python-CIMIS 1.1.0

A comprehensive Python client for the California Irrigation Management Information System (CIMIS) API

Python CIMIS Client

A comprehensive Python client library for the California Irrigation Management Information System (CIMIS) API. This library provides easy access to CIMIS weather station data, spatial data, and station information with built-in CSV export functionality.

Features

• Comprehensive API Coverage: Access all CIMIS API endpoints including weather data, station information, and zip code data
• Multiple Data Sources: Support for both Weather Station Network (WSN) and Spatial CIMIS System (SCS) data
• Flexible Data Retrieval: Get data by station numbers, zip codes, coordinates, or street addresses
• Built-in CSV Export: Export all data with comprehensive column coverage by default
• Easy to Use: Simple, Pythonic interface with sensible defaults
• Error Handling: Comprehensive exception handling with descriptive error messages
• Type Hints: Full type hint support for better IDE integration

Installation

Install from PyPI:

pip install python-CIMIS

Quick Start

from python_cimis import CimisClient
from datetime import date

# Initialize the client with your API key
client = CimisClient(app_key="your-api-key-here")

# Get daily weather data for specific stations
weather_data = client.get_daily_data(
    targets=[2, 8, 127],  # Station numbers
    start_date="2023-01-01",
    end_date="2023-01-05"
)

# Export to CSV with all available columns
client.export_to_csv(weather_data, "weather_data.csv")

# Or get data and export in one step
weather_data = client.get_data_and_export_csv(
    targets=[2, 8, 127],
    start_date=date(2023, 1, 1),
    end_date=date(2023, 1, 5),
    filename="comprehensive_weather_data.csv"
)

API Key

You need a CIMIS API key to use this library. You can obtain one by registering at the CIMIS website.

Usage Examples

Getting Weather Data

By Station Numbers

# Get data for specific weather stations
weather_data = client.get_daily_data(
    targets=[2, 8, 127],
    start_date="2023-01-01",
    end_date="2023-01-31",
    unit_of_measure="E"  # English units (default)
)

By Zip Codes

# Get data for specific zip codes
weather_data = client.get_daily_data(
    targets=["95823", "94503", "93624"],
    start_date="2023-01-01",
    end_date="2023-01-31",
    prioritize_scs=True  # Prioritize Spatial CIMIS System data
)

By Coordinates

# Get data for specific coordinates
weather_data = client.get_data(
    targets=["lat=39.36,lng=-121.74", "lat=38.22,lng=-122.82"],
    start_date="2023-01-01",
    end_date="2023-01-31",
    data_items=["day-asce-eto", "day-sol-rad-avg"]  # Only ETo and solar radiation
)

By Addresses

# Get data for specific addresses
weather_data = client.get_data(
    targets=[
        "addr-name=State Capitol,addr=1315 10th Street Sacramento, CA 95814",
        "addr-name=SF City Hall,addr=1 Dr Carlton B Goodlett Pl, San Francisco, CA 94102"
    ],
    start_date="2023-01-01",
    end_date="2023-01-31",
    data_items=["day-asce-eto", "day-sol-rad-avg"]
)

Getting Station Information

# Get all stations
all_stations = client.get_stations()

# Get specific station
station = client.get_stations(station_number="2")

# Export stations to CSV
client.export_stations_to_csv(all_stations, "all_stations.csv")

Getting Zip Code Information

# Get station zip codes
station_zip_codes = client.get_station_zip_codes()

# Get spatial zip codes
spatial_zip_codes = client.get_spatial_zip_codes()

Custom Data Items

# Specify custom data items
custom_data_items = [
    "day-air-tmp-avg", "day-air-tmp-max", "day-air-tmp-min",
    "day-precip", "day-eto", "day-asce-eto"
]

weather_data = client.get_daily_data(
    targets=[2, 8, 127],
    start_date="2023-01-01",
    end_date="2023-01-31",
    data_items=custom_data_items
)

Hourly Data

# Get hourly data (only available from WSN stations)
hourly_data = client.get_hourly_data(
    targets=[2, 8, 127],
    start_date="2023-01-01",
    end_date="2023-01-01"  # Note: Hourly data requests should be for shorter periods
)

CSV Export Features

The library provides comprehensive CSV export functionality:

• All Columns by Default: Exports all available data columns automatically
• Quality Control Information: Includes QC flags and units for each data point
• Provider Information: Identifies data source (WSN or SCS)
• Flexible Output: Customizable column selection and formatting

CSV Export Example

# Export with all available columns (default behavior)
client.export_to_csv(weather_data, "complete_data.csv")

# The CSV will include columns like:
# Provider_Name, Provider_Type, Date, Julian, Station, Standard, ZipCodes, Scope, Hour,
# day-air-tmp-avg_Value, day-air-tmp-avg_QC, day-air-tmp-avg_Unit,
# day-air-tmp-max_Value, day-air-tmp-max_QC, day-air-tmp-max_Unit,
# ... (all available data items)

Available Data Items

Daily Data Items (WSN + SCS)

• Temperature: day-air-tmp-avg, day-air-tmp-max, day-air-tmp-min
• Humidity: day-rel-hum-avg, day-rel-hum-max, day-rel-hum-min
• Evapotranspiration: day-eto, day-asce-eto, day-asce-etr
• Solar Radiation: day-sol-rad-avg, day-sol-rad-net
• Wind: day-wind-spd-avg, day-wind-run, directional wind components
• Soil: day-soil-tmp-avg, day-soil-tmp-max, day-soil-tmp-min
• Other: day-precip, day-dew-pnt, day-vap-pres-avg, day-vap-pres-max

Hourly Data Items (WSN only)

• Temperature: hly-air-tmp, hly-soil-tmp
• Humidity: hly-rel-hum
• Evapotranspiration: hly-eto, hly-asce-eto, hly-asce-etr
• Solar: hly-sol-rad, hly-net-rad
• Wind: hly-wind-spd, hly-wind-dir, hly-res-wind
• Other: hly-precip, hly-dew-pnt, hly-vap-pres

Error Handling

The library provides comprehensive error handling:

from python_cimis import CimisClient, CimisAPIError, CimisAuthenticationError

client = CimisClient("your-api-key")

try:
    weather_data = client.get_daily_data(
        targets=[999999],  # Invalid station
        start_date="2023-01-01",
        end_date="2023-01-01"
    )
except CimisAuthenticationError:
    print("Invalid API key")
except CimisAPIError as e:
    print(f"API Error: {e}")

Data Models

The library includes comprehensive data models:

• WeatherData: Container for weather data responses
• WeatherRecord: Individual weather data records
• Station: Weather station information
• ZipCode: Zip code information for WSN stations
• SpatialZipCode: Zip code information for SCS data

Requirements

• Python 3.8+
• requests >= 2.25.0

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Disclaimer

This library is not affiliated with the California Department of Water Resources or the CIMIS program. It is an independent client library for accessing the public CIMIS API.

Links

• CIMIS Website
• CIMIS API Documentation
• California Department of Water Resources