* fix(genetic): keep fitness-cache memory in pymalloc and release arena after each run
At fine time resolution (interval_sec=900, ~192 control slots over a multi-day
horizon) the fitness-cache keys are ~1.6 KB int tuples, above CPython's 512-byte
pymalloc threshold, so they are served by glibc malloc in the optimization worker
thread's arena and are not returned to the OS on `self._fitness_cache.clear()`.
With re-optimization every 15 min, RSS stair-steps up to the memory limit within
about a day (OOM / forced restart). At hourly resolution the tuples stay < 512 B,
so pymalloc reclaims them and the effect is negligible. See #1352.
- Store the cache key/genome compactly as bytes (1 byte per gene, 8-byte fallback
for larger state spaces) so entries stay within pymalloc regardless of resolution.
- After each optimization run, gc.collect() + malloc_trim(0) (guarded, glibc-only)
to return freed arena pages to the OS.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* fix(genetic): pack fitness-cache genome as bounded chunks
Storing the genome as a single bytes object still exceeds pymalloc's
512-byte threshold once the genome grows: at 15-min resolution over a
60 h horizon with EV genes the key is ~480 genes, so even the one-byte
encoding is 481 bytes (514 with the object header) and any value >255
switches the whole genome to 8 bytes per gene. Such keys land in glibc
malloc, which does not reliably return the pages (malloc_trim is
glibc-only, absent on musl) — the platform-independent guarantee did
not actually hold for supported settings.
Encode the genome (key and FitnessCacheEntry.genome) as a tuple of
bounded byte chunks instead — 256 one-byte genes or 32 signed-64-bit
genes per chunk, 256 bytes each — built per chunk so the encoder never
materialises an oversized temporary. Every object then stays inside
pymalloc regardless of horizon, on every platform. malloc_trim after a
run is kept as a secondary release for the rest of the run's heap.
Tests: round-trips incl. 480-gene narrow/wide and negative genes, and
sys.getsizeof for the key AND every chunk at 480 genes in both
encodings.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>
* feat: adapt configuration for multi optimization algorithms
Decouple configuration from optimization algorithm parameters. Add to_[algorithm]_param() methods
to the configuration that derive optimization algorithm specific parameters from the configuration.
Add x-scope tags to the configuration options that describe for which specific algorithms the
configuration option is for.
The whole device settings are restructured. There are now general settings for the device classes
with the afore mentioned to_[algorithm]_param() methods. The general device settings got their own
directory `devices/settings`. By this the parameter class also does not have to be a pydantic model
which can be used for future optimization/ simulations speed up.
Also the parameter class for a device is now part of the device module. This better decouples and
also is the natural place for parameters of a device.
Besides this feature there are also fixes and improvements:
* feat: extend home appliance time window settings and simulation
Home appliance can now be configured for multiple runs with per-cycle allowed time windows. The
number of remaining cycles to plan is determined at runtime by reading the
``cycles_completed_measurement_key`` from the measurement store.
* feat: specialiced CycleTimeWindowSequence for time window sequences
Sequence of time windows associated to cycles.
This model specializes ``ValueTimeWindowSequence`` so that the ``value``
field of each ``ValueTimeWindow`` encodes the **cycle index** (0-based
integer) the window belongs to.
Typical use: an appliance that must run ``n`` times per day, each run
constrained to a distinct time window. Assign ``value=0`` to windows
for the first cycle, ``value=1`` for the second, and so on. Multiple
windows may share the same cycle index (their allowed regions are unioned).
Windows with ``value=None`` are silently ignored by all cycle-aware methods.
* fix: Make test_configmigrate also regard the _ANY_SENTENIEL in key values
* chore: Make devices configurations a map instead of a list
This makes config paths stable regardless of declaration order and lets each device settings
class build its own config path from ``self.device_id`` without needing an external index.
Tests are adapted likewise.
Devices configurations are automatically migrated from lists to maps.
* chore: rename levelized_cost_of_storage_kwh to levelized_cost_of_storage_amt kwh
This better fits in the naming scheme and also makes clear the costs are money.
Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
* fix: runtime config update ignored by config file
Runtime settings were handed back to pydantic-settings as init settings,
which rank below the config file and the environment. Any key already
present in EOS.config.json or in the environment silently discarded the
update, so a bulk PUT /v1/config returned 200 without applying anything,
while the granular PUT /v1/config/{path} endpoint kept working.
Add a dedicated runtime settings source ranked directly below the command
line arguments and record granular updates there as well, so both
endpoints share one store that survives re-evaluation of the settings
sources. Environment variables keep precedence over the config file for
all keys that were not set at runtime.
Also repairs revert_settings() and update(), which passed their data
through the same init settings.
Closes#1303
* fix: env vars ignored on first config build
ConfigEOS.__init__ passed self as first positional argument to _setup,
which forwards it to pydantic_settings.BaseSettings.__init__. Its first
positional parameter is _case_sensitive, so the environment source
matched the upper case variable names against the lower case field names
and returned nothing. Environment settings only took effect after the
next configuration setup.
