Add ETL Contract Checks (#619)

* Adds dev dependencies to requirements.txt and re-runs black on codebase

* Adds test and code for national risk index etl, still in progress

* Removes test_data from .gitignore

* Adds test data to nation_risk_index tests

* Creates tests and ETL class for NRI data

* Adds tests for load() and transform() methods of NationalRiskIndexETL

* Updates README.md with info about the NRI dataset

* Adds to dos

* Moves tests and test data into a tests/ dir in national_risk_index

* Moves tmp_dir for tests into data/tmp/tests/

* Promotes fixtures to conftest and relocates national_risk_index tests:
The relocation of national_risk_index tests is necessary because tests 
can only use fixtures specified in conftests within the same package

* Fixes issue with df.equals() in test_transform()

* Files reformatted by black

* Commit changes to other files after re-running black

* Fixes unused import that caused lint checks to fail

* Moves tests/ directory to app root for data_pipeline

* Adds new methods to ExtractTransformLoad base class:
- __init__() Initializes class attributes
- _get_census_fips_codes() Loads a dataframe with the fips codes for 
census block group and tract
- validate_init() Checks that the class was initialized correctly
- validate_output() Checks that the output was loaded correctly

* Adds test for ExtractTransformLoad.__init__() and base.py

* Fixes failing flake8 test

* Changes geo_col to geoid_col and changes is_dataset to is_census in yaml

* Adds test for validate_output()

* Adds remaining tests

* Removes is_dataset from init method

* Makes CENSUS_CSV a class attribute instead of a class global:
This ensures that CENSUS_CSV is only set when the ETL class is for a 
non-census dataset and removes the need to overwrite the value in 
mock_etl fixture

* Re-formats files with black and fixes broken tox tests

data/data-pipeline/data_pipeline/application.py

@@ -3,7 +3,12 @@ import sys
 import click
 
 from data_pipeline.config import settings
-from data_pipeline.etl.runner import etl_runner, score_generate, score_geo, score_post
+from data_pipeline.etl.runner import (
+    etl_runner,
+    score_generate,
+    score_geo,
+    score_post,
+)
 from data_pipeline.etl.sources.census.etl_utils import (
     reset_data_directories as census_reset,
 )

data/data-pipeline/data_pipeline/etl/base.py

@@ -1,8 +1,17 @@
 from pathlib import Path
 from typing import Optional
 
+import pandas as pd
+import yaml
+
 from data_pipeline.config import settings
-from data_pipeline.utils import unzip_file_from_url, remove_all_from_dir
+from data_pipeline.utils import (
+    unzip_file_from_url,
+    remove_all_from_dir,
+    get_module_logger,
+)
+
+logger = get_module_logger(__name__)
 
 
 class ExtractTransformLoad:
@@ -17,7 +26,8 @@ class ExtractTransformLoad:
         GEOID_TRACT_FIELD_NAME (str): The common column name for a Census Tract identifier
     """
 
-    DATA_PATH: Path = settings.APP_ROOT / "data"
+    APP_ROOT: Path = settings.APP_ROOT
+    DATA_PATH: Path = APP_ROOT / "data"
     TMP_PATH: Path = DATA_PATH / "tmp"
     FILES_PATH: Path = settings.APP_ROOT / "files"
     GEOID_FIELD_NAME: str = "GEOID10"
@@ -26,11 +36,51 @@ class ExtractTransformLoad:
     EXPECTED_MAX_CENSUS_BLOCK_GROUPS: int = 220405
     EXPECTED_MAX_CENSUS_TRACTS: int = 73076
 
-    def get_yaml_config(self) -> None:
+    def __init__(self, config_path: Path) -> None:
+        """Inits the class with instance specific variables"""
+
+        # set by _get_yaml_config()
+        self.NAME: str = None
+        self.SOURCE_URL: str = None
+        self.GEOID_COL: str = None
+        self.GEO_LEVEL: str = None
+        self.SCORE_COLS: list = None
+        self.FIPS_CODES: pd.DataFrame = None
+        self.OUTPUT_PATH: Path = None
+        self.CENSUS_CSV: Path = None
+
+        self._get_yaml_config(config_path)
+
+    def _get_yaml_config(self, config_path: Path) -> None:
         """Reads the YAML configuration file for the dataset and stores
         the properies in the instance (upcoming feature)"""
+        # parse the yaml config file
+        try:
+            with open(config_path, "r", encoding="utf-8") as file:
+                config = yaml.safe_load(file)
+        except (FileNotFoundError, yaml.YAMLError) as err:
+            raise err
 
