semvec/pypi-packages huggingface dataset:
kopiccino 1.0.0a1
Script sharing made simple.
Requires Python: >=3.7

# kopiccino: script sharing made ez

_kopiccino_ is a Python port of [package.swift](https://github.com/ColdGrub1384/LibTerm/Commands/builtins/package.swift), an inbuilt package manager for Libterm.

## Why yet another package manager?

[Pip](https://pypi.org/project/pip/) is the de-facto package manager for Python that has made distributing Python software reletively pain-free.
However, what if you wanted to share one-off scripts that simply does not justify the use of a full-blown package?

This is where _kopiccino_ steps in. You simply put into a zip file:
- the main script (entrypoint, in pip terms),
- other modules (if it is a Pip package, see below)

or just place the files/directories into a folder and let _bao_ do the work for you, which yields a _bao_ package (a.k.a a bun).

## Installation

```
pip install kopiccino
```

A bootstrappable version for developemnt based on the latest Github commit is WIP.

## Packages

From script to deployment:

```
$ mkdir helloworld && cd helloworld
$ echo 'print("Hello world!")' >> helloworld.py
# add metadata to helloworld.py here
$ kopiccino pour .
$ ls
helloworld.py  helloworld.zip
```
where `helloworld.zip` is the package bundled with the metadata in [TOML](https://en.wikipedia.org/wiki/TOML) format.
_kopiccino_ parses the main script for the bun metadata, which should have the following attributes defined:

- `__doc__` (str): Docstring at the top of your script (package description)
- `__author__`(str): The code authors.
- `__license__`(str): The [SPDX](https://spdx.org/licenses/) identifer. If your code uses a custom license, put its short form here.
- `__version__`(str): The semantic version of the package (see [this](https://semver.org/).

From there, you can host the package online and provide the direct URL of to the enduser (bun.zip must be in the same path as bun.toml).

## Repositories

To create a local repository, do:

```
mkdir testing && cd testing
kopiccino local init .  # the name of the folder will be the repository nickname
# move your built/unbuilt packages here
kopiccino local register  # register all packages and build them, if needed
```

This creates a `MANIFEST.toml` file which contains a mapping of all packages to their
metadata. If you add any more packages, run `kopiccino local register` again.

Alternatively, you can put your packages as folders (i.e unbuilt), and _kopiccino_
will create them automatically for you.

For backward compatibility, _kopiccino_ can use the Github REST(v3) API to download
packages if the MANIFEST.toml file is not present (i.e in the [LibTerm-Packages](https://github.com/ColdGrub1384/LibTerm-Packages) repo).

## Libterm compatibility

On Libterm, _kopiccino_ uses [userdefaults3](https://github.com/onyxware/userdefaults3) to modify `package.swift` configuration so any packages installed through `package.swift` is known to _kopiccino_ and vice-versa.
face-cropper 1.0.0
A image cropping library
Keywords: computer vision,crop,face recognition

[![PyPI version](https://badge.fury.io/py/face-cropper.svg)](https://badge.fury.io/py/face-cropper)
[![Build Status](https://travis-ci.com/Dave-Lopper/face_cropper_package.svg?branch=master)](https://travis-ci.com/Dave-Lopper/face_cropper_package)
[![Coverage Status](https://coveralls.io/repos/github/Dave-Lopper/face_cropper/badge.svg?branch=master)](https://coveralls.io/github/Dave-Lopper/face_cropper?branch=master)
# Face cropper

Welcome to the face cropper module !  
This module will :   
- Automatically detect faces on a provided picture
- Return the biggest one
- Save it in a location of your choosing !

### Requirements
- Python > 3.7  
- pip > 20.1.1

### Quickstart   
##### Use as a package ?
- `pip install face-cropper`    
##### Use as a CLI ?     
- Clone the repo   
- `pip install -r requirements.txt`   
- `python main.py --image_path=path\to\my\image --saving_path=where\to\save\cropped\image`   
   
     
### CLI documentation   
Just run the main.py module   
##### Required arguments :   
- image_path : The path of the image to be cropped   
- saving_path : The path where the cropped image should be saved   
##### Optionnal arguments :   
- verbose : Wether or not the command should output informations about the face
  detections   

### Module documentation
Simply import the ***crop*** function, and pass it the path of the image to be
cropped as  ***image_path*** !   
It is also possible to pass it another parameter, ***saving_path***, which if
provided will make *face_croper* save the image in the provided location !   
##### Example    
```python
import os

from face_cropper import crop

cropped_image = crop(
    image_path=os.path.join(os.getcwd(), "my_image.jpg")
)
```   
```python
import os

from face_cropper import crop

cropped_image = crop(
    image_path=os.path.join(os.getcwd(), "my_image.jpg"),
    saving_path=os.getcwd()
)
```