Data directory should adopt standard Poetry-suggested python package structure (#457)

* Fixes #456 - Our data directory should adopt standard python package structure * a few missed references * updating readme * updating requirements * Running Black * Fixes for flake8 * updating pylint
2025-02-22 01:31:25 -08:00 · 2021-08-05 15:35:54 -04:00 · 2021-08-05 15:35:54 -04:00 · c1568e87c0
commit c1568e87c0
parent 4d7465c833
61 changed files with 1273 additions and 1256 deletions
--- a/.gitignore
+++ b/.gitignore
@ -133,12 +133,12 @@ cython_debug/
 */data-pipeline/.secrets.*

 # ignore data
-*/data-pipeline/data
-*/data-pipeline/data/census
-*/data-pipeline/data/tiles
-*/data-pipeline/data/tmp
-*/data-pipeline/data/dataset
-*/data-pipeline/data/score
+*/data-pipeline/data_pipeline/data
+*/data-pipeline/data_pipeline/data/census
+*/data-pipeline/data_pipeline/data/tiles
+*/data-pipeline/data_pipeline/data/tmp
+*/data-pipeline/data_pipeline/data/dataset
+*/data-pipeline/data_pipeline/data/score

 # node
 node_modules
--- a/data/data-pipeline/README.md
+++ b/data/data-pipeline/README.md
@ -5,23 +5,26 @@

 <!-- TOC -->

- [About this application](#about-this-application)
-  - [Score comparison workflow](#score-comparison-workflow)
-    - [Workflow Diagram](#workflow-diagram)
-    - [Step 0: Set up your environment](#step-0-set-up-your-environment)
-    - [Step 1: Run the ETL script for each data source](#step-1-run-the-etl-script-for-each-data-source)
-    - [Step 2: Calculate the Justice40 score experiments](#step-2-calculate-the-justice40-score-experiments)
-    - [Step 3: Compare the Justice40 score experiments to other indices](#step-3-compare-the-justice40-score-experiments-to-other-indices)
-  - [Data Sources](#data-sources)
- [Running using Docker](#running-using-docker)
- [Log visualization](#log-visualization)
- [Local development](#local-development)
-  - [Downloading Census Block Groups GeoJSON and Generating CBG CSVs](#downloading-census-block-groups-geojson-and-generating-cbg-csvs)
-  - [Generating mbtiles](#generating-mbtiles)
-  - [Serve the map locally](#serve-the-map-locally)
-  - [Running Jupyter notebooks](#running-jupyter-notebooks)
-  - [Activating variable-enabled Markdown for Jupyter notebooks](#activating-variable-enabled-markdown-for-jupyter-notebooks)
- [Miscellaneous](#miscellaneous)
+- [Justice 40 Score application](#justice-40-score-application)
+  - [About this application](#about-this-application)
+    - [Score generation and comparison workflow](#score-generation-and-comparison-workflow)
+      - [Workflow Diagram](#workflow-diagram)
+      - [Step 0: Set up your environment](#step-0-set-up-your-environment)
+      - [(Optional) Step 0: Run the script to download census data](#optional-step-0-run-the-script-to-download-census-data)
+      - [Step 1: Run the ETL script for each data source](#step-1-run-the-etl-script-for-each-data-source)
+      - [Step 2: Calculate the Justice40 score experiments](#step-2-calculate-the-justice40-score-experiments)
+      - [Step 3: Compare the Justice40 score experiments to other indices](#step-3-compare-the-justice40-score-experiments-to-other-indices)
+    - [Data Sources](#data-sources)
+  - [Running using Docker](#running-using-docker)
+  - [Local development](#local-development)
+    - [Windows Users](#windows-users)
+    - [Setting up Poetry](#setting-up-poetry)
+    - [Downloading Census Block Groups GeoJSON and Generating CBG CSVs](#downloading-census-block-groups-geojson-and-generating-cbg-csvs)
+    - [Generating Map Tiles](#generating-map-tiles)
+    - [Serve the map locally](#serve-the-map-locally)
+    - [Running Jupyter notebooks](#running-jupyter-notebooks)
+    - [Activating variable-enabled Markdown for Jupyter notebooks](#activating-variable-enabled-markdown-for-jupyter-notebooks)
+  - [Miscellaneous](#miscellaneous)

 <!-- /TOC -->

@ -33,7 +36,6 @@ This application is used to compare experimental versions of the Justice40 score

 _**NOTE:** These scores **do not** represent final versions of the Justice40 scores and are merely used for comparative purposes. As a result, the specific input columns and formulas used to calculate them are likely to change over time._

-
 ### Score generation and comparison workflow

 The descriptions below provide a more detailed outline of what happens at each step of ETL and score calculation workflow.
@ -46,45 +48,49 @@ TODO add mermaid diagram

 1. After cloning the project locally, change to this directory: `cd data/data-pipeline`
 1. Choose whether you'd like to run this application using Docker or if you'd like to install the dependencies locally so you can contribute to the project.
-    - **With Docker:** Follow these [installation instructions](https://docs.docker.com/get-docker/) and skip down to the [Running with Docker section](#running-with-docker) for more information
-    - **For Local Development:** Skip down to the [Local Development section](#local-development) for more detailed installation instructions
+   - **With Docker:** Follow these [installation instructions](https://docs.docker.com/get-docker/) and skip down to the [Running with Docker section](#running-with-docker) for more information
+   - **For Local Development:** Skip down to the [Local Development section](#local-development) for more detailed installation instructions

+#### (Optional) Step 0: Run the script to download census data
+
+1. See instructions below for downloading census data, which is a prerequisite for running score code

 #### Step 1: Run the ETL script for each data source

 1. Call the `etl-run` command using the application manager `application.py` **NOTE:** This may take several minutes to execute.
   - With Docker: `docker run --rm -it j40_data_pipeline /bin/sh -c "python3 application.py etl-run"`
-   - With Poetry: `poetry run python application.py etl-run`
-1. The `etl-run` command will execute the corresponding ETL script for each data source in `etl/sources/`. For example, `etl/sources/ejscreen/etl.py` is the ETL script for EJSCREEN data.
-1. Each ETL script will extract the data from its original source, then format the data into `.csv` files that get stored in the relevant folder in `data/dataset/`. For example, HUD Housing data is stored in `data/dataset/hud_housing/usa.csv`
+   - With Poetry: `poetry run etl`
+2. This command will execute the corresponding ETL script for each data source in `data_pipeline/etl/sources/`. For example, `data_pipeline/etl/sources/ejscreen/etl.py` is the ETL script for EJSCREEN data.
+3. Each ETL script will extract the data from its original source, then format the data into `.csv` files that get stored in the relevant folder in `data_pipeline/data/dataset/`. For example, HUD Housing data is stored in `data_pipeline/data/dataset/hud_housing/usa.csv`

 _**NOTE:** You have the option to pass the name of a specific data source to the `etl-run` command using the `-d` flag, which will limit the execution of the ETL process to that specific data source._
-_For example: `poetry run python application.py etl-run -d ejscreen` would only run the ETL process for EJSCREEN data._
+_For example: `poetry run etl -- -d ejscreen` would only run the ETL process for EJSCREEN data._

 #### Step 2: Calculate the Justice40 score experiments

 1. Call the `score-run` command using the application manager `application.py` **NOTE:** This may take several minutes to execute.
   - With Docker: `docker run --rm -it j40_data_pipeline /bin/sh -c "python3 application.py score-run"`
-   - With Poetry: `poetry run python application.py score-run`
+   - With Poetry: `poetry run score`
 1. The `score-run` command will execute the `etl/score/etl.py` script which loads the data from each of the source files added to the `data/dataset/` directory by the ETL scripts in Step 1.
 1. These data sets are merged into a single dataframe using their Census Block Group GEOID as a common key, and the data in each of the columns is standardized in two ways:
-    - Their [percentile rank](https://en.wikipedia.org/wiki/Percentile_rank) is calculated, which tells us what percentage of other Census Block Groups have a lower value for that particular column.
-    - They are normalized using [min-max normalization](https://en.wikipedia.org/wiki/Feature_scaling), which adjusts the scale of the data so that the Census Block Group with the highest value for that column is set to 1, the Census Block Group with the lowest value is set to 0, and all of the other values are adjusted to fit within that range based on how close they were to the highest or lowest value.
+   - Their [percentile rank](https://en.wikipedia.org/wiki/Percentile_rank) is calculated, which tells us what percentage of other Census Block Groups have a lower value for that particular column.
+   - They are normalized using [min-max normalization](https://en.wikipedia.org/wiki/Feature_scaling), which adjusts the scale of the data so that the Census Block Group with the highest value for that column is set to 1, the Census Block Group with the lowest value is set to 0, and all of the other values are adjusted to fit within that range based on how close they were to the highest or lowest value.
 1. The standardized columns are then used to calculate each of the Justice40 score experiments described in greater detail below, and the results are exported to a `.csv` file in [`data/score/csv`](data/score/csv)

 #### Step 3: Compare the Justice40 score experiments to other indices

 We are building a comparison tool to enable easy (or at least straightforward) comparison of the Justice40 score with other existing indices. The goal of having this is so that as we experiment and iterate with a scoring methodology, we can understand how our score overlaps with or differs from other indices that communities, nonprofits, and governmentss use to inform decision making.

