes and list indices.
+
+        Args:
+            path (str): A '/'-separated path to the nested attribute (e.g., "key1/key2/0").
+
+        Returns:
+            Any: The retrieved value.
+
+        Raises:
+            KeyError: If a key is not found in the model.
+            IndexError: If a list index is out of bounds or invalid.
+
+        Example:
+            ```python
+            class Address(PydanticBaseModel):
+                city: str
+
+            class User(PydanticBaseModel):
+                name: str
+                address: Address
+
+            user = User(name="Alice", address=Address(city="New York"))
+            city = user.get_nested_value("address/city")
+            print(city)  # Output: "New York"
+            ```
+        """
+        path_elements = path.strip("/").split("/")
+        model: Any = self
+
+        for key in path_elements:
+            if isinstance(model, list):
+                try:
+                    model = model[int(key)]
+                except (ValueError, IndexError) as e:
+                    raise IndexError(f"Invalid list index at '{path}': {key}; {e}")
+            elif isinstance(model, dict):
+                try:
+                    model = model[key]
+                except Exception as e:
+                    raise KeyError(f"Invalid dict key at '{path}': {key}; {e}")
+            elif isinstance(model, BaseModel):
+                model = getattr(model, key)
+            else:
+                raise KeyError(f"Key '{key}' not found in model.")
+
+        return model
+
+    def set_nested_value(self, path: str, value: Any) -> None:
+        """Set a nested value in the model using a '/'-separated path.
+
+        Supports modifying nested attributes and list indices while preserving Pydantic validation.
+        Automatically initializes missing `Optional`, `Union`, `dict`, and `list` fields if necessary.
+        If a missing field cannot be initialized, raises an exception.
+
+        Triggers the callbacks registered by track_nested_value().
+
+        Args:
+            path (str): A '/'-separated path to the nested attribute (e.g., "key1/key2/0").
+            value (Any): The new value to set.
+
+        Raises:
+            KeyError: If a key is not found in the model.
+            IndexError: If a list index is out of bounds or invalid.
+            ValueError: If a validation error occurs.
+            TypeError: If a missing field cannot be initialized.
+
+        Example:
+            ```python
+            class Address(PydanticBaseModel):
+                city: Optional[str]
+
+            class User(PydanticBaseModel):
+                name: str
+                address: Optional[Address]
+                settings: Optional[Dict[str, Any]]
+
+            user = User(name="Alice", address=None, settings=None)
+            user.set_nested_value("address/city", "Los Angeles")
+            user.set_nested_value("settings/theme", "dark")
+
+            print(user.address.city)  # Output: "Los Angeles"
+            print(user.settings)  # Output: {'theme': 'dark'}
+            ```
+        """
+        path = path.strip("/")
+        # Store old value (if possible)
+        try:
+            old_value = self.get_nested_value(path)
+        except Exception as e:
+            # We can not get the old value
+            # raise ValueError(f"Can not get old (current) value of '{path}': {e}") from e
+            old_value = None
+
+        # Proceed with core logic
+        self._set_nested_value(path, value)
+
+        # Trigger all callbacks whose path is a prefix of set path
+        triggered = set()
+        nested_value_callbacks = get_private_attr(self, "nested_value_callbacks", dict())
+        for cb_path, callbacks in nested_value_callbacks.items():
+            # Match: cb_path == path, or cb_path is a prefix (parent) of path
+            pass
+            if path == cb_path or path.startswith(cb_path + "/"):
+                for cb in callbacks:
+                    # Prevent duplicate calls
+                    if (cb_path, id(cb)) not in triggered:
+                        cb(self, path, old_value, value)
+                        triggered.add((cb_path, id(cb)))
+
+    def _set_nested_value(self, path: str, value: Any) -> None:
+        """Set a nested value core logic.
+
+        Args:
+            path (str): A '/'-separated path to the nested attribute (e.g., "key1/key2/0").
+            value (Any): The new value to set.
+
+        Raises:
+            KeyError: If a key is not found in the model.
+            IndexError: If a list index is out of bounds or invalid.
+            ValueError: If a validation error occurs.
+            TypeError: If a missing field cannot be initialized.
+        """
+        path_elements = path.strip("/").split("/")
+        # The model we are currently working on
+        model: Any = self
+        # The model we get the type information from. It is a pydantic BaseModel
+        parent: BaseModel = model
+        # The field that provides type information for the current key
+        # Fields may have nested types that translates to a sequence of keys, not just one
+        # - my_field: Optional[list[OtherModel]] -> e.g. "myfield/0" for index 0
+        #   parent_key = ["myfield",] ... ["myfield", "0"]
+        #   parent_key_types = [list, OtherModel]
+        parent_key: list[str] = []
+        parent_key_types: list = []
+
+        for i, key in enumerate(path_elements):
+            is_final_key = i == len(path_elements) - 1
+            # Add current key to parent key to enable nested type tracking
+            parent_key.append(key)
+
+            # Get next value
+            next_value = None
+            if isinstance(model, BaseModel):
+                # Track parent and key for possible assignment later
+                parent = model
+                parent_key = [
+                    key,
+                ]
+                parent_key_types = self._get_key_types(model.__class__, key)
+
+                # If this is the final key, set the value
+                if is_final_key:
+                    try:
+                        model.__pydantic_validator__.validate_assignment(model, key, value)
+                    except ValidationError as e:
+                        raise ValueError(f"Error updating model: {e}") from e
+                    return
+
+                # Attempt to access the next attribute, handling None values
+                next_value = getattr(model, key, None)
+
+                # Handle missing values (initialize dict/list/model if necessary)
+                if next_value is None:
+                    next_type = parent_key_types[len(parent_key) - 1]
+                    next_value = self._initialize_value(next_type)
+                    if next_value is None:
+                        raise TypeError(
+                            f"Unable to initialize missing value for key '{key}' in path '{path}' with type {next_type} of {parent_key}:{parent_key_types}."
+                        )
+                    setattr(parent, key, next_value)
+                    # pydantic may copy on validation assignment - reread to get the copied model
+                    next_value = getattr(model, key, None)
+
+            elif isinstance(model, list):
+                # Handle lists (ensure index exists and modify safely)
+                try:
+                    idx = int(key)
+                except Exception as e:
+                    raise IndexError(
+                        f"Invalid list index '{key}' at '{path}': key = '{key}'; parent = '{parent}', parent_key = '{parent_key}'; model = '{model}'; {e}"
+                    )
+
+                # Get next type from parent key type information
+                next_type = parent_key_types[len(parent_key) - 1]
+
+                if len(model) > idx:
+                    next_value = model[idx]
+                else:
+                    # Extend the list with default values if index is out of range
+                    while len(model) <= idx:
+                        next_value = self._initialize_value(next_type)
+                        if next_value is None:
+                            raise TypeError(
+                                f"Unable to initialize missing value for key '{key}' in path '{path}' with type {next_type} of {parent_key}:{parent_key_types}."
+                            )
+                        model.append(next_value)
+
+                if is_final_key:
+                    if (
+                        (isinstance(next_type, type) and not isinstance(value, next_type))
+                        or (next_type is dict and not isinstance(value, dict))
+                        or (next_type is list and not isinstance(value, list))
+                    ):
+                        raise TypeError(
+                            f"Expected type {next_type} for key '{key}' in path '{path}', but got {type(value)}: {value}"
+                        )
+                    model[idx] = value
+                    return
+
+            elif isinstance(model, dict):
+                # Handle dictionaries (auto-create missing keys)
+
+                # Get next type from parent key type information
+                next_type = parent_key_types[len(parent_key) - 1]
+
+                if is_final_key:
+                    if (
+                        (isinstance(next_type, type) and not isinstance(value, next_type))
+                        or (next_type is dict and not isinstance(value, dict))
+                        or (next_type is list and not isinstance(value, list))
+                    ):
+                        raise TypeError(
+                            f"Expected type {next_type} for key '{key}' in path '{path}', but got {type(value)}: {value}"
+                        )
+                    model[key] = value
+                    return
+
+                if key not in model:
+                    next_value = self._initialize_value(next_type)
+                    if next_value is None:
+                        raise TypeError(
+                            f"Unable to initialize missing value for key '{key}' in path '{path}' with type {next_type} of {parent_key}:{parent_key_types}."
+                        )
+                    model[key] = next_value
+                else:
+                    next_value = model[key]
+
+            else:
+                raise KeyError(f"Key '{key}' not found in model.")
+
+            # Move deeper
+            model = next_value
+
+    @staticmethod
+    def _get_key_types(model: Type[BaseModel], key: str) -> List[Union[Type[Any], list, dict]]:
+        """Returns a list of nested types for a given Pydantic model key.
+
+        - Skips `Optional` and `Union`, using only the first non-None type.
+        - Skips dictionary keys and only adds value types.
+        - Keeps `list` and `dict` as origins.
+
+        Args:
+            model (Type[BaseModel]): The Pydantic model class to inspect.
+            key (str): The attribute name in the model.
+
+        Returns:
+            List[Union[Type[Any], list, dict]]: A list of extracted types, preserving `list` and `dict` origins.
+
+        Raises:
+            TypeError: If the key does not exist or lacks a valid type annotation.
+        """
+        if not inspect.isclass(model):
+            raise TypeError(f"Model '{model}' is not of class type.")
+
+        if key not in model.model_fields:
+            raise TypeError(f"Field '{key}' does not exist in model '{model.__name__}'.")
+
+        field_annotation = model.model_fields[key].annotation
+        if not field_annotation:
+            raise TypeError(
+                f"Missing type annotation for field '{key}' in model '{model.__name__}'."
+            )
+
+        nested_types: list[Union[Type[Any], list, dict]] = []
+        queue: list[Any] = [field_annotation]
+
+        while queue:
+            annotation = queue.pop(0)
+            origin = get_origin(annotation)
+            args = get_args(annotation)
+
+            # Handle Union (Optional[X] is treated as Union[X, None])
+            if origin is Union:
+                queue.extend(arg for arg in args if arg is not type(None))
+                continue
+
+            # Handle lists and dictionaries
+            if origin is list:
+                nested_types.append(list)
+                if args:
+                    queue.append(args[0])  # Extract value type for list[T]
+                continue
+
+            if origin is dict:
+                nested_types.append(dict)
+                if len(args) == 2:
+                    queue.append(args[1])  # Extract only the value type for dict[K, V]
+                continue
+
+            # If it's a BaseModel, add it to the list
+            if isinstance(annotation, type) and issubclass(annotation, BaseModel):
+                nested_types.append(annotation)
+                continue
+
+            # Otherwise, it's a standard type (e.g., str, int, bool, float, etc.)
+            nested_types.append(annotation)
+
+        return nested_types
+
+    @staticmethod
+    def _initialize_value(type_hint: Type[Any] | None | list[Any] | dict[Any, Any]) -> Any:
+        """Initialize a missing value based on the provided type hint.
+
+        Args:
+            type_hint (Type[Any] | None | list[Any] | dict[Any, Any]): The type hint that determines
+                how the missing value should be initialized.
+
+        Returns:
+            Any: An instance of the expected type (e.g., list, dict, or Pydantic model), or `None`
+                if initialization is not possible.
+
+        Raises:
+            TypeError: If instantiation fails.
+
+        Example:
+            - For `list[str]`, returns `[]`
+            - For `dict[str, Any]`, returns `{}`
+            - For `Address` (a Pydantic model), returns a new `Address()` instance.
+        """
+        if type_hint is None:
+            return None
+
+        # Handle direct instances of list or dict
+        if isinstance(type_hint, list):
+            return []
+        if isinstance(type_hint, dict):
+            return {}
+
+        origin = get_origin(type_hint)
+
+        # Handle generic list and dictionary
+        if origin is list:
+            return []
+        if origin is dict:
+            return {}
+
+        # Handle Pydantic models
+        if isinstance(type_hint, type) and issubclass(type_hint, BaseModel):
+            try:
+                return type_hint.model_construct()
+            except Exception as e:
+                raise TypeError(f"Failed to initialize model '{type_hint.__name__}': {e}")
+
+        # Handle standard built-in types (int, float, str, bool, etc.)
+        if isinstance(type_hint, type):
+            try:
+                return type_hint()
+            except Exception as e:
+                raise TypeError(f"Failed to initialize instance of '{type_hint.__name__}': {e}")
+
+        raise TypeError(f"Unsupported type hint '{type_hint}' for initialization.")
+
+
+class PydanticBaseModel(PydanticModelNestedValueMixin, BaseModel):
+    """Base model with pendulum datetime support, nested value utilities, and stable hashing.
+
+    This class provides:
+    - ISO 8601 serialization/deserialization of `pendulum.DateTime` fields.
+    - Nested attribute access and mutation via `PydanticModelNestedValueMixin`.
+    - A consistent hash using a UUID for use in sets and as dictionary keys
     """
 
