Measure Space API Python Package

A Python package for accessing weather, climate, air quality, agriculture, pollen, and geocoding APIs provided by MeasureSpace.io.

Features

Global Hourly Weather Forecast

• 5-day forecast at hourly frequency and global scale
• over 20 common weather variables with timezone and weather icons
• available at local and UTC time
• imperial and metric units
• support agriculture, logistics, IoT and many other general weather applications

Global Daily Weather Forecast

• 15-day forecast at daily frequency and global scale
• over 30 common weather variables with timezone, sunrise, sunset and weather icons
• available at local and UTC time
• daytime and nighttime aggregations
• imperial and metric units
• support agriculture, logistics, IoT and many other general weather applications

Global Climate Forecast

• 10-month forecast at daily frequency and global scale
• 11 common variables
• imperial and metric units
• support agriculture and many other general climate applications

Global Air Quality Forecast

• 5-day air quality forecast at hourly and daily frequency and global scale
• 7 common air pollutants including Air Quality Index
• help people plan outdoor activities and make health product marketing more efficient

Global City Geocoding

• dedicated to city geocoding and reverse geocoding
• autocomplete for more than 200,000 cities from 245 countries
• get matched cities based on user inputs
• convert city names to corresponding latitude and longitude info
• find nearest city based on latitude and longitude
• live demo through our weather dashboard search city feature

Agriculture

• growing degree days forecast
• growth stage forecast
• heat stress forecast
• frost stress forecast
• data from past year to next 9 months
• imperial and metric units
• support major crops like corn, soybean, wheat, rice and many others

Global Pollen Forecast

• 10-day pollen forecast at daily frequency and global scale
• 3 common pollen types
• help people plan outdoor activities and make health product marketing more efficient

Installation

Clone the repository and install dependencies:

pip install -e .

Or install from PyPI:

pip install measure-space-api

Usage

Get Weather, Climate, Air Quality, Agriculture and Pollen Variables

Import the package and call the functions:

from measure_space_api import (
    get_hourly_weather, get_daily_weather, get_daily_climate,
    get_hourly_air_quality, get_daily_air_quality,
    get_lat_lon_from_city, get_city_from_lat_lon,
    get_daily_pollen, get_growing_degree_days,
    get_heat_stress_days, get_frost_stress_days,
    get_growth_stage,
)

# Example: Get hourly weather by coordinates
api_key = "YOUR_API_KEY"
params = {
    # Variable names and meaning can be found at https://measurespace.io/documentation#global-hourly-weather-forecast-variables
    "variables": "tp,t2m",
    "unit": "metric"
}
df = get_hourly_weather(api_key, latitude=40.2, longitude=110.2, params=params, return_json=False)
print(df.head())

# Example: Get hourly weather by city name
geocoding_api_key = "YOUR_GEOCODING_API_KEY"
df = get_hourly_weather(api_key, geocoding_api_key, location_name="Beijing", params=params, return_json=False)
print(df.head())

# Example: get metadata (variable description, unit)
get_metadata('tp', unit='metric')

# Example: Get daily pollen forecast by coordinates
pollen_api_key = "YOUR_POLLEN_API_KEY"
data = get_daily_pollen(pollen_api_key, latitude=40.2, longitude=-74.0)
print(data)

# Example: Get daily pollen forecast by city name
data = get_daily_pollen(pollen_api_key, geocoding_api_key=geocoding_api_key, location_name="New York")
print(data)

# Example: Get growing degree days
ag_api_key = "YOUR_AGRICULTURE_API_KEY"
params = {
    'start_date': '2025-01-01',
    'end_date': '2025-06-01',
    'base_temperature': 50,
    'unit': 'F',
}
data = get_growing_degree_days(ag_api_key, latitude=40.2, longitude=-89.0, params=params)
print(data)

# Example: Get crop growth stage
params = {
    'start_date': '2025-04-01',
    'end_date': '2025-09-01',
    'crop_name': 'corn',
    'unit': 'F',
}
data = get_growth_stage(ag_api_key, latitude=40.2, longitude=-89.0, params=params)
print(data)

# Example: Get heat stress days
params = {
    'start_date': '2025-06-01',
    'end_date': '2025-08-31',
    'crop_name': 'corn',
    'heat_stress_threshold': 95,
}
data = get_heat_stress_days(ag_api_key, latitude=40.2, longitude=-89.0, params=params)
print(data)

# Example: Get frost stress days
params = {
    'start_date': '2025-10-01',
    'end_date': '2025-12-31',
    'frost_stress_threshold': 32,
}
data = get_frost_stress_days(ag_api_key, latitude=40.2, longitude=-89.0, params=params)
print(data)

Get City Coordinates

from measure_space_api.main import get_lat_lon_from_city
lat, lon = get_lat_lon_from_city(geocoding_api_key, "Shanghai")
print(lat, lon)

Use Environment Variables

You may use a .env file to store your API keys and load them with python-dotenv.

