Metadata-Version: 2.1
Name: jupytemplate
Version: 0.2.1
Summary: Jupyter extension to support templates
Home-page: https://github.com/donlelef/jupytemplate
Author: Emanuele Fabbiani
Author-email: donlelef@gmail.com
License: MIT licence
Download-URL: https://github.com/donlelef/jupytemplate/archive/v0.2.1.tar.gz
Description: # Jupyter template
        
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        A simple template for jupyter notebooks.
        
        The extension sets up any new Jupyter Notebook 
        with a conventional and general-purpose
        template to shape Data Science analysis.
        
        The template includes conventional sections,
        like *Data Import*, *Processing* and *References*,
        as well as code to perform common operations, like
        importing and configuring charting libraries. 
        
        Moreover, it prompts for a meaningful name whenever
        you try and save a notebook called 'Untitled'. 
        
        But don't worry, you can disable
        this one.
        
        
        ## Motivation
        Jupyter notebooks are awesome tools: they enable fast 
        prototyping and ease result sharing. However, due to 
        their flexibility, they are prone to be abused. 
        
        In order to help Data Scientist keep their notebooks 
        clean, a reasonably flexible yet conventional template
        may help. Moreover, such a template may be also a 
        productivity tool, which speeds up common setup,
        such as library import.
        
        ## Quick start
        It is not mandatory, but you can install the full set of Jupyter 
        extensions.
        ```shell
        pip install jupyter_contrib_nbextensions
        jupyter contrib nbextension install --user
        ```
        Feel free to visit [their repository](https://github.com/ipython-contrib/jupyter_contrib_nbextensions)
        for more information.
        
        Now you can install the package:
        ```shell
        pip install jupytemplate
        ```
        Then, you have to install the javascript files from 
        the Python package in a conventional jupyter directory:
        ```shell
        jupyter nbextension install --py jupytemplate --sys-prefix
        ```
        Finally, you may want to enable the extension:
        ```shell
        jupyter nbextension enable jupytemplate/main --sys-prefix
        ```
        You can easily enable, disable or configure the extension
        by using the [nbextension_configurator](https://github.com/Jupyter-contrib/jupyter_nbextensions_configurator)
        server extension.
        
        
        ## Changing the template
        Template location can be found by running:   
        ```python
        import jupytemplate
        print(jupytemplate.get_template_path())
        ```
        Of course, you can modify the template as you like, do not 
        modify the file name `template.ipynb`.  
        After editing the template, run:
        ```shell
        jupyter nbextension install --py jupytemplate --sys-prefix
        jupyter nbextension enable jupytemplate/main --sys-prefix
        ```
        to make changes effective.
        
        ## References
        Please consider reading the following resources for
        a more comprehensive understanding:
        - Will Kohersen, [Set Your Jupyter Notebook up Right with this Extension](https://towardsdatascience.com/set-your-jupyter-notebook-up-right-with-this-extension-24921838a332)
        - Will Kohersen, [How to Write a Jupyter Notebook Extension](https://towardsdatascience.com/how-to-write-a-jupyter-notebook-extension-a63f9578a38c)
        - Will Kohersen, [Setup extension](https://github.com/WillKoehrsen/Data-Analysis/tree/master/setup)
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: End Users/Desktop
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: JavaScript
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.6
Classifier: Topic :: Utilities
Description-Content-Type: text/markdown
