wxyz_yaml

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experimental Jupyter widgets for YAML

Installation

Prerequisites:

• python >=3.7
• jupyterlab >=3,<4

pip install wxyz_yaml

wxyz

Experimental Widgets for JupyterLab.

build	demo	docs
		DOCS — EXAMPLES — CHANGELOG — CONTRIBUTING

Install and Use

Strongly Discouraged

wxyz_notebooks, not recommended for production use, requires all of the wxyz_* packages.

Some extra(s) dangerous dependencies are available as well

pip install wxyz_notebooks              # wxyz_*
pip install wxyz_notebooks[binder]      # everything used on binder demos, used in tests
pip install wxyz_notebooks[thirdparty]  # some casually co-tested third-party packages
pip install wxyz_notebooks[all]         # everything. it's a lot. good luck.

It is unknown whether the heavier dependencies will continue to work in the future and may carry very specific version pins which might not be solveable with any old:

• operating system
• version of python
• package manager

Motivation

wxyz contains a number of "missing pieces" from the ipywidgets toolbox. It is made up of a number of packages for Python and the browser, in this repo. While many create pixels on the page, some are focused around configurably transforming the traitlets of one widget to another, in the kernel, the browser or both.

Uninstall

We're sad to see you go!

Use pip or conda to uninstall any wxyz_* packages.

Alternatives

If you don't like wxyz, that's fine! There are a number of related tools that might be better suited to your needs.

• formulas
  • a python-side re-implementation of an Excel/LibreOffice reactive functional programming model
• ipyevents
  • fine-grained DOM event control
• ipylab
  • a number of similar utilities as parts of wxyz.lab, and nice support for commands, and additional lumino primitives, e.g. SplitPanel
• ipyregulartable
  • a high-performance datagrid solution, supporting pandas MultiIndex-type data
• jupyter-starters
  • wizard-style project templates, driven by simple configuration, JSON Schema or notebooks
• jupyterlab-tour
  • a pleasant "guided tour" of JupyterLab via CSS selectors and JSON Schema