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876655d2b2
* Refactor CDC life-expectancy (1554) * Update to new tract list (#1554) * Adjust for tests (#1848) * Add tests for cdc_places (#1848) * Add EJScreen tests (#1848) * Add tests for HUD housing (#1848) * Add tests for GeoCorr (#1848) * Add persistent poverty tests (#1848) * Update for sources without zips, for new validation (#1848) * Update tests for new multi-CSV but (#1848) Lucas updated the CDC life expectancy data to handle a bug where two states are missing from the US Overall download. Since virtually none of our other ETL classes download multiple CSVs directly like this, it required a pretty invasive new mocking strategy. * Add basic tests for nature deprived (#1848) * Add wildfire tests (#1848) * Add flood risk tests (#1848) * Add DOT travel tests (#1848) * Add historic redlining tests (#1848) * Add tests for ME and WI (#1848) * Update now that validation exists (#1848) * Adjust for validation (#1848) * Add health insurance back to cdc places (#1848) Ooops * Update tests with new field (#1848) * Test for blank tract removal (#1848) * Add tracts for clipping behavior * Test clipping and zfill behavior (#1848) * Fix bad test assumption (#1848) * Simplify class, add test for tract padding (#1848) * Fix percentage inversion, update tests (#1848) Looking through the transformations, I noticed that we were subtracting a percentage that is usually between 0-100 from 1 instead of 100, and so were endind up with some surprising results. Confirmed with lucasmbrown-usds * Add note about first street data (#1848)
57 lines
1.6 KiB
Python
57 lines
1.6 KiB
Python
import zipfile
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import pandas as pd
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from data_pipeline.config import settings
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from data_pipeline.etl.base import ExtractTransformLoad, ValidGeoLevel
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from data_pipeline.utils import get_module_logger
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logger = get_module_logger(__name__)
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class ExampleETL(ExtractTransformLoad):
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"""A test-only, simple implementation of the ETL base class.
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This can be used for the base tests of the `TestETL` class.
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"""
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INPUT_FIELD_NAME = "Input Field 1"
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EXAMPLE_FIELD_NAME = "Example Field 1"
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NAME = "example_dataset"
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LAST_UPDATED_YEAR = 2017
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SOURCE_URL = "https://www.example.com/example.zip"
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GEO_LEVEL = ValidGeoLevel.CENSUS_TRACT
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LOAD_YAML_CONFIG: bool = True
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def __init__(self):
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self.COLUMNS_TO_KEEP = [
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self.GEOID_TRACT_FIELD_NAME,
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self.EXAMPLE_FIELD_NAME,
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]
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def extract(self):
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# Pretend to download zip from external URL, write it to CSV.
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zip_file_path = (
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settings.APP_ROOT
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/ "tests"
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/ "sources"
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/ "example"
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/ "data"
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/ "input.zip"
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)
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logger.info(f"Extracting {zip_file_path}")
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with zipfile.ZipFile(zip_file_path, "r") as zip_ref:
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zip_ref.extractall(self.get_tmp_path())
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def transform(self):
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logger.info(f"Loading file from {self.get_tmp_path() / 'input.csv'}.")
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df: pd.DataFrame = pd.read_csv(
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self.get_tmp_path() / "input.csv",
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dtype={self.GEOID_TRACT_FIELD_NAME: "string"},
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low_memory=False,
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)
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df[self.EXAMPLE_FIELD_NAME] = df[self.INPUT_FIELD_NAME] * 2
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self.output_df = df
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