mirror of
https://github.com/DOI-DO/j40-cejst-2.git
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6f39033dde
* Add a rough prototype allowing a developer to pre-download data sources for all ETLs * Update code to be more production-ish * Move fetch to Extract part of ETL * Create a downloader to house all downloading operations * Remove unnecessary "name" in data source * Format source files with black * Fix issues from pylint and get the tests working with the new folder structure * Clean up files with black * Fix unzip test * Add caching notes to README * Fix tests (linting and case sensitivity bug) * Address PR comments and add API keys for census where missing * Merging comparator changes from main into this branch for the sake of the PR * Add note on using cache (-u) during pipeline
107 lines
2.8 KiB
Python
107 lines
2.8 KiB
Python
from pathlib import Path
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import pandas as pd
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import geopandas as gpd
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from data_pipeline.config import settings
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from data_pipeline.etl.base import ValidGeoLevel
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from data_pipeline.utils import get_module_logger
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from data_pipeline.etl.datasource import DataSource
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from data_pipeline.etl.datasource import ZIPDataSource
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from data_pipeline.etl.base import ExtractTransformLoad
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from data_pipeline.etl.sources.geo_utils import add_tracts_for_geometries
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logger = get_module_logger(__name__)
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class AbandonedMineETL(ExtractTransformLoad):
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"""Data from Office Of Surface Mining Reclamation and Enforcement's
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eAMLIS. These are the locations of abandoned mines.
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"""
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# Metadata for the baseclass
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NAME = "eamlis"
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GEO_LEVEL = ValidGeoLevel.CENSUS_TRACT
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AML_BOOLEAN: str
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LOAD_YAML_CONFIG: bool = True
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PUERTO_RICO_EXPECTED_IN_DATA = False
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EXPECTED_MISSING_STATES = [
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"10",
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"11",
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"12",
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"15",
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"23",
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"27",
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"31",
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"33",
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"34",
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"36",
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"45",
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"50",
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"55",
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]
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def __init__(self):
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# fetch
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self.eamlis_url = (
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settings.AWS_JUSTICE40_DATASOURCES_URL
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+ "/eAMLIS export of all data.tsv.zip"
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)
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# input
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self.eamlis_source = (
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self.get_sources_path() / "eAMLIS export of all data.tsv"
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)
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# output
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self.TRACT_INPUT_COLUMN_NAME = self.INPUT_GEOID_TRACT_FIELD_NAME
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self.OUTPUT_PATH: Path = (
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self.DATA_PATH / "dataset" / "abandoned_mine_land_inventory_system"
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)
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self.COLUMNS_TO_KEEP = [
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self.GEOID_TRACT_FIELD_NAME,
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self.AML_BOOLEAN,
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]
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self.output_df: pd.DataFrame
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self.df: pd.DataFrame
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def get_data_sources(self) -> [DataSource]:
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return [
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ZIPDataSource(
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source=self.eamlis_url, destination=self.get_sources_path()
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)
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]
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def extract(self, use_cached_data_sources: bool = False) -> None:
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super().extract(
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use_cached_data_sources
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) # download and extract data sources
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self.df = pd.read_csv(
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self.eamlis_source,
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sep="\t",
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low_memory=False,
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)
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def transform(self) -> None:
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gdf = gpd.GeoDataFrame(
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self.df,
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geometry=gpd.points_from_xy(
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x=self.df["Longitude"],
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y=self.df["Latitude"],
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),
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crs="epsg:4326",
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)
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gdf = gdf.drop_duplicates(subset=["geometry"], keep="last")
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gdf_tracts = add_tracts_for_geometries(gdf)
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gdf_tracts = gdf_tracts.drop_duplicates(self.GEOID_TRACT_FIELD_NAME)
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gdf_tracts[self.AML_BOOLEAN] = True
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self.output_df = gdf_tracts[self.COLUMNS_TO_KEEP]
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