Skip to main content

Flexible storage for time series.

Project description

📦 Welcome to TStore

Deployment PyPI Conda
Activity PyPI Downloads Conda Downloads
Python Versions Python Versions
Supported Systems Linux macOS Windows
Project Status Project Status
Build Status Tests Lint Docs
Linting Black Ruff Codespell
Code Coverage Coveralls Codecov
Code Quality Codefactor Codebeat Codacy Codescene
License License
Community Slack GitHub Discussions
Citation DOI

Slack | Docs

🚀 Quick start

Flexible storage for time series

TODO


📖 Explore the TStore documentation

To discover all TStore download, manipulation, analysis and plotting utilities, or how to contribute your custom retrieval to TStore:

🛠️ Installation

conda

TStore can be installed via conda on Linux, Mac, and Windows. Install the package by typing the following command in the terminal:

conda install ts-store

In case conda-forge is not set up for your system yet, see the easy to follow instructions on conda-forge.

pip

TStore can be installed also via pip on Linux, Mac, and Windows. On Windows you can install WinPython to get Python and pip running.

Install the TStore package by typing the following command in the terminal:

pip install ts-store

To install the latest development version via pip, see the documentation.

💭 Feedback and Contributing Guidelines

If you aim to contribute your data or discuss the future development of TStore, we highly suggest to join the TStore Slack Workspace

Feel free to also open a GitHub Issue or a GitHub Discussion specific to your questions or ideas.

Citation

If you are using TStore in your publication please cite our Zenodo repository:

Ghiggi Gionata. ltelab/tstore. Zenodo. https://doi.org/10.5281/zenodo.7753488

If you want to cite a specific software version, have a look at the Zenodo site.

License

The content of this repository is released under the terms of the MIT license.

OUTDATED HERE BELOW

Requirements

Instructions

  1. Create a conda environment:
snakemake -c1 create_environment
  1. Activate it (if using conda, replace mamba for conda):
mamba activate tstore
  1. Register the IPython kernel for Jupyter:
snakemake -c1 register_ipykernel
  1. Activate pre-commit for the git repository:
pre-commit install
pre-commit install --hook-type commit-msg

Acknowledgments

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

ts-store-0.0.1.tar.gz (27.5 kB view details)

Uploaded Source

Built Distribution

ts_store-0.0.1-py3-none-any.whl (25.3 kB view details)

Uploaded Python 3

File details

Details for the file ts-store-0.0.1.tar.gz.

File metadata

  • Download URL: ts-store-0.0.1.tar.gz
  • Upload date:
  • Size: 27.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.11.8

File hashes

Hashes for ts-store-0.0.1.tar.gz
Algorithm Hash digest
SHA256 d8354c03f66f3d855df909fa0de5b3fe72448137c0e46ef3163a958e2a35b5c0
MD5 2c4aadc337e6c8648ca2d055a7f96ba6
BLAKE2b-256 566bb55b68840dfe4175727b3abe13acaa79ff1038e39c4d30195da15bd5b312

See more details on using hashes here.

File details

Details for the file ts_store-0.0.1-py3-none-any.whl.

File metadata

  • Download URL: ts_store-0.0.1-py3-none-any.whl
  • Upload date:
  • Size: 25.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.11.8

File hashes

Hashes for ts_store-0.0.1-py3-none-any.whl
Algorithm Hash digest
SHA256 0c8123e5828ed20c1d214aacb2185eb9b1ba18ce021a70e9205ddd8cb988ac1a
MD5 1b2dea01fe717106e357c7cc068b01ad
BLAKE2b-256 6c2006ac799b7f870a63cc02462264240e34eb7dc00651e202993f64cdcb892e

See more details on using hashes here.

Supported by

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