-Right now, our comparison tool exists simply as a python notebook in `data/data-pipeline/ipython/scoring_comparison.ipynb`.
+Right now, our comparison tool exists simply as a python notebook in `data/data-pipeline/data_pipeline/ipython/scoring_comparison.ipynb`.

 To run this comparison tool:

 1. Make sure you've gone through the above steps to run the data ETL and score generation.
-1. From this directory (`data/data-pipeline`), navigate to the `ipython` directory: `cd ipython`.
+1. From the package directory (`data/data-pipeline/data_pipeline/`), navigate to the `ipython` directory: `cd ipython`.
 1. Ensure you have `pandoc` installed on your computer. If you're on a Mac, run `brew install pandoc`; for other OSes, see pandoc's [installation guide](https://pandoc.org/installing.html).
 1. Install the extra dependencies:
-```
+
+```python
  pip install pypandoc
  pip install requests
  pip install us
@ -92,13 +98,14 @@ To run this comparison tool:
  pip install dynaconf
  pip instal xlsxwriter
 ```
+
 1. Start the notebooks: `jupyter notebook`
 1. In your browser, navigate to one of the URLs returned by the above command.
 1. Select `scoring_comparison.ipynb` from the options in your browser.
 1. Run through the steps in the notebook. You can step through them one at a time by clicking the "Run" button for each cell, or open the "Cell" menu and click "Run all" to run them all at once.
-1. Reports and spreadsheets generated by the comparison tool will be available in `data/data-pipeline/data/comparison_outputs`.
+1. Reports and spreadsheets generated by the comparison tool will be available in `data/data-pipeline/data_pipeline/data/comparison_outputs`.

-*NOTE:* This may take several minutes or over an hour to fully execute and generate the reports.
+_NOTE:_ This may take several minutes or over an hour to fully execute and generate the reports.

 ### Data Sources

@ -110,7 +117,6 @@ To run this comparison tool:
 - **[HUD Recap](etl/sources/hud_recap):** TODO Add description of data source
 - **[CalEnviroScreen](etl/scores/calenviroscreen):** TODO Add description of data source

-
 ## Running using Docker

 We use Docker to install the necessary libraries in a container that can be run in any operating system.
@ -136,13 +142,14 @@ Here's a list of commands:
 You can run the Python code locally without Docker to develop, using Poetry. However, to generate the census data you will need the [GDAL library](https://github.com/OSGeo/gdal) installed locally. Also to generate tiles for a local map, you will need [Mapbox tippeanoe](https://github.com/mapbox/tippecanoe). Please refer to the repos for specific instructions for your OS.

 ### Windows Users
+
 - If you want to download Census data or run tile generation, please install TippeCanoe [following these instrcutions](https://github.com/GISupportICRC/ArcGIS2Mapbox#installing-tippecanoe-on-windows).
 - If you want to generate tiles, you need some pre-requisites for Geopandas as specified in the Poetry requirements. Please follow [these instructions](https://stackoverflow.com/questions/56958421/pip-install-geopandas-on-windows) to install the Geopandas dependency locally.

 ### Setting up Poetry

 - Start a terminal
- Change to this directory (`/data/data-pipeline`)
+- Change to this directory (`/data/data-pipeline/`)
 - Make sure you have Python 3.9 installed: `python -V` or `python3 -V`
 - We use [Poetry](https://python-poetry.org/) for managing dependencies and building the application. Please follow the instructions on their site to download.
 - Install Poetry requirements with `poetry install`
@ -151,33 +158,33 @@ You can run the Python code locally without Docker to develop, using Poetry. How

 - Make sure you have Docker running in your machine
 - Start a terminal
- Change to this directory (i.e. `cd data/data-pipeline`)
- If you want to clear out all data and tiles from all directories, you can run: `poetry run python application.py data-cleanup`.
- Then run `poetry run python application.py census-data-download`
+- Change to the package directory (i.e. `cd data/data-pipeline/data_pipeline/`)
+- If you want to clear out all data and tiles from all directories, you can run: `poetry run cleanup_data`.
+- Then run `poetry run download_census`
  Note: Census files are not kept in the repository and the download directories are ignored by Git

 ### Generating Map Tiles

 - Make sure you have Docker running in your machine
 - Start a terminal
- Change to this directory (i.e. `cd data/data-pipeline`)
- Then run `poetry run python application.py generate-map-tiles`
+- Change to the package directory (i.e. `cd data/data-pipeline/data_pipeline`)
+- Then run `poetry run generate_tiles`

 ### Serve the map locally

 - Start a terminal
- Change to this directory (i.e. `cd data/data-pipeline`)
+- Change to the package directory (i.e. `cd data/data-pipeline/data_pipeline`)
 - For USA high zoom: `docker run --rm -it -v ${PWD}/data/score/tiles/high:/data -p 8080:80 maptiler/tileserver-gl`

 ### Running Jupyter notebooks

 - Start a terminal
- Change to this directory (i.e. `cd data/data-pipeline`)
+- Change to the package directory (i.e. `cd data/data-pipeline/data_pipeline`)
 - Run `poetry run jupyter notebook`. Your browser should open with a Jupyter Notebook tab

 ### Activating variable-enabled Markdown for Jupyter notebooks

- Change to this directory (i.e. `cd data/data-pipeline`)
+- Change to the package directory (i.e. `cd data/data-pipeline/data_pipeline`)
 - Activate a Poetry Shell (see above)
 - Run `jupyter contrib nbextension install --user`
 - Run `jupyter nbextension enable python-markdown/main`
--- a/data/data-pipeline/data_pipeline/init.py
+++ b/data/data-pipeline/data_pipeline/init.py
--- a/data/data-pipeline/data_pipeline/application.py
+++ b/data/data-pipeline/data_pipeline/application.py
@ -1,16 +1,16 @@
 import click

-from config import settings
-from utils import (
-    get_module_logger,
+from .config import settings
+from .etl.runner import etl_runner, score_generate, score_geo
+from .etl.sources.census.etl import download_census_csvs
+from .etl.sources.census.etl_utils import reset_data_directories as census_reset
+from .tile.generate import generate_tiles
+from .utils import (
    data_folder_cleanup,
+    get_module_logger,
    score_folder_cleanup,
    temp_folder_cleanup,
 )
-from etl.sources.census.etl import download_census_csvs
-from etl.sources.census.etl_utils import reset_data_directories as census_reset
-from etl.runner import etl_runner, score_generate, score_geo
-from tile.generate import generate_tiles

 logger = get_module_logger(__name__)

@ -22,9 +22,20 @@ def cli():
    pass


-@cli.command(
-    help="Clean up all data folders",
-)
+@cli.command(help="Clean up all census data folders")
+def census_cleanup():
+    """CLI command to clean up the census data folder"""
+
+    data_path = settings.APP_ROOT / "data"
+
+    # census directories
+    logger.info("Initializing all census data")
+    census_reset(data_path)
+
+    logger.info("Cleaned up all census data files")
+
+
+@cli.command(help="Clean up all data folders")
 def data_cleanup():
    """CLI command to clean up the all the data folders"""

@ -92,9 +103,7 @@ def score_full_run():
    score_generate()


-@cli.command(
-    help="Generate Geojson files with scores baked in",
-)
+@cli.command(help="Generate Geojson files with scores baked in")
 def geo_score():
    """CLI command to generate the score"""

--- a/data/data-pipeline/data_pipeline/config.py
+++ b/data/data-pipeline/data_pipeline/config.py
@ -1,7 +1,9 @@
-from pathlib import Path
+import pathlib

 from dynaconf import Dynaconf

+import data_pipeline
+
 settings = Dynaconf(
    envvar_prefix="DYNACONF",
    settings_files=["settings.toml", ".secrets.toml"],
