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1abdd345c4
The isolated pre-commit mypy hook previously omitted runtime type information that make mypy used, hiding errors involving dependencies such as Pydantic and Pendulum. Makefile, pre-commit and CI now run the same full-project typing policy in the development environment defined by uv.lock. - Use uv run --locked --exact --extra dev and the same mypy arguments for Makefile and the local hook. Check all of src and tests, including on configuration-only changes. - Pin Python 3.13 for local development and the pre-commit CI job, and install the locked pre-commit version in CI. - Disable incremental analysis because existing Pendulum cache state changes mypy 2.3.1 diagnostics. Document the policy, the performance tradeoff and the existing typing debt. - Add a regression test that exercises Makefile, the hook and the CI command in a temporary project, accepting valid dependency types and detecting deliberate Pydantic/Pendulum assignment errors. Resolve the newly detected mypy diagnostics. - Enable the numpydantic and Pydantic mypy plugins, retaining strict Pydantic constructor typing with init_typed = true. Validate raw/coercible payloads through model_validate. - Propagate concrete record, provider and time-window types through generic collections, factories and lookup methods. Preserve runtime field inspection and generated time-window documentation. - Align Pendulum annotations with actual factory/arithmetic results while retaining Pydantic validation adapters at runtime. Correct optional values, array boundaries, REST handlers and plotting interfaces. - Add pinned scipy-stubs and types-psutil, update uv.lock, and supply the plugins' dependencies. - Add runtime regression coverage for validated path defaults, normalized time-series metadata, generic field inspection, invalid timestamps and unsupported provider imports. Runtime and compatibility details: - Validate path defaults as Path objects while retaining raw string defaults needed by migration serialization with exclude_defaults. - Normalize feed-in tariff lists and default charge rates to NumPy arrays; reject missing timestamps/uninitialized values explicitly. Importing into a provider without import support returns HTTP 400. - Public JSON schemas and OpenAPI structure match main (excluding the generated version). Signed-off-by: dr-dimitry Signed-off-by: dr-dimitry Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> Co-authored-by: dr-dimitri <87113560+dr-dimitri@users.noreply.github.com> Co-authored-by: Normann <github@koldrack.com>
71 lines
2.1 KiB
Python
71 lines
2.1 KiB
Python
"""Settings for logging.
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Kept in an extra module to avoid cyclic dependencies on package import.
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"""
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from pathlib import Path
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from typing import Optional
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from pydantic import Field, computed_field, field_validator
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from akkudoktoreos.config.configabc import SettingsBaseModel
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from akkudoktoreos.core.logabc import LOGGING_LEVELS
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class LoggingCommonSettings(SettingsBaseModel):
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"""Logging Configuration."""
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api_level: Optional[str] = Field(
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default=None,
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json_schema_extra={
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"description": "Logging level for API response.",
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"examples": [*LOGGING_LEVELS],
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},
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)
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console_level: Optional[str] = Field(
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default=None,
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json_schema_extra={
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"description": "Logging level for logging to console.",
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"examples": [*LOGGING_LEVELS],
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},
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)
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file_level: Optional[str] = Field(
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default=None,
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json_schema_extra={
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"description": "Logging level for logging to file.",
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"examples": [*LOGGING_LEVELS],
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},
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)
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@computed_field # type: ignore[prop-decorator]
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@property
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def file_path(self) -> Optional[Path]:
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"""Computed log file path based on data output path."""
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try:
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path = SettingsBaseModel.config.general.data_output_path / "eos.log"
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except Exception:
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# Config may not be fully set up
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path = None
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return path
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# Validators
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@field_validator("console_level", "file_level", mode="after")
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@classmethod
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def validate_level(cls, value: Optional[str]) -> Optional[str]:
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"""Validate logging level string."""
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if value is None:
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# Nothing to set
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return None
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if isinstance(value, str):
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level = value.upper()
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if level == "NONE":
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return None
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if level not in LOGGING_LEVELS:
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raise ValueError(f"Logging level {value} not supported")
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value = level
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else:
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raise TypeError(f"Invalid {type(value)} of logging level {value}")
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return value
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