HOURLY_WEATHER_API_KEY=your_hourly_weather_key
DAILY_WEATHER_API_KEY=your_daily_weather_key
DAILY_CLIMATE_API_KEY=your_daily_climate_key
AIR_QUALITY_API_KEY=your_air_quality_key
GEOCODING_API_KEY=your_geocoding_key
POLLEN_API_KEY=your_pollen_key
GROWING_DEGREE_DAYS_API_KEY=your_growing_degree_days_key
HEAT_STRESS_DAYS_API_KEY=your_heat_stress_days_key
FROST_STRESS_DAYS_API_KEY=your_frost_stress_days_key
GROWTH_STAGE_API_KEY=your_growth_stage_key

Call API using API keys from .env file.

from measure_space_api import (
    get_hourly_weather, get_daily_weather, get_daily_climate,
    get_hourly_air_quality, get_daily_air_quality,
    get_lat_lon_from_city, get_city_from_lat_lon,
    get_daily_pollen, get_growing_degree_days,
    get_heat_stress_days, get_frost_stress_days,
    get_growth_stage,
)
from dotenv import load_dotenv
import os

# Load environment variables from .env file
load_dotenv()
# Example: Get hourly weather by coordinates
params = {
    # Variable names and meaning can be found at https://measurespace.io/documentation#global-hourly-weather-forecast-variables
    "variables": "tp,t2m",
    "unit": "metric"
}
df = get_hourly_weather(HOURLY_WEATHER_API_KEY, latitude=40.2, longitude=110.2, params=params, return_json=False)
print(df.head())

API Functions

Weather and Climate

• get_hourly_weather(api_key, geocoding_api_key=None, location_name=None, latitude=None, longitude=None, params={'variables': 'tp, t2m', 'unit': 'metric'}, return_json=True)
• get_daily_weather(api_key, geocoding_api_key=None, location_name=None, latitude=None, longitude=None, params={'variables': 'tp, minT, maxT', 'unit': 'metric'}, return_json=True)
• get_daily_climate(api_key, geocoding_api_key=None, location_name=None, latitude=None, longitude=None, params={'variables': 'tp, tmin, tmax', 'unit': 'metric'}, return_json=True)

Air Quality

• get_hourly_air_quality(api_key, geocoding_api_key=None, location_name=None, latitude=None, longitude=None, params={'variables': 'AQI, DP'}, return_json=True)
• get_daily_air_quality(api_key, geocoding_api_key=None, location_name=None, latitude=None, longitude=None, params={'variables': 'AQI'}, return_json=True)

Pollen

• get_daily_pollen(api_key, geocoding_api_key=None, location_name=None, latitude=None, longitude=None, params={}, return_json=True)

Agriculture

• get_growing_degree_days(api_key, latitude, longitude, params={'start_date': None, 'end_date': None, 'base_temperature': 50, 'lower_cutoff': None, 'upper_cutoff': None, 'unit': 'F'}, return_json=True)
• get_growth_stage(api_key, latitude, longitude, params={'start_date': None, 'end_date': None, 'crop_name': None, 'unit': 'F'}, return_json=True)
• get_heat_stress_days(api_key, latitude, longitude, params={'start_date': None, 'end_date': None, 'crop_name': None, 'heat_stress_threshold': None}, return_json=True)
• get_frost_stress_days(api_key, latitude, longitude, params={'start_date': None, 'end_date': None, 'frost_stress_threshold': None}, return_json=True)

Geocoding

• get_lat_lon_from_city(api_key, location_name)
• get_city_from_lat_lon(api_key, latitude, longitude)

Parameters

• api_key: Your API key for the weather/climate/air quality service
• geocoding_api_key: (Optional) API key for geocoding service
• location_name: (Optional) City name (e.g., "New York", "Beijing, China")
• latitude, longitude: (Optional) Coordinates
• params: (Optional) Dictionary of additional API parameters (e.g., variables, units, local_flag)
• return_json: If True, returns JSON; if False, returns a pandas DataFrame

API Documentation

• See MeasureSpace API Explorer for details on endpoints and parameters.
• See MeasureSpace Documentation for variable names and meanings.

Publish to PyPI

• uv build
• uv publish --token <your-pypi-token>

License

Apache License