-        pass
+        # set dataset specific attributes
+        census_dir = self.DATA_PATH / "census" / "csv"
+        if config["is_census"]:
+            csv_dir = census_dir
+        else:
+            self.CENSUS_CSV = census_dir / "us.csv"
+            self.FIPS_CODES = self._get_census_fips_codes()
+            csv_dir = self.DATA_PATH / "dataset"
+
+        # parse name and set output path
+        name = config.get("name")
+        snake_name = name.replace(" ", "_").lower()  # converts to snake case
+        output_dir = snake_name + (config.get("year") or "")
+        self.OUTPUT_PATH = csv_dir / output_dir / "usa.csv"
+        self.OUTPUT_PATH.parent.mkdir(parents=True, exist_ok=True)
+
+        # set class attributes
+        attrs = ["NAME", "SOURCE_URL", "GEOID_COL", "GEO_LEVEL", "SCORE_COLS"]
+        for attr in attrs:
+            setattr(self, attr, config[attr.lower()])
 
     def check_ttl(self) -> None:
         """Checks if the ETL process can be run based on a the TLL value on the
@@ -44,9 +94,9 @@ class ExtractTransformLoad:
         extract_path: Path = None,
         verify: Optional[bool] = True,
     ) -> None:
-        """Extract the data from
+        """Extract the data from a remote source. By default it provides code
-        a remote source. By default it provides code to get the file from a source url,
+        to get the file from a source url, unzips it and stores it on an
-        unzips it and stores it on an extract_path."""
+        extract_path."""
 
         # this can be accessed via super().extract()
         if source_url and extract_path:
@@ -70,3 +120,53 @@ class ExtractTransformLoad:
         """Clears out any files stored in the TMP folder"""
 
         remove_all_from_dir(self.TMP_PATH)
+
+    # TODO: Add test for this
+    def _get_census_fips_codes(self) -> pd.DataFrame:
+        """Loads FIPS codes for each Census block group and tract"""
+
+        # check that the census data exists
+        if not self.CENSUS_CSV.exists():
+            logger.info("Census data not found, please run download_csv first")
+        # load the census data
+        df = pd.read_csv(
+            self.CENSUS_CSV, dtype={self.GEOID_FIELD_NAME: "string"}
+        )
+        # extract Census tract FIPS code from Census block group
+        df[self.GEOID_TRACT_FIELD_NAME] = df[self.GEOID_FIELD_NAME].str[0:11]
+        return df[[self.GEOID_FIELD_NAME, self.GEOID_TRACT_FIELD_NAME]]
+
+    # TODO: Create tests
+    def validate_output(self) -> None:
+        """Checks that the output of the ETL process adheres to the contract
+        expected by the score module
+
+        Contract conditions:
+        - Output is saved as usa.csv at the path specified by self.OUTPUT_PATH
+        - The output csv has a column named GEOID10 which stores each of the
+          Census block group FIPS codes in data/census/csv/usa.csv
+        - The output csv has a column named GEOID10_TRACT which stores each of
+          Census tract FIPS codes associated with each Census block group
+        - The output csv has each of the columns expected by the score and the
+          name and dtype of those columns match the format expected by score
+        """
+        # read in output file
+        # and check that GEOID cols are present
+        assert self.OUTPUT_PATH.exists(), f"No file found at {self.OUTPUT_PATH}"
+        df_output = pd.read_csv(
+            self.OUTPUT_PATH,
+            dtype={
+                self.GEOID_FIELD_NAME: "string",
+                self.GEOID_TRACT_FIELD_NAME: "string",
+            },
+        )
+
+        # check that the GEOID cols in the output match census data
+        geoid_cols = [self.GEOID_FIELD_NAME, self.GEOID_TRACT_FIELD_NAME]
+        for col in geoid_cols:
+            assert col in self.FIPS_CODES.columns
+        assert self.FIPS_CODES.equals(df_output[geoid_cols])
+
+        # check that the score columns are in the output
+        for col in self.SCORE_COLS:
+            assert col in df_output.columns, f"{col} is missing from output"

data/data-pipeline/data_pipeline/etl/runner.py

@@ -86,6 +86,7 @@ def score_generate() -> None:
     # Post Score Processing
     score_post()
 
