Metadata-Version: 2.1
Name: tsdat
Version: 0.2.0
Summary: A data processing framework used to convert time series data into standardized format.
Home-page: https://github.com/tsdat/tsdat
Author: Carina Lansing <carina.lansing@pnnl.gov>, Maxwell Levin <maxwell.levin@pnnl.gov>
Author-email: carina.lansing@pnnl.gov
License: Simplified BSD (2-clause)
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Topic :: Scientific/Engineering
Classifier: Intended Audience :: Science/Research
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
Requires-Dist: act-atmos
Requires-Dist: cfunits
Requires-Dist: netcdf4
Requires-Dist: numpy
Requires-Dist: pandas (>=1.0.0)
Requires-Dist: pyyaml
Requires-Dist: xarray
Requires-Dist: yamllint
Requires-Dist: boto3
Requires-Dist: cmocean
Requires-Dist: seaborn

# 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

```bash
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 

```bash
git clone https://github.com/tsdat/tsdat.git
```

You can install the tsdat  requirements via:

```bash
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
```bash
pip install twine
```

### 1) Update the version number in setup.py

### 2) Then deploy the new release.

```bash
cd tsdat
python setup.py sdist bdist_wheel
twine upload dist/*
```

```


