Merge "metrics_database": first database integration for metrics logging #9
@ -297,7 +297,7 @@ def _process_sales(
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score_mae=best_score_mae,
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score_r2=best_score_r2,
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best_start_year=best_start_year,
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XGB_params=best_params,
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xgb_params=best_params,
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)
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pipe.stats(stats)
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@ -2,18 +2,17 @@ from pathlib import Path
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import sqlalchemy as sql
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from delta_barth.constants import DB_ECHO
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# ** meta
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metadata = sql.MetaData()
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def get_engine(
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db_path: Path,
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echo: bool = False,
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) -> sql.Engine:
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path = db_path.resolve()
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connection_str: str = f"sqlite:///{str(path)}"
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engine = sql.create_engine(connection_str, echo=DB_ECHO)
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engine = sql.create_engine(connection_str, echo=echo)
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return engine
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@ -31,8 +30,8 @@ sf_stats = sql.Table(
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"sales_forecast_statistics",
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metadata,
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sql.Column("id", sql.Integer, primary_key=True),
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sql.Column("error_code", sql.Integer),
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sql.Column("error_msg", sql.String(length=200)),
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sql.Column("status_code", sql.Integer),
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sql.Column("status_dscr", sql.String(length=200)),
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sql.Column("length_dataset", sql.Integer),
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sql.Column("score_mae", sql.Float, nullable=True),
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sql.Column("score_r2", sql.Float, nullable=True),
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@ -4,14 +4,17 @@ from pathlib import Path
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from typing import TYPE_CHECKING, Final
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import requests
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import sqlalchemy as sql
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from dopt_basics.io import combine_route
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import delta_barth.logging
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from delta_barth import databases as db
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from delta_barth.api.common import (
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LoginRequest,
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LoginResponse,
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validate_credentials,
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)
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from delta_barth.constants import DB_ECHO
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from delta_barth.errors import STATUS_HANDLER
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from delta_barth.logging import logger_session as logger
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from delta_barth.types import DelBarApiError, Status
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@ -36,9 +39,13 @@ class Session:
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def __init__(
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self,
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base_headers: HttpContentHeaders,
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db_folder: str = "data",
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logging_folder: str = "logs",
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) -> None:
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self._data_path: Path | None = None
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self._db_path: Path | None = None
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self._db_folder = db_folder
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self._db_engine: sql.Engine | None = None
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self._logging_dir: Path | None = None
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self._logging_folder = logging_folder
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self._creds: ApiCredentials | None = None
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@ -48,13 +55,31 @@ class Session:
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self._logged_in: bool = False
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def setup(self) -> None:
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self.setup_logging()
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self._setup_db_management()
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self._setup_logging()
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@property
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def data_path(self) -> Path:
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assert self._data_path is not None, "accessed data path not set"
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return self._data_path
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@property
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def db_engine(self) -> sql.Engine:
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assert self._db_engine is not None, "accessed database engine not set"
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return self._db_engine
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@property
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def db_path(self) -> Path:
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if self._db_path is not None:
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return self._db_path
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db_root = (self.data_path / self._db_folder).resolve()
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db_path = db_root / "dopt-data.db"
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if not db_root.exists():
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db_root.mkdir(parents=False)
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self._db_path = db_path
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return self._db_path
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@property
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def logging_dir(self) -> Path:
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if self._logging_dir is not None:
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@ -66,7 +91,12 @@ class Session:
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self._logging_dir = logging_dir
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return self._logging_dir
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def setup_logging(self) -> None:
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def _setup_db_management(self) -> None:
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self._db_engine = db.get_engine(self.db_path, echo=DB_ECHO)
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db.metadata.create_all(self._db_engine)