+
 def score_post() -> None:
     """Posts the score files to the local directory
 

data/data-pipeline/data_pipeline/etl/score/constants.py

@@ -46,8 +46,12 @@ timestamp_str = current_dt.strftime("%Y-%m-%d-%H%M")
 SCORE_DOWNLOADABLE_DIR = DATA_SCORE_DIR / "downloadable"
 SCORE_DOWNLOADABLE_PDF_FILE_NAME = "Draft_Communities_List.pdf"
 SCORE_DOWNLOADABLE_PDF_FILE_PATH = FILES_PATH / SCORE_DOWNLOADABLE_PDF_FILE_NAME
-SCORE_DOWNLOADABLE_CSV_FILE_PATH = SCORE_DOWNLOADABLE_DIR / f"communities-{timestamp_str}.csv"
+SCORE_DOWNLOADABLE_CSV_FILE_PATH = (
-SCORE_DOWNLOADABLE_EXCEL_FILE_PATH = SCORE_DOWNLOADABLE_DIR / f"communities-{timestamp_str}.xlsx"
+    SCORE_DOWNLOADABLE_DIR / f"communities-{timestamp_str}.csv"
+)
+SCORE_DOWNLOADABLE_EXCEL_FILE_PATH = (
+    SCORE_DOWNLOADABLE_DIR / f"communities-{timestamp_str}.xlsx"
+)
 SCORE_DOWNLOADABLE_ZIP_FILE_PATH = (
     SCORE_DOWNLOADABLE_DIR / "Screening_Tool_Data.zip"
 )

data/data-pipeline/data_pipeline/tests/base/config.yaml

@@ -0,0 +1,10 @@
+name: Template
+year: null
+is_census: false
+source_url: https://github.com/usds/justice40-tool/
+geo_level: Census Block Group
+geoid_col: GEO COL
+score_cols:
+  - COL 1
+  - COL 2
+  - COL 3

data/data-pipeline/data_pipeline/tests/base/data/census.csv

@@ -0,0 +1,11 @@
+GEOID10,POPULATION
+050070403001,1000
+050070403002,1500
+050010201001,1000
+050010201002,1500
+150070405001,2000
+150070405002,2250
+150010210101,2000
+150010210102,1500
+150010211011,1750
+150010211012,1500

data/data-pipeline/data_pipeline/tests/base/data/output.csv

@@ -0,0 +1,11 @@
+GEOID10,GEOID10_TRACT,COL 1,COL 2,COL 3
+050070403001,05007040300,10,10,10
+050070403002,05007040300,20,20,20
+050010201001,05001020100,30,30,30
+050010201002,05001020100,40,40,40
+150070405001,15007040500,50,50,50
+150070405002,15007040500,60,60,60
+150010210101,15001021010,70,70,70
+150010210102,15001021010,80,80,80
+150010211011,15001021101,90,90,90
+150010211012,15001021101,100,100,100

data/data-pipeline/data_pipeline/tests/base/invalid_config.yaml

@@ -0,0 +1,10 @@
+name = Template # uses equal sign instead of colon
+year: null
+is_dataset: true
+source_url: https://github.com/usds/justice40-tool/
+geo_level: Census Block Group
+geoid_col: GEO COL
+score_cols:
+  - COL 1
+  - COL 2
+  - COL 3