@ -9,7 +11,7 @@ settings = Dynaconf(
 )

 # set root dir
-settings.APP_ROOT = Path.cwd()
+settings.APP_ROOT = pathlib.Path(data_pipeline.__file__).resolve().parent

 # To set an environment use:
 # Linux/OSX: export ENV_FOR_DYNACONF=staging
--- a/data/data-pipeline/data_pipeline/data/census/init.py
+++ b/data/data-pipeline/data_pipeline/data/census/init.py
--- a/data/data-pipeline/data_pipeline/data/census/csv/init.py
+++ b/data/data-pipeline/data_pipeline/data/census/csv/init.py
--- a/data/data-pipeline/data_pipeline/data/census/geojson/init.py
+++ b/data/data-pipeline/data_pipeline/data/census/geojson/init.py
--- a/data/data-pipeline/data_pipeline/data/census/shp/init.py
+++ b/data/data-pipeline/data_pipeline/data/census/shp/init.py
--- a/data/data-pipeline/data_pipeline/data/dataset/init.py
+++ b/data/data-pipeline/data_pipeline/data/dataset/init.py
--- a/data/data-pipeline/data_pipeline/data/score/csv/init.py
+++ b/data/data-pipeline/data_pipeline/data/score/csv/init.py
--- a/data/data-pipeline/data_pipeline/data/score/geojson/init.py
+++ b/data/data-pipeline/data_pipeline/data/score/geojson/init.py
--- a/data/data-pipeline/data_pipeline/data/tiles/init.py
+++ b/data/data-pipeline/data_pipeline/data/tiles/init.py
--- a/data/data-pipeline/data_pipeline/data/tmp/init.py
+++ b/data/data-pipeline/data_pipeline/data/tmp/init.py
--- a/data/data-pipeline/data_pipeline/etl/init.py
+++ b/data/data-pipeline/data_pipeline/etl/init.py
--- a/data/data-pipeline/data_pipeline/etl/base.py
+++ b/data/data-pipeline/data_pipeline/etl/base.py
@ -1,7 +1,7 @@
 from pathlib import Path

-from config import settings
-from utils import unzip_file_from_url, remove_all_from_dir
+from data_pipeline.config import settings
+from data_pipeline.utils import unzip_file_from_url, remove_all_from_dir


 class ExtractTransformLoad:
--- a/data/data-pipeline/data_pipeline/etl/runner.py
+++ b/data/data-pipeline/data_pipeline/etl/runner.py
@ -1,8 +1,8 @@
 import importlib

-from etl.score.etl_score import ScoreETL
-from etl.score.etl_score_post import PostScoreETL
-from etl.score.etl_score_geo import GeoScoreETL
+from data_pipeline.etl.score.etl_score import ScoreETL
+from data_pipeline.etl.score.etl_score_geo import GeoScoreETL
+from data_pipeline.etl.score.etl_score_post import PostScoreETL


 def etl_runner(dataset_to_run: str = None) -> None:
@ -67,7 +67,9 @@ def etl_runner(dataset_to_run: str = None) -> None:

    # Run the ETLs for the dataset_list
    for dataset in dataset_list:
-        etl_module = importlib.import_module(f"etl.sources.{dataset['module_dir']}.etl")
+        etl_module = importlib.import_module(
+            f"data_pipeline.etl.sources.{dataset['module_dir']}.etl"
+        )
        etl_class = getattr(etl_module, dataset["class_name"])
        etl_instance = etl_class()

--- a/data/data-pipeline/data_pipeline/etl/score/init.py
+++ b/data/data-pipeline/data_pipeline/etl/score/init.py
--- a/data/data-pipeline/data_pipeline/etl/score/etl_score.py
+++ b/data/data-pipeline/data_pipeline/etl/score/etl_score.py
@ -1,9 +1,9 @@
 import collections
 import functools
-import pandas as pd

-from etl.base import ExtractTransformLoad
-from utils import get_module_logger
+import pandas as pd
+from data_pipeline.etl.base import ExtractTransformLoad
+from data_pipeline.utils import get_module_logger

 logger = get_module_logger(__name__)

@ -59,9 +59,7 @@ class ScoreETL(ExtractTransformLoad):
        # Load census data
        census_csv = self.DATA_PATH / "dataset" / "census_acs_2019" / "usa.csv"
        self.census_df = pd.read_csv(
-            census_csv,
-            dtype={self.GEOID_FIELD_NAME: "string"},
-            low_memory=False,
+            census_csv, dtype={self.GEOID_FIELD_NAME: "string"}, low_memory=False,
        )

        # Load housing and transportation data
@ -123,8 +121,7 @@ class ScoreETL(ExtractTransformLoad):

        # Define a named tuple that will be used for each data set input.
        DataSet = collections.namedtuple(
-            typename="DataSet",
-            field_names=["input_field", "renamed_field", "bucket"],
+            typename="DataSet", field_names=["input_field", "renamed_field", "bucket"],
        )

        data_sets = [
@ -141,9 +138,7 @@ class ScoreETL(ExtractTransformLoad):
                bucket=None,
            ),
            DataSet(
-                input_field="ACSTOTPOP",
-                renamed_field="Total population",
-                bucket=None,
+                input_field="ACSTOTPOP", renamed_field="Total population", bucket=None,
            ),
            # The following data sets have buckets, because they're used in the score
            DataSet(
@ -249,9 +244,7 @@ class ScoreETL(ExtractTransformLoad):
        }

        self.df.rename(
-            columns=renaming_dict,
-            inplace=True,
-            errors="raise",
+            columns=renaming_dict, inplace=True, errors="raise",
        )

        columns_to_keep = [data_set.renamed_field for data_set in data_sets]
--- a/data/data-pipeline/data_pipeline/etl/score/etl_score_geo.py
+++ b/data/data-pipeline/data_pipeline/etl/score/etl_score_geo.py
@ -3,8 +3,8 @@ import math
 import pandas as pd
 import geopandas as gpd

-from etl.base import ExtractTransformLoad
-from utils import get_module_logger
+from data_pipeline.etl.base import ExtractTransformLoad
+from data_pipeline.utils import get_module_logger

 logger = get_module_logger(__name__)

@ -46,9 +46,7 @@ class GeoScoreETL(ExtractTransformLoad):

        logger.info("Reading score CSV")
        self.score_usa_df = pd.read_csv(
-            self.TILE_SCORE_CSV,
-            dtype={"GEOID10": "string"},
-            low_memory=False,
+            self.TILE_SCORE_CSV, dtype={"GEOID10": "string"}, low_memory=False,
        )

    def transform(self) -> None:
@ -70,8 +68,7 @@ class GeoScoreETL(ExtractTransformLoad):
        ].reset_index(drop=True)

        usa_simplified.rename(
-            columns={self.TARGET_SCORE_NAME: self.TARGET_SCORE_RENAME_TO},
-            inplace=True,
+            columns={self.TARGET_SCORE_NAME: self.TARGET_SCORE_RENAME_TO}, inplace=True,
        )

        logger.info("Aggregating into tracts (~5 minutes)")
--- a/data/data-pipeline/data_pipeline/etl/score/etl_score_post.py
+++ b/data/data-pipeline/data_pipeline/etl/score/etl_score_post.py
@ -1,7 +1,7 @@
 import pandas as pd

-from etl.base import ExtractTransformLoad
-from utils import get_module_logger
+from data_pipeline.etl.base import ExtractTransformLoad
+from data_pipeline.utils import get_module_logger

 logger = get_module_logger(__name__)

@ -43,8 +43,7 @@ class PostScoreETL(ExtractTransformLoad):

    def extract(self) -> None:
        super().extract(
-            self.CENSUS_COUNTIES_ZIP_URL,
-            self.TMP_PATH,
+            self.CENSUS_COUNTIES_ZIP_URL, self.TMP_PATH,
        )

        logger.info("Reading Counties CSV")
@ -68,8 +67,7 @@ class PostScoreETL(ExtractTransformLoad):
        # rename some of the columns to prepare for merge
        self.counties_df = self.counties_df[["USPS", "GEOID", "NAME"]]
        self.counties_df.rename(
-            columns={"USPS": "State Abbreviation", "NAME": "County Name"},
-            inplace=True,
+            columns={"USPS": "State Abbreviation", "NAME": "County Name"}, inplace=True,
        )

        # remove unnecessary columns
--- a/data/data-pipeline/data_pipeline/etl/sources/init.py
+++ b/data/data-pipeline/data_pipeline/etl/sources/init.py
--- a/data/data-pipeline/data_pipeline/etl/sources/calenviroscreen/README.md
+++ b/data/data-pipeline/data_pipeline/etl/sources/calenviroscreen/README.md
--- a/data/data-pipeline/data_pipeline/etl/sources/calenviroscreen/init.py
+++ b/data/data-pipeline/data_pipeline/etl/sources/calenviroscreen/init.py
--- a/data/data-pipeline/data_pipeline/etl/sources/calenviroscreen/etl.py