* docs: changelog for config priority fixes
* fix(config): preserve device identities and storage costs during migration
* fix(measurement): restore JSON records into the existing singleton
* fix(devices): preserve charge-rate typing and public import compatibility
* feat(measurement): integrate typed energy quality and capacity APIs
Port the locally backed-up measurement extensions to main async storage and PR #1256 device maps. Preserve runtime capacity estimates across #1305 bulk updates. Confirm JSON singleton restore defect on unchanged main and add regression. No production configuration or measurements included.
Co-authored-by: Andreas <drbacke@gmx.de>
* docs(measurement): describe household settings and consolidate regression coverage
* docs(measurement): regenerate configuration and API contracts
* test(measurement): isolate capacity database state between tests
* ruff format fix
* fix(measurement): restore JSON records into the existing singleton
* test(measurement): assert restored timestamps before timezone conversion
* test(measurement): assert restored timestamps before timezone conversion
* fix: preserve imported feed-in revenue during parameter preparation
Cancel GENETIC preparation when imported revenue cannot be read or contains invalid values, preserving the chosen provider instead of replacing it with demo tariffs. Keep valid positive, zero and negative amount/Wh series unchanged.
Adapt the revenue-preservation regressions from PRs #1224 and #1304 to the async main API, including real timestamped imports and simulation repricing. The feature-only direct-marketing override remains outside this main fix.
Co-authored-by: Christin <info@bikinibottom.capital>
Co-authored-by: Normann <github@koldrack.com>
* feat(devices): port slot-aware battery export and direct-use physics
Port scoped device changes from d2e2d58237. Keep PR #1256 parameter conversion structure and separate GENETIC0 devices. Validate physical flows and reprice changed simulation results.
Co-authored-by: Andreas <drbacke@gmx.de>
Co-authored-by: Christin <info@bikinibottom.capital>
* docs(measurement): align API version with refreshed prerequisites
* fix: return only completed optimization results per run
* feat(pvforecast): add calibrated local Akkudoktor backend
Port local PV modeling and outage calibration from feature commits f976335, 6dc58c3 and faed0fd by Andreas. Keep PVForecastAkkudoktor identity and remote default, adapt to async storage, and migrate legacy provider settings.
* fix(cache): distinguish callables in the shared EMS cache
Include the function object in cache keys so methods of one interpolator cannot reuse a probability as a power value. Cover both call orders, keyword arguments, cache hits and separate closures with identical qualified names.
* fix(devices): constrain the physics port and validate export levels
Defer inactive EV deadline fields to the optimizer port, reject nonfinite export rates, and document the hourly Optimize boundary. Verify converter IDs, rates and LCOS, separate GENETIC0 interpolation, physical boundary flows and independent GENETIC repricing.
* docs(pvforecast): regenerate local backend configuration schema
* docs(devices): regenerate slot-physics configuration and OpenAPI schemas
* test: type dynamic Optimize regression arguments
* style: wrap imported tariff test parameter import
* style(pvforecast): apply CI import formatting
* docs(pvforecast): refresh API version after CI formatting
* fix(config): satisfy typed device conversion and migration contracts
* docs(config): refresh validated configuration prerequisite schemas
* fix(measurement): enforce typed capacity and sample validation
* test(devices): align physics regressions with strict type checking
* style(measurement): normalize imports for CI
* docs(measurement): refresh typed measurement API schemas
* docs(devices): refresh API version after prerequisite merge
* test: make optimization dispatch timezones explicit
* docs(interpolator): use portable reStructuredText markup
* docs(devices): refresh API version after docstring compatibility fix
* feat: complete configuration-driven GENETIC optimization and reports (#1329)
* feat(devices): port slot-aware battery export and direct-use physics
Port scoped device changes from d2e2d58237. Keep PR #1256 parameter conversion structure and separate GENETIC0 devices. Validate physical flows and reprice changed simulation results.
Co-authored-by: Andreas <drbacke@gmx.de>
Co-authored-by: Christin <info@bikinibottom.capital>
* feat(optimization): port tested terminal and tail value primitives
Source d2e2d58237. 22 primitive tests pass; integration with the optimizer, forecast horizon and API is still pending.
Co-authored-by: Andreas <drbacke@gmx.de>
Co-authored-by: Christin <info@bikinibottom.capital>
* fix(devices): preserve charge-rate typing and public import compatibility
* feat(measurement): integrate typed energy quality and capacity APIs
Port the locally backed-up measurement extensions to main async storage and PR #1256 device maps. Preserve runtime capacity estimates across #1305 bulk updates. Confirm JSON singleton restore defect on unchanged main and add regression. No production configuration or measurements included.