data/data-pipeline/data_pipeline/tests/base/test_base.py

@@ -0,0 +1,161 @@
+import shutil
+from pathlib import Path
+
+import yaml
+import pytest
+import pandas as pd
+
+from data_pipeline.config import settings
+from data_pipeline.etl.base import ExtractTransformLoad
+
+TEST_DIR = settings.APP_ROOT / "tests" / "base"
+DATA_DIR = TEST_DIR / "data"
+CONFIG_PATH = TEST_DIR / "config.yaml"
+OUTPUT_SRC = DATA_DIR / "output.csv"
+
+
+def remove_output(etl):
+    """Clears output.csv if it is exists"""
+    etl = TemplateETL(CONFIG_PATH)
+    if etl.OUTPUT_PATH.exists():
+        etl.OUTPUT_PATH.unlink()
+    assert etl.OUTPUT_PATH.exists() is False
+
+
+def load_output_source(etl):
+    """Loads output csv so that it can be modified"""
+    df = pd.read_csv(
+        OUTPUT_SRC,
+        dtype={
+            etl.GEOID_FIELD_NAME: "string",
+            etl.GEOID_TRACT_FIELD_NAME: "string",
+        },
+    )
+    return df
+
+
+class TemplateETL(ExtractTransformLoad):
+    """Mock ETL class that inherits from the base ETL"""
+
+    def __init__(self, config_path: Path) -> None:
+        super().__init__(config_path)
+        self.EXTRACTED_CSV: Path = DATA_DIR / "output.csv"
+        self.df: pd.DataFrame = None
+
+
+class TestInit:
+    """Tests the super.init() method in a class that inherits from
+    ExtractTransformLoad"""
+
+    def test_init(self, mock_paths, mock_etl):
+        """Tests that the init method executes successfully
+
+        Validates the following conditions:
+        - The class was instantiated with no errors
+        - All of the class attributes were set correctly by _get_yaml_config()
+        """
+        # setup
+        data_path, tmp_path = mock_paths
+        etl = TemplateETL(CONFIG_PATH)
+        # validation
+        assert etl.NAME == "Template"
+        assert etl.SOURCE_URL == "https://github.com/usds/justice40-tool/"
+        assert etl.GEOID_COL == "GEO COL"
+        assert etl.GEO_LEVEL == "Census Block Group"
+        assert etl.SCORE_COLS == ["COL 1", "COL 2", "COL 3"]
+        assert etl.OUTPUT_PATH == data_path / "dataset" / "template" / "usa.csv"
+        assert etl.CENSUS_CSV.exists()
+
+    def test_init_missing_config(self, mock_etl):
+        """Tests that FileNotFoundError is raised when the class is instantiated
+        with a path to a config.yaml file that doesn't exist
+        """
+        # setup
+        config_path = settings.APP_ROOT / "fake_path"
+        assert config_path.exists() is False
+        # execute
+        with pytest.raises(FileNotFoundError):
+            TemplateETL(config_path)
+
+    def test_init_bad_config(self, mock_etl):
+        """Tests that YAMLError is raised when the class is instantiated with
+        a yaml file that has errors in it
+        """
+        # setup
+        config_path = TEST_DIR / "invalid_config.yaml"
+        assert config_path.exists()
+        # execute
+        with pytest.raises(yaml.YAMLError):
+            TemplateETL(config_path)
+
+
+class TestValidateOutput:
+    """Tests the ExtractTransformLoad.validate_output() method"""
+
+    def test_validate_output_success(self, mock_etl):
+        """Tests that validate_output() runs successfully with valid output"""
+        # setup - instantiate etl class
+        etl = TemplateETL(CONFIG_PATH)
+        # setup - load output file
+        shutil.copyfile(OUTPUT_SRC, etl.OUTPUT_PATH)
+        # validation
+        etl.validate_output()
+
+    def test_validate_output_missing_output(self, mock_etl):
+        """Tests that validate_output() fails if the output isn't written to
+        the location at self.OUTPUT_PATH
+        """
+        # setup - remove output file
+        etl = TemplateETL(CONFIG_PATH)
+        remove_output(etl)
+        # validation
+        with pytest.raises(AssertionError):
+            etl.validate_output()
+
+    def test_validate_missing_geoid_col(self, mock_etl):
+        """Tests that validate_output() fails if the output is missing one of
+        census fips codes columns
+        """
+        # setup - remove output file
+        etl = TemplateETL(CONFIG_PATH)
+        remove_output(etl)
+        # setup - delete GEOID10 col from output
+        df = load_output_source(etl)
+        df.drop(etl.GEOID_FIELD_NAME, axis=1, inplace=True)
+        assert etl.GEOID_FIELD_NAME not in df.columns
+        df.to_csv(etl.OUTPUT_PATH)
+        # validation
+        with pytest.raises(KeyError):
+            etl.validate_output()
+
+    def test_validate_missing_census_block_group(self, mock_etl):
+        """Tests that validate_output() fails if the output is missing one of
+        census block group rows
+        """
+        # setup - remove output file
+        etl = TemplateETL(CONFIG_PATH)
+        remove_output(etl)
+        # setup - remove the first Census Block Group
+        df = load_output_source(etl)
+        df.drop(index=df.index[0], axis=0, inplace=True)  # delete row 1
+        assert len(df) == 9
+        df.to_csv(etl.OUTPUT_PATH)
+        # validation
+        with pytest.raises(AssertionError):
+            etl.validate_output()
+
+    def test_validate_missing_score_col(self, mock_etl):
+        """Tests that validate_output() fails if the output is missing one of
+        the columns used in the score
+        """
+        # setup - remove output file
+        etl = TemplateETL(CONFIG_PATH)
+        remove_output(etl)
+        # setup - delete one of the score columns
+        df = load_output_source(etl)
+        df.drop("COL 1", axis=1, inplace=True)
+        assert "COL 1" not in df.columns
+        df.to_csv(etl.OUTPUT_PATH)
+        # validation
+        with pytest.raises(AssertionError):
+            etl.validate_output()

data/data-pipeline/data_pipeline/tests/conftest.py

@@ -1,4 +1,6 @@
 import os
+from pathlib import Path
+from shutil import copyfile
 
 import pytest
 
@@ -8,6 +10,22 @@ from data_pipeline.etl.base import ExtractTransformLoad
 TMP_DIR = settings.APP_ROOT / "data" / "tmp" / "tests"
 
