Metadata-Version: 1.2
Name: jupyXplorer
Version: 0.0.4
Summary: jupyXplorer: notebooks generator from data
Home-page: https://github.com/hypnosapos/jupyXplorer
Author: Hypnosapos
License: MIT
Description: jupyXplorer
        ===========
        .. image:: https://circleci.com/gh/hypnosapos/jupyXplorer/tree/master.svg?style=svg
           :target: https://circleci.com/gh/hypnosapos/jupyXplorer/tree/master
           :alt: Build Status
        .. image:: https://img.shields.io/pypi/v/jupyxplorer.svg?style=flat-square
           :target: https://pypi.org/project/jupyXplorer
           :alt: Version
        .. image:: https://img.shields.io/pypi/pyversions/jupyxplorer.svg?style=flat-square
           :target: https://pypi.org/project/jupyXplorer
           :alt: Python versions
        .. image:: https://codecov.io/gh/hypnosapos/jupyXplorer/branch/master/graph/badge.svg
           :target: https://codecov.io/gh/hypnosapos/jupyXplorer
           :alt: Coverage
        
        This project aims to generate some util notebooks to get data exploration.
        
        It's based on nbconvert and simply offer you a easy way to analise a feature value (or set of them) of a dataset.
        
        Installation
        ------------
        
        In order to install the utility just use pip:
        
        .. code-block:: bash
        
            pip install jupyXplorer
        
        We provide you a docker image to get started quickly, take a look at **hypnosapos/jupyxplorer** at
        `dockerhub <https://hub.docker.com/r/hypnosapos/jupyxplorer/>`_ and select the best one fit your needs.
        
        
        Usage
        -----
        
        Before notebook generation take a look at our config file example (tests/e2e/sample_config.yaml).
        
        
        .. code-block:: bash
        
            jupyxplorer -c config.yaml -o .output
        
        All notebooks will be ready in directory ".output" of the example above.
        
        Once notebooks are generated we can use them in your jupyter to show results of data analysis.
        
        As we said above, you may use a docker container instead:
        
        .. code-block:: bash
        
           docker run -it -v </path/my_config.yaml>:/tmp/my_config.yaml </path/output>:/tmp/output hypnosapos/jupyxplorer:latest jupyxplorer -c /tmp/my_config.yaml -o /tmp/output
        
        
        If you want to use some required files to execute notebooks before generation (**-e** or **--execute** argument), provide the value of argument "input-dir" (**--input-dir**, or the short form **-i**).
        Here you have an example:
        
        
        .. code-block:: bash
        
            jupyxplorer -i .input -c config.yaml -o .output -e
        
        The resources under that directory would be particular requirement files for python and local dataset files.
        
        Dev
        ---
        
        The development lifecycle is managed by a **Makefile** and CircleCI, where all steps are executed through docker containers.
        Type ``make help`` to see all available commands.
        
        
Platform: UNKNOWN
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Requires-Python: >=3.5
