j40-cejst-2/data/data-pipeline/data_pipeline/etl/sources/ejscreen/etl.py
Travis Newby 03a6d3c660
User Story 2152 – Clean up logging (#2155)
Update logging messages and message consistency

This update includes changes to the level of many log messages. Rather than everything being logged at the info level, it differentiates between debug, info, warning, and error messages. It also changes the default log level to info to avoid much of the noise previously in the logs.

It also removes many extra log messages, and adds additional decorators at the beginning of each pipeline run.
2023-02-08 13:08:55 -06:00

83 lines
3.1 KiB
Python

import pandas as pd
from data_pipeline.etl.base import ExtractTransformLoad
from data_pipeline.etl.base import ValidGeoLevel
from data_pipeline.score import field_names
from data_pipeline.utils import get_module_logger
logger = get_module_logger(__name__)
class EJSCREENETL(ExtractTransformLoad):
"""Load updated EJSCREEN data."""
NAME = "ejscreen"
GEO_LEVEL: ValidGeoLevel = ValidGeoLevel.CENSUS_TRACT
INPUT_GEOID_TRACT_FIELD_NAME: str = "ID"
def __init__(self):
self.EJSCREEN_FTP_URL = "https://gaftp.epa.gov/EJSCREEN/2021/EJSCREEN_2021_USPR_Tracts.csv.zip"
self.EJSCREEN_CSV = (
self.get_tmp_path() / "EJSCREEN_2021_USPR_Tracts.csv"
)
self.CSV_PATH = self.DATA_PATH / "dataset" / "ejscreen"
self.df: pd.DataFrame
self.COLUMNS_TO_KEEP = [
self.GEOID_TRACT_FIELD_NAME,
# pylint: disable=duplicate-code
field_names.AIR_TOXICS_CANCER_RISK_FIELD,
field_names.RESPIRATORY_HAZARD_FIELD,
field_names.DIESEL_FIELD,
field_names.PM25_FIELD,
field_names.OZONE_FIELD,
field_names.TRAFFIC_FIELD,
field_names.RMP_FIELD,
field_names.TSDF_FIELD,
field_names.NPL_FIELD,
field_names.WASTEWATER_FIELD,
field_names.HOUSEHOLDS_LINGUISTIC_ISO_FIELD,
field_names.POVERTY_FIELD,
field_names.OVER_64_FIELD,
field_names.UNDER_5_FIELD,
field_names.LEAD_PAINT_FIELD,
field_names.UST_FIELD,
]
def extract(self) -> None:
super().extract(
self.EJSCREEN_FTP_URL,
self.get_tmp_path(),
verify=False, # EPA EJScreen end point has certificate issues often
)
def transform(self) -> None:
self.df = pd.read_csv(
self.EJSCREEN_CSV,
dtype={self.INPUT_GEOID_TRACT_FIELD_NAME: str},
# EJSCREEN writes the word "None" for NA data.
na_values=["None"],
low_memory=False,
)
# rename ID to Tract ID
self.output_df = self.df.rename(
columns={
self.INPUT_GEOID_TRACT_FIELD_NAME: self.GEOID_TRACT_FIELD_NAME,
"CANCER": field_names.AIR_TOXICS_CANCER_RISK_FIELD,
"RESP": field_names.RESPIRATORY_HAZARD_FIELD,
"DSLPM": field_names.DIESEL_FIELD,
"PM25": field_names.PM25_FIELD,
"OZONE": field_names.OZONE_FIELD,
"PTRAF": field_names.TRAFFIC_FIELD,
"PRMP": field_names.RMP_FIELD,
"PTSDF": field_names.TSDF_FIELD,
"PNPL": field_names.NPL_FIELD,
"PWDIS": field_names.WASTEWATER_FIELD,
"LINGISOPCT": field_names.HOUSEHOLDS_LINGUISTIC_ISO_FIELD,
"LOWINCPCT": field_names.POVERTY_FIELD,
"OVER64PCT": field_names.OVER_64_FIELD,
"UNDER5PCT": field_names.UNDER_5_FIELD,
"PRE1960PCT": field_names.LEAD_PAINT_FIELD,
"UST": field_names.UST_FIELD, # added for 2021 update
},
)