+++ b/data/data-pipeline/data_pipeline/etl/sources/calenviroscreen/etl.py
@ -1,8 +1,8 @@
 import pandas as pd

-from etl.base import ExtractTransformLoad
-from utils import get_module_logger
-from config import settings
+from data_pipeline.etl.base import ExtractTransformLoad
+from data_pipeline.utils import get_module_logger
+from data_pipeline.config import settings

 logger = get_module_logger(__name__)

--- a/data/data-pipeline/data_pipeline/etl/sources/census/README.md
+++ b/data/data-pipeline/data_pipeline/etl/sources/census/README.md
--- a/data/data-pipeline/data_pipeline/etl/sources/census/init.py
+++ b/data/data-pipeline/data_pipeline/etl/sources/census/init.py
--- a/data/data-pipeline/data_pipeline/etl/sources/census/etl.py
+++ b/data/data-pipeline/data_pipeline/etl/sources/census/etl.py
@ -1,11 +1,11 @@
-import os
 import csv
 import json
+import os
 from pathlib import Path

 import geopandas as gpd
+from data_pipeline.utils import get_module_logger, unzip_file_from_url

-from utils import unzip_file_from_url, get_module_logger
 from .etl_utils import get_state_fips_codes

 logger = get_module_logger(__name__)
--- a/data/data-pipeline/data_pipeline/etl/sources/census/etl_utils.py
+++ b/data/data-pipeline/data_pipeline/etl/sources/census/etl_utils.py
@ -1,15 +1,14 @@
-import os
 import csv
-
+import os
 from pathlib import Path
-import pandas as pd
-from config import settings

-from utils import (
-    remove_files_from_dir,
-    remove_all_dirs_from_dir,
-    unzip_file_from_url,
+import pandas as pd
+from data_pipeline.config import settings
+from data_pipeline.utils import (
    get_module_logger,
+    remove_all_dirs_from_dir,
+    remove_files_from_dir,
+    unzip_file_from_url,
 )

 logger = get_module_logger(__name__)
--- a/data/data-pipeline/data_pipeline/etl/sources/census_acs/README.md
+++ b/data/data-pipeline/data_pipeline/etl/sources/census_acs/README.md
--- a/data/data-pipeline/data_pipeline/etl/sources/census_acs/init.py
+++ b/data/data-pipeline/data_pipeline/etl/sources/census_acs/init.py
--- a/data/data-pipeline/data_pipeline/etl/sources/census_acs/etl.py
+++ b/data/data-pipeline/data_pipeline/etl/sources/census_acs/etl.py
@ -1,9 +1,9 @@
 import pandas as pd
 import censusdata

-from etl.base import ExtractTransformLoad
-from etl.sources.census.etl_utils import get_state_fips_codes
-from utils import get_module_logger
+from data_pipeline.etl.base import ExtractTransformLoad
+from data_pipeline.etl.sources.census.etl_utils import get_state_fips_codes
+from data_pipeline.utils import get_module_logger

 logger = get_module_logger(__name__)

--- a/data/data-pipeline/data_pipeline/etl/sources/ejscreen/README.md
+++ b/data/data-pipeline/data_pipeline/etl/sources/ejscreen/README.md
--- a/data/data-pipeline/data_pipeline/etl/sources/ejscreen/init.py
+++ b/data/data-pipeline/data_pipeline/etl/sources/ejscreen/init.py
--- a/data/data-pipeline/data_pipeline/etl/sources/ejscreen/etl.py
+++ b/data/data-pipeline/data_pipeline/etl/sources/ejscreen/etl.py
@ -1,7 +1,7 @@
 import pandas as pd

-from etl.base import ExtractTransformLoad
-from utils import get_module_logger
+from data_pipeline.etl.base import ExtractTransformLoad
+from data_pipeline.utils import get_module_logger

 logger = get_module_logger(__name__)

@ -18,8 +18,7 @@ class EJScreenETL(ExtractTransformLoad):
    def extract(self) -> None:
        logger.info("Downloading EJScreen Data")
        super().extract(
-            self.EJSCREEN_FTP_URL,
-            self.TMP_PATH,
+            self.EJSCREEN_FTP_URL, self.TMP_PATH,
        )

    def transform(self) -> None:
--- a/data/data-pipeline/data_pipeline/etl/sources/housing_and_transportation/README.md
+++ b/data/data-pipeline/data_pipeline/etl/sources/housing_and_transportation/README.md
--- a/data/data-pipeline/data_pipeline/etl/sources/housing_and_transportation/init.py
+++ b/data/data-pipeline/data_pipeline/etl/sources/housing_and_transportation/init.py
--- a/data/data-pipeline/data_pipeline/etl/sources/housing_and_transportation/etl.py
+++ b/data/data-pipeline/data_pipeline/etl/sources/housing_and_transportation/etl.py
@ -1,8 +1,8 @@
 import pandas as pd

-from etl.base import ExtractTransformLoad
-from etl.sources.census.etl_utils import get_state_fips_codes
-from utils import get_module_logger, unzip_file_from_url
+from data_pipeline.etl.base import ExtractTransformLoad
+from data_pipeline.etl.sources.census.etl_utils import get_state_fips_codes
+from data_pipeline.utils import get_module_logger, unzip_file_from_url

 logger = get_module_logger(__name__)

--- a/data/data-pipeline/data_pipeline/etl/sources/hud_housing/README.md
+++ b/data/data-pipeline/data_pipeline/etl/sources/hud_housing/README.md
--- a/data/data-pipeline/etl/sources/housing_and_transportation/init.py
+++ b/data/data-pipeline/etl/sources/housing_and_transportation/init.py
--- a/data/data-pipeline/data_pipeline/etl/sources/hud_housing/etl.py
+++ b/data/data-pipeline/data_pipeline/etl/sources/hud_housing/etl.py
@ -1,7 +1,6 @@
 import pandas as pd
-
-from etl.base import ExtractTransformLoad
-from utils import get_module_logger
+from data_pipeline.etl.base import ExtractTransformLoad
+from data_pipeline.utils import get_module_logger

 logger = get_module_logger(__name__)

@ -35,8 +34,7 @@ class HudHousingETL(ExtractTransformLoad):
    def extract(self) -> None:
        logger.info("Extracting HUD Housing Data")
        super().extract(
-            self.HOUSING_FTP_URL,
-            self.HOUSING_ZIP_FILE_DIR,
+            self.HOUSING_FTP_URL, self.HOUSING_ZIP_FILE_DIR,
        )

    def transform(self) -> None:
@ -50,10 +48,7 @@ class HudHousingETL(ExtractTransformLoad):
            / "140"
            / "Table8.csv"
        )
-        self.df = pd.read_csv(
-            filepath_or_buffer=tmp_csv_file_path,
-            encoding="latin-1",
-        )
+        self.df = pd.read_csv(filepath_or_buffer=tmp_csv_file_path, encoding="latin-1",)

        # Rename and reformat block group ID
        self.df.rename(columns={"geoid": self.GEOID_TRACT_FIELD_NAME}, inplace=True)
--- a/data/data-pipeline/data_pipeline/etl/sources/hud_recap/README.md
+++ b/data/data-pipeline/data_pipeline/etl/sources/hud_recap/README.md
--- a/data/data-pipeline/data_pipeline/etl/sources/hud_recap/init.py
+++ b/data/data-pipeline/data_pipeline/etl/sources/hud_recap/init.py
--- a/data/data-pipeline/data_pipeline/etl/sources/hud_recap/etl.py
+++ b/data/data-pipeline/data_pipeline/etl/sources/hud_recap/etl.py
@ -1,8 +1,8 @@
 import pandas as pd
 import requests

-from etl.base import ExtractTransformLoad
-from utils import get_module_logger
+from data_pipeline.etl.base import ExtractTransformLoad
+from data_pipeline.utils import get_module_logger

 logger = get_module_logger(__name__)

--- a/data/data-pipeline/data_pipeline/etl/sources/tree_equity_score/README.md
+++ b/data/data-pipeline/data_pipeline/etl/sources/tree_equity_score/README.md
--- a/data/data-pipeline/data_pipeline/etl/sources/tree_equity_score/init.py
+++ b/data/data-pipeline/data_pipeline/etl/sources/tree_equity_score/init.py
--- a/data/data-pipeline/data_pipeline/etl/sources/tree_equity_score/etl.py
+++ b/data/data-pipeline/data_pipeline/etl/sources/tree_equity_score/etl.py
@ -1,8 +1,7 @@
-import pandas as pd
 import geopandas as gpd
-
-from etl.base import ExtractTransformLoad
-from utils import get_module_logger
+import pandas as pd
+from data_pipeline.etl.base import ExtractTransformLoad
+from data_pipeline.utils import get_module_logger

 logger = get_module_logger(__name__)

@ -71,8 +70,7 @@ class TreeEquityScoreETL(ExtractTransformLoad):
        logger.info("Downloading Tree Equity Score Data")
        for state in self.states:
            super().extract(
-                f"{self.TES_URL}{state}.zip.zip",
