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Run ETL processes in parallel (#1253)
* 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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30 changed files with 286 additions and 160 deletions
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@ -71,12 +71,12 @@ class EPARiskScreeningEnvironmentalIndicatorsETL(ExtractTransformLoad):
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unzip_file_from_url(
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file_url=self.AGGREGATED_RSEI_SCORE_FILE_URL,
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download_path=self.TMP_PATH,
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unzipped_file_path=self.TMP_PATH / "epa_rsei",
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download_path=self.get_tmp_path(),
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unzipped_file_path=self.get_tmp_path() / "epa_rsei",
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)
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self.df = pd.read_csv(
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filepath_or_buffer=self.TMP_PATH
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filepath_or_buffer=self.get_tmp_path()
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/ "epa_rsei"
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/ "CensusMicroTracts2019_2019_aggregated.csv",
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# The following need to remain as strings for all of their digits, not get
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