semvec/pypi-packages huggingface dataset:
savefig 0.0.4
Save matplotlib figures with embedded metadata for reproducibility and profit
License: MIT

*Remember that time where you tried to remake a figure for your paper and
couldn't seem to get the same results? We've all been there. Well not
anymore!*

This module monkey patches the ``savefig`` command from `matplotlib
<http://matplotlib.org/>`_ and inserts your current git commit hash into
the metadata of the saved file. Currently it supports PNG and PDF figures.

.. image:: https://travis-ci.org/dfm/savefig.svg?branch=master
        :target: https://travis-ci.org/dfm/savefig

Usage
-----

First, install the module `from PyPI <https://pypi.python.org/pypi/savefig>`_::

    pip install savefig

or `from source <https://github.com/dfm/savefig>`_::

    git clone https://github.com/dfm/savefig.git
    cd savefig
    python setup.py install

Then in all your code just add the following lines before importing matplotlib::

    from savefig import monkey_patch
    monkey_patch()

To read the metadata from an existing image file, run::

    python -m savefig /path/to/figure.png

which will give you something like::

    git-hash: 192a639c4a9eb7523e9becd23f359fd7d96e833f
    git-date: 2014-03-29 21:30:27 -0400
    git-author: Dan F-M

You can also get the diff between the saved commit hash and the version used
to make the figure by running::

    python -m savefig /path/to/figure.png --diff


License
-------

Copyright 2014 Dan Foreman-Mackey

Available under the MIT License.
celerybeatmongo 0.1.2
A very simple Celery Beat Scheduler that stores status information in a MongoDB database.
License: MIT
Keywords: celery beat scheduler mongo python

# celerybeatmongo
A very simple Celery Beat Scheduler that stores status information in a MongoDB database.

# Install

```
pip install celerybeatmongo
```

# Details

This project provides a Celery Beat Scheduler that uses MongoDB to store the schedule stats (last run, run count, etc.). This is safer than using a file on your server which could be cleared or corrupted (on Heroku for example). This scheduler aims to replace the default Beat Scheduler provided with Celery. There are a few caveats though:

* Only supports interval scheduling (currently, easy to add support for Crontab and Solar)
* Can only pass native JSON types (dict, list, str, number) to `kwargs`, `args`, and `options` for tasks

## Motivation

I started this project because I run Celerybeat on Heroku and I started noticing that tasks were being dropped. This was because the default Celerybeat Scheduler (`[celery.beat.PersistentScheduler](http://docs.celeryproject.org/en/latest/reference/celery.beat.html#celery.beat.PersistentScheduler)`) uses a shelve database file that it adds the current directory. In Heroku this file was cleared and so the schedule data was not saved reliably. With the `celerybeatmongo.MongoPersistentScheduler` this is not an issue anymore.

# Example

Please see `examples/celery_worker.py` for a simple example to just try it out. 

Running the example requires MongoDB and Redis (you can edit it to use another Broker instead if Redis if you want).
* [Install Redis](https://redis.io/topics/quickstart)
* [Install MongoDB](https://docs.mongodb.com/manual/installation/)

You can run the following to start the example:

1. In a seperate terminal window, start Redis:
 ```shell
 $ redis-server      # start redis
 ```

2. In a seperate terminal window, start MongoDB:
 ```shell
 $ mongod
 ```

3. Then start the example worker:
 ```shell
 $ pip install redis
 $ python examples/celery_worker.py
 ```


# Contribute

Please add issues or put up pull requests if you need more functionality or have suggestions. Its a new project and should be easy to contribute to!
enimda 2.1.0
Entropy-based image border detection algorithm library
License: MIT
Keywords: image border whitespace detection algorithm enimda entropy

ENIMDA
======

Entropy-based image border detection algorithm: finds out if your image has
borders or whitespaces around and helps you to trim border providing whitespace
offsets for every side of a picture, supports animated GIFs.

|pypi| |travisci|

.. |pypi| image:: https://badge.fury.io/py/enimda.svg
    :target: https://badge.fury.io/py/enimda
    :alt: pypi version
.. |travisci| image:: https://travis-ci.org/embali/enimda.svg?branch=master
    :target: https://travis-ci.org/embali/enimda
    :alt: travis ci build status

Algorithm (simplified)
----------------------

For each side of the image starting from top, rotating image counterclockwise
to keep side of interest on top:

* Get upper block 25% of image height
* Get lower block with the same height as the upper one
* Calculate entropy for both blocks and their difference
* Make upper block 1px less
* Repeat from p.2 until we hit image edge
* Border is between blocks with entropy difference maximum

.. image:: https://raw.githubusercontent.com/embali/enimda/master/algorithm.gif
    :alt: Sliding from center to edge - searching for maximum entropy difference
    :width: 300
    :height: 300

Requirements
------------

Python 3.5+

Setup
-----

.. code-block:: bash
    
    python-3.6 -m venv .env
    source .env/bin/activate
    pip install enimda

Usage
-----

Find if image has borders:

.. code-block:: python

    from enimda import ENIMDA


    # Load target image
    em = ENIMDA(fp='test.jpg')

    # Scan for borders with high precision
    borders = em.scan(fast=False)

    # Print found image borders (tuple): top, right, bottom, left
    print(borders)

Demo
----

For demo please refer to `ENIMDA Demo <https://github.com/embali/enimda-demo/>`_

Also it lives at `Picture Instruments <http://picinst.com/>`_ as 'Remove borders'
instrument

Tests
-----

Run tests: py.test
soulapi 0.0.5
soul shell client
License: MIT
Keywords: soul client api

# soul

soul api client

## Install

```bash
pip3 install soulapi
```

## Usage

In a terminal:

1. get help

```bash
soul -h             # get help and available module, method, property
soul -h use         # get help for `use` api
soul -h post       # get help for `post` module
soul -h post like  # get help for `post.like` method
```

2. login: most api need to authorization, so, you should login at first

```bash
soul login PHONE PASSWORD AREA  # use mobile or email to login

soul use SECRET                     # use token directly
```

3. use api

```bash
soul post recommended
```

## LICENSE

MIT