 
+def copy_data_files(src: Path, dst: Path) -> None:
+    """Copies test data from src Path to dst Path for use in testing
+
+    Args
+        src: pathlib.Path instance. The location of the source data file.
+        dst: pathlib.Path instance. Where to copy the source data file to.
+
+    Returns
+        None. This is a void function
+    """
+    if not dst.exists():
+        dst.parent.mkdir(parents=True, exist_ok=True)
+        copyfile(src, dst)
+        assert dst.exists()
+
+
 @pytest.fixture(scope="session")
 def mock_paths(tmp_path_factory) -> tuple:
     """Creates new DATA_PATH and TMP_PATH that point to a temporary local
@@ -23,8 +41,17 @@ def mock_paths(tmp_path_factory) -> tuple:
     return data_path, tmp_path
 
 
+@pytest.fixture(scope="session")
+def mock_census(mock_paths) -> Path:
+    data_path, tmp_path = mock_paths
+    census_src = settings.APP_ROOT / "tests" / "base" / "data" / "census.csv"
+    census_dst = data_path / "census" / "csv" / "us.csv"
+    copy_data_files(census_src, census_dst)
+    return census_dst
+
+
 @pytest.fixture
-def mock_etl(monkeypatch, mock_paths) -> None:
+def mock_etl(monkeypatch, mock_paths, mock_census) -> None:
     """Creates a mock version of the base ExtractTransformLoad class and resets
     global the variables for DATA_PATH and TMP_PATH to the local mock_paths
     """

data/data-pipeline/data_pipeline/tests/sources/national_risk_index/test_etl.py

@@ -1,9 +1,7 @@
-from pathlib import Path
-from shutil import copyfile
-
 import pandas as pd
 
 from data_pipeline.config import settings
+from data_pipeline.tests.conftest import copy_data_files
 from data_pipeline.etl.sources.national_risk_index.etl import (
     NationalRiskIndexETL,
 )
@@ -13,22 +11,6 @@ DATA_DIR = (
 )
 
 
-def copy_data_files(src: Path, dst: Path) -> None:
-    """Copies test data from src Path to dst Path for use in testing
-
-    Args
-        src: pathlib.Path instance. The location of the source data file.
-        dst: pathlib.Path instance. Where to copy the source data file to.
-
-    Returns
-        None. This is a void function
-    """
-    if not dst.exists():
-        dst.parent.mkdir(parents=True, exist_ok=True)
-        copyfile(src, dst)
-        assert dst.exists()
-
-
 class TestNationalRiskIndexETL:
     def test_init(self, mock_etl, mock_paths):
         """Tests that the mock NationalRiskIndexETL class instance was
@@ -45,6 +27,7 @@ class TestNationalRiskIndexETL:
         data_path, tmp_path = mock_paths
         input_csv = tmp_path / "NRI_Table_CensusTracts.csv"
         output_dir = data_path / "dataset" / "national_risk_index_2020"
+        print(input_csv)
         # validation
         assert etl.DATA_PATH == data_path
         assert etl.TMP_PATH == tmp_path
@@ -66,7 +49,7 @@ class TestNationalRiskIndexETL:
         input_src = DATA_DIR / "input.csv"
         input_dst = etl.INPUT_CSV
         acs_src = DATA_DIR / "acs.csv"
-        acs_dst = DATA_DIR / etl.BLOCK_GROUP_CSV
+        acs_dst = etl.BLOCK_GROUP_CSV
         for src, dst in [(input_src, input_dst), (acs_src, acs_dst)]:
             copy_data_files(src, dst)
         # setup - read in sample output as dataframe

data/data-pipeline/data_pipeline/utils.py

@@ -189,12 +189,14 @@ def score_folder_cleanup() -> None:
     remove_all_from_dir(data_path / "score" / "tiles")
     downloadable_cleanup()
 
+
 def downloadable_cleanup() -> None:
     """Remove all files from downloadable directory in the local data/score path"""
 
     data_path = settings.APP_ROOT / "data"
     remove_all_from_dir(data_path / "score" / "downloadable")
 
+
 def temp_folder_cleanup() -> None:
     """Remove all files and directories from the local data/tmp temporary path"""
 

data/data-pipeline/pyproject.toml

@@ -64,6 +64,7 @@ disable = [
   "C0116", # Disables missing function or method docstring
   "C0115", # Disables missing class docstring
   "R0915", # Disables too many statements (score generation transform)
+  "W0231", # Disables super init not called
 ]
 
 [tool.pylint.FORMAT]