Allow for Census Tract search in UI

client/package.json

@@ -85,6 +85,7 @@
     "gatsby-plugin-env-variables": "^2.2.0",
     "gatsby-plugin-robots-txt": "^1.7.0",
     "gatsby-plugin-sitemap": "^4.10.0",
+    "js-search": "^2.0.1",
     "mapbox-gl": "^1.13.2",
     "maplibre-gl": "^1.14.0",
     "query-string": "^7.1.3",

client/src/components/J40Map.tsx

@@ -130,7 +130,7 @@ const J40Map = ({location}: IJ40Interface) => {
   const onClick = (event: MapEvent | React.MouseEvent<HTMLButtonElement>) => {
     // Stop all propagation / bubbling / capturing
     event.preventDefault();
-    event.stopPropagation();
+    (event as React.MouseEvent<HTMLButtonElement>).stopPropagation?.();
 
     // Check if the click is for territories. Given the territories component's design, it can be
     // guaranteed that each territory control will have an id. We use this ID to determine
@@ -167,8 +167,9 @@ const J40Map = ({location}: IJ40Interface) => {
         default:
           break;
       }
-    } else {
-      // This else clause will fire when the ID is null or empty. This is the case where the map is clicked
+    } else if (event.target && (event.target as HTMLElement).nodeName == 'DIV' ) {
+      // This else clause will fire when the user clicks on the map and will ignore other controls
+      // such as the search box and buttons.
 
       // @ts-ignore
       const feature = event.features && event.features[0];

client/src/components/MapSearch/MapSearch.tsx

@@ -4,6 +4,8 @@ import {LngLatBoundsLike} from 'maplibre-gl';
 import {useIntl} from 'gatsby-plugin-intl';
 import {Search} from '@trussworks/react-uswds';
 import {useWindowSize} from 'react-use';
+import * as JsSearch from 'js-search';
+import * as constants from '../../data/constants';
 
 import MapSearchMessage from '../MapSearchMessage';
 
@@ -14,6 +16,16 @@ interface IMapSearch {
   goToPlace(bounds: LngLatBoundsLike):void;
 }
 
+interface ISearchResult {
+  addresstype: string;
+  lat: string;
+  lon: string;
+  boundingbox: string[];
+  type: string;
+  // eslint-disable-next-line camelcase
+  place_rank: number;
+}
+
 const MapSearch = ({goToPlace}:IMapSearch) => {
   // State to hold if the search results are empty or not:
   const [isSearchResultsNull, setIsSearchResultsNull] = useState(false);
@@ -30,44 +42,118 @@ const MapSearch = ({goToPlace}:IMapSearch) => {
    */
   const {width, height} = useWindowSize();
   const [placeholderText, setPlaceholderText]= useState(EXPLORE_COPY.MAP.SEARCH_PLACEHOLDER);
+  const [tractSearch, setTractSearch] = useState<JsSearch | null>(null);
+
+  /**
+   * Gets the tract search data and loads in the state.
+   */
+  const getTractSearchData = async () => {
+    const searchDataUrl = `${constants.TILE_BASE_URL}/${constants.MAP_TRACT_SEARCH_PATH}`;
+    fetch(searchDataUrl)
+        .then((response) => {
+          if (response.ok) {
+            return response.json();
+          } else {
+            throw new Error(`${response.statusText} error with status code of ${response.status}`);
+          }
+        })
+        .then((data) => {
+          // We use JsSearch to make it easy to load and quick to search.
+          const search = new JsSearch.Search('GEOID10');
+          search.indexStrategy = new JsSearch.ExactWordIndexStrategy();
+          search.addIndex('GEOID10');
+          search.addDocuments(data);
+          setTractSearch(search);
+        })
+        .catch((error) =>
+          console.error('Unable to read search tract table:', error));
+  };
 
   useEffect( () => {
    width > height ? setPlaceholderText(EXPLORE_COPY.MAP.SEARCH_PLACEHOLDER): setPlaceholderText(EXPLORE_COPY.MAP.SEARCH_PLACEHOLDER_MOBILE);
   }, [width]);
 
