src/delta_barth/analysis/forecast.py

@@ -403,13 +403,13 @@ def _export_on_fail(
 
 def pipeline_sales_forecast(
     session: Session,
-    company_id: int | None = None,
+    company_ids: list[int] | None = None,
     start_date: Datetime | None = None,
 ) -> SalesPrognosisResultsExport:
     logger_pipelines.info("[PIPELINES] Starting main sales forecast pipeline...")
     response, status = get_sales_prognosis_data(
         session,
-        company_id=company_id,
+        company_ids=company_ids,
         start_date=start_date,
     )
     if status != STATUS_HANDLER.SUCCESS:

src/delta_barth/api/requests.py

@@ -20,7 +20,7 @@ if TYPE_CHECKING:
 # ** sales data
 # ** import
 class SalesPrognosisRequestP(BaseModel):
-    FirmaId: SkipValidation[int | None]
+    FirmaIds: SkipValidation[list[int] | None]
     BuchungsDatum: SkipValidation[Datetime | None]
 
 
@@ -55,20 +55,14 @@ class SalesPrognosisResultsExport(ExportResponse):
 
 def get_sales_prognosis_data(
     session: Session,
-    company_id: int | None = None,
+    company_ids: list[int] | None = None,
     start_date: Datetime | None = None,
 ) -> tuple[SalesPrognosisResponse, Status]:
-    # TODO check elimination of assertion for login, #25
-    # _, status = session.assert_login()
-    # if status != STATUS_HANDLER.SUCCESS:
-    #     response = SalesPrognosisResponse(daten=tuple())
-    #     return response, status
-
     ROUTE: Final[str] = "verkauf/umsatzprognosedaten"
     URL: Final = combine_route(session.base_url, ROUTE)
 
     sales_prog_req = SalesPrognosisRequestP(
-        FirmaId=company_id,
+        FirmaIds=company_ids,
         BuchungsDatum=start_date,
     )
     empty_response = SalesPrognosisResponse(daten=tuple())

src/delta_barth/constants.py

@@ -50,7 +50,7 @@ class KnownDelBarApiErrorCodes(enum.Enum):
 
 
 # ** API
-API_CON_TIMEOUT: Final[float] = 10.0  # secs to response
+API_CON_TIMEOUT: Final[float] = 20.0  # secs to response
 MAX_LOGIN_RETRIES: Final[int] = 1
 
 # ** API response parsing

src/delta_barth/pipelines.py

@@ -44,14 +44,14 @@ def _write_performance_metrics_wrapped(
 
 
 def pipeline_sales_forecast(
-    company_id: int | None,
+    company_ids: list[int] | None,
     start_date: Datetime | None,
 ) -> JsonExportResponse:
     PIPELINE_NAME: Final[str] = "sales_forecast"
     logger.info("[EXT-CALL PIPELINES] Starting main sales forecast pipeline...")
     t_start = time.perf_counter_ns()
     result = forecast.pipeline_sales_forecast(
-        SESSION, company_id=company_id, start_date=start_date
+        SESSION, company_ids=company_ids, start_date=start_date
     )
     export = JsonExportResponse(result.model_dump_json())
     t_end = time.perf_counter_ns()

tests/analysis/test_forecast.py

@@ -432,6 +432,8 @@ def test_export_on_fail():
 
 @patch("delta_barth.session.CFG_HOT_RELOAD", False)
 def test_pipeline_sales_forecast_SuccessDbWrite(exmpl_api_sales_prognosis_resp, session):
+    date = Datetime(2023, 8, 15)
+    company_ids = [5661, 1027, 1024]
     with (
         patch(
             "delta_barth.analysis.forecast.get_sales_prognosis_data",
@@ -440,7 +442,7 @@ def test_pipeline_sales_forecast_SuccessDbWrite(exmpl_api_sales_prognosis_resp,
     ):
         get_mock.return_value = exmpl_api_sales_prognosis_resp, STATUS_HANDLER.SUCCESS
         sess_mock.cfg.forecast.threshold_month_data_points = 1
-        result = fc.pipeline_sales_forecast(None)  # type: ignore
+        result = fc.pipeline_sales_forecast(None, company_ids, date)  # type: ignore
     assert result.status == STATUS_HANDLER.SUCCESS
     assert len(result.response.daten) > 0
 

tests/api/test_requests.py

@@ -11,7 +11,7 @@ def test_get_sales_prognosis_data_Success(session):
     resp, status = session.login()
     # test without company ID
     assert status.code == 0
-    date = Datetime(2022, 6, 1)
+    date = Datetime(2023, 12, 15)
     resp, status = requests_.get_sales_prognosis_data(session, None, date)
     assert status.code == 0
     assert len(resp.daten) > 0
@@ -21,26 +21,25 @@ def test_get_sales_prognosis_data_Success(session):
     assert len(resp.daten) == 0
     # test with company ID
     assert status.code == 0
-    date = Datetime(2022, 6, 1)
+    date = Datetime(2023, 8, 15)
-    company_id = 1024
+    company_ids = [5661, 1027]
-    resp, status = requests_.get_sales_prognosis_data(session, company_id, date)
+    resp, status = requests_.get_sales_prognosis_data(session, company_ids, date)
     assert status.code == 0
     assert len(resp.daten) > 0
     date = Datetime(2030, 1, 1)
-    resp, status = requests_.get_sales_prognosis_data(session, company_id, date)
+    resp, status = requests_.get_sales_prognosis_data(session, company_ids, date)
     assert status.code == 0
     assert len(resp.daten) == 0
     # test with non-existent company ID
     assert status.code == 0
     date = Datetime(2022, 6, 1)
-    company_id = 1000024
+    company_ids = [1000024]
-    resp, status = requests_.get_sales_prognosis_data(session, company_id, date)
+    resp, status = requests_.get_sales_prognosis_data(session, company_ids, date)
-    # TODO check if this behaviour is still considered "successful"
     assert status.code == 0
     assert len(resp.daten) == 0
     # test without date
-    company_id = 1024
+    company_ids = [1024]
-    resp, status = requests_.get_sales_prognosis_data(session, company_id, None)
+    resp, status = requests_.get_sales_prognosis_data(session, company_ids, None)
     assert status.code == 0
     assert len(resp.daten) > 0
     # test without filters

tests/test_pipelines.py

@@ -1,4 +1,5 @@
 import json
+from datetime import datetime as Datetime
 from unittest.mock import patch
 
 import pytest
@@ -47,6 +48,8 @@ def test_write_performance_metrics_FailStartingTime(session):
 
 @patch("delta_barth.session.CFG_HOT_RELOAD", False)
 def test_sales_prognosis_pipeline(exmpl_api_sales_prognosis_resp, session, monkeypatch):
+    date = Datetime(2023, 8, 15)
+    company_ids = [5661, 1027, 1024]
     with (
         patch(
             "delta_barth.analysis.forecast.get_sales_prognosis_data",
@@ -56,7 +59,7 @@ def test_sales_prognosis_pipeline(exmpl_api_sales_prognosis_resp, session, monke
     ):
         get_mock.return_value = (exmpl_api_sales_prognosis_resp, STATUS_HANDLER.SUCCESS)
         sess_mock.cfg.forecast.threshold_month_data_points = 1
-        json_export = pl.pipeline_sales_forecast(None, None)
+        json_export = pl.pipeline_sales_forecast(company_ids, date)
 
     assert isinstance(json_export, str)
     parsed_resp = json.loads(json_export)