add dummy data pipeline

src/delta_barth/analysis/forecast.py

@@ -1,6 +1,5 @@
 from __future__ import annotations
 
-import dataclasses as dc
 from collections.abc import Mapping, Set
 from datetime import datetime as Datetime
 from typing import TYPE_CHECKING, Final
@@ -18,6 +17,7 @@ from delta_barth.api.requests import (
 )
 from delta_barth.constants import (
     COL_MAP_SALES_PROGNOSIS,
+    DUMMY_DATA_PATH,
     FEATURES_SALES_PROGNOSIS,
     MIN_NUMBER_DATAPOINTS,
 )
@@ -52,12 +52,12 @@ def _parse_api_resp_to_df(
     return pd.DataFrame(data)
 
 
-def _parse_df_to_api_resp(
-    data: pd.DataFrame,
-) -> SalesPrognosisResponse:
-    df_formatted = data.to_dict(orient="records")
+# def _parse_df_to_api_resp(
+#     data: pd.DataFrame,
+# ) -> SalesPrognosisResponse:
+#     df_formatted = data.to_dict(orient="records")
 
-    return SalesPrognosisResponse(daten=tuple(df_formatted))  # type: ignore
+#     return SalesPrognosisResponse(daten=tuple(df_formatted))  # type: ignore
 
 
 def _parse_df_to_results(
@@ -75,11 +75,11 @@ def _parse_api_resp_to_df_wrapped(
     return _parse_api_resp_to_df(resp)
 
 
-@wrap_result()
-def _parse_df_to_api_resp_wrapped(
-    data: pd.DataFrame,
-) -> SalesPrognosisResponse:
-    return _parse_df_to_api_resp(data)
+# @wrap_result()
+# def _parse_df_to_api_resp_wrapped(
+#     data: pd.DataFrame,
+# ) -> SalesPrognosisResponse:
+#     return _parse_df_to_api_resp(data)
 
 
 @wrap_result()
@@ -261,7 +261,6 @@ def _postprocess_sales(
         pipe.fail(res.status)
         return pipe
 
-    # res = _parse_df_to_api_resp_wrapped(res.result)
     res = _parse_df_to_results_wrapped(res.unwrap())
     if res.status != STATUS_HANDLER.SUCCESS:
         pipe.fail(res.status)
@@ -327,6 +326,21 @@ def pipeline_sales_dummy(
     session: Session,
     company_id: int | None = None,
     start_date: Datetime | None = None,
-) -> SalesPrognosisResultsExport:  # pragma: no cover
+) -> SalesPrognosisResultsExport:
     """prototype dummy function for tests by DelBar"""
-    ...
+    _, _, _ = session, company_id, start_date
+
+    data_pth = DUMMY_DATA_PATH / "exmp_sales_prognosis_output.pkl"
+    assert data_pth.exists(), "sales forecast dummy data not existent"
+    data = pd.read_pickle(data_pth)
+    pipe: PipeResult[SalesPrognosisResultsExport] = PipeResult(None, STATUS_HANDLER.SUCCESS)
+    res = _parse_df_to_results_wrapped(data)
+
+    if res.status != STATUS_HANDLER.SUCCESS:
+        pipe.fail(res.status)
+        return _export_on_fail(res.status)
+
+    return SalesPrognosisResultsExport(
+        response=res.unwrap(),
+        status=res.status,
+    )

src/delta_barth/constants.py

@@ -1,8 +1,17 @@
 import enum
+from pathlib import Path
 from typing import Final
 
 from delta_barth.types import DualDict, HttpContentHeaders
 
+# ** lib path
+lib_path = Path(__file__).parent
+assert lib_path is not None, "lib path not resolved"
+LIB_PATH: Final[Path] = lib_path
+dummy_data_pth = LIB_PATH / "_dummy_data"
+assert dummy_data_pth.exists(), f"dummy data path not found: {dummy_data_pth}"
+DUMMY_DATA_PATH: Final[Path] = dummy_data_pth
+
 # ** error handling
 DEFAULT_INTERNAL_ERR_CODE: Final[int] = 100
 DEFAULT_API_ERR_CODE: Final[int] = 400

src/delta_barth/pipelines.py

@@ -16,3 +16,18 @@ def pipeline_sales_forecast(
     status = JsonStatus(result.status.model_dump_json())
 
     return response, status
+
+
+def pipeline_sales_forecast_dummy(
+    company_id: int | None,
+    start_date: Datetime | None,
+) -> tuple[JsonResponse, JsonStatus]:
+    result = forecast.pipeline_sales_dummy(
+        SESSION,
+        company_id=company_id,
+        start_date=start_date,
+    )
+    response = JsonResponse(result.response.model_dump_json())
+    status = JsonStatus(result.status.model_dump_json())
+
+    return response, status

tests/analysis/test_forecast.py

@@ -115,14 +115,14 @@ def test_parse_api_resp_to_df(exmpl_api_sales_prognosis_resp):
     assert all(col in features for col in df.columns)
 
