Documentation:

• VisiData plugins
• configurable options
• creating new commands
• writing a new data loader
• writing a new data saver

You can use this template with cookiecutter, or create a new repository based on the template and modify by hand.

• Python 3.7
• cookiecutter

Run cookiecutter gh:visidata/visidata-plugin and then answer the prompts. This will help set the fundamentals for your plugin structure.

If you are not using cookiecutter, rename {{cookiecutter.plugin_name}}.py to the name of your plugin, and add the plugin code to it.

To publish a plugin:

1. Make public Github repo with your .py file.
2. Fork [visidata:dlc](https://github.com/visidata/dlc)
3. Add a row to `visidata-plugins.jsonl' with all of the necessary information. (If using cookiecutter, it will create a template for your row in plugins-sample.jsonl.)

• name: short name of the plugin (like vfake). Less than 20 characters.
• description: a one-line searchable description of the core features. Less than 1000 characters.
• maintainer: like Your Name <[email protected]>.
• latest_release: date of most recent release, ISO formatted like 2020-02-02.
• latest_ver: version of most recent release, like v1.4.
• url: link to the primary page (which may be the raw .py file itself, if it describes itself effectively).
• visidata_ver: version of VisiData required, like v2.0.
• pydeps: space-separated list of PyPI dependencies (like in requirements.txt).
• vdplugindeps: space-separated list of vd plugin dependencies.
• sha256: SHA256 hash of plugin .py of most recent release. A script for obtaining this has can be found in vdhash.py.

4. Submit a PR to the visidata/dlc repo.
5. We will do basic review and then merge the PR.
6. VisiData users will be able to see the plugin using plugins-sheet within 24 hours.