Metadata-Version: 2.3
Name: ts-data-generator
Version: 0.1.0
Summary: A Python library for generating synthetic time series data
License: MIT
Keywords: synthetic data,data generator,python,time series
Author: Manoj Manivannan
Author-email: manojm18@live.in
Requires-Python: >=3.8
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Provides-Extra: dev
Requires-Dist: black ; extra == "dev"
Requires-Dist: flake8 ; extra == "dev"
Requires-Dist: matplotlib
Requires-Dist: pandas
Requires-Dist: pydantic
Requires-Dist: pytest
Requires-Dist: python-dotenv
Description-Content-Type: text/markdown

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# Synthetic Time Series Data Generator

[![Python](https://img.shields.io/pypi/v/ts-data-generator)](https://pypi.org/project/ts-data-generator) ![CI](https://github.com/manojmanivannan/ts-data-generator/actions/workflows/ci.yaml/badge.svg)

A Python library for generating synthetic time series data

<sup>Special thanks to: [Nike-Inc](https://github.com/Nike-Inc/timeseries-generator) repo

<img src="https://github.com/manojmanivannan/ts-data-generator/raw/main/notebooks/image.png" alt="MarineGEO circle logo" style="height: 1000px; width:800px;"/>

<!-- ![Tutorial][tutorial] -->

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## Installation
### PyPi (recommended)
You can install with pip directly by
```bash
pip install ts-data-generator
```

### Repo
After cloning this repo and creating a virtual environment, run the following command:
```bash
pip install --editable .
```


## Usage

Check the sample notebook [here](https://github.com/manojmanivannan/ts-data-generator/blob/main/notebooks/sample.ipynb)

#### Release method
1. `git tag <x.x.x>`
2. `git push origin <x.x.x>`

<!-- [tutorial]: /notebooks/test.gif -->