     # Enable custom serialization globally in config
@@ -96,6 +642,17 @@ class PydanticBaseModel(BaseModel):
         validate_assignment=True,
     )
 
+    _uuid: str = PrivateAttr(default_factory=lambda: str(uuid.uuid4()))
+    """str: A private UUID string generated on instantiation, used for hashing."""
+
+    def __hash__(self) -> int:
+        """Returns a stable hash based on the instance's UUID.
+
+        Returns:
+            int: Hash value derived from the model's UUID.
+        """
+        return hash(self._uuid)
+
     @field_validator("*", mode="before")
     def validate_and_convert_pendulum(cls, value: Any, info: ValidationInfo) -> Any:
         """Validator to convert fields of type `pendulum.DateTime`.
@@ -124,8 +681,8 @@ class PydanticBaseModel(BaseModel):
         if expected_type is pendulum.DateTime or expected_type is AwareDatetime:
             try:
                 value = to_datetime(value)
-            except:
+            except Exception as e:
-                pass
+                raise ValueError(f"Cannot convert {value!r} to datetime: {e}")
         return value
 
     # Override Pydantic’s serialization for all DateTime fields
@@ -373,6 +930,10 @@ class PydanticDateTimeDataFrame(PydanticBaseModel):
         index = pd.Index([to_datetime(dt, in_timezone=self.tz) for dt in df.index])
         df.index = index
 
+        # Check if 'date_time' column exists, if not, create it
+        if "date_time" not in df.columns:
+            df["date_time"] = df.index
+
         dtype_mapping = {
             "int": int,
             "float": float,
@@ -509,3 +1070,27 @@ class PydanticDateTimeSeries(PydanticBaseModel):
 
 class ParametersBaseModel(PydanticBaseModel):
     model_config = ConfigDict(extra="forbid")
+
+
+def set_private_attr(
+    model: Union[PydanticBaseModel, PydanticModelNestedValueMixin], key: str, value: Any
+) -> None:
+    """Set a private attribute for a model instance (not stored in model itself)."""
+    if model not in _model_private_state:
+        _model_private_state[model] = {}
+    _model_private_state[model][key] = value
+
+
+def get_private_attr(
+    model: Union[PydanticBaseModel, PydanticModelNestedValueMixin], key: str, default: Any = None
+) -> Any:
+    """Get a private attribute or return default."""
+    return _model_private_state.get(model, {}).get(key, default)
+
+
+def del_private_attr(
+    model: Union[PydanticBaseModel, PydanticModelNestedValueMixin], key: str
+) -> None:
+    """Delete a private attribute."""
+    if model in _model_private_state and key in _model_private_state[model]:
+        del _model_private_state[model][key]

src/akkudoktoreos/devices/battery.py

@@ -3,7 +3,6 @@ from typing import Any, Optional
 import numpy as np
 from pydantic import Field, field_validator
 
-from akkudoktoreos.core.logging import get_logger
 from akkudoktoreos.devices.devicesabc import (
     DeviceBase,
     DeviceOptimizeResult,
@@ -11,8 +10,6 @@ from akkudoktoreos.devices.devicesabc import (
 )
 from akkudoktoreos.utils.utils import NumpyEncoder
 
-logger = get_logger(__name__)
-
 
 def max_charging_power_field(description: Optional[str] = None) -> float:
     if description is None:
@@ -121,7 +118,8 @@ class Battery(DeviceBase):
 
     def _setup(self) -> None:
         """Sets up the battery parameters based on configuration or provided parameters."""
-        assert self.parameters is not None
+        if self.parameters is None:
+            raise ValueError(f"Parameters not set: {self.parameters}")
         self.capacity_wh = self.parameters.capacity_wh
         self.initial_soc_percentage = self.parameters.initial_soc_percentage
         self.charging_efficiency = self.parameters.charging_efficiency

src/akkudoktoreos/devices/devices.py

@@ -1,15 +1,12 @@
 from typing import Optional
 
 from akkudoktoreos.core.coreabc import SingletonMixin
-from akkudoktoreos.core.logging import get_logger
 from akkudoktoreos.devices.battery import Battery
 from akkudoktoreos.devices.devicesabc import DevicesBase
 from akkudoktoreos.devices.generic import HomeAppliance
 from akkudoktoreos.devices.inverter import Inverter
 from akkudoktoreos.devices.settings import DevicesCommonSettings
 
-logger = get_logger(__name__)
-
 
 class Devices(SingletonMixin, DevicesBase):
     def __init__(self, settings: Optional[DevicesCommonSettings] = None):
@@ -40,9 +37,13 @@ class Devices(SingletonMixin, DevicesBase):
 
 
 # Initialize the Devices simulation, it is a singleton.
-devices = Devices()
+devices: Optional[Devices] = None
 
 
 def get_devices() -> Devices:
+    global devices
+    # Fix circular import at runtime
+    if devices is None:
+        devices = Devices()
     """Gets the EOS Devices simulation."""
     return devices

src/akkudoktoreos/devices/devicesabc.py

@@ -3,6 +3,7 @@
 from enum import Enum
 from typing import Optional, Type
 
+from loguru import logger
 from pendulum import DateTime
 from pydantic import Field, computed_field
 
@@ -12,12 +13,9 @@ from akkudoktoreos.core.coreabc import (
     EnergyManagementSystemMixin,
     PredictionMixin,
 )
-from akkudoktoreos.core.logging import get_logger
 from akkudoktoreos.core.pydantic import ParametersBaseModel
 from akkudoktoreos.utils.datetimeutil import to_duration
 
-logger = get_logger(__name__)
-
 
 class DeviceParameters(ParametersBaseModel):
     device_id: str = Field(description="ID of device", examples="device1")
@@ -170,7 +168,8 @@ class DevicesBase(DevicesStartEndMixin, PredictionMixin):
     def add_device(self, device: Optional["DeviceBase"]) -> None:
         if device is None:
             return
-        assert device.device_id not in self.devices, f"{device.device_id} already registered"
+        if device.device_id in self.devices:
+            raise ValueError(f"{device.device_id} already registered")
         self.devices[device.device_id] = device
 
     def remove_device(self, device: Type["DeviceBase"] | str) -> bool:

src/akkudoktoreos/devices/generic.py

@@ -3,11 +3,8 @@ from typing import Optional
 import numpy as np
 from pydantic import Field
 
-from akkudoktoreos.core.logging import get_logger
 from akkudoktoreos.devices.devicesabc import DeviceBase, DeviceParameters
 
-logger = get_logger(__name__)
-
 
 class HomeApplianceParameters(DeviceParameters):
     """Home Appliance Device Simulation Configuration."""
@@ -34,7 +31,8 @@ class HomeAppliance(DeviceBase):
         super().__init__(parameters)
 
     def _setup(self) -> None:
-        assert self.parameters is not None
+        if self.parameters is None:
+            raise ValueError(f"Parameters not set: {self.parameters}")
         self.load_curve = np.zeros(self.hours)  # Initialize the load curve with zeros
         self.duration_h = self.parameters.duration_h
         self.consumption_wh = self.parameters.consumption_wh

src/akkudoktoreos/devices/heatpump.py

@@ -1,6 +1,7 @@
-import logging
 from typing import List, Sequence
 
+from loguru import logger
+
 
 class Heatpump:
     MAX_HEAT_OUTPUT = 5000
@@ -21,7 +22,6 @@ class Heatpump:
     def __init__(self, max_heat_output: int, hours: int):
         self.max_heat_output = max_heat_output
         self.hours = hours
-        self.log = logging.getLogger(__name__)
 
     def __check_outside_temperature_range__(self, temp_celsius: float) -> bool:
         """Check if temperature is in valid range between -100 and 100 degree Celsius.
@@ -58,7 +58,7 @@ class Heatpump:
                 f"Outside temperature '{outside_temperature_celsius}' not in range "
                 "(min: -100 Celsius, max: 100 Celsius)"
             )
-            self.log.error(err_msg)
+            logger.error(err_msg)
             raise ValueError(err_msg)
 
     def calculate_heating_output(self, outside_temperature_celsius: float) -> float:
@@ -86,7 +86,7 @@ class Heatpump:
                 f"Outside temperature '{outside_temperature_celsius}' not in range "
                 "(min: -100 Celsius, max: 100 Celsius)"
             )
-            self.log.error(err_msg)
+            logger.error(err_msg)
             raise ValueError(err_msg)
 
     def calculate_heat_power(self, outside_temperature_celsius: float) -> float:
@@ -110,7 +110,7 @@ class Heatpump:
                 f"Outside temperature '{outside_temperature_celsius}' not in range "
                 "(min: -100 Celsius, max: 100 Celsius)"
             )
-            self.log.error(err_msg)
+            logger.error(err_msg)
             raise ValueError(err_msg)
 
     def simulate_24h(self, temperatures: Sequence[float]) -> List[float]:

src/akkudoktoreos/devices/inverter.py

@@ -1,13 +1,11 @@
 from typing import Optional
 
+from loguru import logger
 from pydantic import Field
 
-from akkudoktoreos.core.logging import get_logger
 from akkudoktoreos.devices.devicesabc import DeviceBase, DeviceParameters
 from akkudoktoreos.prediction.interpolator import get_eos_load_interpolator
 
-logger = get_logger(__name__)
-
 
 class InverterParameters(DeviceParameters):
     """Inverter Device Simulation Configuration."""
@@ -27,8 +25,25 @@ class Inverter(DeviceBase):
         self.parameters: Optional[InverterParameters] = None
         super().__init__(parameters)
 
+        self.scr_lookup: dict = {}
+
+    def _calculate_scr(self, consumption: float, generation: float) -> float:
+        """Check if the consumption and production is in the lookup table. If not, calculate and store the value."""
+        if consumption not in self.scr_lookup:
+            self.scr_lookup[consumption] = {}
+
+        if generation not in self.scr_lookup[consumption]:
+            scr = self.self_consumption_predictor.calculate_self_consumption(
+                consumption, generation
+            )
+            self.scr_lookup[consumption][generation] = scr
+            return scr
+
+        return self.scr_lookup[consumption][generation]
+
     def _setup(self) -> None:
-        assert self.parameters is not None
+        if self.parameters is None:
+            raise ValueError(f"Parameters not set: {self.parameters}")
         if self.parameters.battery_id is None:
             # For the moment raise exception
             # TODO: Make battery configurable by config
@@ -41,7 +56,8 @@ class Inverter(DeviceBase):
         )  # Maximum power that the inverter can handle
 
     def _post_setup(self) -> None:
-        assert self.parameters is not None
+        if self.parameters is None:
+            raise ValueError(f"Parameters not set: {self.parameters}")
         self.battery = self.devices.get_device_by_id(self.parameters.battery_id)
 
     def process_energy(
@@ -60,9 +76,8 @@ class Inverter(DeviceBase):
                 grid_import = -remaining_power  # Negative indicates feeding into the grid
                 self_consumption = self.max_power_wh
             else:
-                scr = self.self_consumption_predictor.calculate_self_consumption(
+                # Calculate scr with lookup table
-                    consumption, generation
+                scr = self._calculate_scr(consumption, generation)
-                )
 
                 # Remaining power after consumption
                 remaining_power = (generation - consumption) * scr  # EVQ

src/akkudoktoreos/devices/settings.py

@@ -3,13 +3,10 @@ from typing import Optional
 from pydantic import Field
 
 from akkudoktoreos.config.configabc import SettingsBaseModel
-from akkudoktoreos.core.logging import get_logger
 from akkudoktoreos.devices.battery import BaseBatteryParameters
 from akkudoktoreos.devices.generic import HomeApplianceParameters
 from akkudoktoreos.devices.inverter import InverterParameters
 
-logger = get_logger(__name__)
-
 
 class DevicesCommonSettings(SettingsBaseModel):
     """Base configuration for devices simulation settings."""