+  useEffect(()=>{
+    getTractSearchData();
+  }, []);
+
+  /**
+   * Searchs for a given Census tract ID.
+   * @param {string} tract the 11 digit tract ID as a string
+   * @return {Array} an array of one search result, or null if no result found
+   */
+  const searchForTract = (tract: string): [ISearchResult] | [] => {
+    // We create a bounding box just to get the tract in the view box.
+    // The size is not important.
+    const BOUNDING_BOX_SIZE_DD = 0.2;
+    if (tractSearch) {
+      // Convert 10 digit tracts to 11.
+      const searchTerm = tract.length == 10 ? '0' + tract : tract;
+      const result = tractSearch.search(searchTerm);
+      if (result.length > 0) {
+        const lat = Number(result[0].INTPTLAT10);
+        const lon = Number(result[0].INTPTLON10);
+        return [{
+          addresstype: 'tract',
+          boundingbox: [
+            (lat - (BOUNDING_BOX_SIZE_DD / 2)).toString(),
+            (lat + (BOUNDING_BOX_SIZE_DD / 2)).toString(),
+            (lon - (BOUNDING_BOX_SIZE_DD / 2)).toString(),
+            (lon + (BOUNDING_BOX_SIZE_DD / 2)).toString(),
+          ],
+          lat: result[0].INTPTLAT10,
+          lon: result[0].INTPTLON10,
+          type: 'tract',
+          place_rank: 1,
+        }];
+      }
+    }
+    return [];
+  };
+
   /*
     onSearchHandler will
      1. extract the search term from the input field
-     2. fetch data from the API and return the results as JSON and results to US only
-     3. if data is valid, destructure the boundingBox values from the search results
-     4. pan the map to that location
+     2. Determine if the search term is a Census Tract or not.
+     3. If it is a Census Tract, it will search the tract table for a bounding box.
+     4. If it is NOT a Census Tract, it will fetch data from the API and return the
+        results as JSON and results to US only. If data is valid, destructure the
+        boundingBox values from the search results.
+     4. Pan the map to that location
   */
   const onSearchHandler = async (event: React.FormEvent<HTMLFormElement>) => {
     event.preventDefault();
+    event.stopPropagation();
 
     const searchTerm = (event.currentTarget.elements.namedItem('search') as HTMLInputElement).value;
+    let searchResults = null;
 
-    const searchResults = await fetch(
-        `https://nominatim.openstreetmap.org/search?q=${searchTerm}&format=json&countrycodes=us`,
-        {
-          mode: 'cors',
-        })
-        .then((response) => {
-          if (!response.ok) {
-            throw new Error('Network response was not OK');
-          }
-          return response.json();
-        })
-        .catch((error) => {
-          console.error('There has been a problem with your fetch operation:', error);
-        });
-
+    // If the search term a Census tract
+    const isTract = /^\d{10,11}$/.test(searchTerm);
+    if (isTract) {
+      setIsSearchResultsNull(false);
+      searchResults = searchForTract(searchTerm);
+    } else {
+      searchResults = await fetch(
+          `https://nominatim.openstreetmap.org/search?q=${searchTerm}&format=json&countrycodes=us`,
+          {
+            mode: 'cors',
+          })
+          .then((response) => {
+            if (!response.ok) {
+              throw new Error('Network response was not OK');
+            }
+            return response.json();
+          })
+          .catch((error) => {
+            console.error('There has been a problem with your fetch operation:', error);
+          });
+      console.log('Nominatum search results: ', searchResults);
+    }
 
     // If results are valid, set isSearchResultsNull to false and pan map to location:
     if (searchResults && searchResults.length > 0) {
       setIsSearchResultsNull(false);
-      console.log('Nominatum search results: ', searchResults);
-
       const [latMin, latMax, longMin, longMax] = searchResults[0].boundingbox;
       goToPlace([[Number(longMin), Number(latMin)], [Number(longMax), Number(latMax)]]);
     } else {

client/src/components/MapSearch/__snapshots__/MapSearch.test.tsx.snap

@@ -23,7 +23,7 @@ exports[`rendering of the MapSearch checks if component renders 1`] = `
         data-testid="textInput"
         id="search-field"
         name="search"
-        placeholder="Search for an address, city, state or ZIP"
+        placeholder="Search for an address, city, state, ZIP or Census Tract"
         type="search"
       />
       <button

