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Add database support for measurements and historic prediction data. (#848)
The database supports backend selection, compression, incremental data load, automatic data saving to storage, automatic vaccum and compaction. Make SQLite3 and LMDB database backends available. Update tests for new interface conventions regarding data sequences, data containers, data providers. This includes the measurements provider and the prediction providers. Add database documentation. The fix includes several bug fixes that are not directly related to the database implementation but are necessary to keep EOS running properly and to test and document the changes. * fix: config eos test setup Make the config_eos fixture generate a new instance of the config_eos singleton. Use correct env names to setup data folder path. * fix: startup with no config Make cache and measurements complain about missing data path configuration but do not bail out. * fix: soc data preparation and usage for genetic optimization. Search for soc measurments 48 hours around the optimization start time. Only clamp soc to maximum in battery device simulation. * fix: dashboard bailout on zero value solution display Do not use zero values to calculate the chart values adjustment for display. * fix: openapi generation script Make the script also replace data_folder_path and data_output_path to hide real (test) environment pathes. * feat: add make repeated task function make_repeated_task allows to wrap a function to be repeated cyclically. * chore: removed index based data sequence access Index based data sequence access does not make sense as the sequence can be backed by the database. The sequence is now purely time series data. * chore: refactor eos startup to avoid module import startup Avoid module import initialisation expecially of the EOS configuration. Config mutation, singleton initialization, logging setup, argparse parsing, background task definitions depending on config and environment-dependent behavior is now done at function startup. * chore: introduce retention manager A single long-running background task that owns the scheduling of all periodic server-maintenance jobs (cache cleanup, DB autosave, …) * chore: canonicalize timezone name for UTC Timezone names that are semantically identical to UTC are canonicalized to UTC. * chore: extend config file migration for default value handling Extend the config file migration handling values None or nonexisting values that will invoke a default value generation in the new config file. Also adapt test to handle this situation. * chore: extend datetime util test cases * chore: make version test check for untracked files Check for files that are not tracked by git. Version calculation will be wrong if these files will not be commited. * chore: bump pandas to 3.0.0 Pandas 3.0 now performs inference on the appropriate resolution (a.k.a. unit) for the output dtype which may become datetime64[us] (before it was ns). Also numeric dtype detection is now more strict which needs a different detection for numerics. * chore: bump pydantic-settings to 2.12.0 pydantic-settings 2.12.0 under pytest creates a different behaviour. The tests were adapted and a workaround was introduced. Also ConfigEOS was adapted to allow for fine grain initialization control to be able to switch off certain settings such as file settings during test. * chore: remove sci learn kit from dependencies The sci learn kit is not strictly necessary as long as we have scipy. * chore: add documentation mode guarding for sphinx autosummary Sphinx autosummary excecutes functions. Prevent exceptions in case of pure doc mode. * chore: adapt docker-build CI workflow to stricter GitHub handling Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
This commit is contained in:
Bobby Noelte
GitHub
@@ -24,7 +24,7 @@ from akkudoktoreos.optimization.genetic.geneticparams import (
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)
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from akkudoktoreos.optimization.genetic.geneticsolution import GeneticSolution
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from akkudoktoreos.optimization.optimization import OptimizationSolution
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from akkudoktoreos.utils.datetimeutil import DateTime, compare_datetimes, to_datetime
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from akkudoktoreos.utils.datetimeutil import DateTime, to_datetime
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# The executor to execute the CPU heavy energy management run
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executor = ThreadPoolExecutor(max_workers=1)
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@@ -44,6 +44,15 @@ class EnergyManagementStage(Enum):
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return self.value
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async def ems_manage_energy() -> None:
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"""Repeating task for managing energy.
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This task should be executed by the server regularly
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to ensure proper energy management.
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"""
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await EnergyManagement().run()
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class EnergyManagement(
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SingletonMixin, ConfigMixin, PredictionMixin, AdapterMixin, PydanticBaseModel
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):
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@@ -286,6 +295,9 @@ class EnergyManagement(
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error_msg = f"Adapter update failed - phase {cls._stage}: {e}\n{trace}"
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logger.error(error_msg)
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# Remember energy run datetime.
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EnergyManagement._last_run_datetime = to_datetime()
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# energy management run finished
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cls._stage = EnergyManagementStage.IDLE
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@@ -346,73 +358,3 @@ class EnergyManagement(
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)
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# Run optimization in background thread to avoid blocking event loop
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await loop.run_in_executor(executor, func)
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async def manage_energy(self) -> None:
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"""Repeating task for managing energy.
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This task should be executed by the server regularly (e.g., every 10 seconds)
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to ensure proper energy management. Configuration changes to the energy management interval
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will only take effect if this task is executed.
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- Initializes and runs the energy management for the first time if it has never been run
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before.
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- If the energy management interval is not configured or invalid (NaN), the task will not
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trigger any repeated energy management runs.
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- Compares the current time with the last run time and runs the energy management if the
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interval has elapsed.
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- Logs any exceptions that occur during the initialization or execution of the energy
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management.
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Note: The task maintains the interval even if some intervals are missed.
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"""
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current_datetime = to_datetime()
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interval = self.config.ems.interval # interval maybe changed in between
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if EnergyManagement._last_run_datetime is None:
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# Never run before
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try:
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# Remember energy run datetime.
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EnergyManagement._last_run_datetime = current_datetime
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# Try to run a first energy management. May fail due to config incomplete.
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await self.run()
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except Exception as e:
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trace = "".join(traceback.TracebackException.from_exception(e).format())
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message = f"EOS init: {e}\n{trace}"
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logger.error(message)
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return
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if interval is None or interval == float("nan"):
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# No Repetition
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return
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if (
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compare_datetimes(current_datetime, EnergyManagement._last_run_datetime).time_diff
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< interval
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):
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# Wait for next run
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return
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try:
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await self.run()
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except Exception as e:
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trace = "".join(traceback.TracebackException.from_exception(e).format())
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message = f"EOS run: {e}\n{trace}"
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logger.error(message)
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# Remember the energy management run - keep on interval even if we missed some intervals
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while (
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compare_datetimes(current_datetime, EnergyManagement._last_run_datetime).time_diff
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>= interval
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):
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EnergyManagement._last_run_datetime = EnergyManagement._last_run_datetime.add(
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seconds=interval
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)
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# Initialize the Energy Management System, it is a singleton.
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ems = EnergyManagement()
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def get_ems() -> EnergyManagement:
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"""Gets the EOS Energy Management System."""
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return ems
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