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https://github.com/DOI-DO/j40-cejst-2.git
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43e005cc10
* Adds a substantially refactored ETL test to the National Risk Index, to be used as a model for other tests
134 lines
3.5 KiB
Python
134 lines
3.5 KiB
Python
import importlib
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from data_pipeline.etl.score.etl_score import ScoreETL
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from data_pipeline.etl.score.etl_score_geo import GeoScoreETL
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from data_pipeline.etl.score.etl_score_post import PostScoreETL
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from . import constants
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def get_datasets_to_run(dataset_to_run: str):
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"""Returns a list of appropriate datasets to run given input args
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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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dataset_list = constants.DATASET_LIST
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etls_to_search = dataset_list + [constants.CENSUS_INFO]
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if dataset_to_run:
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dataset_element = next(
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(item for item in etls_to_search if item["name"] == dataset_to_run),
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None,
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)
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if not dataset_element:
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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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return dataset_list
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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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dataset_list = get_datasets_to_run(dataset_to_run)
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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"data_pipeline.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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# run validate
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etl_instance.validate()
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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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def score_post(data_source: str = "local") -> None:
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"""Posts the score files to the local directory
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Args:
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data_source (str): Source for the census data (optional)
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Options:
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- local (default): fetch census data from the local data directory
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- aws: fetch census from AWS S3 J40 data repository
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Returns:
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None
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"""
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# Post Score Processing
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score_post = PostScoreETL(data_source=data_source)
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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(data_source: str = "local") -> None:
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"""Generates the geojson files with score data baked in
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Args:
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data_source (str): Source for the census data (optional)
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Options:
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- local (default): fetch census data from the local data directory
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- aws: fetch census from AWS S3 J40 data repository
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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(data_source=data_source)
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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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