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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>
245 lines
10 KiB
Python
245 lines
10 KiB
Python
import json
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import shutil
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import tempfile
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from pathlib import Path
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from typing import Any
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import pytest
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from akkudoktoreos.config import configmigrate
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from akkudoktoreos.config.config import ConfigEOS, SettingsEOSDefaults
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from akkudoktoreos.core.version import __version__
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# Test data directory and known migration pairs
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DIR_TESTDATA = Path(__file__).absolute().parent.joinpath("testdata")
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MIGRATION_PAIRS = [
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(
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DIR_TESTDATA / "eos_config_minimal_0_1_0.json",
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DIR_TESTDATA / "eos_config_minimal_now.json",
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),
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(
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DIR_TESTDATA / "eos_config_andreas_0_1_0.json",
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DIR_TESTDATA / "eos_config_andreas_now.json",
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),
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# Add more pairs here:
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# (DIR_TESTDATA / "old_config_X.json", DIR_TESTDATA / "expected_config_X.json"),
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]
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# Any sentinel in expected data
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_ANY_SENTINEL = "__ANY__"
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def _dict_contains(superset: Any, subset: Any, path="") -> list[str]:
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"""Recursively verify that all key-value pairs from a subset dictionary or list exist in a superset.
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Supports nested dictionaries and lists. Extra keys in superset are allowed.
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Numeric values (int/float) are compared with tolerance.
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Args:
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superset (Any): The dictionary or list that should contain all items from `subset`.
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subset (Any): The expected dictionary or list.
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path (str, optional): Current nested path used for error reporting. Defaults to "".
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Returns:
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list[str]: A list of strings describing mismatches or missing keys. Empty list if all subset items are present.
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"""
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errors = []
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if isinstance(subset, dict) and isinstance(superset, dict):
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for key, sub_value in subset.items():
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full_path = f"{path}/{key}" if path else key
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if key not in superset:
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errors.append(f"Missing key: {full_path}")
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continue
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errors.extend(_dict_contains(superset[key], sub_value, full_path))
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elif isinstance(subset, list) and isinstance(superset, list):
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for i, elem in enumerate(subset):
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if i >= len(superset):
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full_path = f"{path}[{i}]" if path else f"[{i}]"
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errors.append(f"List too short at {full_path}: expected element {elem}")
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continue
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errors.extend(_dict_contains(superset[i], elem, f"{path}[{i}]" if path else f"[{i}]"))
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else:
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# "__ANY__" in expected means "accept whatever value the migration produces"
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if subset == _ANY_SENTINEL:
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return errors
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# Compare values (with numeric tolerance)
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if isinstance(subset, (int, float)) and isinstance(superset, (int, float)):
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if abs(float(subset) - float(superset)) > 1e-6:
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errors.append(f"Value mismatch at {path}: expected {subset}, got {superset}")
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elif subset != superset:
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errors.append(f"Value mismatch at {path}: expected {subset}, got {superset}")
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return errors
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class TestConfigMigration:
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"""Tests for migrate_config_file()"""
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@pytest.fixture
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def tmp_config_file(self, config_default_dirs) -> Path:
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"""Create a temporary valid config file with an invalid version."""
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config_default_dir_user, _, _, _ = config_default_dirs
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config_file_user = config_default_dir_user.joinpath(ConfigEOS.CONFIG_FILE_NAME)
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# Create a default config object (simulates the latest schema)
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default_config = SettingsEOSDefaults()
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# Dump to JSON
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config_json = json.loads(default_config.model_dump_json())
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# Corrupt the version (simulate outdated config)
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config_json["general"]["version"] = "0.0.0-old"
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# Write file
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with config_file_user.open("w", encoding="utf-8") as f:
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json.dump(config_json, f, indent=4)
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return config_file_user
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def test_migrate_config_file_from_invalid_version(self, tmp_config_file: Path):
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"""Test that migration updates an outdated config version successfully."""
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backup_file = tmp_config_file.with_suffix(".bak")
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# Run migration
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result = configmigrate.migrate_config_file(tmp_config_file, backup_file)
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# Verify success
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assert result is True, "Migration should succeed even from invalid version."
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# Verify backup exists
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assert backup_file.exists(), "Backup file should be created before migration."
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# Verify version updated
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with tmp_config_file.open("r", encoding="utf-8") as f:
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migrated_data = json.load(f)
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assert migrated_data["general"]["version"] == __version__, \
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"Migrated config should have updated version."