client/src/components/MapTractLayers/MapTractLayers.tsx

@@ -38,13 +38,8 @@ export const featureURLForTilesetName = (tilesetName: string): string => {
   } else {
     // The feature tile base URL and path can either point locally or the CDN.
     // This is selected based on the DATA_SOURCE env variable.
-    const featureTileBaseURL = process.env.DATA_SOURCE === 'local' ?
-        process.env.GATSBY_LOCAL_TILES_BASE_URL :
-        process.env.GATSBY_CDN_TILES_BASE_URL;
-
-    const featureTilePath = process.env.DATA_SOURCE === 'local' ?
-      process.env.GATSBY_DATA_PIPELINE_SCORE_PATH_LOCAL :
-      process.env.GATSBY_2_0_SCORE_PATH;
+    const featureTileBaseURL = constants.TILE_BASE_URL;
+    const featureTilePath = constants.TILE_PATH;
 
     return [
       featureTileBaseURL,

client/src/data/constants.tsx

@@ -380,3 +380,13 @@ export const CENSUS_TRACT_SURVEY_LINKS = {
   EN: "https://eop.gov1.qualtrics.com/jfe/form/SV_8J5wGa8Ya4dMP9c",
   ES: "https://eop.gov1.qualtrics.com/jfe/form/SV_eJXos5X4yekq6cC",
 };
+
+export const TILE_BASE_URL = process.env.DATA_SOURCE === "local" ?
+process.env.GATSBY_LOCAL_TILES_BASE_URL :
+process.env.GATSBY_CDN_TILES_BASE_URL;
+
+export const TILE_PATH = process.env.DATA_SOURCE === "local" ?
+process.env.GATSBY_DATA_PIPELINE_SCORE_PATH_LOCAL :
+process.env.GATSBY_1_0_SCORE_PATH;
+
+export const MAP_TRACT_SEARCH_PATH = "data_pipeline/data/score/search/tracts.json";

client/src/data/copy/explore.tsx

@@ -92,7 +92,7 @@ export const MAP = defineMessages({
   },
   SEARCH_PLACEHOLDER: {
     id: 'explore.map.page.map.search.placeholder.text',
-    defaultMessage: 'Search for an address, city, state or ZIP',
+    defaultMessage: 'Search for an address, city, state, ZIP or Census Tract',
     description: 'On the explore the map page, on the map, the placeholder text for search',
   },
   SEARCH_PLACEHOLDER_MOBILE: {

client/src/intl/en.json

@@ -688,7 +688,7 @@
     "description": "On the explore the map page, on the map, the placeholder text for search"
   },
   "explore.map.page.map.search.placeholder.text": {
-    "defaultMessage": "Search for an address, city, state or ZIP",
+    "defaultMessage": "Search for an address, city, state, ZIP or Census Tract",
     "description": "On the explore the map page, on the map, the placeholder text for search"
   },
   "explore.map.page.map.search.results.empty.text": {

client/src/intl/es.json

@@ -172,7 +172,7 @@
   "explore.map.page.map.layer.selector.tribal.long": "Tierras tribales",
   "explore.map.page.map.layer.selector.tribal.short": "Tribal",
   "explore.map.page.map.search.placeholder.mobile.text": "Búsqueda de ubicaciones ",
-  "explore.map.page.map.search.placeholder.text": "Busque una dirección, ciudad, estado o código postal.",
+  "explore.map.page.map.search.placeholder.text": "Busque una dirección, ciudad, estado, código postal o distrito censal.",
   "explore.map.page.map.search.results.empty.text": "No se encontró la ubicación o ubicación desconocida. Intente una búsqueda distinta.",
   "explore.map.page.map.territoryFocus.alaska.long": "Alaska",
   "explore.map.page.map.territoryFocus.alaska.short": "AK",

