Skip to main content

Ensemble forecast time series

Project description

efts-io

ci documentation pypi version

Overview

Plain text files are not well suited to storing the large volumes of data generated for and by ensemble streamflow forecasts with numerical weather prediction models. netCDF is a binary file format developed primarily for climate, ocean and meteorological data. netCDF has traditionally been used to store time slices of gridded data, rather than complete time series of point data. efts-io is for handling the latter. It reads and writes netCDF data following the NetCDF for Water Forecasting Conventions v2.0.

Installation

With pip:

pip install efts-io

Development workflow

See contributing.md if you want to contribute. This project follows practices from a template and the page copier-uv: Working on a project. Many thanks to Timothée Mazzucotelli for sharing this template.

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

efts_io-0.4.0.tar.gz (138.0 kB view details)

Uploaded Source

Built Distribution

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

efts_io-0.4.0-py3-none-any.whl (60.4 kB view details)

Uploaded Python 3

File details

Details for the file efts_io-0.4.0.tar.gz.

File metadata

  • Download URL: efts_io-0.4.0.tar.gz
  • Upload date:
  • Size: 138.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.5

File hashes

Hashes for efts_io-0.4.0.tar.gz
Algorithm Hash digest
SHA256 9b41a523b6bdd3de736c301ef1de339c06c40af62c459d2a48a8f6dbc0e71b20
MD5 6f55e2639107312ae6a9d88c9f7f9eb9
BLAKE2b-256 3ed9e3c9ce16caed71943c1dea9cee31c52efa9afca3fb6d2fbc23be6c656b3e

See more details on using hashes here.

File details

Details for the file efts_io-0.4.0-py3-none-any.whl.

File metadata

  • Download URL: efts_io-0.4.0-py3-none-any.whl
  • Upload date:
  • Size: 60.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.5

File hashes

Hashes for efts_io-0.4.0-py3-none-any.whl
Algorithm Hash digest
SHA256 05515a8ba382214d66b5c338f76cc918aadabd6d570de31a20ad99ef097ba250
MD5 36a0609e3e5b6bc5730d1d3b295eba99
BLAKE2b-256 e69ece7d5125d8bfe830372522bcecc46bd12fc847df7ab5fa6fe33f8b261459

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