-                f"{self.TMP_PATH}/{state}",
+                f"{self.TES_URL}{state}.zip.zip", f"{self.TMP_PATH}/{state}",
            )

    def transform(self) -> None:
--- a/data/data-pipeline/data_pipeline/ipython/ACS
+++ b/data/data-pipeline/data_pipeline/ipython/ACS
--- a/data/data-pipeline/data_pipeline/ipython/EJScreen
+++ b/data/data-pipeline/data_pipeline/ipython/EJScreen
--- a/data/data-pipeline/data_pipeline/ipython/Score
+++ b/data/data-pipeline/data_pipeline/ipython/Score
--- a/data/data-pipeline/data_pipeline/ipython/Score_Dissolve_Script.ipynb
+++ b/data/data-pipeline/data_pipeline/ipython/Score_Dissolve_Script.ipynb
--- a/data/data-pipeline/data_pipeline/ipython/county_lookup.ipynb
+++ b/data/data-pipeline/data_pipeline/ipython/county_lookup.ipynb
@ -3,38 +3,33 @@
  {
   "cell_type": "code",
   "execution_count": null,
-   "id": "7185e18d",
-   "metadata": {},
-   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import csv\n",
    "from pathlib import Path\n",
    "import os\n",
    "import sys"
-   ]
+   ],
+   "outputs": [],
+   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
-   "id": "174bbd09",
-   "metadata": {},
-   "outputs": [],
   "source": [
    "module_path = os.path.abspath(os.path.join(\"..\"))\n",
    "if module_path not in sys.path:\n",
    "    sys.path.append(module_path)\n",
    "    \n",
-    "from utils import unzip_file_from_url\n",
-    "from etl.sources.census.etl_utils import get_state_fips_codes"
-   ]
+    "from data_pipeline.utils import unzip_file_from_url\n",
+    "from data_pipeline.etl.sources.census.etl_utils import get_state_fips_codes"
+   ],
+   "outputs": [],
+   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
-   "id": "dd090fcc",
-   "metadata": {},
-   "outputs": [],
   "source": [
    "DATA_PATH = Path.cwd().parent / \"data\"\n",
    "TMP_PATH: Path = DATA_PATH / \"tmp\"\n",
@ -43,98 +38,92 @@
    "COUNTY_SCORE_CSV = DATA_PATH / \"score\" / \"csv\" / \"usa-county.csv\"\n",
    "CENSUS_COUNTIES_ZIP_URL = \"https://www2.census.gov/geo/docs/maps-data/data/gazetteer/2020_Gazetteer/2020_Gaz_counties_national.zip\"\n",
    "CENSUS_COUNTIES_TXT = TMP_PATH / \"2020_Gaz_counties_national.txt\""
-   ]
+   ],
+   "outputs": [],
+   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
-   "id": "cf2e266b",
-   "metadata": {
-    "scrolled": true
-   },
-   "outputs": [],
   "source": [
    "unzip_file_from_url(CENSUS_COUNTIES_ZIP_URL, TMP_PATH, TMP_PATH)"
-   ]
+   ],
+   "outputs": [],
+   "metadata": {
+    "scrolled": true
+   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
-   "id": "9ff96da8",
-   "metadata": {},
-   "outputs": [],
   "source": [
    "counties_df = pd.read_csv(CENSUS_COUNTIES_TXT, sep=\"\\t\", dtype={\"GEOID\": \"string\", \"USPS\": \"string\"}, low_memory=False)\n",
    "counties_df = counties_df[['USPS', 'GEOID', 'NAME']]\n",
    "counties_df.rename(columns={\"USPS\": \"State Abbreviation\", \"NAME\": \"County Name\"}, inplace=True)\n",
    "counties_df.head()"
-   ]
+   ],
+   "outputs": [],
+   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
-   "id": "5af103da",
-   "metadata": {},
-   "outputs": [],
   "source": [
    "states_df = pd.read_csv(STATE_CSV, dtype={\"fips\": \"string\", \"state_abbreviation\": \"string\"})\n",
    "states_df.rename(columns={\"fips\": \"State Code\", \"state_name\": \"State Name\", \"state_abbreviation\": \"State Abbreviation\"}, inplace=True)\n",
    "states_df.head()"
-   ]
+   ],
+   "outputs": [],
+   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
-   "id": "c8680258",
-   "metadata": {},
-   "outputs": [],
   "source": [
    "county_state_merged = counties_df.join(states_df, rsuffix=' Other')\n",
    "del county_state_merged[\"State Abbreviation Other\"]\n",
    "county_state_merged.head()"
-   ]
+   ],
+   "outputs": [],
+   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
-   "id": "58dca55a",
-   "metadata": {},
-   "outputs": [],
   "source": [
    "score_df = pd.read_csv(SCORE_CSV, dtype={\"GEOID10\": \"string\"})\n",
    "score_df[\"GEOID\"] = score_df.GEOID10.str[:5]\n",
    "score_df.head()"
-   ]
+   ],
+   "outputs": [],
+   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
-   "id": "45e04d42",
-   "metadata": {},
-   "outputs": [],
   "source": [
    "score_county_state_merged = score_df.join(county_state_merged, rsuffix='_OTHER')\n",
    "del score_county_state_merged[\"GEOID_OTHER\"]\n",
    "score_county_state_merged.head()"
-   ]
+   ],
+   "outputs": [],
+   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
-   "id": "a5a0b32b",
-   "metadata": {},
-   "outputs": [],
   "source": [
    "score_county_state_merged.to_csv(COUNTY_SCORE_CSV, index=False)"
-   ]
+   ],
+   "outputs": [],
+   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
-   "id": "b690937e",
-   "metadata": {},
+   "source": [],
   "outputs": [],
-   "source": []
+   "metadata": {}
  }
 ],
 "metadata": {
@ -158,4 +147,4 @@
 },
 "nbformat": 4,
 "nbformat_minor": 5
-}
+}
--- a/data/data-pipeline/data_pipeline/ipython/scoring_comparison.ipynb
+++ b/data/data-pipeline/data_pipeline/ipython/scoring_comparison.ipynb
--- a/data/data-pipeline/etl/sources/tree_equity_score/init.py
+++ b/data/data-pipeline/etl/sources/tree_equity_score/init.py
--- a/data/data-pipeline/data_pipeline/tile/generate.py
+++ b/data/data-pipeline/data_pipeline/tile/generate.py
@ -1,9 +1,8 @@
-from pathlib import Path
 import os
+from pathlib import Path
 from subprocess import call

-from utils import remove_all_from_dir
-from utils import get_module_logger
+from data_pipeline.utils import get_module_logger, remove_all_from_dir

 logger = get_module_logger(__name__)

@ -28,7 +27,7 @@ def generate_tiles(data_path: Path) -> None:
    os.mkdir(low_tile_path)

    # generate high mbtiles file
-    logger.info(f"Generating USA High mbtiles file")
+    logger.info("Generating USA High mbtiles file")
    cmd = "tippecanoe "
    cmd += f"--minimum-zoom={USA_HIGH_MIN_ZOOM} --maximum-zoom={USA_HIGH_MAX_ZOOM} --layer=blocks "
    cmd += f"--output={high_tile_path}/usa_high.mbtiles "
@ -36,7 +35,7 @@ def generate_tiles(data_path: Path) -> None:
    call(cmd, shell=True)

    # generate high mvts
-    logger.info(f"Generating USA High mvt folders and files")
+    logger.info("Generating USA High mvt folders and files")
    cmd = "tippecanoe "
    cmd += f"--minimum-zoom={USA_HIGH_MIN_ZOOM} --maximum-zoom={USA_HIGH_MAX_ZOOM} --no-tile-compression "
    cmd += f"--output-to-directory={high_tile_path} "
@ -44,7 +43,7 @@ def generate_tiles(data_path: Path) -> None:
    call(cmd, shell=True)

    # generate low mbtiles file
-    logger.info(f"Generating USA Low mbtiles file")
+    logger.info("Generating USA Low mbtiles file")
    cmd = "tippecanoe "
    cmd += f"--minimum-zoom={USA_LOW_MIN_ZOOM} --maximum-zoom={USA_LOW_MAX_ZOOM} --layer=blocks "
    cmd += f"--output={low_tile_path}/usa_low.mbtiles "
@ -52,7 +51,7 @@ def generate_tiles(data_path: Path) -> None:
    call(cmd, shell=True)

    # generate low mvts
-    logger.info(f"Generating USA Low mvt folders and files")
+    logger.info("Generating USA Low mvt folders and files")
    cmd = "tippecanoe "
    cmd += f"--minimum-zoom={USA_LOW_MIN_ZOOM} --maximum-zoom={USA_LOW_MAX_ZOOM} --no-tile-compression "
    cmd += f"--output-to-directory={low_tile_path} "
--- a/data/data-pipeline/data_pipeline/utils.py
+++ b/data/data-pipeline/data_pipeline/utils.py
@ -1,13 +1,13 @@
-from pathlib import Path
-import os
 import logging
+import os
 import shutil
 import zipfile
-import urllib3
+from pathlib import Path

 import requests
+import urllib3

-from config import settings
+from .config import settings


 def get_module_logger(module_name: str) -> logging.Logger:
@ -97,10 +97,7 @@ def remove_all_dirs_from_dir(dir_path: Path) -> None:


