Skip to main content

EDITION2! A python package to support forecast submission, evaluation and access to FTP site for DESTIN-E S2S AI prediction project

Project description

AI_weather_quest

To participate in the AI Weather Quest, you will need to install the AI-WQ-package Python package. This package requires Python version 3, and its source code is available on GitHub.

AI-WQ-package is a Python library designed to streamline participation in the AI Weather Quest. This guide provides step-by-step instructions on how to:

  • Submit a forecast to the AI Weather Quest competition.
  • Evaluate sub-seasonal forecasts using tools developed by the AI Weather Quest.
  • Download training data for initially developing sub-seasonal forecast models.

The package leverages capability developed through xarray for efficient data handling.

We highly recommend use the ReadTheDocs documentation as a guide for using this package: https://ecmwf-ai-weather-quest.readthedocs.io/en/latest/

Installation

To install the AI-WQ-package on Linux, run the following command:

python3 -m pip install AI-WQ-package

For guidance on installing Python 3 or pip, refer to the official documentation.

Dependencies

The AI-WQ-package requires the following dependencies:

  • numpy (version 1.23 or higher)
  • xarray (version 2024.09.0 or higher)
  • dask (version 2024.9.0)
  • pandas (version 2.2.3 or higher)
  • scipy (version 1.14.1 or higher)
  • netCDF4 (version 1.7.2 or higher)
  • requests (versions 2.32.2 or higher)
  • matplotlib (versions 3.8 or higher)
  • cartopy (versions 0.22 or higher)

If these dependencies conflict with your current working environment, consider installing the package in a new virtual environment.

Upgrading the Package

To upgrade to the latest version, run:

python3 -m pip install --upgrade AI-WQ-package

This project is being actively developed. New updates may be released periodically with detailed annoucements given on the ECMWF-hosted forum.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

ai_wq_package_edition2-1.0.6.tar.gz (33.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

ai_wq_package_edition2-1.0.6-py3-none-any.whl (37.5 kB view details)

Uploaded Python 3

File details

Details for the file ai_wq_package_edition2-1.0.6.tar.gz.

File metadata

  • Download URL: ai_wq_package_edition2-1.0.6.tar.gz
  • Upload date:
  • Size: 33.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.11

File hashes

Hashes for ai_wq_package_edition2-1.0.6.tar.gz
Algorithm Hash digest
SHA256 48633289a328814d84dec9a10a10cb232104a96e41358c16b19f353128754e99
MD5 8b6b0a014e81f9219580a1e9e5275429
BLAKE2b-256 c03dec2dfef14cf9ddb7bd29ad132a5905fa00893b506bcc456deb1a5c27748b

See more details on using hashes here.

File details

Details for the file ai_wq_package_edition2-1.0.6-py3-none-any.whl.

File metadata

File hashes

Hashes for ai_wq_package_edition2-1.0.6-py3-none-any.whl
Algorithm Hash digest
SHA256 400ea7763c96681c958dc6d96aba3193539a4c873e1cd3b740267fec52d809bf
MD5 cf5ab81e1272d6cc93c76d57a5ae7c35
BLAKE2b-256 c3f358865749b6175bea555474dfce60d815b5e270e9275a74743b8e259ab036

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page