nbterm
jupyter_contrib_nbextensions
nbterm | jupyter_contrib_nbextensions | |
---|---|---|
7 | 7 | |
738 | 5,174 | |
- | 0.2% | |
0.0 | 0.0 | |
9 months ago | about 1 month ago | |
Python | JavaScript | |
MIT License | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
nbterm
- Code completion in nbterm?
- Pryrite: Interactively execute shell code blocks in a Markdown file
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4 ways to run Jupyter notebooks
Last but not least, you may be a command line nerd wondering if you have to use a browser or fancy IDE. It turns out you also have an option. The nbterm project allows you to interactively run Jupyter notebooks from the command line.
- Show HN: Euporie, a Tui for Jupyter Notebooks
- Jupyter Notebook in the Terminal
- Nbterm: Jupyter Notebooks in the Terminal
jupyter_contrib_nbextensions
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Error installing Jupyter Contrib Nbextensions - "contrib" sub-command not found
I'm trying to install Jupyter Contrib Nbextensions.
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Install jupyter notebook
You can add additional features to jupyter notebook by using Jupyter Notebook extensions. Features like Autopep8, ExecuteTime, Code Wrap, etc are avaiable.
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Logging the execution time of every cell in a Jupiter notebook and being able to view how long each cell took to execute afterwards?
You can try something like this: https://github.com/ipython-contrib/jupyter_contrib_nbextensions/tree/master/src/jupyter_contrib_nbextensions/nbextensions/execute_time
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Simple way to measure cell execution time in ipython notebook
I have been using Execute Time in Nbextension for quite some time now. It is great.
- Trabajando a 100 por hora en Jupyter Notebook
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4 ways to run Jupyter notebooks
Note that the Jupyter notebook is fairly configurable, so you can checkout the extensions once you’re comfortable with the basic setup.
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How to view all your variables in a Jupyter notebook
Now if you want to get fancy, Jupyter has an extension available through nbextensions. The Variable Inspector extension will give you a nice option for viewing variables in an output similar to the %whos output above. For developers used to an IDE with an automatically updating variable inspector, this extension may prove useful and worth checking out.
What are some alternatives?
vim-ipython-cell - Seamlessly run Python code in IPython from Vim
jupyter-themes - Custom Jupyter Notebook Themes
uniplot - Lightweight plotting to the terminal. 4x resolution via Unicode.
python_blogposts - Blog posts I've created about python, pandas, and related topics as a series of notebooks.
jupyter - An interface to communicate with Jupyter kernels.
jupytext.vim - Vim plugin for editing Jupyter ipynb files via jupytext
jupytext - Jupyter Notebooks as Markdown Documents, Julia, Python or R scripts
UnicodePlots.jl - Unicode-based scientific plotting for working in the terminal
matascii - ASCII back-end for matplotlib
klipse - Klipse is a JavaScript plugin for embedding interactive code snippets in tech blogs.
pryrite - Pryrite, interactively execute shell code blocks in a markdown file
gnuplotlib - gnuplot for numpy