 def unzip_file_from_url(
-    file_url: str,
-    download_path: Path,
-    unzipped_file_path: Path,
-    verify: bool = False,
+    file_url: str, download_path: Path, unzipped_file_path: Path, verify: bool = False,
 ) -> None:
    """Downloads a zip file from a remote URL location and unzips it in a specific directory, removing the temporary file after

--- a/data/data-pipeline/poetry.lock
+++ b/data/data-pipeline/poetry.lock
@ -33,7 +33,7 @@ tests = ["coverage[toml] (>=5.0.2)", "hypothesis", "pytest"]

 [[package]]
 name = "astroid"
-version = "2.6.5"
+version = "2.6.6"
 description = "An abstract syntax tree for Python with inference support."
 category = "dev"
 optional = false
@ -53,6 +53,14 @@ category = "main"
 optional = false
 python-versions = ">=3.5"

+[[package]]
+name = "atomicwrites"
+version = "1.4.0"
+description = "Atomic file writes."
+category = "dev"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
+
 [[package]]
 name = "attrs"
 version = "21.2.0"
@ -116,11 +124,11 @@ uvloop = ["uvloop (>=0.15.2)"]

 [[package]]
 name = "bleach"
-version = "3.3.1"
+version = "4.0.0"
 description = "An easy safelist-based HTML-sanitizing tool."
 category = "main"
 optional = false
-python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
+python-versions = ">=3.6"

 [package.dependencies]
 packaging = "*"
@ -129,7 +137,7 @@ webencodings = "*"

 [[package]]
 name = "censusdata"
-version = "1.13"
+version = "1.14"
 description = "Download data from U.S. Census API"
 category = "main"
 optional = false
@ -160,7 +168,7 @@ pycparser = "*"

 [[package]]
 name = "charset-normalizer"
-version = "2.0.3"
+version = "2.0.4"
 description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
 category = "main"
 optional = false
@ -231,7 +239,7 @@ testing = ["pytest (>=4.6)", "pytest-checkdocs (>=1.2.3)", "pytest-flake8", "pyt

 [[package]]
 name = "debugpy"
-version = "1.4.0"
+version = "1.4.1"
 description = "An implementation of the Debug Adapter Protocol for Python"
 category = "main"
 optional = false
@ -385,6 +393,14 @@ zipp = ">=0.5"
 docs = ["sphinx", "jaraco.packaging (>=8.2)", "rst.linker (>=1.9)"]
 testing = ["pytest (>=4.6)", "pytest-checkdocs (>=2.4)", "pytest-flake8", "pytest-cov", "pytest-enabler (>=1.0.1)", "packaging", "pep517", "pyfakefs", "flufl.flake8", "pytest-black (>=0.3.7)", "pytest-mypy", "importlib-resources (>=1.3)"]

+[[package]]
+name = "iniconfig"
+version = "1.1.1"
+description = "iniconfig: brain-dead simple config-ini parsing"
+category = "dev"
+optional = false
+python-versions = "*"
+
 [[package]]
 name = "ipykernel"
 version = "6.0.3"
@ -408,7 +424,7 @@ test = ["pytest (!=5.3.4)", "pytest-cov", "flaky", "nose", "ipyparallel"]

 [[package]]
 name = "ipython"
-version = "7.25.0"
+version = "7.26.0"
 description = "IPython: Productive Interactive Computing"
 category = "main"
 optional = false
@ -932,7 +948,7 @@ pyparsing = ">=2.0.2"

 [[package]]
 name = "pandas"
-version = "1.3.0"
+version = "1.3.1"
 description = "Powerful data structures for data analysis, time series, and statistics"
 category = "main"
 optional = false
@ -995,11 +1011,15 @@ python-versions = "*"

 [[package]]
 name = "platformdirs"
-version = "2.0.2"
+version = "2.2.0"
 description = "A small Python module for determining appropriate platform-specific dirs, e.g. a \"user data dir\"."
 category = "dev"
 optional = false
-python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
+python-versions = ">=3.6"
+
+[package.extras]
+docs = ["Sphinx (>=4)", "furo (>=2021.7.5b38)", "proselint (>=0.10.2)", "sphinx-autodoc-typehints (>=1.12)"]
+test = ["appdirs (==1.4.4)", "pytest (>=6)", "pytest-cov (>=2.7)", "pytest-mock (>=3.6)"]

 [[package]]
 name = "pluggy"
@ -1127,6 +1147,28 @@ category = "main"
 optional = false
 python-versions = ">=3.6"

+[[package]]
+name = "pytest"
+version = "6.2.4"
+description = "pytest: simple powerful testing with Python"
+category = "dev"
+optional = false
+python-versions = ">=3.6"
+
+[package.dependencies]
+atomicwrites = {version = ">=1.0", markers = "sys_platform == \"win32\""}
+attrs = ">=19.2.0"
+colorama = {version = "*", markers = "sys_platform == \"win32\""}
+importlib-metadata = {version = ">=0.12", markers = "python_version < \"3.8\""}
+iniconfig = "*"
+packaging = "*"
+pluggy = ">=0.12,<1.0.0a1"
+py = ">=1.8.2"
+toml = "*"
+
+[package.extras]
+testing = ["argcomplete", "hypothesis (>=3.56)", "mock", "nose", "requests", "xmlschema"]
+
 [[package]]
 name = "python-dateutil"
 version = "2.8.2"
@ -1172,7 +1214,7 @@ python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*"

 [[package]]
 name = "pyzmq"
-version = "22.1.0"
+version = "22.2.0"
 description = "Python bindings for 0MQ"
 category = "main"
 optional = false
@ -1214,7 +1256,7 @@ python-versions = "*"

 [[package]]
 name = "regex"
-version = "2021.7.6"
+version = "2021.8.3"
 description = "Alternative regular expression module, to replace re."
 category = "dev"
 optional = false
@ -1329,7 +1371,7 @@ python-versions = ">=2.6, !=3.0.*, !=3.1.*, !=3.2.*"

 [[package]]
 name = "tomli"
-version = "1.1.0"
+version = "1.2.0"
 description = "A lil' TOML parser"
 category = "dev"
 optional = false
@ -1345,7 +1387,7 @@ python-versions = ">= 3.5"

 [[package]]
 name = "tox"
-version = "3.24.0"
+version = "3.24.1"
 description = "tox is a generic virtualenv management and test command line tool"
 category = "dev"
 optional = false
@ -1390,7 +1432,7 @@ python-versions = "*"

 [[package]]
 name = "types-requests"
-version = "2.25.0"
+version = "2.25.2"
 description = "Typing stubs for requests"
 category = "main"
 optional = false
@ -1419,7 +1461,7 @@ socks = ["PySocks (>=1.5.6,!=1.5.7,<2.0)"]

 [[package]]
 name = "virtualenv"
-version = "20.6.0"
+version = "20.7.0"
 description = "Virtual Python Environment builder"
 category = "dev"
 optional = false
@ -1435,7 +1477,7 @@ six = ">=1.9.0,<2"

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 [[package]]
 name = "wcwidth"
@ -1487,7 +1529,7 @@ testing = ["pytest (>=4.6)", "pytest-checkdocs (>=2.4)", "pytest-flake8", "pytes
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 ]
 virtualenv = [
-    {file = "virtualenv-20.6.0-py2.py3-none-any.whl", hash = "sha256:e4fc84337dce37ba34ef520bf2d4392b392999dbe47df992870dc23230f6b758"},
-    {file = "virtualenv-20.6.0.tar.gz", hash = "sha256:51df5d8a2fad5d1b13e088ff38a433475768ff61f202356bb9812c454c20ae45"},
+    {file = "virtualenv-20.7.0-py2.py3-none-any.whl", hash = "sha256:fdfdaaf0979ac03ae7f76d5224a05b58165f3c804f8aa633f3dd6f22fbd435d5"},
+    {file = "virtualenv-20.7.0.tar.gz", hash = "sha256:97066a978431ec096d163e72771df5357c5c898ffdd587048f45e0aecc228094"},
 ]
 wcwidth = [
    {file = "wcwidth-0.2.5-py2.py3-none-any.whl", hash = "sha256:beb4802a9cebb9144e99086eff703a642a13d6a0052920003a230f3294bbe784"},
--- a/data/data-pipeline/pyproject.toml
+++ b/data/data-pipeline/pyproject.toml
@ -1,11 +1,8 @@
 [tool.poetry]
 authors = ["Your Name <you@example.com>"]
 description = "ETL and Generation of Justice 40 Score"
-name = "score"
+name = "data-pipeline"
 version = "0.1.0"
-packages = [
-    { include = "etl" },  # required for poetry packaging to install in tox
-]

 [tool.poetry.dependencies]
 CensusData = "^1.13"
@ -23,12 +20,13 @@ types-requests = "^2.25.0"

 [tool.poetry.dev-dependencies]
 black = {version = "^21.6b0", allow-prereleases = true}
-mypy = "^0.910"
-tox = "^3.24.0"
 flake8 = "^3.9.2"
-pylint = "^2.9.6"
 liccheck = "^0.6.2"
+mypy = "^0.910"
+pylint = "^2.9.6"
+pytest = "^6.2.4"
 safety = "^1.10.3"
+tox = "^3.24.0"

 [build-system]
 build-backend = "poetry.core.masonry.api"
@ -38,66 +36,72 @@ requires = ["poetry-core>=1.0.0"]

 [tool.pylint."MESSAGE CONTROL"]
 disable = [
-  "C0114",  # Disables module docstrings
-  "R0201",  # Disables method could have been a function
