A data processing framework used to convert time series data into standardized format.
Project description
Time Series Data Library
This library provides general utility methods for working with time series datasets, which are stored as Xarray Dataset objects. In particular, it will provide declarative methods for being able standardize, apply Q/C checks, correct, and transform datastreams as a whole, reducing the amount of coding required for data processing.
Getting Started
Installation
You can install tsdat and its dependencies using pip
pip3 install tsdat
Documentation
For help using tsdat, please see our documentation at https://tsdat.readthedocs.io/
Docker
Please see https://hub.docker.com/orgs/tsdat for the list of available tsdat docker images.
Installation from Source
If you will be developing/contributing to the tsdat code base, first clone the repository from
git clone https://github.com/tsdat/tsdat.git
You can install the tsdat requirements via:
pip3 install -r requirements.txt
Releasing to pypi
TODO: to be replaced by CICD build instead of manual process.
Prereq: Make sure that you have twine installed
pip install twine
1) Update the version number in setup.py
2) Then deploy the new release.
cd tsdat
python setup.py sdist bdist_wheel
twine upload dist/*
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