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

@@ -24,6 +24,7 @@ DATA_CENSUS_DIR = DATA_PATH / "census"
 DATA_CENSUS_CSV_DIR = DATA_CENSUS_DIR / "csv"
 DATA_CENSUS_CSV_FILE_PATH = DATA_CENSUS_CSV_DIR / "us.csv"
 DATA_CENSUS_CSV_STATE_FILE_PATH = DATA_CENSUS_CSV_DIR / "fips_states_2010.csv"
+DATA_CENSUS_GEOJSON_FILE_PATH = DATA_CENSUS_DIR / "geojson" / "us.json"
 
 # Score paths
 DATA_SCORE_DIR = DATA_PATH / "score"
@@ -46,6 +47,9 @@ DATA_SCORE_JSON_INDEX_FILE_PATH = (
 ## Tile path
 DATA_SCORE_TILES_DIR = DATA_SCORE_DIR / "tiles"
 
+## Tiles search
+DATA_TILES_SEARCH_DIR = DATA_SCORE_DIR / "search"
+
 # Downloadable paths
 if not os.environ.get("J40_VERSION_LABEL_STRING"):
     version_str = "beta"
@@ -82,6 +86,7 @@ SCORE_VERSIONING_README_FILE_NAME = f"readme-version-{version_str}.md"
 SCORE_VERSIONING_README_FILE_PATH = (
     FILES_PATH / SCORE_VERSIONING_README_FILE_NAME
 )
+SCORE_TRACT_SEARCH_FILE_PATH = DATA_TILES_SEARCH_DIR / "tracts.json"
 
 # For the codebook
 CEJST_SCORE_COLUMN_NAME = "score_name"

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

@@ -4,6 +4,7 @@ from pathlib import Path
 import numpy as np
 from numpy import float64
 import pandas as pd
+import geopandas as gpd
 
 from data_pipeline.content.schemas.download_schemas import CodebookConfig
 from data_pipeline.content.schemas.download_schemas import CSVConfig
@@ -42,10 +43,12 @@ class PostScoreETL(ExtractTransformLoad):
         self.input_counties_df: pd.DataFrame
         self.input_states_df: pd.DataFrame
         self.input_score_df: pd.DataFrame
+        self.input_census_geo_df: gpd.GeoDataFrame
 
         self.output_score_county_state_merged_df: pd.DataFrame
         self.output_score_tiles_df: pd.DataFrame
         self.output_downloadable_df: pd.DataFrame
+        self.output_tract_search_df: pd.DataFrame
 
         # Define some constants for the YAML file
         # TODO: Implement this as a marshmallow schema.
@@ -105,6 +108,18 @@ class PostScoreETL(ExtractTransformLoad):
 
         return df
 
+    def _extract_census_geojson(self, geo_path: Path) -> gpd.GeoDataFrame:
+        """
+        Read in the Census Geo JSON data.
+
+        Returns:
+           gpd.GeoDataFrame: the census geo json data
+        """
+        logger.debug("Reading Census GeoJSON")
+        with open(geo_path, "r", encoding="utf-8") as file:
+            data = gpd.read_file(file)
+        return data
+
     def extract(self, use_cached_data_sources: bool = False) -> None:
 
         super().extract(
@@ -131,6 +146,9 @@ class PostScoreETL(ExtractTransformLoad):
         self.input_score_df = self._extract_score(
             constants.DATA_SCORE_CSV_FULL_FILE_PATH
         )
+        self.input_census_geo_df = self._extract_census_geojson(
+            constants.DATA_CENSUS_GEOJSON_FILE_PATH
+        )
 
     def _transform_counties(
         self, initial_counties_df: pd.DataFrame
@@ -392,7 +410,23 @@ class PostScoreETL(ExtractTransformLoad):
 
