semvec/pypi-packages huggingface dataset:
django-reactify 1.4.0
A package to reactify Django app.
Requires Python: >=3.6
Keywords: django reactjs

===============
Django Reactify
===============

Django Reactify is an app that allows developers to add and use React components in their Django app without using the legacy `create-react-app <https://github.com/facebookincubator/create-react-app>`_.

Quick start
-----------

1. Install the package via the following command:

    pip install django-reactify

2. Add "reactify" to your INSTALLED_APPS setting like this::

    INSTALLED_APPS = [
        ...
        'reactify',
    ]

3. Run the following command:

    python manage.py reactify <app_name>

   Ensure that the templates directory exists in the specified app name.

    - Replace the app name with the existing Django app you want to reactify.

    - This command does the following:

        * Creates barbel and webpack configuration files in the app's root directory.

        * Creates package.json file with the scripts to run React development server.

        * Creates a react folder directory with the necessary files and subdirectories where you can add your react component files and redux actions and reducers.

        * Creates a react folder directory with the necessary files and subdirectories where you can add your react component files and redux actions and reducers.

        * Installs the basic npm development packages.

        * starts the react development server that listens on the changes made to the react components and compile a minimal js file that is rendered to the view.

4. cd into the django app (app_name) directory and run the following command:

    npm run dev


5. Add the new view function to the views file to render the compiled version of the react app.

    def index(request):
        template_name = '<app_name>/index.html'

        return render(request, template_name)

6. Add more React components to the react app's component folder.

Managing React Routes
---------------------
If you don't configure Django urls to accept the Routes declared in the react, you will encouter 404 error.

To fix this, lets say you have react routes as follows:

    <Switch>
        <Route exact path="/" component={Main} />

        <Route exact path="/login" component={LoginPage} />

        <Route exact path="/services" component={ServicesPage} />

        <Route exact path="/about" component={AboutPage} />

In the app urls file use `re_path`,

    from django.urls import re_path

    from .views import index

    urlpatterns = [
        re_path(r'', index, name="home"),
        ]
skytemple-dtef 1.8.0
Dungeon Tile Exchange Format: A format for standardized rule-based tilesets with 256 adjacency combinations.

|logo|

SkyTemple Dungeon Tile Exchange Format (DTEF)
=============================================

|build| |pypi-version| |pypi-downloads| |pypi-license| |pypi-pyversions| |discord|

.. |logo| image:: https://raw.githubusercontent.com/SkyTemple/skytemple/master/skytemple/data/icons/hicolor/256x256/apps/skytemple.png

.. |build| image:: https://img.shields.io/github/actions/workflow/status/SkyTemple/skytemple-dtef/build-test-publish.yml
    :target: https://pypi.org/project/skytemple-dtef/
    :alt: Build Status

.. |pypi-version| image:: https://img.shields.io/pypi/v/skytemple-dtef
    :target: https://pypi.org/project/skytemple-dtef/
    :alt: Version

.. |pypi-downloads| image:: https://img.shields.io/pypi/dm/skytemple-dtef
    :target: https://pypi.org/project/skytemple-dtef/
    :alt: Downloads

.. |pypi-license| image:: https://img.shields.io/pypi/l/skytemple-dtef
    :alt: License (GPLv3)

.. |pypi-pyversions| image:: https://img.shields.io/pypi/pyversions/skytemple-dtef
    :alt: Supported Python versions

.. |discord| image:: https://img.shields.io/discord/710190644152369162?label=Discord
    :target: https://discord.gg/skytemple
    :alt: Discord

.. |kofi| image:: https://www.ko-fi.com/img/githubbutton_sm.svg
    :target: https://ko-fi.com/I2I81E5KH
    :alt: Ko-Fi

A specification / standard for dungeon tilesets. The specification can be found in "docs/format.rst".

Additionally this repository contains a reference implementation for importing / exporting tilesets from the
game Pokémon Mystery Dungeon Explorers of Sky. This implementation supports a specific subset of the standard,
which is documented in "docs/SkyTemple.rst".

The goal of this standard is to make it easy to exchange rule-based tilesets between different games, tools and engines.

Part of PMDCollab_, a collaborative effort for standardizing PMD related development efforts.

.. _PMDCollab: http://pmdcollab.org/

|kofi|
pycoverm 0.6.2
Simple Python interface to CoverM's fast coverage estimation functions
Requires Python: >=3.8
Keywords: bioinformatics

# pyCoverM

This package is still in experimental stages and aims to be a simple Python interface to [CoverM](https://github.com/wwood/CoverM)'s fast coverage estimation functions. Currently, pyCoverM provides two functions: `is_bam_sorted`, which checks whether a BAM file is sorted by coordinate, and `get_coverages_from_bam`, that computes average contig coverages from sorted BAM files.

## Installation

```
pip install pycoverm
```

## Usage

```rust
/// is_bam_sorted(bam_file)
/// --
///
/// Checks whether a BAM file is sorted by coordinate.
///
/// Parameters
/// ----------
/// bam_file : str
///     Path to a BAM file.
///
/// Returns
/// -------
/// bool
///     Returns `True` if the BAM file is sorted by coordinate and `False`
///     otherwise.
```

```rust
/// get_coverages_from_bam(bam_list, contig_end_exclusion=75, min_identity=0.97,
/// trim_lower=0.0, trim_upper=0.0, contig_list=None, threads=1)
/// --
///
/// Computes contig mean coverages from sorted BAM files. All BAM files must be
/// mapped to the same reference.
/// Trimmed means will be computed if `trim_min` and/or `trim_max` are set to
/// values greater than 0.
///
/// Parameters
/// ----------
/// bam_list : list
///     Paths to input BAM files.
/// contig_end_exclusion : int, optional
///     Exclude bases at the ends of reference sequences from calculation.
///     Default is 75.
/// min_identity : float, optional
///     Exclude reads by overall identity to the reference sequences.
///     Default is 0.97.
/// trim_lower : float, optional
///     Fraction to trim from the lower tail of the coverage distribution.
///     Default is 0.0.
/// trim_upper : float, optional
///     Fraction to trim from the upper tail of the coverage distribution.
///     Default is 0.0.
/// contig_set : set, optional
///     If provided, only the coverages of the contigs within `contig_set` will
///     returned.
///     Default is None (return the coverages of all contigs).
/// threads : int, optional
///     Number of threads to use for coverage computation. Default is 1.
///
/// Returns
/// -------
/// tuple
///     A tuple whose fist element is a list of the contig names and the second
///     one is a numpy matrix of contig coverages in the input BAM files.
```