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# Verify it still matches the structure of SettingsEOSDefaults
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new_model = SettingsEOSDefaults(**migrated_data)
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assert isinstance(new_model, SettingsEOSDefaults)
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def test_migrate_config_file_already_current(self, tmp_path: Path):
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"""Test that a current config file returns True immediately."""
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config_path = tmp_path / "EOS_current.json"
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default = SettingsEOSDefaults()
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with config_path.open("w", encoding="utf-8") as f:
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f.write(default.model_dump_json(indent=4))
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backup_file = config_path.with_suffix(".bak")
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result = configmigrate.migrate_config_file(config_path, backup_file)
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assert result is True
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assert not backup_file.exists(), "No backup should be made if config is already current."
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@pytest.mark.parametrize("old_file, expected_file", MIGRATION_PAIRS)
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def test_migrate_old_version_config(self, tmp_path: Path, old_file: Path, expected_file: Path):
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"""Ensure migration from old → new schema produces the expected output."""
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# --- Prepare temporary working file based on expected file name ---
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working_file = expected_file.with_suffix(".new")
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shutil.copy(old_file, working_file)
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# Backup file path (inside tmp_path to avoid touching repo files)
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backup_file = tmp_path / f"{old_file.stem}.bak"
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failed = False
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try:
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assert working_file.exists(), f"Working config file is missing: {working_file}"
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# --- Perform migration ---
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result = configmigrate.migrate_config_file(working_file, backup_file)
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# --- Assertions ---
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assert result is True, f"Migration failed for {old_file.name}"
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assert configmigrate.mapped_count >= 1, f"No mapped migrations for {old_file.name}"
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assert configmigrate.auto_count >= 1, f"No automatic migrations for {old_file.name}"
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assert len(configmigrate.skipped_paths) <= 3, (
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f"Too many skipped paths in {old_file.name}: {configmigrate.skipped_paths}"
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)
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assert backup_file.exists(), f"Backup file not created for {old_file.name}"
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# --- Compare migrated result with expected output ---
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old_data = json.loads(old_file.read_text(encoding="utf-8"))
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new_data = json.loads(working_file.read_text(encoding="utf-8"))
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expected_data = json.loads(expected_file.read_text(encoding="utf-8"))
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# Check version
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assert new_data["general"]["version"] == __version__, (
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f"Expected version {__version__}, got {new_data['general']['version']}"
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)
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# Recursive subset comparison
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errors = _dict_contains(new_data, expected_data)
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assert not errors, (
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f"Migrated config for {old_file.name} is missing or mismatched fields:\n" +
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"\n".join(errors) + f"\n{new_data}"
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)
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# --- Compare migrated result with migration map ---
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# Ensure all expected mapped fields are actually migrated and correct
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missing_migrations = []
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mismatched_values = []
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for old_path, mapping in configmigrate.MIGRATION_MAP.items():
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if mapping is None:
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continue # skip intentionally dropped fields
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# Determine new path (string or tuple)
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new_path = mapping[0] if isinstance(mapping, tuple) else mapping
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# Get value from expected data (if present)
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expected_value = configmigrate._get_json_nested_value(expected_data, new_path)
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if expected_value is None:
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continue # new field not present in expected config
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# Check that migration recorded this old path
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if old_path.strip("/") not in configmigrate.migrated_source_paths:
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missing_migrations.append(f"{old_path} → {new_path}")
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continue
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# Verify the migrated value matches the expected one
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new_value = configmigrate._get_json_nested_value(new_data, new_path)
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if new_value != expected_value:
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# Check if this mapping uses _KEEP_DEFAULT and the old value was None/missing
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old_value = configmigrate._get_json_nested_value(old_data, old_path)
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keep_default = (
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isinstance(mapping, tuple)
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and configmigrate._KEEP_DEFAULT in mapping
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)
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if keep_default and old_value is None:
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continue # acceptable: old was None, new model keeps its default
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mismatched_values.append(
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f"{old_path} → {new_path}: expected {expected_value!r}, got {new_value!r}"
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)
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assert not missing_migrations, (
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"Some expected migration map entries were not migrated:\n"
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+ "\n".join(missing_migrations)
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)
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assert not mismatched_values, (
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"Migrated values differ from expected results:\n"
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+ "\n".join(mismatched_values)
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)
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# Validate migrated config with schema
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new_model = SettingsEOSDefaults(**new_data)
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assert isinstance(new_model, SettingsEOSDefaults)
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except Exception:
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# mark failure and re-raise so pytest records the error and the working_file is kept
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failed = True
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raise
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finally:
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# Remove the .new working file only if the test passed (failed == False)
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if not failed and working_file.exists():
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working_file.unlink(missing_ok=True)
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