src/akkudoktoreos/measurement/measurement.py

@@ -9,6 +9,7 @@ The measurements can be added programmatically or imported from a file or JSON s
 from typing import Any, ClassVar, List, Optional
 
 import numpy as np
+from loguru import logger
 from numpydantic import NDArray, Shape
 from pendulum import DateTime, Duration
 from pydantic import Field, computed_field
@@ -16,11 +17,8 @@ from pydantic import Field, computed_field
 from akkudoktoreos.config.configabc import SettingsBaseModel
 from akkudoktoreos.core.coreabc import SingletonMixin
 from akkudoktoreos.core.dataabc import DataImportMixin, DataRecord, DataSequence
-from akkudoktoreos.core.logging import get_logger
 from akkudoktoreos.utils.datetimeutil import to_duration
 
-logger = get_logger(__name__)
-
 
 class MeasurementCommonSettings(SettingsBaseModel):
     """Measurement Configuration."""

src/akkudoktoreos/optimization/genetic.py

@@ -1,10 +1,10 @@
-import logging
 import random
 import time
 from typing import Any, Optional
 
 import numpy as np
 from deap import algorithms, base, creator, tools
+from loguru import logger
 from pydantic import Field, field_validator, model_validator
 from typing_extensions import Self
 
@@ -13,8 +13,7 @@ from akkudoktoreos.core.coreabc import (
     DevicesMixin,
     EnergyManagementSystemMixin,
 )
-from akkudoktoreos.core.ems import EnergieManagementSystemParameters, SimulationResult
+from akkudoktoreos.core.ems import EnergyManagementParameters, SimulationResult
-from akkudoktoreos.core.logging import get_logger
 from akkudoktoreos.core.pydantic import ParametersBaseModel
 from akkudoktoreos.devices.battery import (
     Battery,
@@ -26,11 +25,9 @@ from akkudoktoreos.devices.generic import HomeAppliance, HomeApplianceParameters
 from akkudoktoreos.devices.inverter import Inverter, InverterParameters
 from akkudoktoreos.utils.utils import NumpyEncoder
 
-logger = get_logger(__name__)
-
 
 class OptimizationParameters(ParametersBaseModel):
-    ems: EnergieManagementSystemParameters
+    ems: EnergyManagementParameters
     pv_akku: Optional[SolarPanelBatteryParameters]
     inverter: Optional[InverterParameters]
     eauto: Optional[ElectricVehicleParameters]
@@ -121,8 +118,8 @@ class optimization_problem(ConfigMixin, DevicesMixin, EnergyManagementSystemMixi
         # Set a fixed seed for random operations if provided or in debug mode
         if self.fix_seed is not None:
             random.seed(self.fix_seed)
-        elif logger.level == logging.DEBUG:
+        elif logger.level == "DEBUG":
-            self.fix_seed = random.randint(1, 100000000000)
+            self.fix_seed = random.randint(1, 100000000000)  # noqa: S311
             random.seed(self.fix_seed)
 
     def decode_charge_discharge(

src/akkudoktoreos/optimization/optimization.py

@@ -3,9 +3,6 @@ from typing import List, Optional
 from pydantic import Field
 
 from akkudoktoreos.config.configabc import SettingsBaseModel
-from akkudoktoreos.core.logging import get_logger
-
-logger = get_logger(__name__)
 
 
 class OptimizationCommonSettings(SettingsBaseModel):

src/akkudoktoreos/optimization/optimizationabc.py

@@ -3,11 +3,8 @@
 from pydantic import ConfigDict
 
 from akkudoktoreos.core.coreabc import ConfigMixin, PredictionMixin
-from akkudoktoreos.core.logging import get_logger
 from akkudoktoreos.core.pydantic import PydanticBaseModel
 
-logger = get_logger(__name__)
-
 
 class OptimizationBase(ConfigMixin, PredictionMixin, PydanticBaseModel):
     """Base class for handling optimization data.

src/akkudoktoreos/prediction/elecprice.py

@@ -1,9 +1,20 @@
 from typing import Optional
 
-from pydantic import Field
+from pydantic import Field, field_validator
 
 from akkudoktoreos.config.configabc import SettingsBaseModel
+from akkudoktoreos.prediction.elecpriceabc import ElecPriceProvider
 from akkudoktoreos.prediction.elecpriceimport import ElecPriceImportCommonSettings
+from akkudoktoreos.prediction.prediction import get_prediction
+
+prediction_eos = get_prediction()
+
+# Valid elecprice providers
+elecprice_providers = [
+    provider.provider_id()
+    for provider in prediction_eos.providers
+    if isinstance(provider, ElecPriceProvider)
+]
 
 
 class ElecPriceCommonSettings(SettingsBaseModel):
@@ -17,7 +28,23 @@ class ElecPriceCommonSettings(SettingsBaseModel):
     charges_kwh: Optional[float] = Field(
         default=None, ge=0, description="Electricity price charges (€/kWh).", examples=[0.21]
     )
+    vat_rate: Optional[float] = Field(
+        default=1.19,
+        ge=0,
+        description="VAT rate factor applied to electricity price when charges are used.",
+        examples=[1.19],
+    )
 
     provider_settings: Optional[ElecPriceImportCommonSettings] = Field(
         default=None, description="Provider settings", examples=[None]
     )
+
+    # Validators
+    @field_validator("provider", mode="after")
+    @classmethod
+    def validate_provider(cls, value: Optional[str]) -> Optional[str]:
+        if value is None or value in elecprice_providers:
+            return value
+        raise ValueError(
+            f"Provider '{value}' is not a valid electricity price provider: {elecprice_providers}."
+        )

src/akkudoktoreos/prediction/elecpriceabc.py

@@ -9,11 +9,8 @@ from typing import List, Optional
 
 from pydantic import Field, computed_field
 
-from akkudoktoreos.core.logging import get_logger
 from akkudoktoreos.prediction.predictionabc import PredictionProvider, PredictionRecord
 
-logger = get_logger(__name__)
-
 
 class ElecPriceDataRecord(PredictionRecord):
     """Represents a electricity price data record containing various price attributes at a specific datetime.

src/akkudoktoreos/prediction/elecpriceakkudoktor.py

@@ -11,17 +11,15 @@ from typing import Any, List, Optional, Union
 import numpy as np
 import pandas as pd
 import requests
+from loguru import logger
 from pydantic import ValidationError
 from statsmodels.tsa.holtwinters import ExponentialSmoothing
 
-from akkudoktoreos.core.logging import get_logger
+from akkudoktoreos.core.cache import cache_in_file
 from akkudoktoreos.core.pydantic import PydanticBaseModel
 from akkudoktoreos.prediction.elecpriceabc import ElecPriceProvider
-from akkudoktoreos.utils.cacheutil import cache_in_file
 from akkudoktoreos.utils.datetimeutil import to_datetime, to_duration
 
-logger = get_logger(__name__)
-
 
 class AkkudoktorElecPriceMeta(PydanticBaseModel):
     start_timestamp: str
@@ -104,12 +102,13 @@ class ElecPriceAkkudoktor(ElecPriceProvider):
             - add the file cache again.
         """
         source = "https://api.akkudoktor.net"
-        assert self.start_datetime  # mypy fix
+        if not self.start_datetime:
+            raise ValueError(f"Start DateTime not set: {self.start_datetime}")
         # Try to take data from 5 weeks back for prediction
         date = to_datetime(self.start_datetime - to_duration("35 days"), as_string="YYYY-MM-DD")
         last_date = to_datetime(self.end_datetime, as_string="YYYY-MM-DD")
         url = f"{source}/prices?start={date}&end={last_date}&tz={self.config.general.timezone}"
-        response = requests.get(url)
+        response = requests.get(url, timeout=10)
         logger.debug(f"Response from {url}: {response}")
         response.raise_for_status()  # Raise an error for bad responses
         akkudoktor_data = self._validate_data(response.content)
@@ -148,7 +147,8 @@ class ElecPriceAkkudoktor(ElecPriceProvider):
         """
         # Get Akkudoktor electricity price data
         akkudoktor_data = self._request_forecast(force_update=force_update)  # type: ignore
-        assert self.start_datetime  # mypy fix
+        if not self.start_datetime:
+            raise ValueError(f"Start DateTime not set: {self.start_datetime}")
 
         # Assumption that all lists are the same length and are ordered chronologically
         # in ascending order and have the same timestamps.
@@ -178,7 +178,10 @@ class ElecPriceAkkudoktor(ElecPriceProvider):
         )
 
         amount_datasets = len(self.records)
-        assert highest_orig_datetime  # mypy fix
+        if not highest_orig_datetime:  # mypy fix
+            error_msg = f"Highest original datetime not available: {highest_orig_datetime}"
+            logger.error(error_msg)
+            raise ValueError(error_msg)
 
         # some of our data is already in the future, so we need to predict less. If we got less data we increase the prediction hours
         needed_hours = int(

