semvec/pypi-packages huggingface dataset:
wagtail-lightadmin 0.13.1
A lighter admin for wagtail
License: MIT
Keywords: wagtail,admin,light

########################
Custom admin for wagtail
########################

.. image:: http://img.shields.io/pypi/v/wagtail_lightadmin.svg
   :target: https://pypi.python.org/pypi/wagtail_lightadmin/
.. image:: http://img.shields.io/badge/license-MIT-blue.svg
   :target: https://github.com/leukeleu/wagtail_lightadmin/blob/master/LICENSE
.. image:: http://img.shields.io/travis/leukeleu/wagtail_lightadmin/master.svg
   :target: https://travis-ci.org/leukeleu/wagtail_lightadmin

Features
========

This app customises the wagtail admin as follows:

Rich text
---------

Some of the less useful features are removed (HR, undo/redo, H4, H5).

Headings/paragraph come first (though https://stackoverflow.com/questions/10773813/adding-something-to-the-top-of-a-json-object).

The active state of the rich text (.expand) does not expand anymore

Publication flow
----------------

The "submit for moderation" button is hidden (it's mostly confusing for the type of clients we have).

Provides a LinkBlock
--------------------

It has the same UI as when you insert a link in a RichText but has the advantage of being avialable out of it.

In case you are using this block to replace a PageChooserBlock you can also use the pagechooser_fallback template tag.
The PageChooserBlock initially only saves the pk of the page you want to link to. This template tag gets the corresponding
page and extracts the URL and the page title from it to try and display what you would expect.
A similar logic is used to try and keep the page the editor initially picked on the admin side.


Install & setup
===============

`pip install wagtail_lightadmin`

Add `wagtail_lightadmin` to your installed apps.

Tell Wagtail to use the light rich text widget in your settings_default.py::

    WAGTAILADMIN_RICH_TEXT_EDITORS = {
        'default': {
            'WIDGET': 'wagtail.wagtailadmin.rich_text.HalloRichTextArea',
            'OPTIONS': {
                'plugins': {
                    'halloheadings': {'formatBlocks': ['p', 'h2', 'h3']},
                    'halloformat': {},
                    'hallolists': {},
                    'hallowagtaillink': {},
                    'hallorequireparagraphs': {},
                    'hallowagtailembeds': {},
                    'hallowagtailimage': {},
                    'hallowagtaildoclink': {},
                },
            }
        },
    }

Make sure django knows about the new static files

`manage.py collectstatic --no-input`
OptimalCluster 0.1.0
Python implementation of various algorithms to find the optimal number of clusters
License: MIT
Requires Python: >=3.6

# OptimalCluster
OptimalCluster is the Python implementation of various algorithms to find the optimal number of clusters. The algorithms include elbow, elbow-k_factor, silhouette, gap statistics, gap statistics with standard error, and gap statistics without log. Various types of visualizations are also supported.

For references about the different algorithms visit the following sites:

elbow : [Elbow Method](https://en.wikipedia.org/wiki/Elbow_method_(clustering).)

elbow_kf : 

silhouette : [Silhouette Score](https://scikit-learn.org/stable/modules/generated/sklearn.metrics.silhouette_score.html)

gap_stat : [Paper](http://www.web.stanford.edu/~hastie/Papers/gap.pdf)  |  [Python](https://anaconda.org/milesgranger/gap-statistic/notebook)

gap_stat_wolog : [Paper](https://core.ac.uk/reader/12172514)

# Installation

To install the OptimalCluster package through the Python Package index (PyPI) run the following command:
```
pip install OptimalCluster
```

## Documentation

Visit this link : [Documentation](https://github.com/shreyas-bk/OptimalCluster/blob/master/Documentation.md)

## Example

Visit this link : [Example](https://colab.research.google.com/github/shreyas-bk/OptimalClusterExampleNB/blob/master/Example.ipynb)