Skip to main content

Pipeline to Aggregate Data for Optimised Cloud Capabilities

Project description

PADOCC Package

Padocc (Pipeline to Aggregate Data for Optimal Cloud Capabilities) is a Data Aggregation pipeline for creating Kerchunk (or alternative) files to represent various datasets in different original formats. Currently the Pipeline supports writing JSON/Parquet Kerchunk files for input NetCDF/HDF files. Further developments will allow GeoTiff, GRIB and possibly MetOffice (.pp) files to be represented, as well as using the Pangeo Rechunker tool to create Zarr stores for Kerchunk-incompatible datasets.

Example Notebooks at this link

Documentation hosted at this link

Kerchunk Pipeline

Pre-release b

Release date: 20th January 2025

This pre-release contains updated source code and source code documentation, but some of the main descriptors that are hand-written (not source) may be out of date. Please refer to the release notes for details on what has changed.

Installation

To install this package, clone the repository using git clone (and switch to the MigrationOO branch - git checkout MigrationOO if release v1.3 has not been released.)

Then follow the steps below to install the package with the necessary dependencies.

python -m venv .venv
source .venv/bin/activate
pip install poetry
poetry install

Usage

Please refer to the tests/ scripts for how to use the GroupOperation and ProjectOperation classes.

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

padocc-1.3.0b0.tar.gz (9.9 MB view details)

Uploaded Source

Built Distribution

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

padocc-1.3.0b0-py3-none-any.whl (10.0 MB view details)

Uploaded Python 3

File details

Details for the file padocc-1.3.0b0.tar.gz.

File metadata

  • Download URL: padocc-1.3.0b0.tar.gz
  • Upload date:
  • Size: 9.9 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.5 CPython/3.12.5 Darwin/24.2.0

File hashes

Hashes for padocc-1.3.0b0.tar.gz
Algorithm Hash digest
SHA256 55c8524347c752e13325afbc54a58914dfa1e8af1d00c2337f0d15de750769c5
MD5 d797bd6d771f856cfadf8b00e005eb8f
BLAKE2b-256 89d755ce28bfc1f5c398493c88d6a02316d6a97b4d5e7e14977f0792f73b3afc

See more details on using hashes here.

File details

Details for the file padocc-1.3.0b0-py3-none-any.whl.

File metadata

  • Download URL: padocc-1.3.0b0-py3-none-any.whl
  • Upload date:
  • Size: 10.0 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.5 CPython/3.12.5 Darwin/24.2.0

File hashes

Hashes for padocc-1.3.0b0-py3-none-any.whl
Algorithm Hash digest
SHA256 91eae0aca7b20bc28c2d9a6755fef663be0e932d754c707e7cc268ef2150e755
MD5 1e8527d982283c74f95fa627429ebf28
BLAKE2b-256 33b37f275b3b771ab65b473370627d3ddc2918ff0a4d1ce8ff405680d10c6088

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