src/akkudoktoreos/prediction/elecpriceenergycharts.py

@@ -0,0 +1,257 @@
+"""Retrieves and processes electricity price forecast data from Energy-Charts.
+
+This module provides classes and mappings to manage electricity price data obtained from the
+Energy-Charts API, including support for various electricity price attributes such as temperature,
+humidity, cloud cover, and solar irradiance. The data is mapped to the `ElecPriceDataRecord`
+format, enabling consistent access to forecasted and historical electricity price attributes.
+"""
+
+from datetime import datetime
+from typing import Any, List, Optional, Union
+
+import numpy as np
+import pandas as pd
+import requests
+from loguru import logger
+from pydantic import ValidationError
+from statsmodels.tsa.holtwinters import ExponentialSmoothing
+
+from akkudoktoreos.core.cache import cache_in_file
+from akkudoktoreos.core.pydantic import PydanticBaseModel
+from akkudoktoreos.prediction.elecpriceabc import ElecPriceProvider
+from akkudoktoreos.utils.datetimeutil import to_datetime, to_duration
+
+
+class EnergyChartsElecPrice(PydanticBaseModel):
+    license_info: str
+    unix_seconds: List[int]
+    price: List[float]
+    unit: str
+    deprecated: bool
+
+
+class ElecPriceEnergyCharts(ElecPriceProvider):
+    """Fetch and process electricity price forecast data from Energy-Charts.
+
+    ElecPriceEnergyCharts is a singleton-based class that retrieves electricity price forecast data
+    from the Energy-Charts API and maps it to `ElecPriceDataRecord` fields, applying
+    any necessary scaling or unit corrections. It manages the forecast over a range
+    of hours into the future and retains historical data.
+
+    Attributes:
+        hours (int, optional): Number of hours in the future for the forecast.
+        historic_hours (int, optional): Number of past hours for retaining data.
+        start_datetime (datetime, optional): Start datetime for forecasts, defaults to the current datetime.
+        end_datetime (datetime, computed): The forecast's end datetime, computed based on `start_datetime` and `hours`.
+        keep_datetime (datetime, computed): The datetime to retain historical data, computed from `start_datetime` and `historic_hours`.
+
+    Methods:
+        provider_id(): Returns a unique identifier for the provider.
+        _request_forecast(): Fetches the forecast from the Energy-Charts API.
+        _update_data(): Processes and updates forecast data from Energy-Charts in ElecPriceDataRecord format.
+    """
+
+    highest_orig_datetime: Optional[datetime] = None
+
+    @classmethod
+    def provider_id(cls) -> str:
+        """Return the unique identifier for the Energy-Charts provider."""
+        return "ElecPriceEnergyCharts"
+
+    @classmethod
+    def _validate_data(cls, json_str: Union[bytes, Any]) -> EnergyChartsElecPrice:
+        """Validate Energy-Charts Electricity Price forecast data."""
+        try:
+            energy_charts_data = EnergyChartsElecPrice.model_validate_json(json_str)
+        except ValidationError as e:
+            error_msg = ""
+            for error in e.errors():
+                field = " -> ".join(str(x) for x in error["loc"])
+                message = error["msg"]
+                error_type = error["type"]
+                error_msg += f"Field: {field}\nError: {message}\nType: {error_type}\n"
+            logger.error(f"Energy-Charts schema change: {error_msg}")
+            raise ValueError(error_msg)
+        return energy_charts_data
+
+    @cache_in_file(with_ttl="1 hour")
+    def _request_forecast(self, start_date: Optional[str] = None) -> EnergyChartsElecPrice:
+        """Fetch electricity price forecast data from Energy-Charts API.
+
+        This method sends a request to Energy-Charts API to retrieve forecast data for a specified
+        date range. The response data is parsed and returned as JSON for further processing.
+
+        Returns:
+            dict: The parsed JSON response from Energy-Charts API containing forecast data.
+
+        Raises:
+            ValueError: If the API response does not include expected `electricity price` data.
+        """
+        source = "https://api.energy-charts.info"
+        if start_date is None:
+            # Try to take data from 5 weeks back for prediction
+            start_date = to_datetime(
+                self.start_datetime - to_duration("35 days"), as_string="YYYY-MM-DD"
+            )
+
+        last_date = to_datetime(self.end_datetime, as_string="YYYY-MM-DD")
+        url = f"{source}/price?bzn=DE-LU&start={start_date}&end={last_date}"
+        response = requests.get(url, timeout=30)
+        logger.debug(f"Response from {url}: {response}")
+        response.raise_for_status()  # Raise an error for bad responses
+        energy_charts_data = self._validate_data(response.content)
+        # We are working on fresh data (no cache), report update time
+        self.update_datetime = to_datetime(in_timezone=self.config.general.timezone)
+        return energy_charts_data
+
+    def _parse_data(self, energy_charts_data: EnergyChartsElecPrice) -> pd.Series:
+        # Assumption that all lists are the same length and are ordered chronologically
+        # in ascending order and have the same timestamps.
+
+        # Get charges_kwh in wh
+        charges_wh = (self.config.elecprice.charges_kwh or 0) / 1000
+
+        # Initialize
+        highest_orig_datetime = None  # newest datetime from the api after that we want to update.
+        series_data = pd.Series(dtype=float)  # Initialize an empty series
+
+        # Iterate over timestamps and prices together
+        for unix_sec, price_eur_per_mwh in zip(
+            energy_charts_data.unix_seconds, energy_charts_data.price
+        ):
+            orig_datetime = to_datetime(unix_sec, in_timezone=self.config.general.timezone)
+
+            # Track the latest datetime
+            if highest_orig_datetime is None or orig_datetime > highest_orig_datetime:
+                highest_orig_datetime = orig_datetime
+
+            # Convert EUR/MWh to EUR/Wh, apply charges and VAT if charges > 0
+            if charges_wh > 0:
+                vat_rate = self.config.elecprice.vat_rate or 1.19
+                price_wh = ((price_eur_per_mwh / 1_000_000) + charges_wh) * vat_rate
+            else:
+                price_wh = price_eur_per_mwh / 1_000_000
+
+            # Store in series
+            series_data.at[orig_datetime] = price_wh
+
+        return series_data
+
+    def _cap_outliers(self, data: np.ndarray, sigma: int = 2) -> np.ndarray:
+        mean = data.mean()
+        std = data.std()
+        lower_bound = mean - sigma * std
+        upper_bound = mean + sigma * std
+        capped_data = data.clip(min=lower_bound, max=upper_bound)
+        return capped_data
+
+    def _predict_ets(self, history: np.ndarray, seasonal_periods: int, hours: int) -> np.ndarray:
+        clean_history = self._cap_outliers(history)
+        model = ExponentialSmoothing(
+            clean_history, seasonal="add", seasonal_periods=seasonal_periods
+        ).fit()
+        return model.forecast(hours)
+
+    def _predict_median(self, history: np.ndarray, hours: int) -> np.ndarray:
+        clean_history = self._cap_outliers(history)
+        return np.full(hours, np.median(clean_history))
+
+    def _update_data(
+        self, force_update: Optional[bool] = False
+    ) -> None:  # tuple[np.ndarray, np.ndarray, np.ndarray]:
+        """Update forecast data in the ElecPriceDataRecord format.
+
+        Retrieves data from Energy-Charts, maps each Energy-Charts field to the corresponding
+        `ElecPriceDataRecord` and applies any necessary scaling.
+
+        The final mapped and processed data is inserted into the sequence as `ElecPriceDataRecord`.
+        """
+        # New prices are available every day at 14:00
+        now = pd.Timestamp.now(tz=self.config.general.timezone)
+        midnight = now.normalize()
+        hours_ahead = 23 if now.time() < pd.Timestamp("14:00").time() else 47
+        end = midnight + pd.Timedelta(hours=hours_ahead)
+
+        if not self.start_datetime:
+            raise ValueError(f"Start DateTime not set: {self.start_datetime}")
+
+        # Determine if update is needed and how many days
+        past_days = 35
+        if self.highest_orig_datetime:
+            history_series = self.key_to_series(
+                key="elecprice_marketprice_wh", start_datetime=self.start_datetime
+            )
+            # If history lower, then start_datetime
+            if history_series.index.min() <= self.start_datetime:
+                past_days = 0
+
+            needs_update = end > self.highest_orig_datetime
+        else:
+            needs_update = True
+
+        if needs_update:
+            logger.info(
+                f"Update ElecPriceEnergyCharts is needed, last in history: {self.highest_orig_datetime}"
+            )
+            # Set start_date try to take data from 5 weeks back for prediction
+            start_date = to_datetime(
+                self.start_datetime - to_duration(f"{past_days} days"), as_string="YYYY-MM-DD"
+            )
+            # Get Energy-Charts electricity price data
+            energy_charts_data = self._request_forecast(
+                start_date=start_date, force_update=force_update
+            )  # type: ignore
+
+            # Parse and store data
+            series_data = self._parse_data(energy_charts_data)
+            self.highest_orig_datetime = series_data.index.max()
+            self.key_from_series("elecprice_marketprice_wh", series_data)
+        else:
+            logger.info(
+                f"No Update ElecPriceEnergyCharts is needed, last in history: {self.highest_orig_datetime}"
+            )
+
+        # Generate history array for prediction
+        history = self.key_to_array(
+            key="elecprice_marketprice_wh",
+            end_datetime=self.highest_orig_datetime,
+            fill_method="linear",
+        )
+
+        amount_datasets = len(self.records)
+        if not self.highest_orig_datetime:  # mypy fix
+            error_msg = f"Highest original datetime not available: {self.highest_orig_datetime}"
+            logger.error(error_msg)
+            raise ValueError(error_msg)
+
+        # some of our data is already in the future, so we need to predict less. If we got less data we increase the prediction hours
+        needed_hours = int(
+            self.config.prediction.hours
+            - ((self.highest_orig_datetime - self.start_datetime).total_seconds() // 3600)
+        )
+
+        if needed_hours <= 0:
+            logger.warning(
+                f"No prediction needed. needed_hours={needed_hours}, hours={self.config.prediction.hours},highest_orig_datetime {self.highest_orig_datetime}, start_datetime {self.start_datetime}"
+            )  # this might keep data longer than self.start_datetime + self.config.prediction.hours in the records
+            return
+
+        if amount_datasets > 800:  # we do the full ets with seasons of 1 week
+            prediction = self._predict_ets(history, seasonal_periods=168, hours=needed_hours)
+        elif amount_datasets > 168:  # not enough data to do seasons of 1 week, but enough for 1 day
+            prediction = self._predict_ets(history, seasonal_periods=24, hours=needed_hours)
+        elif amount_datasets > 0:  # not enough data for ets, do median
+            prediction = self._predict_median(history, hours=needed_hours)
+        else:
+            logger.error("No data available for prediction")
+            raise ValueError("No data available")
+
+        # write predictions into the records, update if exist.
+        prediction_series = pd.Series(
+            data=prediction,
+            index=[
+                self.highest_orig_datetime + to_duration(f"{i + 1} hours")
+                for i in range(len(prediction))
+            ],
+        )
+        self.key_from_series("elecprice_marketprice_wh", prediction_series)

src/akkudoktoreos/prediction/elecpriceimport.py

@@ -9,15 +9,13 @@ format, enabling consistent access to forecasted and historical elecprice attrib
 from pathlib import Path
 from typing import Optional, Union
 
+from loguru import logger
 from pydantic import Field, field_validator
 
 from akkudoktoreos.config.configabc import SettingsBaseModel
-from akkudoktoreos.core.logging import get_logger
 from akkudoktoreos.prediction.elecpriceabc import ElecPriceProvider
 from akkudoktoreos.prediction.predictionabc import PredictionImportProvider
 
-logger = get_logger(__name__)
-
 
 class ElecPriceImportCommonSettings(SettingsBaseModel):
     """Common settings for elecprice data import from file or JSON String."""
@@ -63,6 +61,9 @@ class ElecPriceImport(ElecPriceProvider, PredictionImportProvider):
         return "ElecPriceImport"
 
     def _update_data(self, force_update: Optional[bool] = False) -> None:
+        if self.config.elecprice.provider_settings is None:
+            logger.debug(f"{self.provider_id()} data update without provider settings.")
+            return
         if self.config.elecprice.provider_settings.import_file_path:
             self.import_from_file(
                 self.config.elecprice.provider_settings.import_file_path,

src/akkudoktoreos/prediction/interpolator.py

@@ -14,7 +14,7 @@ class SelfConsumptionProbabilityInterpolator:
         self.filepath = filepath
         # Load the RegularGridInterpolator
         with open(self.filepath, "rb") as file:
-            self.interpolator: RegularGridInterpolator = pickle.load(file)
+            self.interpolator: RegularGridInterpolator = pickle.load(file)  # noqa: S301
 
     @lru_cache(maxsize=128)
     def generate_points(

src/akkudoktoreos/prediction/load.py

@@ -2,14 +2,23 @@
 
 from typing import Optional, Union
 
-from pydantic import Field
+from pydantic import Field, field_validator
 
 from akkudoktoreos.config.configabc import SettingsBaseModel
-from akkudoktoreos.core.logging import get_logger
+from akkudoktoreos.prediction.loadabc import LoadProvider
 from akkudoktoreos.prediction.loadakkudoktor import LoadAkkudoktorCommonSettings
 from akkudoktoreos.prediction.loadimport import LoadImportCommonSettings
+from akkudoktoreos.prediction.loadvrm import LoadVrmCommonSettings
+from akkudoktoreos.prediction.prediction import get_prediction
 
-logger = get_logger(__name__)
+prediction_eos = get_prediction()
+
+# Valid load providers
+load_providers = [
+    provider.provider_id()
+    for provider in prediction_eos.providers
+    if isinstance(provider, LoadProvider)
+]
 
 
 class LoadCommonSettings(SettingsBaseModel):
@@ -21,6 +30,14 @@ class LoadCommonSettings(SettingsBaseModel):
         examples=["LoadAkkudoktor"],
     )
 
-    provider_settings: Optional[Union[LoadAkkudoktorCommonSettings, LoadImportCommonSettings]] = (
+    provider_settings: Optional[
-        Field(default=None, description="Provider settings", examples=[None])
+        Union[LoadAkkudoktorCommonSettings, LoadVrmCommonSettings, LoadImportCommonSettings]
-    )
+    ] = Field(default=None, description="Provider settings", examples=[None])
+
+    # Validators
+    @field_validator("provider", mode="after")
+    @classmethod
+    def validate_provider(cls, value: Optional[str]) -> Optional[str]:
+        if value is None or value in load_providers:
+            return value
+        raise ValueError(f"Provider '{value}' is not a valid load provider: {load_providers}.")

src/akkudoktoreos/prediction/loadabc.py

@@ -9,11 +9,8 @@ from typing import List, Optional
 
 from pydantic import Field
 
-from akkudoktoreos.core.logging import get_logger
 from akkudoktoreos.prediction.predictionabc import PredictionProvider, PredictionRecord
 
-logger = get_logger(__name__)
-
 
 class LoadDataRecord(PredictionRecord):
     """Represents a load data record containing various load attributes at a specific datetime."""

src/akkudoktoreos/prediction/loadakkudoktor.py

@@ -3,15 +3,13 @@
 from typing import Optional
 
 import numpy as np
+from loguru import logger
 from pydantic import Field
 
 from akkudoktoreos.config.configabc import SettingsBaseModel
-from akkudoktoreos.core.logging import get_logger
 from akkudoktoreos.prediction.loadabc import LoadProvider
 from akkudoktoreos.utils.datetimeutil import compare_datetimes, to_datetime, to_duration
 
-logger = get_logger(__name__)
-
 
 class LoadAkkudoktorCommonSettings(SettingsBaseModel):
     """Common settings for load data import from file."""
@@ -122,10 +120,11 @@ class LoadAkkudoktor(LoadProvider):
             }
             if date.day_of_week < 5:
                 # Monday to Friday (0..4)
-                values["load_mean_adjusted"] = hourly_stats[0] + weekday_adjust[date.hour]
+                value_adjusted = hourly_stats[0] + weekday_adjust[date.hour]
             else:
                 # Saturday, Sunday (5, 6)
-                values["load_mean_adjusted"] = hourly_stats[0] + weekend_adjust[date.hour]
+                value_adjusted = hourly_stats[0] + weekend_adjust[date.hour]
+            values["load_mean_adjusted"] = max(0, value_adjusted)
             self.update_value(date, values)
             date += to_duration("1 hour")
         # We are working on fresh data (no cache), report update time

src/akkudoktoreos/prediction/loadimport.py

@@ -9,15 +9,13 @@ format, enabling consistent access to forecasted and historical load attributes.
 from pathlib import Path
 from typing import Optional, Union
 
