aiowwlln 0.1.0

A simple Python API for the WWLLN

⚡️ aiowwlln: A simple Python3 wrapper for WWLLN

aiowwlln is a simple, asyncio-driven Python library for retrieving information on lightning strikes from the World Wide Lightning Location Network (WWLLNN).

NOTE: This library is built on an unofficial API; therefore, it may stop working at any time.

Installation

pip install aiowwlln

Python Versions

aiowwlln is currently supported on:

• Python 3.5
• Python 3.6
• Python 3.7

However, running the test suite currently requires Python 3.6 or higher; tests run on Python 3.5 will fail.

Usage

aiowwlln starts within an aiohttp ClientSession:

import asyncio

from aiohttp import ClientSession

from aiowwlln import Client


async def main() -> None:
    """Create the aiohttp session and run the example."""
    async with ClientSession() as websession:
        # YOUR CODE HERE


asyncio.get_event_loop().run_until_complete(main())

Create a client, initialize it, then get to it:

import asyncio

from aiohttp import ClientSession

from aiowwlln import Client


async def main() -> None:
    """Create the aiohttp session and run the example."""
    async with ClientSession() as websession:
        client = aiowwlln.Client(websession)

        # Create a client:
        client = Client(websession)

        # Get all strike data:
        await client.dump()

        # Get strike data within a 50 km radius around a set of coordinates:
        await client.within_radius(
            56.1621538, 92.2333561, 50
        )

        # Get strike data within a 10 mile radius around a set of coordinates:
        await client.within_radius(
            56.1621538, 92.2333561, 10, unit="imperial"
        )

        # Get the nearest strike to a set of coordinates:
        await client.nearest(56.1621538, 92.2333561)


asyncio.get_event_loop().run_until_complete(main())

Contributing

1. Check for open features/bugs or initiate a discussion on one.
2. Fork the repository.
3. Install the dev environment: make init.
4. Enter the virtual environment: pipenv shell
5. Code your new feature or bug fix.
6. Write a test that covers your new functionality.
7. Run tests and ensure 100% code coverage: make coverage
8. Add yourself to AUTHORS.md.
9. Submit a pull request!