semvec/pypi-packages huggingface dataset:
wagtail-draftail-anchors 0.7.0
A Draftail extension to add anchor identifiers to rich text
Requires Python: >=3.6

# Wagtail Draftail Anchors

Adds the ability to add and edit anchors in the Draftail rich text editor, as well as automatically adding
(slug-form) anchor ids to all headings.

## Installation

Install using `pip`:

```
pip install wagtail-draftail-anchors
```

Add `'wagtail_draftail_anchors'` to `INSTALLED_APPS` below `wagtail.admin`.

Add `'anchor-identifier'` to the features of any rich text field where you have overridden the default feature list. The feature must be added before any heading('h1',...,'h6') feature:

```
body = RichTextField(features=['anchor-identifier', 'h2', 'h3', 'bold', 'italic', 'link'])
```

## Configuration

### Rendered representation of anchors

By default, `anchor-identifier` rich text entities will be rendered as HTML `anchor` elements, e.g.:

``` html
<a href="#my-element" id="my-element" data-id="my-element">My element</a>
```

This package provides an alternative renderer that renders `anchor-identifier` entities as HTML `span` elements, e.g.:

``` html
<span id="my-element">My element</span>
```

The desired renderer can be specified using the `DRAFTAIL_ANCHORS_RENDERER` setting. To use the `span` renderer, configure your application as follows:

``` python
DRAFTAIL_ANCHORS_RENDERER = "wagtail_draftail_anchors.rich_text.render_span"
```

It is possible to define your own renderer. It should be a callable that takes a `dict` of attributes, and returns a string containing the opening tag of the HTML element that represents the anchor target. The `dict` passed to the renderer, for an anchor with an identifier of `"my-anchor"`, would look like the following:

``` python
{"data-id": "my-anchor", "href": "#my-anchor", "id": "my-anchor", "linktype": "my-anchor"}
```

If you define your own renderer, you should set the value of `DRAFTAIL_ANCHORS_RENDERER` to your custom renderer's import path.

See `render_span` and `render_a` in `wagtail_draftail_anchors.rich_text` for examples.
rosbags-dataframe 0.10.1
Python library to convert ros message streams to pandas dataframes.
Requires Python: >=3.10
Keywords: conversion, dataframe, message, msg, pandas, ros, ros2, rosbag, rosbag1, rosbag2, rosbags, series

.. image:: https://gitlab.com/ternaris/rosbags-dataframe/badges/master/pipeline.svg
   :target: https://gitlab.com/ternaris/rosbags-dataframe/-/commits/master
   :alt: pipeline status

.. image:: https://gitlab.com/ternaris/rosbags-dataframe/badges/master/coverage.svg
   :target: https://gitlab.com/ternaris/rosbags-dataframe/-/commits/master
   :alt: coverage report


=================
Rosbags-dataframe
=================

Rosbags-dataframe a python library to ease the create of pandas dataframes from rosbag messages. It is part of the larger `Rosbags <https://gitlab.com/ternaris/rosbags>`_ ecosystem.

Rosbags-dataframe does not have any dependencies on the ROS software stacks and can be used on its own or alongside ROS1 or ROS2.


Getting started
===============

Rosbags-dataframe is published on PyPI and does not have any special dependencies. Simply install with pip::

   pip install rosbags-dataframe


Get a dataframe from a rosbag:

.. code-block:: python

   from pathlib import Path

   from rosbags.dataframe import get_dataframe
   from rosbags.highlevel import AnyReader

   with AnyReader([Path('test1.bag'), Path('test2.bag')]) as reader:
       dataframe = get_dataframe(reader, '/gps', ['latitude', 'longitude'])


Documentation
=============

Read the `documentation <https://ternaris.gitlab.io/rosbags-dataframe/>`_ for further information.

.. end documentation


Contributing
============

Thank you for considering to contribute to rosbags-dataframe.

To submit issues or create merge requests please follow the instructions provided in the `contribution guide <https://gitlab.com/ternaris/rosbags-dataframe/-/blob/master/CONTRIBUTING.rst>`_.

By contributing to rosbags-dataframe you accept and agree to the terms and conditions laid out in there.


Development
===========

Clone the repository and setup your local checkout::

   git clone https://gitlab.com/ternaris/rosbags-dataframe.git

   cd rosbags-dataframe
   python -m venv venv
   . venv/bin/activate

   pip install -r requirements-dev.txt
   pip install -e .


This creates a new virtual environment with the necessary python dependencies and installs rosbags-dataframe in editable mode. The rosbags-dataframe code base uses pytest as its test runner, run the test suite by simply invoking::

   pytest


To build the documentation from its source run sphinx-build::

   sphinx-build -a docs public


The entry point to the local documentation build should be available under ``public/index.html``.


Support
=======

Professional support is available from `Ternaris <https://ternaris.com>`_.