+from loguru import logger
 from pydantic import Field, field_validator
 
 from akkudoktoreos.config.configabc import SettingsBaseModel
-from akkudoktoreos.core.logging import get_logger
 from akkudoktoreos.prediction.loadabc import LoadProvider
 from akkudoktoreos.prediction.predictionabc import PredictionImportProvider
 
-logger = get_logger(__name__)
-
 
 class LoadImportCommonSettings(SettingsBaseModel):
     """Common settings for load data import from file or JSON string."""
@@ -62,6 +60,9 @@ class LoadImport(LoadProvider, PredictionImportProvider):
         return "LoadImport"
 
     def _update_data(self, force_update: Optional[bool] = False) -> None:
+        if self.config.load.provider_settings is None:
+            logger.debug(f"{self.provider_id()} data update without provider settings.")
+            return
         if self.config.load.provider_settings.import_file_path:
             self.import_from_file(self.config.provider_settings.import_file_path, key_prefix="load")
         if self.config.load.provider_settings.import_json:

src/akkudoktoreos/prediction/loadvrm.py

@@ -0,0 +1,109 @@
+"""Retrieves load forecast data from VRM API."""
+
+from typing import Any, Optional, Union
+
+import requests
+from loguru import logger
+from pendulum import DateTime
+from pydantic import Field, ValidationError
+
+from akkudoktoreos.config.configabc import SettingsBaseModel
+from akkudoktoreos.core.pydantic import PydanticBaseModel
+from akkudoktoreos.prediction.loadabc import LoadProvider
+from akkudoktoreos.utils.datetimeutil import to_datetime
+
+
+class VrmForecastRecords(PydanticBaseModel):
+    vrm_consumption_fc: list[tuple[int, float]]
+    solar_yield_forecast: list[tuple[int, float]]
+
+
+class VrmForecastResponse(PydanticBaseModel):
+    success: bool
+    records: VrmForecastRecords
+    totals: dict
+
+
+class LoadVrmCommonSettings(SettingsBaseModel):
+    """Common settings for VRM API."""
+
+    load_vrm_token: str = Field(
+        default="your-token", description="Token for Connecting VRM API", examples=["your-token"]
+    )
+    load_vrm_idsite: int = Field(default=12345, description="VRM-Installation-ID", examples=[12345])
+
+
+class LoadVrm(LoadProvider):
+    """Fetch Load forecast data from VRM API."""
+
+    @classmethod
+    def provider_id(cls) -> str:
+        return "LoadVrm"
+
+    @classmethod
+    def _validate_data(cls, json_str: Union[bytes, Any]) -> VrmForecastResponse:
+        """Validate the VRM API load forecast response."""
+        try:
+            return VrmForecastResponse.model_validate_json(json_str)
+        except ValidationError as e:
+            error_msg = "\n".join(
+                f"Field: {' -> '.join(str(x) for x in err['loc'])}\n"
+                f"Error: {err['msg']}\nType: {err['type']}"
+                for err in e.errors()
+            )
+            logger.error(f"VRM-API schema validation failed:\n{error_msg}")
+            raise ValueError(error_msg)
+
+    def _request_forecast(self, start_ts: int, end_ts: int) -> VrmForecastResponse:
+        """Fetch forecast data from Victron VRM API."""
+        base_url = "https://vrmapi.victronenergy.com/v2/installations"
+        installation_id = self.config.load.provider_settings.load_vrm_idsite
+        api_token = self.config.load.provider_settings.load_vrm_token
+
+        url = f"{base_url}/{installation_id}/stats?type=forecast&start={start_ts}&end={end_ts}&interval=hours"
+        headers = {"X-Authorization": f"Token {api_token}", "Content-Type": "application/json"}
+
+        logger.debug(f"Requesting VRM load forecast: {url}")
+        try:
+            response = requests.get(url, headers=headers, timeout=30)
+            response.raise_for_status()
+        except requests.RequestException as e:
+            logger.error(f"Error during VRM API request: {e}")
+            raise RuntimeError("Failed to fetch load forecast from VRM API") from e
+
+        self.update_datetime = to_datetime(in_timezone=self.config.general.timezone)
+        return self._validate_data(response.content)
+
+    def _ts_to_datetime(self, timestamp: int) -> DateTime:
+        """Convert UNIX ms timestamp to timezone-aware datetime."""
+        return to_datetime(timestamp / 1000, in_timezone=self.config.general.timezone)
+
+    def _update_data(self, force_update: Optional[bool] = False) -> None:
+        """Fetch and store VRM load forecast as load_mean and related values."""
+        start_date = self.start_datetime.start_of("day")
+        end_date = self.start_datetime.add(hours=self.config.prediction.hours)
+        start_ts = int(start_date.timestamp())
+        end_ts = int(end_date.timestamp())
+
+        logger.info(f"Updating Load forecast from VRM: {start_date} to {end_date}")
+        vrm_forecast_data = self._request_forecast(start_ts, end_ts)
+
+        load_mean_data = []
+        for timestamp, value in vrm_forecast_data.records.vrm_consumption_fc:
+            date = self._ts_to_datetime(timestamp)
+            rounded_value = round(value, 2)
+
+            self.update_value(
+                date,
+                {"load_mean": rounded_value, "load_std": 0.0, "load_mean_adjusted": rounded_value},
+            )
+
+            load_mean_data.append((date, rounded_value))
+
+        logger.debug(f"Updated load_mean with {len(load_mean_data)} entries.")
+        self.update_datetime = to_datetime(in_timezone=self.config.general.timezone)
+
+
+if __name__ == "__main__":
+    lv = LoadVrm()
+    lv._update_data()

src/akkudoktoreos/prediction/prediction.py

@@ -32,12 +32,15 @@ from pydantic import Field
 
 from akkudoktoreos.config.configabc import SettingsBaseModel
 from akkudoktoreos.prediction.elecpriceakkudoktor import ElecPriceAkkudoktor
+from akkudoktoreos.prediction.elecpriceenergycharts import ElecPriceEnergyCharts
 from akkudoktoreos.prediction.elecpriceimport import ElecPriceImport
 from akkudoktoreos.prediction.loadakkudoktor import LoadAkkudoktor
 from akkudoktoreos.prediction.loadimport import LoadImport
+from akkudoktoreos.prediction.loadvrm import LoadVrm
 from akkudoktoreos.prediction.predictionabc import PredictionContainer
 from akkudoktoreos.prediction.pvforecastakkudoktor import PVForecastAkkudoktor
 from akkudoktoreos.prediction.pvforecastimport import PVForecastImport
+from akkudoktoreos.prediction.pvforecastvrm import PVForecastVrm
 from akkudoktoreos.prediction.weatherbrightsky import WeatherBrightSky
 from akkudoktoreos.prediction.weatherclearoutside import WeatherClearOutside
 from akkudoktoreos.prediction.weatherimport import WeatherImport
@@ -83,10 +86,13 @@ class Prediction(PredictionContainer):
     providers: List[
         Union[
             ElecPriceAkkudoktor,
+            ElecPriceEnergyCharts,
             ElecPriceImport,
             LoadAkkudoktor,
+            LoadVrm,
             LoadImport,
             PVForecastAkkudoktor,
+            PVForecastVrm,
             PVForecastImport,
             WeatherBrightSky,
             WeatherClearOutside,
@@ -97,10 +103,13 @@ class Prediction(PredictionContainer):
 
 # Initialize forecast providers, all are singletons.
 elecprice_akkudoktor = ElecPriceAkkudoktor()
+elecprice_energy_charts = ElecPriceEnergyCharts()
 elecprice_import = ElecPriceImport()
 load_akkudoktor = LoadAkkudoktor()
+load_vrm = LoadVrm()
 load_import = LoadImport()
 pvforecast_akkudoktor = PVForecastAkkudoktor()
+pvforecast_vrm = PVForecastVrm()
 pvforecast_import = PVForecastImport()
 weather_brightsky = WeatherBrightSky()
 weather_clearoutside = WeatherClearOutside()
@@ -114,10 +123,13 @@ def get_prediction() -> Prediction:
     prediction = Prediction(
         providers=[
             elecprice_akkudoktor,
+            elecprice_energy_charts,
             elecprice_import,
             load_akkudoktor,
+            load_vrm,
             load_import,
             pvforecast_akkudoktor,
+            pvforecast_vrm,
             pvforecast_import,
             weather_brightsky,
             weather_clearoutside,

src/akkudoktoreos/prediction/predictionabc.py

@@ -10,6 +10,7 @@ and manipulation of configuration and prediction data in a clear, scalable, and
 
 from typing import List, Optional
 
+from loguru import logger
 from pendulum import DateTime
 from pydantic import Field, computed_field
 
@@ -22,11 +23,8 @@ from akkudoktoreos.core.dataabc import (
     DataRecord,
     DataSequence,
 )
-from akkudoktoreos.core.logging import get_logger
 from akkudoktoreos.utils.datetimeutil import to_duration
 
-logger = get_logger(__name__)
-
 
 class PredictionBase(DataBase, MeasurementMixin):
     """Base class for handling prediction data.
@@ -206,9 +204,6 @@ class PredictionProvider(PredictionStartEndKeepMixin, DataProvider):
             force_enable (bool, optional): If True, forces the update even if the provider is disabled.
             force_update (bool, optional): If True, forces the provider to update the data even if still cached.
         """
-        # Update prediction configuration
-        self.config.update()
-
         # Check after configuration is updated.
         if not force_enable and not self.enabled():
             return

src/akkudoktoreos/prediction/pvforecast.py

@@ -1,15 +1,24 @@
 """PV forecast module for PV power predictions."""
 
-from typing import Any, ClassVar, List, Optional, Self
+from typing import Any, List, Optional, Self, Union
 
 from pydantic import Field, computed_field, field_validator, model_validator
 
 from akkudoktoreos.config.configabc import SettingsBaseModel
-from akkudoktoreos.core.logging import get_logger
+from akkudoktoreos.prediction.prediction import get_prediction
+from akkudoktoreos.prediction.pvforecastabc import PVForecastProvider
 from akkudoktoreos.prediction.pvforecastimport import PVForecastImportCommonSettings
+from akkudoktoreos.prediction.pvforecastvrm import PVforecastVrmCommonSettings
 from akkudoktoreos.utils.docs import get_model_structure_from_examples
 
-logger = get_logger(__name__)
+prediction_eos = get_prediction()
+
+# Valid PV forecast providers
+pvforecast_providers = [
+    provider.provider_id()
+    for provider in prediction_eos.providers
+    if isinstance(provider, PVForecastProvider)
+]
 
 
 class PVForecastPlaneSetting(SettingsBaseModel):
@@ -17,14 +26,18 @@ class PVForecastPlaneSetting(SettingsBaseModel):
 
     # latitude: Optional[float] = Field(default=None, description="Latitude in decimal degrees, between -90 and 90, north is positive (ISO 19115) (°)")
     surface_tilt: Optional[float] = Field(
-        default=None,
+        default=30.0,
+        ge=0.0,
+        le=90.0,
         description="Tilt angle from horizontal plane. Ignored for two-axis tracking.",
         examples=[10.0, 20.0],
     )
     surface_azimuth: Optional[float] = Field(
-        default=None,
+        default=180.0,
+        ge=0.0,
+        le=360.0,
         description="Orientation (azimuth angle) of the (fixed) plane. Clockwise from north (north=0, east=90, south=180, west=270).",
-        examples=[10.0, 20.0],
+        examples=[180.0, 90.0],
     )
     userhorizon: Optional[List[float]] = Field(
         default=None,
@@ -71,7 +84,7 @@ class PVForecastPlaneSetting(SettingsBaseModel):
         default=None, description="Model of the inverter of this plane.", examples=[None]
     )
     inverter_paco: Optional[int] = Field(
-        default=None, description="AC power rating of the inverter. [W]", examples=[6000, 4000]
+        default=None, description="AC power rating of the inverter [W].", examples=[6000, 4000]
     )
     modules_per_string: Optional[int] = Field(
         default=None,
@@ -122,24 +135,30 @@ class PVForecastCommonSettings(SettingsBaseModel):
         examples=["PVForecastAkkudoktor"],
     )
 
