ab85f165c7
1) finish the step allowing the use of es6
- this include some tweak to web pack configuration to speed up
recompile in watch mode (in particular cache sourcemaps).
- enable eslint (error only), on obvious mistakes.
- setup babel to compile to es5 as a target.
2) Make the test pass under Casper that does not always have
`Function.prototype.bind` defined, which we cannot patch only in the
tests.
3) Write an actual shortcut editor that list and allow to modify most of
the command mode shortcut.
The logic to persist the shortcuts is a bit tricky as there are default
keyboard shortcuts, and so when you "unbind" them you need to re-unbind
them at next startup. This does not work for a few shortcut for
technical reasons: `<Esc>`, `<Shift>`, as well as `<Ctrl-Shift-P>` and `<F>`
which register asynchronously, so are not detected as "default"
shortcuts.
|
||
|---|---|---|
| docs | ||
| git-hooks | ||
| notebook | ||
| scripts | ||
| tools | ||
| .babelrc | ||
| .bowerrc | ||
| .dockerignore | ||
| .eslintignore | ||
| .eslintrc.json | ||
| .gitignore | ||
| .gitmodules | ||
| .mailmap | ||
| .travis.yml | ||
| bower.json | ||
| circle.yml | ||
| CONTRIBUTING.rst | ||
| COPYING.md | ||
| Dockerfile | ||
| MANIFEST.in | ||
| package.json | ||
| README.md | ||
| readthedocs.yml | ||
| setup.cfg | ||
| setup.py | ||
| setupbase.py | ||
| webpack.config.js | ||
Jupyter Notebook
The Jupyter notebook is a web-based notebook environment for interactive computing.
Jupyter notebook, the language-agnostic evolution of IPython notebook
Jupyter notebook is the language-agnostic HTML notebook application for Project Jupyter. In 2015, Jupyter notebook was released as part of The Big Split™ of the IPython codebase. IPython 3 was the last major monolithic release containing both language-agnostic code, such as the IPython notebook, and language specific code, such as the IPython kernel for Python. As computing spans many languages, Project Jupyter will continue to develop the language-agnostic Jupyter notebook in this repo and with the help of the community develop language specific kernels which are found in their own discrete repos. [The Big Split™ announcement] [Jupyter Ascending blog post]
Installation
You can find the installation documentation for the Jupyter platform, on ReadTheDocs. The documentation for advanced usage of Jupyter notebook can be found here.
For a local installation, make sure you have pip installed and run:
$ pip install notebook
Usage - Running Jupyter notebook
Running in a local installation
Launch with:
$ jupyter notebook
Running in a Docker container
If you are using Linux and have a
Docker daemon running,
e.g. reachable on localhost, start a container with:
$ docker run --rm -it -p 8888:8888 -v "$(pwd):/notebooks" jupyter/notebook
In your browser, open the URL http://localhost:8888/.
All notebooks from your session will be saved in the current directory.
On other platforms, such as Windows and OS X, that use
docker-machine with docker, a container can be started using
docker-machine. In the browser, open the URL http://ip:8888/ where ip is
the IP address returned from the command docker-machine ip <MACHINE>:
$ docker-machine ip <MACHINE>
For example,
$ docker-machine ip myjupytermachine
192.168.99.104
In browser, open http://192.168.99.104:8888.
NOTE: With the deprecated boot2docker, use the command boot2docker ip to
determine the URL.
Development Installation
See CONTRIBUTING.rst for how to set up a local development installation.
Contributing
If you are interested in contributing to the project, see CONTRIBUTING.rst.