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logger.info("[SESSION] Successfully setup DB management")
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def _setup_logging(self) -> None:
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delta_barth.logging.setup_logging(self.logging_dir)
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logger.info("[SESSION] Successfully setup logging")
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@ -161,10 +161,11 @@ class SalesForecastStatistics(Statistics):
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score_mae: float | None = None
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score_r2: float | None = None
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best_start_year: int | None = None
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XGB_params: BestParametersXGBRegressor | None = None
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xgb_params: BestParametersXGBRegressor | None = None
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class BestParametersXGBRegressor(t.TypedDict):
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forecast_id: t.NotRequired[int]
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n_estimators: int
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learning_rate: float
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max_depth: int
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@ -158,7 +158,6 @@ def test_preprocess_sales_FailOnTargetFeature(
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assert pipe.results is None
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@pytest.mark.new
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def test_process_sales_Success(sales_data_real_preproc):
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data = sales_data_real_preproc.copy()
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pipe = PipeResult(data, STATUS_HANDLER.SUCCESS)
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@ -178,10 +177,9 @@ def test_process_sales_Success(sales_data_real_preproc):
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assert pipe.statistics.score_mae is not None
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assert pipe.statistics.score_r2 is not None
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assert pipe.statistics.best_start_year is not None
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assert pipe.statistics.XGB_params is not None
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assert pipe.statistics.xgb_params is not None
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@pytest.mark.new
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def test_process_sales_FailTooFewPoints(sales_data_real_preproc):
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data = sales_data_real_preproc.copy()
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data = data.iloc[:20, :]
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@ -205,10 +203,9 @@ def test_process_sales_FailTooFewPoints(sales_data_real_preproc):
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assert pipe.statistics.score_mae is None
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assert pipe.statistics.score_r2 is None
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assert pipe.statistics.best_start_year is None
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assert pipe.statistics.XGB_params is None
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assert pipe.statistics.xgb_params is None
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@pytest.mark.new
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def test_process_sales_FailTooFewMonthPoints(sales_data_real_preproc):
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data = sales_data_real_preproc.copy()
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pipe = PipeResult(data, STATUS_HANDLER.SUCCESS)
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@ -232,10 +229,9 @@ def test_process_sales_FailTooFewMonthPoints(sales_data_real_preproc):
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assert pipe.statistics.score_mae is None
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assert pipe.statistics.score_r2 is None
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assert pipe.statistics.best_start_year is None
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assert pipe.statistics.XGB_params is None
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assert pipe.statistics.xgb_params is None
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@pytest.mark.new
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def test_process_sales_FailNoReliableForecast(sales_data_real_preproc):
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data = sales_data_real_preproc.copy()
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data["betrag"] = 10000
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@ -278,7 +274,7 @@ def test_process_sales_FailNoReliableForecast(sales_data_real_preproc):
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assert pipe.statistics.score_mae is None
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assert pipe.statistics.score_r2 is None
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assert pipe.statistics.best_start_year is None
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assert pipe.statistics.XGB_params is None
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assert pipe.statistics.xgb_params is None
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def test_postprocess_sales_Success(
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119
tests/test_databases.py
Normal file
119
tests/test_databases.py
Normal file
@ -0,0 +1,119 @@
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from dataclasses import asdict
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import pytest
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import sqlalchemy as sql
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from delta_barth import databases as db
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from delta_barth.types import BestParametersXGBRegressor, SalesForecastStatistics
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def test_get_engine(tmp_path):
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db_path = tmp_path / "test_db.db"
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engine = db.get_engine(db_path)
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assert isinstance(engine, sql.Engine)
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assert "sqlite" in str(engine.url)
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assert db_path.parent.name in str(engine.url)
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def test_write_sales_forecast_statistics_small(session):
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eng = session.db_engine
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code = 0
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descr = "Test case to write stats"
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length = 32
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stats = SalesForecastStatistics(code, descr, length)
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_ = stats.xgb_params
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stats_to_write = asdict(stats)
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_ = stats_to_write.pop("xgb_params")
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with eng.begin() as conn:
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res = conn.execute(sql.insert(db.sf_stats).values(stats_to_write))
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_ = res.inserted_primary_key[0]
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with eng.begin() as conn:
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res = conn.execute(sql.select(db.sf_stats))
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inserted = tuple(res.mappings())[0]
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data = dict(**inserted)
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del data["id"]
