Research
Security News
Malicious npm Package Targets Solana Developers and Hijacks Funds
A malicious npm package targets Solana developers, rerouting funds in 2% of transactions to a hardcoded address.
jupyter_client
contains the reference implementation of the Jupyter protocol.
It also provides client and kernel management APIs for working with kernels.
It also provides the jupyter kernelspec
entrypoint
for installing kernelspecs for use with Jupyter frontends.
The Jupyter Contributor Guides provide extensive information on contributing code or documentation to Jupyter projects. The limited instructions below for setting up a development environment are for your convenience.
You'll need Python and pip
on the search path. Clone the Jupyter Client git repository to your computer, for example in /my/project/jupyter_client
cd /my/projects/
git clone git@github.com:jupyter/jupyter_client.git
Now create an editable install and download the dependencies of code and test suite by executing:
cd /my/projects/jupyter_client/
pip install -e ".[test]"
pytest
The last command runs the test suite to verify the setup. During development, you can pass filenames to pytest
, and it will execute only those tests.
The documentation of Jupyter Client is generated from the files in docs/
using Sphinx. Instructions for setting up Sphinx with a selection of optional modules are in the Documentation Guide. You'll also need the make
command.
For a minimal Sphinx installation to process the Jupyter Client docs, execute:
pip install ".[doc]"
The following commands build the documentation in HTML format and check for broken links:
cd /my/projects/jupyter_client/docs/
make html linkcheck
Point your browser to the following URL to access the generated documentation:
file:///my/projects/jupyter_client/docs/_build/html/index.html
jupyter-client
has adopted automatic code formatting so you shouldn't
need to worry too much about your code style.
As long as your code is valid,
the pre-commit hook should take care of how it should look.
You can invoke the pre-commit hook by hand at any time with:
pre-commit run
which should run any autoformatting on your code and tell you about any errors it couldn't fix automatically. You may also install black integration into your text editor to format code automatically.
If you have already committed files before setting up the pre-commit
hook with pre-commit install
, you can fix everything up using
pre-commit run --all-files
. You need to make the fixing commit
yourself after that.
Some of the hooks only run on CI by default, but you can invoke them by
running with the --hook-stage manual
argument.
The Jupyter Development Team is the set of all contributors to the Jupyter project. This includes all of the Jupyter subprojects.
The core team that coordinates development on GitHub can be found here: https://github.com/jupyter/.
Jupyter uses a shared copyright model. Each contributor maintains copyright over their contributions to Jupyter. But, it is important to note that these contributions are typically only changes to the repositories. Thus, the Jupyter source code, in its entirety is not the copyright of any single person or institution. Instead, it is the collective copyright of the entire Jupyter Development Team. If individual contributors want to maintain a record of what changes/contributions they have specific copyright on, they should indicate their copyright in the commit message of the change, when they commit the change to one of the Jupyter repositories.
With this in mind, the following banner should be used in any source code file to indicate the copyright and license terms:
# Copyright (c) Jupyter Development Team.
# Distributed under the terms of the Modified BSD License.
FAQs
Jupyter protocol implementation and client libraries
We found that jupyter-client demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 12 open source maintainers collaborating on the project.
Did you know?
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