49 lines
1.6 KiB
Python
49 lines
1.6 KiB
Python
import importlib
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import json
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from unittest.mock import patch
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import pytest
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import delta_barth.pipelines
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from delta_barth import pipelines as pl
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from delta_barth.errors import STATUS_HANDLER
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def test_write_performance_metrics(session): ...
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@patch("delta_barth.analysis.forecast.SALES_BASE_NUM_DATAPOINTS_MONTHS", 1)
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def test_sales_prognosis_pipeline(exmpl_api_sales_prognosis_resp):
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with patch(
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"delta_barth.analysis.forecast.get_sales_prognosis_data",
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) as mock:
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mock.return_value = (exmpl_api_sales_prognosis_resp, STATUS_HANDLER.SUCCESS)
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importlib.reload(delta_barth.pipelines)
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json_export = pl.pipeline_sales_forecast(None, None)
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assert isinstance(json_export, str)
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parsed_resp = json.loads(json_export)
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assert "response" in parsed_resp
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assert "status" in parsed_resp
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assert "daten" in parsed_resp["response"]
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assert len(parsed_resp["response"]["daten"]) > 0
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assert "code" in parsed_resp["status"]
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assert parsed_resp["status"]["code"] == 0
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def test_sales_prognosis_pipeline_dummy():
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json_export = pl.pipeline_sales_forecast_dummy(None, None)
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assert isinstance(json_export, str)
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parsed_resp = json.loads(json_export)
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assert "response" in parsed_resp
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assert "status" in parsed_resp
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assert "daten" in parsed_resp["response"]
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assert len(parsed_resp["response"]["daten"]) > 0
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entry = parsed_resp["response"]["daten"][0]
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assert entry["jahr"] == 2022
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assert entry["monat"] == 11
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assert entry["vorhersage"] == pytest.approx(47261.058594)
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assert "code" in parsed_resp["status"]
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assert parsed_resp["status"]["code"] == 0
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