| .. | ||
| workspace | ||
| Dockerfile | ||
| README.md | ||
Jupyter workspace
Workspace equipped with Jupyterlab and has a suite of tools for utilizing Jupyter notebooks
Start
docker run --name space-1 -d -p 8020-8040:8020-8040 --restart=always alnoda/jupyter-workspace
and open localhost:8020 in browser.
Features
- JupyterLab - Web-based interactive development environment for notebooks, code, and data.
- jpterm - jpterm aims to be the equivalent of JupyterLab in the terminal.
- Euporie - Euporie is a terminal based interactive computing environment for Jupyter.
- jut - Render Jupyter notebook in the terminal
- nbpreview - A terminal viewer for Jupyter notebooks. It’s like cat for ipynb files.
- nbterm - Jupyter Notebooks in the terminal.
- jupyter-python - Python LSP Server for Jupyterlab. Support for code completion, syntax highlighting
- NBClient - Tool for running Jupyter Notebooks in different execution contexts, including the command line.
- nbconvert - Jupyter Notebook Conversion
- papermill - Papermill is a tool for parameterizing and executing Jupyter Notebooks.
- Jupytext - Jupyter Notebooks as Markdown Documents, Julia, Python or R scripts.
- Alnoda workspace features
Links
NBClient
NBClient is a tool for running Jupyter Notebooks in different execution contexts,
including the command line. NBClient makes it possible to run command jupyter execute which runs Notebook cells one-by-one.
For example:
jupyter execute my-notebook.ipynb
This will execute each note in the notebook.
NBClient might handy, if you need to automate such tasks as web scrapping, data analysis or preparation, retraining of machine learning models.
Nbterm
Nbterm lets you view, edit and execute Jupyter Notebooks in the terminal, and produce the new notebook as a result of execution.
One of the differences between NBClient and Nbterm, is that the latter produces new notebook as a result. This is especially useful if you plan to use notebooks as reports.
An example use-case would be querying datasase, computing statistics from new orders or client activity, and providing read-only executed notebook via NBviewer. Such notebook will contain both code, SQL as well as results of execution - statistics, chartss and plots.
For example:
nbterm --run notebook.ipynb --save-path /home/project/notebook-1.ipynb
Because flag --save-path was defined, executed notebook has been saved.
Papermill
Papermill is a tool for parameterizing, executing, and analyzing Jupyter Notebooks.
Papermill solves the problem of parameterizing notebooks in a simple and efficient way. Jupyter notebooks allow users to tag cells. Papermill lets you to tag a cell, which contains parameters with parameters tag.
To parameterize a notebook, designate a cell with the tag parameters.
As an example, open Jupyter notebook from the Quickstart page, and create a new note.
First thing to do - is to enable tags. Click View -> Cell Toolbar -> Tags. This will enable the tags UI.
Open terminal and execute with different parameters, for example:
papermill mynotebook.ipynb mynotebook-1.ipynb -p PARAM1 "My name" -p PARAM2 "Slim Shady"
Nbconvert
Nbconvert tool allows you to convert an .ipynb notebook file into various static formats including executable scripts.
For example:
jupyter nbconvert --to script mynotebook.ipynb --output /home/project/newfile
Now you can execute this newly-generated python script
python /home/project/newfile.py
Nbconvert can convert to other formats too, such as HTML, PDF, LaTeX. Check tutorial about reports.
nbless
The nbless Python package includes nbconv shell command, which makes conversion
of python notebooks into various commands, including .py executable scripts.
To try it with the example notebook, execute in terminal
nbconv mynotebook.ipynb --exporter python --out_file /home/project/mynotebook.py
You will see that file 'mynotebook.py' has appeared in the '/home/project' folder.
Jupytext
Jupytext can save Jupyter notebooks as python or markdown:
jupytext --to py mynotebook.ipynb --output /home/project/myscript.py