├── requirements.txt ├── LICENSE ├── README.md ├── locator.py └── .gitignore /requirements.txt: -------------------------------------------------------------------------------- 1 | requests==2.31.0 2 | geopandas==0.14.3 3 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | MIT License 2 | 3 | Copyright (c) 2024 Amir Boroumand 4 | 5 | Permission is hereby granted, free of charge, to any person obtaining a copy 6 | of this software and associated documentation files (the "Software"), to deal 7 | in the Software without restriction, including without limitation the rights 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 9 | copies of the Software, and to permit persons to whom the Software is 10 | furnished to do so, subject to the following conditions: 11 | 12 | The above copyright notice and this permission notice shall be included in all 13 | copies or substantial portions of the Software. 14 | 15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 21 | SOFTWARE. 22 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | Python MIT License 2 | 3 | # School District Locator 4 | 5 | The School District Locator is a Python tool designed to map any given street address in the United States to its corresponding school district. Utilizing the U.S. Census Bureau Geocoding Services API for address geocoding and GeoPandas for spatial analysis with school district shapefiles, this tool provides a quick and accurate lookup for determining the school district of a particular address. 6 | 7 | ## Features 8 | 9 | - Address to school district mapping 10 | - Utilizes U.S. Census Bureau Geocoding Services for precise address location 11 | - Spatial analysis with GeoPandas for accurate district identification 12 | - Supports Shapefile boundary file format 13 | 14 | ## Getting Started 15 | 16 | ### Prerequisites 17 | 18 | Ensure you have Python 3.6+ installed on your system. 19 | 20 | ### Installation 21 | 22 | Clone the repository to your local machine: 23 | 24 | ```bash 25 | git clone https://github.com/steelcityamir/school-district-locator.git 26 | ``` 27 | 28 | Navigate to the cloned directory: 29 | 30 | ```bash 31 | cd school-district-locator 32 | ``` 33 | 34 | Install the required libraries using pip: 35 | 36 | ```bash 37 | pip install -r requirements.txt 38 | ``` 39 | 40 | ### Download boundary data from NECS 41 | 42 | 1. Go to https://data-nces.opendata.arcgis.com/datasets/nces::school-district-boundaries-current/about 43 | 2. Click Download button to view file formats 44 | 3. Look for the Shapefile and click Download 45 | 4. This will download a zip file containing the shapefile and associated files 46 | 5. Unzip the files into the repo directory 47 | 6. Rename the files to: 48 | - `school_district_boundaries.cpg` 49 | - `school_district_boundaries.dbf` 50 | - `school_district_boundaries.prj` 51 | - `school_district_boundaries.shp` 52 | - `school_district_boundaries.shx` 53 | - `school_district_boundaries.xml` 54 | 55 | ### Usage 56 | 57 | Run the script from your command line: 58 | 59 | ```bash 60 | python3 locator.py 61 | ``` 62 | 63 | Follow the on-screen prompts to input the street address, city, state, and ZIP code for the location you're interested in. 64 | 65 | ![screenshot](https://github.com/steelcityamir/school-district-locator/assets/54147931/10f754b4-fc2e-4eac-8d7b-d18bd7a6a5a9) 66 | 67 | 68 | ## License 69 | 70 | This project is licensed under the MIT License - see the LICENSE file for details. 71 | 72 | ## Acknowledgments 73 | 74 | - U.S. Census Bureau for providing the Geocoding Services API. 75 | - National Center for Education Statistics (NECS) for providing school district data. 76 | - The GeoPandas team for their excellent work on the geospatial analysis library. 77 | 78 | ## Support 79 | 80 | For support, please open an issue in the GitHub issue tracker for this project. 81 | -------------------------------------------------------------------------------- /locator.py: -------------------------------------------------------------------------------- 1 | import requests 2 | import geopandas as gpd 3 | from shapely.geometry import Point 4 | from typing import Tuple, Optional 5 | 6 | def geocode_address(street: str, city: str, state: str, zip_code: str) -> Optional[Tuple[float, float]]: 7 | """ 8 | Geocode a street address using the U.S. Census Bureau Geocoding Services API. 9 | 10 | Parameters: 11 | - street: The street address 12 | - city: The city name 13 | - state: The state abbreviation 14 | - zip_code: The ZIP code 15 | 16 | Returns: 17 | - A tuple containing the latitude and longitude (lat, lon) of the address, or None if not found. 