get-weather-data 3.0.0

Get historical weather data for US ZIP codes from NOAA stations

Get Weather Data

Get historical weather data for US ZIP codes. Uses NOAA weather station data (GHCN Daily and GSOD) with automatic station selection based on proximity.

Installation

pip install get-weather-data

Or with uv:

uv pip install get-weather-data

Quick Start

Python API

from get_weather_data import Weather

# Initialize and set up database (downloads ~50MB first time)
weather = Weather()
weather.setup()

# Get weather for a ZIP code and date
result = weather.get("10001", "2024-01-15")

print(f"Max temp: {result.tmax / 10:.1f} °C")
print(f"Min temp: {result.tmin / 10:.1f} °C")
print(f"Station: {result.station_name}")

Command Line

# Set up database (first time only)
get-weather setup

# Get weather for a location and date
get-weather get 10001 2024-01-15

# Process a CSV file
get-weather process input.csv output.csv

Features

• Simple API: One class, three methods: setup(), get(), process_csv()
• Automatic station selection: Finds nearest weather stations for each ZIP code
• Two data sources: GHCN Daily (~100K US stations) and GSOD (~3K stations)
• Batch processing: Process CSV files with ZIP codes and dates
• Local database: SQLite database for fast repeated queries
• CLI tool: Command-line interface for quick lookups

Usage Examples

Get Weather for a Date Range

from datetime import date
from get_weather_data import Weather

weather = Weather()

results = weather.get_range(
    zipcode="90210",
    start_date=date(2024, 7, 1),
    end_date=date(2024, 7, 7),
)

for r in results:
    print(f"{r.date}: High {r.tmax/10:.0f}°C, Low {r.tmin/10:.0f}°C")

Process a CSV File

from get_weather_data import Weather

weather = Weather()

# Input CSV should have zip, year, month, day columns
weather.process_csv(
    input_path="locations.csv",
    output_path="locations_with_weather.csv",
    zipcode_column="zip",
    year_column="year",
    month_column="month",
    day_column="day",
)

More examples in the examples/ directory.

Data Sources

This package uses data from NOAA's National Centers for Environmental Information:

• GHCN Daily: Global Historical Climatology Network daily summaries
• GSOD: Global Summary of the Day from USAF/WBAN stations
• GeoNames: ZIP code to coordinates mapping

Weather Variables

Variable	Description	Unit
tmax	Maximum temperature	tenths of °C
tmin	Minimum temperature	tenths of °C
tavg	Average temperature	tenths of °C
prcp	Precipitation	tenths of mm
snow	Snowfall	mm
snwd	Snow depth	mm
awnd	Average wind speed	tenths of m/s

Database Setup

The first time you run setup(), the package downloads:

• GHCN station list (~20K US stations)
• ISD station list (~3K US stations)
• US ZIP code coordinates from GeoNames

Then it builds an index mapping each ZIP code to nearby weather stations. This takes a few minutes but only needs to be done once.

weather = Weather()
weather.setup()  # Downloads data, builds index

# Check what was imported
info = weather.info()
print(f"GHCN stations: {info['ghcn_stations']:,}")
print(f"USAF stations: {info['usaf_stations']:,}")
print(f"ZIP codes: {info['zipcodes']:,}")

Configuration

Custom database location:

weather = Weather(database_path="/path/to/my.db")

Or via CLI:

get-weather --database /path/to/my.db setup

License

MIT License. See LICENSE for details.

Authors

• Suriyan Laohaprapanon
• Gaurav Sood