 
-def test_parse_df_to_api_resp_ValidData(valid_df):
-    ret = fc._parse_df_to_api_resp(valid_df)
-    assert len(ret.daten) > 0
+# def test_parse_df_to_api_resp_ValidData(valid_df):
+#     ret = fc._parse_df_to_api_resp(valid_df)
+#     assert len(ret.daten) > 0
 
 
-def test_parse_df_to_api_resp_InvalidData(invalid_df):
-    with pytest.raises(ValidationError):
-        _ = fc._parse_df_to_api_resp(invalid_df)
+# def test_parse_df_to_api_resp_InvalidData(invalid_df):
+#     with pytest.raises(ValidationError):
+#         _ = fc._parse_df_to_api_resp(invalid_df)
 
 
 def test_parse_df_to_results_ValidData(valid_results):
@@ -248,3 +248,14 @@ def test_pipeline_sales_prognosis(exmpl_api_sales_prognosis_resp):
 
     assert result.status == STATUS_HANDLER.SUCCESS
     assert len(result.response.daten) > 0
+
+
+def test_pipeline_sales_prognosis_dummy():
+    result = fc.pipeline_sales_dummy(None)  # type: ignore
+
+    assert result.status == STATUS_HANDLER.SUCCESS
+    assert len(result.response.daten) > 0
+    entry = result.response.daten[0]
+    assert entry.jahr == 2022
+    assert entry.monat == 11
+    assert entry.vorhersage == pytest.approx(47261.058594)

tests/api/test_requests.py

@@ -74,7 +74,6 @@ def test_get_sales_prognosis_data_FailLogin(session, mock_get):
     assert status.api_server_error.hints == json["hints"]
 
 
-@pytest.mark.new
 @pytest.mark.api_con_required
 def test_get_sales_prognosis_data_FailApiServer(session, mock_get):
     code = 405

tests/conftest.py

@@ -97,7 +97,7 @@ def exmpl_api_sales_prognosis_resp() -> SalesPrognosisResponse:
 def exmpl_api_sales_prognosis_output() -> pd.DataFrame:
     pwd = Path.cwd()
     assert "barth" in pwd.parent.name.lower(), "not in project root directory"
-    data_pth = pwd / "./tests/_test_data/exmp_sales_prognosis_ouput.pkl"
+    data_pth = pwd / "./tests/_test_data/exmp_sales_prognosis_output.pkl"
     assert data_pth.exists(), "file to API sales data not found"
 
     return pd.read_pickle(data_pth)

tests/test_pipelines.py

@@ -2,6 +2,8 @@ import importlib
 import json
 from unittest.mock import patch
 
+import pytest
+
 import delta_barth.pipelines
 from delta_barth import pipelines as pl
 from delta_barth.errors import STATUS_HANDLER
@@ -26,3 +28,20 @@ def test_sales_prognosis_pipeline(exmpl_api_sales_prognosis_resp):
     parsed_stat = json.loads(json_stat)
     assert "code" in parsed_stat
     assert parsed_stat["code"] == 0
+
+
+def test_sales_prognosis_pipeline_dummy():
+    json_resp, json_stat = pl.pipeline_sales_forecast_dummy(None, None)
+
+    assert isinstance(json_resp, str)
+    assert isinstance(json_stat, str)
+    parsed_resp = json.loads(json_resp)
+    assert "daten" in parsed_resp
+    assert len(parsed_resp["daten"]) > 0
+    entry = parsed_resp["daten"][0]
+    assert entry["jahr"] == 2022
+    assert entry["monat"] == 11
+    assert entry["vorhersage"] == pytest.approx(47261.058594)
+    parsed_stat = json.loads(json_stat)
+    assert "code" in parsed_stat
+    assert parsed_stat["code"] == 0