https://github.com/metacall/jupyter-kernel
Wrapper Kernel for MetaCall Core Library leveraging IPython and Jupyter
https://github.com/metacall/jupyter-kernel
ipython jupyter-notebook metacall python wrapper-kernel
Last synced: about 14 hours ago
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Wrapper Kernel for MetaCall Core Library leveraging IPython and Jupyter
- Host: GitHub
- URL: https://github.com/metacall/jupyter-kernel
- Owner: metacall
- License: apache-2.0
- Created: 2021-05-20T15:10:14.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2023-03-01T07:58:44.000Z (almost 3 years ago)
- Last Synced: 2025-09-22T16:55:49.357Z (3 months ago)
- Topics: ipython, jupyter-notebook, metacall, python, wrapper-kernel
- Language: Python
- Homepage: https://metacall-jupyter-kernel.readthedocs.io/
- Size: 927 KB
- Stars: 15
- Watchers: 4
- Forks: 8
- Open Issues: 4
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: docs/contributing.rst
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
Awesome Lists containing this project
README
# `MetaCall Jupyter Kernel`: Wrapper Kernel for MetaCall Core Library leveraging IPython and Jupyter
[](https://github.com/psf/black)
[](https://mybinder.org/v2/gh/metacall/jupyter-kernel/master)
## Introduction
MetaCall Jupyter Kernel is an open-source wrapper kernel that implements cross-language function calls through the [MetaCall Core](https://github.com/metacall/core) and the [Polyglot REPL](https://github.com/metacall/polyglot-repl). MetaCall Core is an open-source library that brings the polyglot programming experience to Developers. With MetaCall, developers can embed different programming languages through an easy-to-use high-level API.
The Kernel exposes the MetaCall Core API which can be loaded and launched through a Jupyter Notebook interface. With this Notebook, the
users can try out writing, mixing and embedding code in different programming languages. The project is available on [PyPi](https://pypi.org/project/metacall-jupyter/).
## Key features
`metacall_jupyter` is designed to be simple and concise with the following key features:
- You can call functions in different programming languages, through cross-language function calls.
- You use a high-level API to execute code in different programming languages.
- Lists all the available functions and modules from the MetaCall's meta-object protocol.
- Official support for Python and NodeJS with the Polyglot REPL.
- Simple and intuitive user-experience centred around Polyglot development and components.
## Installation
It is recommended to use a Virtual Environment to manage your dependencies and the application build. We will first start with setting up the Local Project Environment:
```sh
git clone https://github.com/metacall/jupyter-kernel.git
virtualenv env
source env/bin/activate
```
Next we can download all the dependenices and setup the Kernel:
```sh
curl -sL https://raw.githubusercontent.com/metacall/install/master/install.sh | sh
python3 -m pip install --upgrade pip
pip3 install -r requirements.txt
python3 setup.py install
python3 -m metacall_jupyter.install
metacall npm install
```
Start your Jupyter Notebook by pushing the following command:
```sh
python3 -m metacall_jupyter.launcher
```
You can pick `metacall_jupyter` from the drop-down options and start working with the Jupyter Notebook interface. Example Notebook are found [here](examples).
## Docker
Build the image:
```sh
docker build -t metacall/jupyter .
```
Run the image:
```sh
docker run --rm --network=host -it metacall/jupyter
```
## Testing
To run the tests, push the following command:
```sh
pytest test-kernel.py
```
The script will run all the tests. To generate a coverage report, we are using the `pytest-cov` plugin, which can be invoked by pushing the following command:
```sh
pytest --cov=metacall_jupyter test-kernel.py
```
## Documentation
Our official documentation is available at [**metacall-jupyter-kernel.readthedocs.io**](https://metacall-jupyter-kernel.readthedocs.io/en/latest/index.html).
To edit the documentation you need a GitHub account. Once you have created one and logged in, you can edit any page by navigating to the corresponding file and clicking the edit (pen) icon. Alternatively create a fork, and then clone the repo and `cd` into the `docs` directory. Let us set the doucmentation up:
```sh
virtualenv env
source env/bin/activate
pip install -r requirements.txt
make html
```
You can now open the documentation site on `_build/html/index.html` in your browser. Make corresponding changes on the documentation site and then run `make clean && make html` to update the documentation. You can now create a pull request to get your changes merged into the upstream branch.
## Contributing
To get started with contributing, check out the [Code of Conduct](CODE_OF_CONDUCT.md) and create an [Issue](https://github.com/metacall/jupyter-kernel/issues/new) to get started.
If you are new to Git & GitHub, you can find more information [here](https://metacall-jupyter-kernel.readthedocs.io/en/latest/contributing.html). It contains all the information about making the changes, linting, running the CI locally and submitting the pull request.
You can view the [Change Log](CHANGELOG.md) to see what has changed in the project, since its inception.
## LICENSE
[Apache-2.0 License](LICENSE)