Metadata-Version: 1.0
Name: nb-conda-kernels
Version: 2.1.1
Summary: Launch Jupyter kernels for any installed conda environment
Home-page: https://github.com/Anaconda-Platform/nb_conda_kernels
Author: Continuum Analytics
Author-email: UNKNOWN
License: UNKNOWN
Description: # nb_conda_kernels
        Manage your `conda` environment-based kernels inside the Jupyter Notebook.
        
        This package defines a custom KernelSpecManager that automatically
        creates KernelSpecs for each conda environment. When you create a new
        notebook, you can choose a kernel corresponding to the environment
        you wish to run within. This will allow you to have different versions
        of python, libraries, etc. for different notebooks.
        
        **Important Note** : To use a Python kernel from a conda environment,
        don't forget to install `ipykernel` in that environment or it won't
        show up on the kernel list. Similary, to use an R kernel, install
        `r-irkernel`.
        
        ## Installation
        ```shell
        conda install nb_conda_kernels
        ```
        
        ### Getting Started
        You'll need conda installed, either from [Anaconda](https://www.continuum.io/downloads) or [miniconda](http://conda.pydata.org/miniconda.html). 
        
        ```shell
        conda create -n nb_conda_kernels nb_conda_kernels python=YOUR_FAVORITE_PYTHON
        conda activate nb_conda_kernels
        # Remove just the package, leave the dependencies
        conda remove nb_conda_kernels --force
        # Install the test packages
        conda install --file requirements.txt
        python setup.py develop
        python -m nb_conda_kernels.install --enable --prefix="${CONDA_PREFIX}"
        # or on windows
        python -m nb_conda_kernels.install --enable --prefix="%CONDA_PREFIX"
        ```
        
        We _still_ use `npm` for testing things, so then run:
        ```shell
        npm install
        ```
        
        Finally, you are ready to run the tests!
        ```shell
        npm run test
        ```
        Note that the tests assume the existence of `ipykernel` in the
        base/root conda environment:
        ```shell
        conda install -n root ipykernel
        ```
        In addition, there needs to be at least one conda environment
        with the `R` kernel, and it need not be root;
        ```shell
        conda create -n nbrtest r-irkernel
        ```
        
        ## Changelog
        
        ### 2.1.1
        - move to a full conda-based approach to build and test
        - add support for conda 4.4 and later, which can remove `conda` from the PATH
        
        ### 2.1.0
        - add support for regex-based filtering of conda environments that should not appear in the list
        
        ### 2.0.0
        - change kernel naming scheme to leave default kernels in place
        
        ### 1.0.3
        - ignore build cleanup on windows due to poorly-behaved PhantomJS processes
        
        ### 1.0.2
        - use [Travis-CI](https://travis-ci.org/Anaconda-Platform/nb_conda_kernels) for continuous integration
        - use [Coveralls](https://coveralls.io/github/Anaconda-Platform/nb_conda_kernels) for code coverage
        - use a [conda-forge](https://github.com/conda-forge/nb_conda_kernels-feedstock) for cross-platform `conda` package building
        
        ### 1.0.1
        - minor build changes
        
        ### 1.0.0
        - update to notebook 4.2
        
Platform: UNKNOWN