         return final_df
 
+    def _create_tract_search_data(
+        self, census_geojson: gpd.GeoDataFrame
+    ) -> pd.DataFrame:
+        """
+        Generate a dataframe with only the tract IDs and the center lat/lon of each tract.
+
+        Returns:
+            pd.DataFrame: a dataframe with the tract search data
+        """
+        logger.debug("Creating Census tract search data")
+        columns_to_extract = ["GEOID10", "INTPTLAT10", "INTPTLON10"]
+        return pd.DataFrame(census_geojson[columns_to_extract])
+
     def transform(self) -> None:
+        self.output_tract_search_df = self._create_tract_search_data(
+            self.input_census_geo_df
+        )
         transformed_counties = self._transform_counties(self.input_counties_df)
         transformed_states = self._transform_states(self.input_states_df)
         transformed_score = self._transform_score(self.input_score_df)
@@ -409,6 +443,9 @@ class PostScoreETL(ExtractTransformLoad):
         self.output_score_county_state_merged_df = (
             output_score_county_state_merged_df
         )
+        self.output_tract_search_df = self._create_tract_search_data(
+            self.input_census_geo_df
+        )
 
     def _load_score_csv_full(
         self, score_county_state_merged: pd.DataFrame, score_csv_path: Path
@@ -592,6 +629,13 @@ class PostScoreETL(ExtractTransformLoad):
         ]
         zip_files(version_data_documentation_zip_path, files_to_compress)
 
+    def _load_search_tract_data(self, output_path: Path):
+        """Write the Census tract search data."""
+        logger.debug("Writing Census tract search data")
+        output_path.parent.mkdir(parents=True, exist_ok=True)
+        # We use the records orientation to easily import the JSON in JS.
+        self.output_tract_search_df.to_json(output_path, orient="records")
+
     def load(self) -> None:
         self._load_score_csv_full(
             self.output_score_county_state_merged_df,
@@ -600,4 +644,5 @@ class PostScoreETL(ExtractTransformLoad):
         self._load_tile_csv(
             self.output_score_tiles_df, constants.DATA_SCORE_CSV_TILES_FILE_PATH
         )
+        self._load_search_tract_data(constants.SCORE_TRACT_SEARCH_FILE_PATH)
         self._load_downloadable_zip(constants.SCORE_DOWNLOADABLE_DIR)

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

@@ -3,6 +3,7 @@ from importlib import reload
 from pathlib import Path
 
 import pandas as pd
+import geopandas as gpd
 import pytest
 from data_pipeline import config
 from data_pipeline.etl.score import etl_score_post
@@ -144,3 +145,13 @@ def downloadable_data_expected():
     return pd.read_pickle(
         pytest.SNAPSHOT_DIR / "downloadable_data_expected.pkl"
     )
+
+
+@pytest.fixture()
+def census_geojson_sample_data(sample_data_dir) -> gpd.GeoDataFrame:
+    with open(
+        sample_data_dir / "census_60.geojson", "r", encoding="utf-8"
+    ) as file:
+        data = gpd.read_file(file)
+        return data
+    return None

data/data-pipeline/data_pipeline/etl/score/tests/test_score_post.py

@@ -5,9 +5,12 @@ from pathlib import Path
 
 import pandas.api.types as ptypes
 import pandas.testing as pdt
+import pandas as pd
+import geopandas as gpd
 from data_pipeline.content.schemas.download_schemas import CSVConfig
 from data_pipeline.etl.score import constants
 from data_pipeline.utils import load_yaml_dict_from_file
+from data_pipeline.etl.score.etl_score_post import PostScoreETL
 
 # See conftest.py for all fixtures used in these tests
 
@@ -150,3 +153,16 @@ def test_load_downloadable_zip(etl, monkeypatch, score_data_expected):
     assert constants.SCORE_DOWNLOADABLE_EXCEL_FILE_PATH.is_file()
     assert constants.SCORE_DOWNLOADABLE_CSV_ZIP_FILE_PATH.is_file()
     assert constants.SCORE_DOWNLOADABLE_XLS_ZIP_FILE_PATH.is_file()
+
+
+def test_create_tract_search_data(census_geojson_sample_data: gpd.GeoDataFrame):
+    # Sanity check
+    assert len(census_geojson_sample_data) > 0
+    
+    result = PostScoreETL()._create_tract_search_data(census_geojson_sample_data)
+    assert isinstance(result, pd.DataFrame)
+    assert not result.columns.empty
+    columns = ["GEOID10", "INTPTLAT10", "INTPTLON10"]
+    for col in columns:
+        assert col in result.columns
+    assert len(census_geojson_sample_data) == len(result)