The Meteostat Python library provides a simple API for accessing open weather and climate data. The historical observations and statistics are collected by Meteostat from different public interfaces, most of which are governmental.

Among the data sources are national weather services like the National Oceanic and Atmospheric Administration (NOAA) and Germany's national meteorological service (DWD).

Are you looking for a hosted solution? Try our JSON API.

The Meteostat Python package is available through PyPI:

pip install meteostat

Meteostat requires Python 3.6 or higher. If you want to visualize data, please install Matplotlib, too.

The Meteostat Python library is divided into multiple classes which provide access to the actual data. The documentation covers all aspects of the library:

• Selecting Locations
  • Geographical Point
  • Weather Stations
• Time Series
  • Hourly Data
  • Daily Data
  • Monthly Data
• Miscellaneous Data
  • Climate Normals
• Library
  • Contributing
  • Formats & Units
  • Data Sources
  • Terms & License

Let's plot 2018 temperature data for Vancouver, BC:

# Import Meteostat library and dependencies
from datetime import datetime
import matplotlib.pyplot as plt
from meteostat import Point, Daily

# Set time period
start = datetime(2018, 1, 1)
end = datetime(2018, 12, 31)

# Create Point for Vancouver, BC
location = Point(49.2497, -123.1193, 70)

# Get daily data for 2018
data = Daily(location, start, end)
data = data.fetch()

# Plot line chart including average, minimum and maximum temperature
data.plot(y=['tavg', 'tmin', 'tmax'])
plt.show()

Take a look at the expected output:

Instructions on building and testing the Meteostat Python package can be found in the documentation. More information about the Meteostat bulk data interface is available here.

If you want to support the project financially, you can make a donation using one of the following services:

• GitHub
• Patreon
• PayPal

Meteorological data is provided under the terms of the Creative Commons Attribution-NonCommercial 4.0 International Public License (CC BY-NC 4.0). You may build upon the material for any purpose, even commercially. However, you are not allowed to redistribute Meteostat data "as-is" for commercial purposes.

By using the Meteostat Python library you agree to our terms of service. All meteorological data sources used by the Meteostat project are listed here.

The code of this library is available under the MIT license.