18 | """ 19 | url = "https://geocoding.geo.census.gov/geocoder/locations/address" 20 | params = { 21 | "street": street, 22 | "city": city, 23 | "state": state, 24 | "zip": zip_code, 25 | "benchmark": "Public_AR_Current", 26 | "format": "json", 27 | } 28 | 29 | try: 30 | response = requests.get(url, params=params) 31 | response.raise_for_status() # Raises HTTPError for bad responses 32 | 33 | # Parse the JSON response 34 | data = response.json() 35 | if data['result']['addressMatches']: 36 | match = data['result']['addressMatches'][0] 37 | coordinates = match['coordinates'] 38 | lat = coordinates['y'] 39 | lon = coordinates['x'] 40 | return (lat, lon) 41 | else: 42 | print("No match found for this address.") 43 | return None 44 | except requests.RequestException as e: 45 | print(f"Request failed: {e}") 46 | return None 47 | 48 | def find_school_district(lat: float, lon: float) -> str: 49 | """ 50 | Identifies the school district for a given latitude and longitude using a shapefile. 51 | 52 | This function loads a shapefile containing school district boundaries, creates a point 53 | from the provided latitude and longitude, and checks which school district polygon contains 54 | the point. It returns the name of the school district if found. 55 | 56 | Parameters: 57 | - lat (float): The latitude of the address. 58 | - lon (float): The longitude of the address. 59 | 60 | Returns: 61 | - str: The name of the school district the address belongs to, or "District not found" if not found. 62 | """ 63 | 64 | # Load the shapefile 65 | gdf = gpd.read_file('school_district_boundaries.shp') 66 | 67 | # Create a Point object from the latitude and longitude 68 | point = Point(lon, lat) 69 | 70 | # Check which polygon from the shapefile contains the point 71 | # The result is a GeoDataFrame with the rows that match the condition 72 | containing_district = gdf[gdf.contains(point)] 73 | 74 | if not containing_district.empty: 75 | # Assuming the district name is in a column named 'NAME' 76 | return containing_district.iloc[0]['NAME'] 77 | else: 78 | return "District not found." 79 | 80 | if __name__ == "__main__": 81 | street = input("Enter the street address: ") 82 | city = input("Enter the city: ") 83 | state = input("Enter the state abbreviation: ") 84 | zip_code = input("Enter the ZIP code: ") 85 | 86 | coordinates = geocode_address(street, city, state, zip_code) 87 | 88 | if coordinates: 89 | lat, lon = coordinates 90 | district_name = find_school_district(lat, lon) 91 | print(f"The address is in the school district: {district_name}") 92 | else: 93 | print("Unable to geocode the address.") 94 | -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | # Byte-compiled / optimized / DLL files 2 | __pycache__/ 3 | *.py[cod] 4 | *$py.class 5 | 6 | # C extensions 7 | *.so 8 | 9 | # Distribution / packaging 10 | .Python 11 | build/ 12 | develop-eggs/ 13 | dist/ 14 | downloads/ 15 | eggs/ 16 | .eggs/ 17 | lib/ 18 | lib64/ 19 | parts/ 20 | sdist/ 21 | var/ 22 | wheels/ 23 | share/python-wheels/ 24 | *.egg-info/ 25 | .installed.cfg 26 | *.egg 27 | MANIFEST 28 | 29 | # PyInstaller 30 | # Usually these files are written by a python script from a template 31 | # before PyInstaller builds the exe, so as to inject date/other infos into it. 32 | *.manifest 33 | *.spec 34 | 35 | # Installer logs 36 | pip-log.txt 37 | pip-delete-this-directory.txt 38 | 39 | # Unit test / coverage reports 40 | htmlcov/ 41 | .tox/ 42 | .nox/ 43 | .coverage 44 | .coverage.* 45 | .cache 46 | nosetests.xml 47 | coverage.xml 48 | *.cover 49 | *.py,cover 50 | .hypothesis/ 51 | .pytest_cache/ 52 | cover/ 53 | 54 | # Translations 55 | *.mo 56 | *.pot 57 | 58 | # Django stuff: 59 | *.log 60 | local_settings.py 61 | db.sqlite3 62 | db.sqlite3-journal 63 | 64 | # Flask stuff: 65 | instance/ 66 | .webassets-cache 67 | 68 | # Scrapy stuff: 69 | .scrapy 70 | 71 | # Sphinx documentation 72 | docs/_build/ 73 | 74 | # PyBuilder 75 | .pybuilder/ 76 | target/ 77 | 78 | # Jupyter Notebook 79 | .ipynb_checkpoints 80 | 81 | # IPython 82 | profile_default/ 83 | ipython_config.py 84 | 85 | # pyenv 86 | # For a library or package, you might want to ignore these files since the code is 87 | # intended to run in multiple environments; 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