<commit_before># scijava-jupyter-kernel
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---

`scijava-jupyter-kernel` aims to be a polyglot [Jupyter](http://jupyter.org/) kernel. It uses the [Scijava scripting languages](https://imagej.net/Scripting#Supported_languages) to execute the code in Jupyter client and it's possible to use different languages in the same notebook.

Some of the supported languages are Groovy (default), Python, Beanshell, Clojure, Java, Javascript, Ruby and Scala.

The kernel has been originally created to work with ImageJ. See [here](https://imagej.net/Scijava_Jupyter_Kernel) for more details.

*Under the hood `scijava-jupyter-kernel` uses the [Beaker base kernel](https://github.com/twosigma/beakerx/tree/master/kernel/base).*

## Documentation

A documentation is available as a series of notebooks [here](./notebooks/Welcome.ipynb).

## Installation - Standalone

- Install [Anaconda](https://www.continuum.io/downloads)
- Install `scijava-jupyter-kernel` with :

```bash
# Add the conda-forge channel
conda config --add channels conda-forge

# Create an isolated environment called `java_env` and install the kernel
conda create --name java_env scijava-jupyter-kernel

# Install the `java_env` environment
source install java_env
```

- Usage :

```bash
# Activate the `java_env` environment
source activate java_env
<commit_msg>Update instructions for environment activation<commit_after># scijava-jupyter-kernel
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---

`scijava-jupyter-kernel` aims to be a polyglot [Jupyter](http://jupyter.org/) kernel. It uses the [Scijava scripting languages](https://imagej.net/Scripting#Supported_languages) to execute the code in Jupyter client and it's possible to use different languages in the same notebook.

Some of the supported languages are Groovy (default), Python, Beanshell, Clojure, Java, Javascript, Ruby and Scala.

The kernel has been originally created to work with ImageJ. See [here](https://imagej.net/Scijava_Jupyter_Kernel) for more details.

*Under the hood `scijava-jupyter-kernel` uses the [Beaker base kernel](https://github.com/twosigma/beakerx/tree/master/kernel/base).*

## Documentation

A documentation is available as a series of notebooks [here](./notebooks/Welcome.ipynb).

## Installation - Standalone

- Install [Anaconda](https://www.continuum.io/downloads)
- Install `scijava-jupyter-kernel` with :

```bash
# Add the conda-forge channel
conda config --add channels conda-forge

# Create an isolated environment called `java_env` and install the kernel
conda create --name java_env scijava-jupyter-kernel
```

- Usage :

```bash
# Activate the `java_env` environment
source activate java_env

{'fraction_non_alphanumeric': 0.13450292397660818, 'fraction_numerical': 0.0, 'mean_word_length': 5.386363636363637, 'pattern_counts': {'":': 0, '<': 3, '<?xml version=': 0, '>': 3, 'https://': 24, 'lorem ipsum': 0, 'www.': 2, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 4, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'dir': 'git-commits-cleaned', 'id': '1477593', 'n_tokens_mistral': 1400, 'n_tokens_neox': 1357, 'n_words': 277}