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Run ETL processes in parallel (#1253)

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* WIP on parallelizing

* switching to get_tmp_path for nri

* switching to get_tmp_path everywhere necessary

* fixing linter errors

* moving heavy ETLs to front of line

* add hold

* moving cdc places up

* removing unnecessary print

* moving h&t up

* adding parallel to geo post

* better census labels

* switching to concurrent futures

* fixing output
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Lucas Merrill Brown 2022-02-11 14:04:53 -05:00 • committed by GitHub
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30 changed files with 286 additions and 160 deletions
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data/data-pipeline/data_pipeline/etl/sources/doe_energy_burden/etl.py
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@ -37,12 +37,12 @@ class DOEEnergyBurden(ExtractTransformLoad):
unzip_file_from_url(
file_url=self.DOE_FILE_URL,
download_path=self.TMP_PATH,
unzipped_file_path=self.TMP_PATH / "doe_energy_burden",
download_path=self.get_tmp_path(),
unzipped_file_path=self.get_tmp_path() / "doe_energy_burden",
)
self.raw_df = pd.read_csv(
filepath_or_buffer=self.TMP_PATH
filepath_or_buffer=self.get_tmp_path()
/ "doe_energy_burden"
/ "DOE_LEAD_AMI_TRACT_2018_ALL.csv",
# The following need to remain as strings for all of their digits, not get converted to numbers.