+    provider_settings: Optional[
+        Union[PVForecastImportCommonSettings, PVforecastVrmCommonSettings]
+    ] = Field(default=None, description="Provider settings", examples=[None])
+
     planes: Optional[list[PVForecastPlaneSetting]] = Field(
         default=None,
         description="Plane configuration.",
         examples=[get_model_structure_from_examples(PVForecastPlaneSetting, True)],
     )
 
-    max_planes: ClassVar[int] = 6  # Maximum number of planes that can be set
+    max_planes: Optional[int] = Field(
+        default=0,
+        ge=0,
+        description="Maximum number of planes that can be set",
+    )
 
-    @field_validator("planes")
+    # Validators
-    def validate_planes(
+    @field_validator("provider", mode="after")
-        cls, planes: Optional[list[PVForecastPlaneSetting]]
+    @classmethod
-    ) -> Optional[list[PVForecastPlaneSetting]]:
+    def validate_provider(cls, value: Optional[str]) -> Optional[str]:
-        if planes is not None and len(planes) > cls.max_planes:
+        if value is None or value in pvforecast_providers:
-            raise ValueError(f"Maximum number of supported planes: {cls.max_planes}.")
+            return value
-        return planes
+        raise ValueError(
-
+            f"Provider '{value}' is not a valid PV forecast provider: {pvforecast_providers}."
-    provider_settings: Optional[PVForecastImportCommonSettings] = Field(
-        default=None, description="Provider settings", examples=[None]
         )
 
     ## Computed fields

src/akkudoktoreos/prediction/pvforecastabc.py

@@ -7,13 +7,11 @@ Notes:
 from abc import abstractmethod
 from typing import List, Optional
 
+from loguru import logger
 from pydantic import Field
 
-from akkudoktoreos.core.logging import get_logger
 from akkudoktoreos.prediction.predictionabc import PredictionProvider, PredictionRecord
 
-logger = get_logger(__name__)
-
 
 class PVForecastDataRecord(PredictionRecord):
     """Represents a pvforecast data record containing various pvforecast attributes at a specific datetime."""

src/akkudoktoreos/prediction/pvforecastakkudoktor.py

@@ -27,14 +27,14 @@ Example:
             "planes": [
                 {
                     "peakpower": 5.0,
-                    "surface_azimuth": -10,
+                    "surface_azimuth": 170,
                     "surface_tilt": 7,
                     "userhorizon": [20, 27, 22, 20],
                     "inverter_paco": 10000,
                 },
                 {
                     "peakpower": 4.8,
-                    "surface_azimuth": -90,
+                    "surface_azimuth": 90,
                     "surface_tilt": 7,
                     "userhorizon": [30, 30, 30, 50],
                     "inverter_paco": 10000,
@@ -78,24 +78,22 @@ Methods:
 from typing import Any, List, Optional, Union
 
 import requests
-from pydantic import Field, ValidationError, computed_field
+from loguru import logger
+from pydantic import Field, ValidationError, computed_field, field_validator
 
-from akkudoktoreos.core.logging import get_logger
+from akkudoktoreos.core.cache import cache_in_file
 from akkudoktoreos.core.pydantic import PydanticBaseModel
 from akkudoktoreos.prediction.pvforecastabc import (
     PVForecastDataRecord,
     PVForecastProvider,
 )
-from akkudoktoreos.utils.cacheutil import cache_in_file
 from akkudoktoreos.utils.datetimeutil import compare_datetimes, to_datetime
 
-logger = get_logger(__name__)
-
 
 class AkkudoktorForecastHorizon(PydanticBaseModel):
     altitude: int
-    azimuthFrom: int
+    azimuthFrom: float
-    azimuthTo: int
+    azimuthTo: float
 
 
 class AkkudoktorForecastMeta(PydanticBaseModel):
@@ -114,6 +112,30 @@ class AkkudoktorForecastMeta(PydanticBaseModel):
     horizont: List[List[AkkudoktorForecastHorizon]]
     horizontString: List[str]
 
+    @field_validator("power", "azimuth", "tilt", "powerInverter", mode="before")
+    @classmethod
+    def ensure_list(cls, v: Any) -> List[int]:
+        return v if isinstance(v, list) else [v]
+
+    @field_validator("horizont", mode="before")
+    @classmethod
+    def normalize_horizont(cls, v: Any) -> List[List[AkkudoktorForecastHorizon]]:
+        if isinstance(v, list):
+            # Case: flat list of dicts
+            if v and isinstance(v[0], dict):
+                return [v]
+            # Already in correct nested form
+            if v and isinstance(v[0], list):
+                return v
+        return v
+
+    @field_validator("horizontString", mode="before")
+    @classmethod
+    def parse_horizont_string(cls, v: Any) -> List[str]:
+        if isinstance(v, str):
+            return [s.strip() for s in v.split(",")]
+        return v
+
 
 class AkkudoktorForecastValue(PydanticBaseModel):
     datetime: str
@@ -221,13 +243,18 @@ class PVForecastAkkudoktor(PVForecastProvider):
 
         for i in range(len(self.config.pvforecast.planes)):
             query_params.append(f"power={int(self.config.pvforecast.planes_peakpower[i] * 1000)}")
-            query_params.append(f"azimuth={int(self.config.pvforecast.planes_azimuth[i])}")
+            # EOS orientation of of pv modules in azimuth in degree:
+            #   north=0, east=90, south=180, west=270
+            # Akkudoktor orientation of pv modules in azimuth in degree:
+            #   north=+-180, east=-90, south=0, west=90
+            azimuth_akkudoktor = int(self.config.pvforecast.planes_azimuth[i]) - 180
+            query_params.append(f"azimuth={azimuth_akkudoktor}")
             query_params.append(f"tilt={int(self.config.pvforecast.planes_tilt[i])}")
             query_params.append(
                 f"powerInverter={int(self.config.pvforecast.planes_inverter_paco[i])}"
             )
             horizon_values = ",".join(
-                str(int(h)) for h in self.config.pvforecast.planes_userhorizon[i]
+                str(round(h)) for h in self.config.pvforecast.planes_userhorizon[i]
             )
             query_params.append(f"horizont={horizon_values}")
 
@@ -262,12 +289,12 @@ class PVForecastAkkudoktor(PVForecastProvider):
         Raises:
             ValueError: If the API response does not include expected `meta` data.
         """
-        response = requests.get(self._url())
+        response = requests.get(self._url(), timeout=10)
         response.raise_for_status()  # Raise an error for bad responses
         logger.debug(f"Response from {self._url()}: {response}")
         akkudoktor_data = self._validate_data(response.content)
         # We are working on fresh data (no cache), report update time
-        self.update_datetime = to_datetime(in_timezone=self.config.general.timezone)
+
         return akkudoktor_data
 
     def _update_data(self, force_update: Optional[bool] = False) -> None:
@@ -303,7 +330,8 @@ class PVForecastAkkudoktor(PVForecastProvider):
             logger.error(f"Akkudoktor schema change: {error_msg}")
             raise ValueError(error_msg)
 
-        assert self.start_datetime  # mypy fix
+        if not self.start_datetime:
+            raise ValueError(f"Start DateTime not set: {self.start_datetime}")
 
         # Iterate over forecast data points
         for forecast_values in zip(*akkudoktor_data.values):
@@ -390,28 +418,28 @@ if __name__ == "__main__":
             "planes": [
                 {
                     "peakpower": 5.0,
-                    "surface_azimuth": -10,
+                    "surface_azimuth": 170,
                     "surface_tilt": 7,
                     "userhorizon": [20, 27, 22, 20],
                     "inverter_paco": 10000,
                 },
                 {
                     "peakpower": 4.8,
-                    "surface_azimuth": -90,
+                    "surface_azimuth": 90,
                     "surface_tilt": 7,
                     "userhorizon": [30, 30, 30, 50],
                     "inverter_paco": 10000,
                 },
                 {
                     "peakpower": 1.4,
-                    "surface_azimuth": -40,
+                    "surface_azimuth": 140,
                     "surface_tilt": 60,
                     "userhorizon": [60, 30, 0, 30],
                     "inverter_paco": 2000,
                 },
                 {
                     "peakpower": 1.6,
-                    "surface_azimuth": 5,
+                    "surface_azimuth": 185,
                     "surface_tilt": 45,
                     "userhorizon": [45, 25, 30, 60],
                     "inverter_paco": 1400,

src/akkudoktoreos/prediction/pvforecastimport.py

@@ -9,15 +9,13 @@ format, enabling consistent access to forecasted and historical pvforecast attri
 from pathlib import Path
 from typing import Optional, Union
 
+from loguru import logger
 from pydantic import Field, field_validator
 
 from akkudoktoreos.config.configabc import SettingsBaseModel
-from akkudoktoreos.core.logging import get_logger
 from akkudoktoreos.prediction.predictionabc import PredictionImportProvider
 from akkudoktoreos.prediction.pvforecastabc import PVForecastProvider
 
-logger = get_logger(__name__)
-
 
 class PVForecastImportCommonSettings(SettingsBaseModel):
     """Common settings for pvforecast data import from file or JSON string."""
@@ -63,6 +61,9 @@ class PVForecastImport(PVForecastProvider, PredictionImportProvider):
         return "PVForecastImport"
 
     def _update_data(self, force_update: Optional[bool] = False) -> None:
+        if self.config.pvforecast.provider_settings is None:
+            logger.debug(f"{self.provider_id()} data update without provider settings.")
+            return
         if self.config.pvforecast.provider_settings.import_file_path is not None:
             self.import_from_file(
                 self.config.pvforecast.provider_settings.import_file_path,

src/akkudoktoreos/prediction/pvforecastvrm.py

@@ -0,0 +1,110 @@
+"""Retrieves pvforecast data from VRM API."""
+
+from typing import Any, Optional, Union
+
+import requests
+from loguru import logger
+from pendulum import DateTime
+from pydantic import Field, ValidationError
+
+from akkudoktoreos.config.configabc import SettingsBaseModel
+from akkudoktoreos.core.pydantic import PydanticBaseModel
+from akkudoktoreos.prediction.pvforecastabc import PVForecastProvider
+from akkudoktoreos.utils.datetimeutil import to_datetime
+
+
+class VrmForecastRecords(PydanticBaseModel):
+    vrm_consumption_fc: list[tuple[int, float]]
+    solar_yield_forecast: list[tuple[int, float]]
+
+
+class VrmForecastResponse(PydanticBaseModel):
+    success: bool
+    records: VrmForecastRecords
+    totals: dict
+
+
+class PVforecastVrmCommonSettings(SettingsBaseModel):
+    """Common settings for VRM API."""
+
+    pvforecast_vrm_token: str = Field(
+        default="your-token", description="Token for Connecting VRM API", examples=["your-token"]
+    )
+    pvforecast_vrm_idsite: int = Field(
+        default=12345, description="VRM-Installation-ID", examples=[12345]
+    )
+
+
+class PVForecastVrm(PVForecastProvider):
+    """Fetch and process PV forecast data from VRM API."""
+
+    @classmethod
+    def provider_id(cls) -> str:
+        """Return the unique identifier for the PV-Forecast-Provider."""
+        return "PVForecastVrm"
+
+    @classmethod
+    def _validate_data(cls, json_str: Union[bytes, Any]) -> VrmForecastResponse:
+        """Validate the VRM forecast response data against the expected schema."""
+        try:
+            return VrmForecastResponse.model_validate_json(json_str)
+        except ValidationError as e:
+            error_msg = "\n".join(
+                f"Field: {' -> '.join(str(x) for x in err['loc'])}\n"
+                f"Error: {err['msg']}\nType: {err['type']}"
+                for err in e.errors()
+            )
+            logger.error(f"VRM-API schema change:\n{error_msg}")
+            raise ValueError(error_msg)
+
+    def _request_forecast(self, start_ts: int, end_ts: int) -> VrmForecastResponse:
+        """Fetch forecast data from Victron VRM API."""
+        source = "https://vrmapi.victronenergy.com/v2/installations"
+        id_site = self.config.pvforecast.provider_settings.pvforecast_vrm_idsite
+        api_token = self.config.pvforecast.provider_settings.pvforecast_vrm_token
+        headers = {"X-Authorization": f"Token {api_token}", "Content-Type": "application/json"}
+        url = f"{source}/{id_site}/stats?type=forecast&start={start_ts}&end={end_ts}&interval=hours"
+        logger.debug(f"Requesting VRM forecast: {url}")
+
+        try:
+            response = requests.get(url, headers=headers, timeout=30)
+            response.raise_for_status()
+        except requests.RequestException as e:
+            logger.error(f"Failed to fetch pvforecast: {e}")
+            raise RuntimeError("Failed to fetch pvforecast from VRM API") from e
+
+        self.update_datetime = to_datetime(in_timezone=self.config.general.timezone)
+        return self._validate_data(response.content)
+
+    def _ts_to_datetime(self, timestamp: int) -> DateTime:
+        """Convert UNIX ms timestamp to timezone-aware datetime."""
+        return to_datetime(timestamp / 1000, in_timezone=self.config.general.timezone)
+
+    def _update_data(self, force_update: Optional[bool] = False) -> None:
+        """Update forecast data in the PVForecastDataRecord format."""
+        start_date = self.start_datetime.start_of("day")
+        end_date = self.start_datetime.add(hours=self.config.prediction.hours)
+        start_ts = int(start_date.timestamp())
+        end_ts = int(end_date.timestamp())
+
+        logger.info(f"Updating PV forecast from VRM: {start_date} to {end_date}")
+        vrm_forecast_data = self._request_forecast(start_ts, end_ts)
+
+        pv_forecast = []
+        for timestamp, value in vrm_forecast_data.records.solar_yield_forecast:
+            date = self._ts_to_datetime(timestamp)
+            dc_power = round(value, 2)
+            ac_power = round(dc_power * 0.96, 2)
+            self.update_value(
+                date, {"pvforecast_dc_power": dc_power, "pvforecast_ac_power": ac_power}
+            )
+            pv_forecast.append((date, dc_power))
+
+        logger.debug(f"Updated pvforecast_dc_power with {len(pv_forecast)} entries.")
+        self.update_datetime = to_datetime(in_timezone=self.config.general.timezone)
+
+
+# Example usage
+if __name__ == "__main__":
+    pv = PVForecastVrm()
+    pv._update_data()

