semvec/pypi-packages huggingface dataset:
pydbow 0.1.2
Python Implementation of Bags of Binary Words
License: MIT
Requires Python: >=3.6

Bags of Binary Words
===================================

PyDBoW is a Python implementation of Bags of Binary Words algorithm.

## Requirements

- OpenCV
- numpy

## Installation

``` bash
pip install pydbow
```

## Usage

Refer to [demo.ipynb](https://github.com/goktug97/PyDBoW/tree/master/demo.ipynb) and
[demo.py](https://github.com/goktug97/PyDBoW/tree/master/demo.py) for example usage.

## Running tests

``` bash
python -m pytest
```

## License
PyDBoW is licensed under the MIT License.

Images are taken from https://github.com/commaai/comma10k
optext-python 0.1.1
Extension of Optional type inspired by Rust Option<T>.
License: MIT
Requires Python: >=3.8,<3.11
Keywords: option,python,rust

# Optext

[![Python package](https://github.com/kagemeka/optext/actions/workflows/python-package.yml/badge.svg)](https://github.com/kagemeka/optext/actions/workflows/python-package.yml)
[![readthedocs build status](https://readthedocs.org/projects/optext/badge/?version=latest)](https://optext.readthedocs.io/en/latest/?badge=latest)
[![PyPI version](https://badge.fury.io/py/optext.svg)](https://badge.fury.io/py/optext)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)


[`Optext`'s documentation](https://optext.readthedocs.io/)
---
pytest-click 1.1.0
Pytest plugin for Click
License: MIT

pytest-click
============

|Build| |Coverage| |Version| |Python versions| |License|

`pytest <https://github.com/pytest-dev/pytest>`_ plugin for `Click <http://click.pocoo.org/>`_.

Installation
------------

The current stable release:

::

    pip install pytest_click

Usage
-----

```pytest-click`` comes with some configurable fixtures - ``cli_runner`` and ``isolated_cli_runner``.

.. code:: python

    import click


    def test_cli(cli_runner):
        @click.command()
        @click.argument("name")
        def hello(name):
            click.echo("Hello %s!" % name)

        result = cli_runner.invoke(hello, ["Peter"])
        assert result.exit_code == 0
        assert result.output == "Hello Peter!\n"

.. code:: python

    import click


    def test_fixture(isolated_cli_runner):
        @click.command()
        @click.argument("f", type=click.File())
        def cat(f):
            click.echo(f.read())

        with open("hello.txt", "w") as f:
            f.write("Hello World!")

        result = isolated_cli_runner.invoke(cat, ["hello.txt"])
        assert result.exit_code == 0
        assert result.output == "Hello World!\n"

Both runners can be configured via ``runner_setup`` mark:

.. code:: python

    import pytest


    @pytest.mark.runner_setup(charset="cp1251", env={"test": 1}, echo_stdin=True)
    def test_runner_setup(cli_runner):
        ...

All kwargs will be passed to ``click.testing.CliRunner`` initialization.


.. |Build| image:: https://github.com/Stranger6667/pytest-click/workflows/build/badge.svg
   :target: https://github.com/Stranger6667/pytest-click/actions
.. |Coverage| image:: https://codecov.io/github/Stranger6667/pytest-click/coverage.svg?branch=master
    :target: https://codecov.io/github/Stranger6667/pytest-click?branch=master
.. |Version| image:: https://img.shields.io/pypi/v/pytest-click.svg
   :target: https://pypi.org/project/pytest-click/
.. |Python versions| image:: https://img.shields.io/pypi/pyversions/pytest-click.svg
   :target: https://pypi.org/project/pytest-click/
.. |License| image:: https://img.shields.io/pypi/l/pytest-click.svg
   :target: https://opensource.org/licenses/MIT
resgen 1.0.1
This package was made to help generate responsive images in bulk
License: MIT
Requires Python: >=3.2
Keywords: responsive images python web development developer response_images_gen responsive images generator

# Responsive generator
Responsive images generator is a command line python package that would convert all the images in your folder to responsive ones
in their own designated folder. The main goal of this package is to help developers quickly generate
responsive images in bulk.

### Image Sizes that would be generated
The Image sizes that would be generated would be based on the recommendations of this [article](https://medium.com/hceverything/applying-srcset-choosing-the-right-sizes-for-responsive-images-at-different-breakpoints-a0433450a4a3)
- 1920px (For FullHD Screens and up)
- 1600px (For desktops anf tables in portrait mode
- 1366px (Desktop)
- 1024px (1024X768 screens)
- 768px (Useful for 2x 375px mobile screens as well as any device)
- 640px (for smartphones)


## Installation and updating
Use the package manager [pip](https://pip.pypa.io/en/stable/) to install Res like below. 
Rerun this command to check for and install  updates .

```bash
pip install resgen
```

## Usage

**Make use you have python installed and Python script has been added to [Windows Path](https://datatofish.com/add-python-to-windows-path/), [Mac's Path](https://www.educative.io/edpresso/how-to-add-python-to-the-path-variable-in-mac) or Linux Path**

You need to run the command in the folder where your image folder would be
For example, in the tree below,  if your image folder is  images, you run the command in root

```bash
├── root
│   ├── images

````
While inside the folder, set the output folder and input folder

```bash
resgen  --input_folder  [input_folder] --output_folder [output_folder] 
```
or (if you havent added Python/Script to path)
```bash
python -m resgen  --input_folder  [input_folder] --output_folder [output_folder] 
```


- input_folder: The name of the input folder where the images are. