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https://github.com/DOI-DO/j40-cejst-2.git
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b404fdcc43
* generate Geo-aware scores for all zoom levels * usa high progress * testing dissolve * checkpoint * changing type * removing breakpoint * validation notebooks * quick update * score validation * fixes for county merge * code completed
137 lines
3.2 KiB
Python
137 lines
3.2 KiB
Python
import importlib
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from etl.score.etl_score import ScoreETL
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from etl.score.etl_score_post import PostScoreETL
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from etl.score.etl_score_geo import GeoScoreETL
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def etl_runner(dataset_to_run: str = None) -> None:
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"""Runs all etl processes or a specific one
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Args:
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dataset_to_run (str): Run a specific ETL process. If missing, runs all processes (optional)
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Returns:
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None
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"""
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# this list comes from YAMLs
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dataset_list = [
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{
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"name": "tree_equity_score",
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"module_dir": "tree_equity_score",
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"class_name": "TreeEquityScoreETL",
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},
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{
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"name": "census_acs",
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"module_dir": "census_acs",
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"class_name": "CensusACSETL",
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},
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{
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"name": "ejscreen",
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"module_dir": "ejscreen",
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"class_name": "EJScreenETL",
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},
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{
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"name": "housing_and_transportation",
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"module_dir": "housing_and_transportation",
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"class_name": "HousingTransportationETL",
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},
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{
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"name": "hud_housing",
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"module_dir": "hud_housing",
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"class_name": "HudHousingETL",
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},
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{
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"name": "calenviroscreen",
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"module_dir": "calenviroscreen",
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"class_name": "CalEnviroScreenETL",
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},
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{
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"name": "hud_recap",
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"module_dir": "hud_recap",
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"class_name": "HudRecapETL",
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},
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]
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if dataset_to_run:
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dataset_element = next(
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(item for item in dataset_list if item["name"] == dataset_to_run),
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None,
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)
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if not dataset_list:
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raise ValueError("Invalid dataset name")
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else:
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# reset the list to just the dataset
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dataset_list = [dataset_element]
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# Run the ETLs for the dataset_list
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for dataset in dataset_list:
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etl_module = importlib.import_module(
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f"etl.sources.{dataset['module_dir']}.etl"
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)
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etl_class = getattr(etl_module, dataset["class_name"])
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etl_instance = etl_class()
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# run extract
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etl_instance.extract()
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# run transform
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etl_instance.transform()
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# run load
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etl_instance.load()
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# cleanup
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etl_instance.cleanup()
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# update the front end JSON/CSV of list of data sources
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pass
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def score_generate() -> None:
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"""Generates the score and saves it on the local data directory
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Args:
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None
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Returns:
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None
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"""
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# Score Gen
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score_gen = ScoreETL()
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score_gen.extract()
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score_gen.transform()
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score_gen.load()
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# Post Score Processing
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score_post = PostScoreETL()
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score_post.extract()
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score_post.transform()
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score_post.load()
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score_post.cleanup()
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def score_geo() -> None:
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"""Generates the geojson files with score data baked in
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Args:
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None
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Returns:
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None
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"""
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# Score Geo
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score_geo = GeoScoreETL()
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score_geo.extract()
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score_geo.transform()
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score_geo.load()
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def _find_dataset_index(dataset_list, key, value):
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for i, element in enumerate(dataset_list):
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if element[key] == value:
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return i
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return -1
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