src/akkudoktoreos/prediction/weather.py

@@ -2,11 +2,22 @@
 
 from typing import Optional
 
-from pydantic import Field
+from pydantic import Field, field_validator
 
 from akkudoktoreos.config.configabc import SettingsBaseModel
+from akkudoktoreos.prediction.prediction import get_prediction
+from akkudoktoreos.prediction.weatherabc import WeatherProvider
 from akkudoktoreos.prediction.weatherimport import WeatherImportCommonSettings
 
+prediction_eos = get_prediction()
+
+# Valid weather providers
+weather_providers = [
+    provider.provider_id()
+    for provider in prediction_eos.providers
+    if isinstance(provider, WeatherProvider)
+]
+
 
 class WeatherCommonSettings(SettingsBaseModel):
     """Weather Forecast Configuration."""
@@ -20,3 +31,13 @@ class WeatherCommonSettings(SettingsBaseModel):
     provider_settings: Optional[WeatherImportCommonSettings] = Field(
         default=None, description="Provider settings", examples=[None]
     )
+
+    # Validators
+    @field_validator("provider", mode="after")
+    @classmethod
+    def validate_provider(cls, value: Optional[str]) -> Optional[str]:
+        if value is None or value in weather_providers:
+            return value
+        raise ValueError(
+            f"Provider '{value}' is not a valid weather provider: {weather_providers}."
+        )

src/akkudoktoreos/prediction/weatherabc.py

@@ -14,11 +14,8 @@ import pandas as pd
 import pvlib
 from pydantic import Field
 
-from akkudoktoreos.core.logging import get_logger
 from akkudoktoreos.prediction.predictionabc import PredictionProvider, PredictionRecord
 
-logger = get_logger(__name__)
-
 
 class WeatherDataRecord(PredictionRecord):
     """Represents a weather data record containing various weather attributes at a specific datetime.

src/akkudoktoreos/prediction/weatherbrightsky.py

@@ -7,23 +7,21 @@ format, enabling consistent access to forecasted and historical weather attribut
 """
 
 import json
-from typing import Dict, List, Optional, Tuple
+from typing import Dict, List, Optional, Tuple, Union
 
+import numpy as np
 import pandas as pd
 import pvlib
 import requests
+from loguru import logger
 
-from akkudoktoreos.core.logging import get_logger
+from akkudoktoreos.core.cache import cache_in_file
 from akkudoktoreos.prediction.weatherabc import WeatherDataRecord, WeatherProvider
-from akkudoktoreos.utils.cacheutil import cache_in_file
+from akkudoktoreos.utils.datetimeutil import to_datetime, to_duration
-from akkudoktoreos.utils.datetimeutil import to_datetime
 
-logger = get_logger(__name__)
+WheaterDataBrightSkyMapping: List[Tuple[str, Optional[str], Optional[Union[str, float]]]] = [
-
-
-WheaterDataBrightSkyMapping: List[Tuple[str, Optional[str], Optional[float]]] = [
     # brightsky_key, description, corr_factor
-    ("timestamp", "DateTime", None),
+    ("timestamp", "DateTime", "to datetime in timezone"),
     ("precipitation", "Precipitation Amount (mm)", 1),
     ("pressure_msl", "Pressure (mb)", 1),
     ("sunshine", None, None),
@@ -96,10 +94,11 @@ class WeatherBrightSky(WeatherProvider):
             ValueError: If the API response does not include expected `weather` data.
         """
         source = "https://api.brightsky.dev"
-        date = to_datetime(self.start_datetime, as_string="YYYY-MM-DD")
+        date = to_datetime(self.start_datetime, as_string=True)
-        last_date = to_datetime(self.end_datetime, as_string="YYYY-MM-DD")
+        last_date = to_datetime(self.end_datetime, as_string=True)
         response = requests.get(
-            f"{source}/weather?lat={self.config.general.latitude}&lon={self.config.general.longitude}&date={date}&last_date={last_date}&tz={self.config.general.timezone}"
+            f"{source}/weather?lat={self.config.general.latitude}&lon={self.config.general.longitude}&date={date}&last_date={last_date}&tz={self.config.general.timezone}",
+            timeout=10,
         )
         response.raise_for_status()  # Raise an error for bad responses
         logger.debug(f"Response from {source}: {response}")
@@ -133,7 +132,8 @@ class WeatherBrightSky(WeatherProvider):
             error_msg = f"No WeatherDataRecord key for '{description}'"
             logger.error(error_msg)
             raise ValueError(error_msg)
-        return self.key_to_series(key)
+        series = self.key_to_series(key)
+        return series
 
     def _description_from_series(self, description: str, data: pd.Series) -> None:
         """Update a weather data with a pandas Series based on its description.
@@ -170,7 +170,7 @@ class WeatherBrightSky(WeatherProvider):
         brightsky_data = self._request_forecast(force_update=force_update)  # type: ignore
 
         # Get key mapping from description
-        brightsky_key_mapping: Dict[str, Tuple[Optional[str], Optional[float]]] = {}
+        brightsky_key_mapping: Dict[str, Tuple[Optional[str], Optional[Union[str, float]]]] = {}
         for brightsky_key, description, corr_factor in WheaterDataBrightSkyMapping:
             if description is None:
                 brightsky_key_mapping[brightsky_key] = (None, None)
@@ -192,6 +192,9 @@ class WeatherBrightSky(WeatherProvider):
                 value = brightsky_record[brightsky_key]
                 corr_factor = item[1]
                 if value and corr_factor:
+                    if corr_factor == "to datetime in timezone":
+                        value = to_datetime(value, in_timezone=self.config.general.timezone)
+                    else:
                         value = value * corr_factor
                 setattr(weather_record, key, value)
             self.insert_by_datetime(weather_record)
@@ -216,14 +219,40 @@ class WeatherBrightSky(WeatherProvider):
         self._description_from_series(description, dhi)
 
         # Add Preciptable Water (PWAT) with a PVLib method.
-        description = "Temperature (°C)"
+        key = WeatherDataRecord.key_from_description("Temperature (°C)")
-        temperature = self._description_to_series(description)
+        assert key  # noqa: S101
-
+        temperature = self.key_to_array(
-        description = "Relative Humidity (%)"
+            key=key,
-        humidity = self._description_to_series(description)
+            start_datetime=self.start_datetime,
-
+            end_datetime=self.end_datetime,
+            interval=to_duration("1 hour"),
+        )
+        if any(x is None or isinstance(x, float) and np.isnan(x) for x in temperature):
+            # We can not calculate PWAT
+            debug_msg = f"Innvalid temperature '{temperature}'"
+            logger.debug(debug_msg)
+            return
+        key = WeatherDataRecord.key_from_description("Relative Humidity (%)")
+        assert key  # noqa: S101
+        humidity = self.key_to_array(
+            key=key,
+            start_datetime=self.start_datetime,
+            end_datetime=self.end_datetime,
+            interval=to_duration("1 hour"),
+        )
+        if any(x is None or isinstance(x, float) and np.isnan(x) for x in humidity):
+            # We can not calculate PWAT
+            debug_msg = f"Innvalid humidity '{humidity}'"
+            logger.debug(debug_msg)
+            return
+        data = pvlib.atmosphere.gueymard94_pw(temperature, humidity)
         pwat = pd.Series(
-            data=pvlib.atmosphere.gueymard94_pw(temperature, humidity), index=temperature.index
+            data=data,
+            index=pd.DatetimeIndex(
+                pd.date_range(
+                    start=self.start_datetime, end=self.end_datetime, freq="1h", inclusive="left"
+                )
+            ),
         )
         description = "Preciptable Water (cm)"
         self._description_from_series(description, pwat)

src/akkudoktoreos/prediction/weatherclearoutside.py

@@ -18,15 +18,12 @@ from typing import Dict, List, Optional, Tuple
 import pandas as pd
 import requests
 from bs4 import BeautifulSoup
+from loguru import logger
 
-from akkudoktoreos.core.logging import get_logger
+from akkudoktoreos.core.cache import cache_in_file
 from akkudoktoreos.prediction.weatherabc import WeatherDataRecord, WeatherProvider
-from akkudoktoreos.utils.cacheutil import cache_in_file
 from akkudoktoreos.utils.datetimeutil import to_datetime, to_duration, to_timezone
 
-logger = get_logger(__name__)
-
-
 WheaterDataClearOutsideMapping: List[Tuple[str, Optional[str], Optional[float]]] = [
     # clearoutside_key, description, corr_factor
     ("DateTime", "DateTime", None),
@@ -88,12 +85,12 @@ class WeatherClearOutside(WeatherProvider):
         """Requests weather forecast from ClearOutside.
 