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result = SalesForecastStatistics(**data)
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assert result.status_code == code
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assert result.status_dscr == descr
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assert result.length_dataset == length
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assert result.score_mae is None
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assert result.score_r2 is None
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assert result.best_start_year is None
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assert result.xgb_params is None
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def test_write_sales_forecast_statistics_large(session):
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eng = session.db_engine
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code = 0
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descr = "Test case to write stats"
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length = 32
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score_mae = 3.54
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score_r2 = 0.56
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best_start_year = 2020
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xgb_params = BestParametersXGBRegressor(
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n_estimators=2,
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learning_rate=0.3,
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max_depth=2,
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min_child_weight=5,
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gamma=0.5,
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subsample=0.8,
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colsample_bytree=5.25,
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early_stopping_rounds=5,
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)
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stats = SalesForecastStatistics(
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code,
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descr,
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length,
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score_mae,
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score_r2,
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best_start_year,
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xgb_params,
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)
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xgb_params = stats.xgb_params
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assert xgb_params is not None
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stats_to_write = asdict(stats)
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_ = stats_to_write.pop("xgb_params")
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with eng.begin() as conn:
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res = conn.execute(sql.insert(db.sf_stats).values(stats_to_write))
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sf_id = res.inserted_primary_key[0]
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xgb_params["forecast_id"] = sf_id
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res = conn.execute(sql.insert(db.sf_XGB).values(xgb_params))
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with eng.begin() as conn:
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res_stats = conn.execute(sql.select(db.sf_stats))
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res_xgb = conn.execute(sql.select(db.sf_XGB))
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# reconstruct best XGB parameters
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inserted_xgb = tuple(res_xgb.mappings())[0]
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data_xgb = dict(**inserted_xgb)
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del data_xgb["id"]
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xgb_stats = BestParametersXGBRegressor(**data_xgb)
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# reconstruct other statistics
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inserted = tuple(res_stats.mappings())[0]
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data_inserted = dict(**inserted)
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stats_id_fk = data_inserted["id"] # foreign key in XGB parameters
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del data_inserted["id"]
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stats = SalesForecastStatistics(**data_inserted, xgb_params=xgb_stats)
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assert stats.status_code == code
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assert stats.status_dscr == descr
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assert stats.length_dataset == length
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assert stats.score_mae == pytest.approx(score_mae)
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assert stats.score_r2 == pytest.approx(score_r2)
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assert stats.best_start_year == best_start_year
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assert stats.xgb_params is not None
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# compare xgb_stats
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assert stats.xgb_params["forecast_id"] == stats_id_fk # type: ignore
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assert stats.xgb_params["n_estimators"] == 2
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assert stats.xgb_params["learning_rate"] == pytest.approx(0.3)
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assert stats.xgb_params["max_depth"] == 2
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assert stats.xgb_params["min_child_weight"] == 5
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assert stats.xgb_params["gamma"] == pytest.approx(0.5)
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assert stats.xgb_params["subsample"] == pytest.approx(0.8)
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assert stats.xgb_params["colsample_bytree"] == pytest.approx(5.25)
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assert stats.xgb_params["early_stopping_rounds"] == 5
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@ -43,6 +43,22 @@ def test_session_set_DataPath(tmp_path):
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assert isinstance(session.data_path, Path)
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def test_session_setup_db_management(tmp_path):
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str_path = str(tmp_path)
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foldername: str = "data_test"
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target_db_dir = tmp_path / foldername
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session = delta_barth.session.Session(HTTP_BASE_CONTENT_HEADERS, db_folder=foldername)
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session.set_data_path(str_path)
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db_path = session.db_path
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assert db_path.parent.exists()
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assert db_path.parent == target_db_dir
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assert not db_path.exists()
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session.setup()
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assert session._db_engine is not None
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assert db_path.exists()
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@patch("delta_barth.logging.ENABLE_LOGGING", True)
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@patch("delta_barth.logging.LOGGING_TO_FILE", True)
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def test_session_setup_logging(tmp_path):
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