Metadata-Version: 2.1
Name: ml-stars
Version: 0.1.0.dev1
Summary: Primitives and Pipelines for Time Series Data.
Home-page: https://github.com/sintel-dev/ml-stars
Author: MIT Data To AI Lab
Author-email: dailabmit@gmail.com
License: MIT license
Description: <p align="left">
        <img width=15% src="https://dai.lids.mit.edu/wp-content/uploads/2018/06/Logo_DAI_highres.png" alt=“DAI-Lab” />
        <i>An open source project from Data to AI Lab at MIT.</i>
        </p>
        
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        # ml-stars
        
        Primitives and Pipelines for Time Series Data.
        
        - Documentation: https://sinte-dev.github.io/ml-stars
        - Homepage: https://github.com/sinte-dev/ml-stars
        
        # Overview
        
        TODO: Provide a short overview of the project here.
        
        # Install
        
        ## Requirements
        
        **ml-stars** has been developed and tested on [Python 3.6, 3.7 and 3.8](https://www.python.org/downloads/)
        
        Also, although it is not strictly required, the usage of a [virtualenv](https://virtualenv.pypa.io/en/latest/)
        is highly recommended in order to avoid interfering with other software installed in the system
        in which **ml-stars** is run.
        
        These are the minimum commands needed to create a virtualenv using python3.6 for **ml-stars**:
        
        ```bash
        pip install virtualenv
        virtualenv -p $(which python3.6) ml-stars-venv
        ```
        
        Afterwards, you have to execute this command to activate the virtualenv:
        
        ```bash
        source ml-stars-venv/bin/activate
        ```
        
        Remember to execute it every time you start a new console to work on **ml-stars**!
        
        <!-- Uncomment this section after releasing the package to PyPI for installation instructions
        ## Install from PyPI
        
        After creating the virtualenv and activating it, we recommend using
        [pip](https://pip.pypa.io/en/stable/) in order to install **ml-stars**:
        
        ```bash
        pip install ml-stars
        ```
        
        This will pull and install the latest stable release from [PyPI](https://pypi.org/).
        -->
        
        ## Install from source
        
        With your virtualenv activated, you can clone the repository and install it from
        source by running `make install` on the `stable` branch:
        
        ```bash
        git clone git@github.com:sinte-dev/ml-stars.git
        cd ml-stars
        git checkout stable
        make install
        ```
        
        ## Install for Development
        
        If you want to contribute to the project, a few more steps are required to make the project ready
        for development.
        
        Please head to the [Contributing Guide](https://sinte-dev.github.io/ml-stars/contributing.html#get-started)
        for more details about this process.
        
        # Quickstart
        
        In this short tutorial we will guide you through a series of steps that will help you
        getting started with **ml-stars**.
        
        TODO: Create a step by step guide here.
        
        # What's next?
        
        For more details about **ml-stars** and all its possibilities
        and features, please check the [documentation site](
        https://sinte-dev.github.io/ml-stars/).
        
        
        # History
        
Keywords: mlstars
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Requires-Python: >=3.6,<3.9
Description-Content-Type: text/markdown
Provides-Extra: test
Provides-Extra: dev