-  "R0903",  # Disables too few public methods
-  "C0103",  # Disables name case styling
-  "W0511",  # Disables FIXME warning
-  "W1203",  # Disables f-string interpolation for logging warning
-  # Errors temporarily ignored for further discussion
-  "W0107",  # Disables unnecessary pass
-  "W0221",  # Disables arguments differ
-  "R0902",  # Disables too many instance attributes
-  "R0914",  # Disables too many local variables
-  "W0621",  # Disables redefined outer name
-  "C0302",  # Disables too many lines in module
-  "R1732",  # Disables consider using "with"
-  "R1720",  # Disables unnecessary "else" after "raise"
-  "C0206",  # Disables consider iteratig with ".items()"
-  "C0200",  # Disables consider using "enumerate" instead of "range" + "len"
-  "W0612",  # Disables unused variable
-  "W0613",  # Disables unused argument
-  "C0116",  # Disables missing function or method docstring
-  "C0115",  # Disables missing class docstring
+  "C0114", # Disables module docstrings
+  "R0201", # Disables method could have been a function
+  "R0903", # Disables too few public methods
+  "C0103", # Disables name case styling
+  "W0511", # Disables FIXME warning
+  "W1203", # Disables f-string interpolation for logging warning  # Errors temporarily ignored for further discussion
+  "W0107", # Disables unnecessary pass
+  "W0221", # Disables arguments differ
+  "R0902", # Disables too many instance attributes
+  "R0914", # Disables too many local variables
+  "W0621", # Disables redefined outer name
+  "C0302", # Disables too many lines in module
+  "R1732", # Disables consider using "with"
+  "R1720", # Disables unnecessary "else" after "raise"
+  "C0206", # Disables consider iteratig with ".items()"
+  "C0200", # Disables consider using "enumerate" instead of "range" + "len"
+  "W0612", # Disables unused variable
+  "W0613", # Disables unused argument
+  "C0116", # Disables missing function or method docstring
+  "C0115", # Disables missing class docstring
 ]

 [tool.pylint.FORMAT]
-max-line-length=150
+max-line-length = 150

 [tool.pylint.SIMILARITIES]
 # Configures how pylint detects repetitive code
-min-similarity-lines = 4
 ignore-comments = "yes"
 ignore-docstrings = "yes"
 ignore-imports = "yes"
+min-similarity-lines = 4

 [tool.liccheck]
 # Authorized and unauthorized licenses in LOWER CASE
 authorized_licenses = [
-        "bsd",
-        "new bsd",
-        "bsd license",
-        "bsd 3-clause",
-        "new bsd license",
-        "simplified bsd",
-        "apache",
-        "apache 2.0",
-        "apache license 2.0",
-        "apache software license",
-        "apache software",
-        "gnu lgpl",
-        "gnu lesser general public license v2 (lgplv2)",
-        "gnu general public license v2 (gplv2)",
-        "gnu library or lesser general public license (lgpl)",
-        "lgpl with exceptions or zpl",
-        "isc license",
-        "isc license (iscl)",
-        "mit",
-        "mit license",
-        "mozilla public license 2.0 (mpl 2.0)",
-        "public domain",
-        "python software foundation license",
-        "python software foundation",
-        "zpl 2.1",
-        "gpl v3"
+  "bsd",
+  "new bsd",
+  "bsd license",
+  "bsd 3-clause",
+  "new bsd license",
+  "simplified bsd",
+  "apache",
+  "apache 2.0",
+  "apache license 2.0",
+  "apache software license",
+  "apache software",
+  "gnu lgpl",
+  "gnu lesser general public license v2 (lgplv2)",
+  "gnu general public license v2 (gplv2)",
+  "gnu library or lesser general public license (lgpl)",
+  "lgpl with exceptions or zpl",
+  "isc license",
+  "isc license (iscl)",
+  "mit",
+  "mit license",
+  "mozilla public license 2.0 (mpl 2.0)",
+  "public domain",
+  "python software foundation license",
+  "python software foundation",
+  "zpl 2.1",
+  "gpl v3",
 ]
+
+[tool.poetry.scripts]
+cleanup_data = 'data_pipeline.application:data_cleanup'
+download_census = 'data_pipeline.application:census_data_download'
+etl = 'data_pipeline.application:etl_run'
+generate_tiles = 'data_pipeline.application:generate_map_tiles'
+score = 'data_pipeline.application:score_run'
--- a/data/data-pipeline/requirements.txt
+++ b/data/data-pipeline/requirements.txt
@ -1,23 +1,24 @@
 appdirs==1.4.4; python_full_version >= "3.6.2"
 appnope==0.1.2; sys_platform == "darwin" and python_version >= "3.7" and platform_system == "Darwin"
 argon2-cffi==20.1.0; python_version >= "3.6"
-astroid==2.6.5; python_version >= "3.6" and python_version < "4.0"
+astroid==2.6.6; python_version >= "3.6" and python_version < "4.0"
 async-generator==1.10; python_full_version >= "3.6.1" and python_version >= "3.7"
+atomicwrites==1.4.0; python_version >= "3.6" and python_full_version < "3.0.0" and sys_platform == "win32" or sys_platform == "win32" and python_version >= "3.6" and python_full_version >= "3.4.0"
 attrs==21.2.0; python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.5.0" and python_version >= "3.6"
 backcall==0.2.0; python_version >= "3.7"
 backports.entry-points-selectable==1.1.0; python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.5.0" and python_version >= "2.7"
 black==21.7b0; python_full_version >= "3.6.2"
-bleach==3.3.1; python_version >= "3.7" and python_full_version < "3.0.0" or python_full_version >= "3.5.0" and python_version >= "3.7"
-censusdata==1.13; python_version >= "2.7"
+bleach==4.0.0; python_version >= "3.7"
+censusdata==1.14; python_version >= "2.7"
 certifi==2021.5.30; python_version >= "3.7" and python_full_version < "3.0.0" or python_full_version >= "3.6.0" and python_version >= "3.7"
 cffi==1.14.6; implementation_name == "pypy" and python_version >= "3.6"
-charset-normalizer==2.0.3; python_full_version >= "3.6.0" and python_version >= "3"
+charset-normalizer==2.0.4; python_full_version >= "3.6.0" and python_version >= "3"
 click-plugins==1.1.1; python_version >= "3.6"
 click==8.0.1; python_version >= "3.6"
 cligj==0.7.2; python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.3.0" and python_version < "4" and python_version >= "3.6"
 colorama==0.4.4; platform_system == "Windows" and python_version >= "3.7" and python_full_version >= "3.6.2" and sys_platform == "win32" and python_version < "4.0" and (python_version >= "3.7" and python_full_version < "3.0.0" and sys_platform == "win32" or sys_platform == "win32" and python_version >= "3.7" and python_full_version >= "3.5.0")
 configparser==5.0.2; python_version >= "3.6"
-debugpy==1.4.0; python_version >= "3.7" and python_full_version < "3.0.0" or python_full_version >= "3.5.0" and python_version >= "3.7"
+debugpy==1.4.1; python_version >= "3.7" and python_full_version < "3.0.0" or python_full_version >= "3.5.0" and python_version >= "3.7"
 decorator==5.0.9; python_version >= "3.7"
 defusedxml==0.7.1; python_version >= "3.7" and python_full_version < "3.0.0" or python_full_version >= "3.5.0" and python_version >= "3.7"
 distlib==0.3.2; python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.5.0"
@ -29,10 +30,11 @@ fiona==1.8.20; python_version >= "3.6"
 flake8==3.9.2; (python_version >= "2.7" and python_full_version < "3.0.0") or (python_full_version >= "3.5.0")
 geopandas==0.9.0; python_version >= "3.6"
 idna==3.2; python_version >= "3.5" and python_full_version < "3.0.0" or python_full_version >= "3.6.0" and python_version >= "3.5"
-importlib-metadata==3.10.1; python_version < "3.8" and python_version >= "3.7" and (python_version >= "3.6" and python_full_version < "3.0.0" and python_version < "3.8" or python_full_version >= "3.5.0" and python_version < "3.8" and python_version >= "3.6") and python_full_version >= "3.6.2"