Co-authored-by: Andreas <drbacke@gmx.de>
* test(integration): validate optimizer economics and document measurement settings
* docs(integration): record tested checkpoint and remaining consolidation work
* docs(development): define isolated PR packages and remaining porting gates
* docs(integration): refresh API version after measurement reconciliation
* docs(integration): record PR readiness verification results
* docs(development): record publication and verification of PR 1322
* test(measurement): assert restored timestamps before timezone conversion
* docs(development): record corrected PR head and CI progress
* docs(integration): refresh API version after prerequisite alignment
* docs(integration): define parallel packages and Optimize compatibility gates
* fix: preserve imported feed-in revenue during parameter preparation
Cancel GENETIC preparation when imported revenue cannot be read or contains invalid values, preserving the chosen provider instead of replacing it with demo tariffs. Keep valid positive, zero and negative amount/Wh series unchanged.
Adapt the revenue-preservation regressions from PRs #1224 and #1304 to the async main API, including real timestamped imports and simulation repricing. The feature-only direct-marketing override remains outside this main fix.
Co-authored-by: Christin <info@bikinibottom.capital>
Co-authored-by: Normann <github@koldrack.com>
* test(integration): verify tariff protection with mapped device physics
* fix: return only completed optimization results per run
* test(integration): verify algorithm aliases and mapped-device contracts
* fix(cache): distinguish callables in the shared EMS cache
Include the function object in cache keys so methods of one interpolator cannot reuse a probability as a power value. Cover both call orders, keyword arguments, cache hits and separate closures with identical qualified names.
* fix(devices): constrain the physics port and validate export levels
Defer inactive EV deadline fields to the optimizer port, reject nonfinite export rates, and document the hourly Optimize boundary. Verify converter IDs, rates and LCOS, separate GENETIC0 interpolation, physical boundary flows and independent GENETIC repricing.
* feat(pvforecast): add calibrated local Akkudoktor backend
Port local PV modeling and outage calibration from feature commits f976335, 6dc58c3 and faed0fd by Andreas. Keep PVForecastAkkudoktor identity and remote default, adapt to async storage, and migrate legacy provider settings.
* docs(integration): record combined compatibility checks and green JSON PR CI
* test: type dynamic Optimize regression arguments
* docs(integration): record Optimize fix PR publication
* docs(integration): record imported tariff protection PR
* style(pvforecast): apply CI import formatting
* style(integration): align combined regression imports
* test: make optimization dispatch timezones explicit
* docs(interpolator): use portable reStructuredText markup
* chore: validate combined integration with locked mypy
* docs: hand off six validated pull requests for manual review
* feat: report genetic interval and terminal value diagnostics
* feat(devices): reconcile flexible profiles and EV deadlines with cycle scheduling
Adapt the flexible consumer primitives from d2e2d582 while retaining the keyed settings and per-cycle scheduling introduced by #1256. Preserve slot battery physics and GENETIC0 flat-load conversion. Cover energy conservation, deadlines, window intersections, DST, completed cycles and EV converters.
* test: satisfy typed genetic PDF chart contracts
* feat(optimization): resolve quarter-hour GENETIC requests from configuration
* test(genetic): verify real device scheduling, measurement and export contracts
Register appliance completed-cycle measurement keys so the real store accepts both default and custom counters. Exercise complete low-budget optimizer runs, persisted measurements, generic solution output and instructions, including zero-power phases, EV departure boundaries, per-cycle windows and LCOS.
* fix: bound genetic report forecasts to executable horizon
* feat: complete native genetic scheduling and retained result contracts
* fix: retain missing raw samples when dropna is disabled
* fix: align local optimization slots and measurement instants
* docs: explain complete genetic rollout and PR dependencies
* feat: expose retained GENETIC report through the versioned API
* docs: regenerate complete genetic configuration and API schema
* docs: format consolidation and review handoff markdown
* test: align isolated EMS fixture with native genetic run options
* test(genetic): clean up singleton measurements after device integration tests
* test: freeze the clock without replacing timestamp conversion
* fix: preserve explicit warmstart timezones in runtime requests
* test(genetic): validate device schedules in UTC and Berlin
Use explicit Berlin origins for Berlin wall-clock windows, compare absolute deadline instants correctly, and run all real device optimizer scenarios under both UTC and Europe/Berlin. Compare exported starts in the run timezone instead of assuming the output timezone matches the host.
* fix: start automatic genetic runs in the site timezone
* Preserve aware GENETIC snapshot times across host timezones
* docs: specify site clock and rehearsed merge resolutions
* test: isolate invalid measurement records and refresh API version
* fix: render single-slot genetic tail diagnostics
* docs: refresh schema version after report fix
* fix: preserve configuration-only Optimize API contract
* docs: refresh configuration request schema
---------
Co-authored-by: Christin <info@bikinibottom.capital>
Co-authored-by: Normann <github@koldrack.com>
---------
Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
Co-authored-by: Bobby Noelte <b0661n0e17e@gmail.com>
Co-authored-by: r0b2g1t <r0b2g1t@users.noreply.github.com>
Co-authored-by: Normann <github@koldrack.com>
Co-authored-by: Christin <info@bikinibottom.capital>
