semvec/pypi-packages huggingface dataset:
pycrop 1.0.1
Methods to manipulate images
License: MIT
Keywords: pillow,contain,cover

# PyCrop

1. What it does
2. functions
    1. Contain
    2. Cover
3. Installation

## What it does
Methods to manipulate images

## Functions

### 1.Cover
- params:
    - path:str - image absolute path
    - size:list - output image size (width:int, height:int)
    - point:list - point from where image is cropped and resized
    - savepath:str - image destination path
    - quality:int - output image quality (from 0 to 100%)
- returns:
    - (resize status, output image path):tuple

Based on size, it will crop evenly distributed rectagle from point coordinates (in percentage).

### 2.Contain
- params:
    - path:str - image absolute path
    - size:list - output image size (width:int, height:int)
    - savepath:str - image destination path
    - quality:int - output image quality (from 0 to 100%)
- returns:
    - (resize status, output image path):tuple 

Function will fit source image in rectagle which has same dimensions as size.

## Installation

To install the package by `pip` run following command

```sh
$ pip install pycrop
```

or

```sh
$ pip install git+https://github.com/giorgi94/pycrop.git
```
prophepy 0.0.4
Python mocks made for humans
License: MIT
Requires Python: >=3.7,<4.0

# Prophepy

Python mocks made for humans.
Heavily inspired by the great PHP's [Prophecy](https://github.com/phpspec/prophecy).

## Usage

```python
from examples.calculator import Calculator
from examples.displayer import Displayer
from prophepy import prophesize

calculator = prophesize(Calculator)
displayer = Displayer(calculator._reveal())

calculator.add(2, 3)._should_be_called()
calculator.add(2, 3)._will_return(5)
displayer.display_add(2, 3)

calculator.check_prophecies()
```

## Install

`pip install prophepy`

## Tests

`python -m unittest tests/test.py`
pychemy 0.5.0
Helpers for handling chemical formulas in Python
License: MIT
Requires Python: >=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, <4
Keywords: chemistry mass spectrometry chemoinformatics analysis molecular

PyChemy
=======

.. image:: https://travis-ci.org/ginkgobioworks/pychemy.svg?branch=master
    :target: https://travis-ci.org/ginkgobioworks/pychemy

Helpers for handling chemical formulas in Python. Mostly adopted from work of
`Christoph Gohlke <http://www.lfd.uci.edu/~gohlke/>`_. Added methods that are useful for mass spec
data analysis.

Depends on `Open Babel <http://openbabel.org/>`_ and its Python bindings for handling InChI strings.


Development
-----------

Development requires Docker and Make on your host system. Everything else, including Open Babel, is
taken care of inside the Docker containers.

Spin up your container using the provided ``docker-compose.yml`` file and ``Makefile`` by running
``make image``. This creates an image with a correct git configuration for your user, which makes it
easy to release. All of the commands you should need to run are defined the ``Makefile`` as targets.
All of the targets except for ``image``, are meant to be run inside the Docker container, but can be
run from the host machine by having ``-ext`` appended to them. For example, to run tests, you could
either call ``make test`` from a shell inside the container, or ``make test-ext`` from the host.

This project supports both Python 2 and Python 3. To test Python 3, make run the ``make
test`` and ``make test-ext`` with the ``TOXENV`` environment set to ``py3``, e.g.:

::

    TOXENV=py3 ./make test-ext


All pull requests are run through the Travis CI process specified in ``.travis.yml`` and must pass
all unit and doc tests in Python 2 and Python 3 before being accepted.

Deployment
----------

Deployment of tagged commits happens to PyPI automatically via Travis CI. To bump and deploy a new
version directly, you must have access to write to the master branch. Run ``make bump/[foo]-ext``,
where ``[foo]`` is ``major``, ``minor``, or ``patch``. Then ``git push origin --tags master``. If
you do not have access to the master branch, do the same thing, but in a separate branch, and make
a pull request.