+importlib-metadata==3.10.1; python_version < "3.8" and python_version >= "3.7" and (python_version >= "3.6" and python_full_version < "3.0.0" and python_version < "3.8" or python_full_version >= "3.5.0" and python_version < "3.8" and python_version >= "3.6") and python_full_version >= "3.6.2" and (python_version >= "3.6" and python_full_version < "3.0.0" and python_version < "3.8" or python_full_version >= "3.4.0" and python_version >= "3.6" and python_version < "3.8")
+iniconfig==1.1.1; python_version >= "3.6"
 ipykernel==6.0.3; python_version >= "3.7"
 ipython-genutils==0.2.0; python_version >= "3.7"
-ipython==7.25.0; python_version >= "3.7"
+ipython==7.26.0; python_version >= "3.7"
 ipywidgets==7.6.3
 isort==5.9.3; python_full_version >= "3.6.1" and python_version < "4.0" and python_version >= "3.6"
 jedi==0.18.0; python_version >= "3.7"
@ -66,55 +68,56 @@ nest-asyncio==1.5.1; python_full_version >= "3.6.1" and python_version >= "3.7"
 notebook==6.4.0; python_version >= "3.6"
 numpy==1.21.1; python_version >= "3.7"
 packaging==21.0; python_version >= "3.7" and python_full_version < "3.0.0" or python_full_version >= "3.5.0" and python_version >= "3.7"
-pandas==1.3.0; python_full_version >= "3.7.1"
+pandas==1.3.1; python_full_version >= "3.7.1"
 pandocfilters==1.4.3; python_version >= "3.7" and python_full_version < "3.0.0" or python_full_version >= "3.4.0" and python_version >= "3.7"
 parso==0.8.2; python_version >= "3.7"
 pathspec==0.9.0; python_full_version >= "3.6.2"
 pexpect==4.8.0; sys_platform != "win32" and python_version >= "3.7"
 pickleshare==0.7.5; python_version >= "3.7"
-platformdirs==2.0.2; python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.5.0"
-pluggy==0.13.1; python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.5.0"
+platformdirs==2.2.0; python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.5.0" and python_version >= "3.6"
+pluggy==0.13.1; python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.5.0" and python_version >= "3.6"
 prometheus-client==0.11.0; python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.4.0" and python_version >= "3.6"
 prompt-toolkit==3.0.19; python_full_version >= "3.6.1" and python_version >= "3.7"
 ptyprocess==0.7.0; sys_platform != "win32" and python_version >= "3.7" and os_name != "nt"
-py==1.10.0; python_version >= "3.6" and python_full_version < "3.0.0" and implementation_name == "pypy" or implementation_name == "pypy" and python_version >= "3.6" and python_full_version >= "3.5.0"
+py==1.10.0; python_version >= "3.6" and python_full_version < "3.0.0" and implementation_name == "pypy" or python_full_version >= "3.5.0" and python_version >= "3.6" and implementation_name == "pypy"
 pycodestyle==2.7.0; python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.5.0"
 pycparser==2.20; python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.4.0" and python_version >= "3.6"
 pyflakes==2.3.1; python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.5.0"
 pygments==2.9.0; python_version >= "3.7"
 pylint==2.9.6; python_version >= "3.6" and python_version < "4.0"
-pyparsing==2.4.7; python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.5.0" and python_version >= "3.6"
+pyparsing==2.4.7; python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.3.0" and python_version >= "3.6"
 pyproj==3.1.0; python_version >= "3.7"
 pyrsistent==0.18.0; python_version >= "3.6"
+pytest==6.2.4; python_version >= "3.6"
 python-dateutil==2.8.2; python_full_version >= "3.7.1" and python_version >= "3.7"
 pytz==2021.1; python_full_version >= "3.7.1" and python_version >= "2.7"
 pywin32==301; sys_platform == "win32" and python_version >= "3.6"
 pywinpty==1.1.3; os_name == "nt" and python_version >= "3.6"
 pyyaml==5.4.1; python_version >= "3.5" and python_full_version < "3.0.0" or python_full_version >= "3.6.0" and python_version >= "3.5"
-pyzmq==22.1.0; python_full_version >= "3.6.1" and python_version >= "3.7"
+pyzmq==22.2.0; python_full_version >= "3.6.1" and python_version >= "3.7"
 qtconsole==5.1.1; python_version >= "3.6"
 qtpy==1.9.0; python_version >= "3.6"
-regex==2021.7.6; python_full_version >= "3.6.2"
+regex==2021.8.3; python_full_version >= "3.6.2"
 requests==2.26.0; (python_version >= "2.7" and python_full_version < "3.0.0") or (python_full_version >= "3.6.0")
 safety==1.10.3; python_version >= "3.5"
 semantic-version==2.8.5; python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.4.0" and python_version >= "2.7"
 send2trash==1.7.1; python_version >= "3.6"
 shapely==1.7.1; python_version >= "3.6"
-six==1.16.0; python_full_version >= "3.7.1" and python_version >= "3.6" and (python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.5.0") and (python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.3.0" and python_version >= "3.6") and (python_version >= "3.7" and python_full_version < "3.0.0" or python_full_version >= "3.5.0" and python_version >= "3.7") and (python_version >= "3.5" and python_full_version < "3.0.0" or python_full_version >= "3.3.0" and python_version >= "3.5")
+six==1.16.0; python_full_version >= "3.7.1" and python_version >= "3.6" and (python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.5.0") and (python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.3.0" and python_version >= "3.6") and (python_version >= "3.7" and python_full_version < "3.0.0" or python_full_version >= "3.3.0" and python_version >= "3.7") and (python_version >= "3.5" and python_full_version < "3.0.0" or python_full_version >= "3.3.0" and python_version >= "3.5")
 terminado==0.10.1; python_version >= "3.6"
 testpath==0.5.0; python_version >= "3.7"
 toml==0.10.2; python_version >= "3.6" and python_full_version < "3.0.0" and python_version < "4.0" or python_full_version >= "3.5.0" and python_version >= "3.6" and python_version < "4.0"
-tomli==1.1.0; python_version >= "3.6" and python_full_version >= "3.6.2"
+tomli==1.2.0; python_version >= "3.6" and python_full_version >= "3.6.2"
 tornado==6.1; python_full_version >= "3.6.1" and python_version >= "3.7"
-tox==3.24.0; (python_version >= "2.7" and python_full_version < "3.0.0") or (python_full_version >= "3.5.0")
+tox==3.24.1; (python_version >= "2.7" and python_full_version < "3.0.0") or (python_full_version >= "3.5.0")
 traitlets==5.0.5; python_full_version >= "3.6.1" and python_version >= "3.7"
 typed-ast==1.4.3; python_version < "3.8" and python_full_version >= "3.6.2" and python_version >= "3.6" and implementation_name == "cpython"
-types-requests==2.25.0
+types-requests==2.25.2
 typing-extensions==3.10.0.0; python_version < "3.8" and python_full_version >= "3.6.2" and python_version >= "3.6"
 urllib3==1.26.6; python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.6.0" and python_version < "4" and python_version >= "2.7"
-virtualenv==20.6.0; python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.5.0"
+virtualenv==20.7.0; python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.5.0"
 wcwidth==0.2.5; python_full_version >= "3.6.1" and python_version >= "3.7"
-webencodings==0.5.1; python_version >= "3.7" and python_full_version < "3.0.0" or python_full_version >= "3.5.0" and python_version >= "3.7"
+webencodings==0.5.1; python_version >= "3.7"
 widgetsnbextension==3.5.1
 wrapt==1.12.1; python_version >= "3.6" and python_version < "4.0"
 zipp==3.5.0; python_version < "3.8" and python_version >= "3.6"
--- a/data/data-pipeline/tile/init.py
+++ b/data/data-pipeline/tile/init.py
--- a/data/data-pipeline/tox.ini
+++ b/data/data-pipeline/tox.ini
@ -9,9 +9,9 @@ skip_missing_interpreters = true
 # lints python code in src and tests
 basepython = python3.9
 deps = -rrequirements.txt
-commands = black etl application.py config.py utils.py
-           flake8 etl application.py config.py utils.py
-           # pylint etl application.py config.py utils.py
+commands = black data_pipeline
+           flake8 data_pipeline
+           pylint data_pipeline

 [testenv:checkdeps]
 # checks the dependencies for security vulnerabilities and open source licenses