         Returns:
-            response: Weather forecast request reponse from ClearOutside.
+            response: Weather forecast request response from ClearOutside.
         """
         source = "https://clearoutside.com/forecast"
         latitude = round(self.config.general.latitude, 2)
         longitude = round(self.config.general.longitude, 2)
-        response = requests.get(f"{source}/{latitude}/{longitude}?desktop=true")
+        response = requests.get(f"{source}/{latitude}/{longitude}?desktop=true", timeout=10)
         response.raise_for_status()  # Raise an error for bad responses
         logger.debug(f"Response from {source}: {response}")
         # We are working on fresh data (no cache), report update time

src/akkudoktoreos/prediction/weatherimport.py

@@ -9,15 +9,13 @@ format, enabling consistent access to forecasted and historical weather attribut
 from pathlib import Path
 from typing import Optional, Union
 
+from loguru import logger
 from pydantic import Field, field_validator
 
 from akkudoktoreos.config.configabc import SettingsBaseModel
-from akkudoktoreos.core.logging import get_logger
 from akkudoktoreos.prediction.predictionabc import PredictionImportProvider
 from akkudoktoreos.prediction.weatherabc import WeatherProvider
 
-logger = get_logger(__name__)
-
 
 class WeatherImportCommonSettings(SettingsBaseModel):
     """Common settings for weather data import from file or JSON string."""
@@ -63,6 +61,9 @@ class WeatherImport(WeatherProvider, PredictionImportProvider):
         return "WeatherImport"
 
     def _update_data(self, force_update: Optional[bool] = False) -> None:
+        if self.config.weather.provider_settings is None:
+            logger.debug(f"{self.provider_id()} data update without provider settings.")
+            return
         if self.config.weather.provider_settings.import_file_path:
             self.import_from_file(
                 self.config.weather.provider_settings.import_file_path, key_prefix="weather"

src/akkudoktoreos/server/dash/admin.py

@@ -0,0 +1,297 @@
+"""Admin UI components for EOS Dashboard.
+
+This module provides functions to generate administrative UI components
+for the EOS dashboard.
+"""
+
+import json
+from pathlib import Path
+from typing import Any, Optional, Union
+
+import requests
+from fasthtml.common import Select
+from loguru import logger
+from monsterui.foundations import stringify
+from monsterui.franken import (  # Select, TODO: Select from FrankenUI does not work - using Select from FastHTML instead
+    H3,
+    Button,
+    ButtonT,
+    Card,
+    Details,
+    Div,
+    DivHStacked,
+    DividerLine,
+    Grid,
+    Input,
+    Options,
+    P,
+    Summary,
+    UkIcon,
+)
+from platformdirs import user_config_dir
+
+from akkudoktoreos.server.dash.components import Error, Success
+from akkudoktoreos.server.dash.configuration import get_nested_value
+from akkudoktoreos.utils.datetimeutil import to_datetime
+
+# Directory to export files to, or to import files from
+export_import_directory = Path(user_config_dir("net.akkudoktor.eosdash", "akkudoktor"))
+
+
+def AdminButton(*c: Any, cls: Optional[Union[str, tuple]] = None, **kwargs: Any) -> Button:
+    """Creates a styled button for administrative actions.
+
+    Args:
+        *c (Any): Positional arguments representing the button's content.
+        cls (Optional[Union[str, tuple]]): Additional CSS classes for styling. Defaults to None.
+        **kwargs (Any): Additional keyword arguments passed to the `Button`.
+
+    Returns:
+        Button: A styled `Button` component for admin actions.
+    """
+    new_cls = f"{ButtonT.primary}"
+    if cls:
+        new_cls += f" {stringify(cls)}"
+    kwargs["cls"] = new_cls
+    return Button(*c, submit=False, **kwargs)
+
+
+def AdminConfig(
+    eos_host: str, eos_port: Union[str, int], data: Optional[dict], config: Optional[dict[str, Any]]
+) -> tuple[str, Union[Card, list[Card]]]:
+    """Creates a configuration management card with save-to-file functionality.
+
+    Args:
+        eos_host (str): The hostname of the EOS server.
+        eos_port (Union[str, int]): The port of the EOS server.
+        data (Optional[dict]): Incoming data containing action and category for processing.
+
+    Returns:
+        tuple[str, Union[Card, list[Card]]]: A tuple containing the configuration category label and the `Card` UI component.
+    """
+    server = f"http://{eos_host}:{eos_port}"
+    eos_hostname = "EOS server"
+    eosdash_hostname = "EOSdash server"
+
+    category = "configuration"
+    # save config file
+    status = (None,)
+    config_file_path = "<unknown>"
+    try:
+        if config:
+            config_file_path = get_nested_value(config, ["general", "config_file_path"])
+    except Exception as e:
+        logger.debug(f"general.config_file_path: {e}")
+    # export config file
+    export_to_file_next_tag = to_datetime(as_string="YYYYMMDDHHmmss")
+    export_to_file_status = (None,)
+    # import config file
+    import_from_file_status = (None,)
+
+    if data and data.get("category", None) == category:
+        # This data is for us
+        if data["action"] == "save_to_file":
+            # Safe current configuration to file
+            try:
+                result = requests.put(f"{server}/v1/config/file", timeout=10)
+                result.raise_for_status()
+                config_file_path = result.json()["general"]["config_file_path"]
+                status = Success(f"Saved to '{config_file_path}' on '{eos_hostname}'")
+            except requests.exceptions.HTTPError as e:
+                detail = result.json()["detail"]
+                status = Error(
+                    f"Can not save actual config to file on '{eos_hostname}': {e}, {detail}"
+                )
+            except Exception as e:
+                status = Error(f"Can not save actual config to file on '{eos_hostname}': {e}")
+        elif data["action"] == "export_to_file":
+            # Export current configuration to file
+            export_to_file_tag = data.get("export_to_file_tag", export_to_file_next_tag)
+            export_to_file_path = export_import_directory.joinpath(
+                f"eos_config_{export_to_file_tag}.json"
+            )
+            try:
+                if not config:
+                    raise ValueError(f"No config from '{eos_hostname}'")
+                export_to_file_path.parent.mkdir(parents=True, exist_ok=True)
+                with export_to_file_path.open("w", encoding="utf-8", newline="\n") as fd:
+                    json.dump(config, fd, indent=4, sort_keys=True)
+                export_to_file_status = Success(
+                    f"Exported to '{export_to_file_path}' on '{eosdash_hostname}'"
+                )
+            except requests.exceptions.HTTPError as e:
+                detail = result.json()["detail"]
+                export_to_file_status = Error(
+                    f"Can not export actual config to '{export_to_file_path}' on '{eosdash_hostname}': {e}, {detail}"
+                )
+            except Exception as e:
+                export_to_file_status = Error(
+                    f"Can not export actual config to '{export_to_file_path}' on '{eosdash_hostname}': {e}"
+                )
+        elif data["action"] == "import_from_file":
+            import_file_name = data.get("import_file_name", None)
+            import_from_file_pathes = list(
+                export_import_directory.glob("*.json")
+            )  # expand generator object
+            import_file_path = None
+            for f in import_from_file_pathes:
+                if f.name == import_file_name:
+                    import_file_path = f
+            if import_file_path:
+                try:
+                    with import_file_path.open("r", encoding="utf-8", newline=None) as fd:
+                        import_config = json.load(fd)
+                    result = requests.put(f"{server}/v1/config", json=import_config, timeout=10)
+                    result.raise_for_status()
+                    import_from_file_status = Success(
+                        f"Config imported from '{import_file_path}' on '{eosdash_hostname}'"
+                    )
+                except requests.exceptions.HTTPError as e:
+                    detail = result.json()["detail"]
+                    import_from_file_status = Error(
+                        f"Can not import config from '{import_file_name}' on '{eosdash_hostname}' {e}, {detail}"
+                    )
+                except Exception as e:
+                    import_from_file_status = Error(
+                        f"Can not import config from '{import_file_name}' on '{eosdash_hostname}' {e}"
+                    )
+            else:
+                import_from_file_status = Error(
+                    f"Can not import config from '{import_file_name}', not found in '{export_import_directory}' on '{eosdash_hostname}'"
+                )
+
+    # Update for display, in case we added a new file before
+    import_from_file_names = [f.name for f in list(export_import_directory.glob("*.json"))]
+
+    return (
+        category,
+        [
+            Card(
+                Details(
+                    Summary(
+                        Grid(
+                            DivHStacked(
+                                UkIcon(icon="play"),
+                                AdminButton(
+                                    "Save to file",
+                                    hx_post="/eosdash/admin",
+                                    hx_target="#page-content",
+                                    hx_swap="innerHTML",
+                                    hx_vals='{"category": "configuration", "action": "save_to_file"}',
+                                ),
+                                P(f"'{config_file_path}' on '{eos_hostname}'"),
+                            ),
+                            status,
+                        ),
+                        cls="list-none",
+                    ),
+                    P(f"Safe actual configuration to '{config_file_path}' on '{eos_hostname}'."),
+                ),
+            ),
+            Card(
+                Details(
+                    Summary(
+                        Grid(
+                            DivHStacked(
+                                UkIcon(icon="play"),
+                                AdminButton(
+                                    "Export to file",
+                                    hx_post="/eosdash/admin",
+                                    hx_target="#page-content",
+                                    hx_swap="innerHTML",
+                                    hx_vals='js:{"category": "configuration", "action": "export_to_file", "export_to_file_tag": document.querySelector("[name=\'chosen_export_file_tag\']").value }',
+                                ),
+                                P("'eos_config_"),
+                                Input(
+                                    id="export_file_tag",
+                                    name="chosen_export_file_tag",
+                                    value=export_to_file_next_tag,
+                                ),
+                                P(".json'"),
+                            ),
+                            export_to_file_status,
+                        ),
+                        cls="list-none",
+                    ),
+                    P(
+                        f"Export actual configuration to 'eos_config_{export_to_file_next_tag}.json' on '{eosdash_hostname}'."
+                    ),
+                ),
+            ),
+            Card(
+                Details(
+                    Summary(
+                        Grid(
+                            DivHStacked(
+                                UkIcon(icon="play"),
+                                AdminButton(
+                                    "Import from file",
+                                    hx_post="/eosdash/admin",
+                                    hx_target="#page-content",
+                                    hx_swap="innerHTML",
+                                    hx_vals='js:{ "category": "configuration", "action": "import_from_file", "import_file_name": document.querySelector("[name=\'selected_import_file_name\']").value }',
+                                ),
+                                Select(
+                                    *Options(*import_from_file_names),
+                                    id="import_file_name",
+                                    name="selected_import_file_name",  # Name of hidden input field with selected value
+                                    placeholder="Select file",
+                                ),
+                            ),
+                            import_from_file_status,
+                        ),
+                        cls="list-none",
+                    ),
+                    P(f"Import configuration from config file on '{eosdash_hostname}'."),
+                ),
+            ),
+        ],
+    )
+
+
+def Admin(eos_host: str, eos_port: Union[str, int], data: Optional[dict] = None) -> Div:
+    """Generates the administrative dashboard layout.
+
+    This includes configuration management and other administrative tools.
+
+    Args:
+        eos_host (str): The hostname of the EOS server.
+        eos_port (Union[str, int]): The port of the EOS server.
+        data (Optional[dict], optional): Incoming data to trigger admin actions. Defaults to None.
+
+    Returns:
+        Div: A `Div` component containing the assembled admin interface.
+    """
+    # Get current configuration from server
+    server = f"http://{eos_host}:{eos_port}"
+    try:
+        result = requests.get(f"{server}/v1/config", timeout=10)
+        result.raise_for_status()
+        config = result.json()
+    except requests.exceptions.HTTPError as e:
+        config = {}
+        detail = result.json()["detail"]
+        warning_msg = f"Can not retrieve configuration from {server}: {e}, {detail}"
+        logger.warning(warning_msg)
+        return Error(warning_msg)
+    except Exception as e:
+        warning_msg = f"Can not retrieve configuration from {server}: {e}"
+        logger.warning(warning_msg)
+        return Error(warning_msg)
+
+    rows = []
+    last_category = ""
+    for category, admin in [
+        AdminConfig(eos_host, eos_port, data, config),
+    ]:
+        if category != last_category:
+            rows.append(H3(category))
+            rows.append(DividerLine())
+            last_category = category
+        if isinstance(admin, list):
+            for card in admin:
+                rows.append(card)
+        else:
+            rows.append(admin)
+
+    return Div(*rows, cls="space-y-4")

src/akkudoktoreos/server/dash/assets/favicon/site.webmanifest

@@ -0,0 +1 @@
+{"name":"","short_name":"","icons":[{"src":"/android-chrome-192x192.png","sizes":"192x192","type":"image/png"},{"src":"/android-chrome-512x512.png","sizes":"512x512","type":"image/png"}],"theme_color":"#ffffff","background_color":"#ffffff","display":"standalone"}

src/akkudoktoreos/server/dash/bokeh.py

@@ -0,0 +1,38 @@
+# Module taken from https://github.com/koaning/fh-altair
+# MIT license
+
+from typing import Optional
+
+from bokeh.embed import components
+from bokeh.models import Plot
+from monsterui.franken import H4, Card, NotStr, Script
+
+BokehJS = [
+    Script(src="https://cdn.bokeh.org/bokeh/release/bokeh-3.7.0.min.js", crossorigin="anonymous"),
+    Script(
+        src="https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.7.0.min.js",
+        crossorigin="anonymous",
+    ),
+    Script(
+        src="https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.7.0.min.js", crossorigin="anonymous"
+    ),
+    Script(
+        src="https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.7.0.min.js", crossorigin="anonymous"
+    ),
+    Script(
+        src="https://cdn.bokeh.org/bokeh/release/bokeh-mathjax-3.7.0.min.js",
+        crossorigin="anonymous",
+    ),
+]
+
+
+def Bokeh(plot: Plot, header: Optional[str] = None) -> Card:
+    """Converts an Bokeh plot to a FastHTML FT component."""
+    script, div = components(plot)
+    if header:
+        header = H4(header, cls="mt-2")
+    return Card(
+        NotStr(div),
+        NotStr(script),
+        header=header,
+    )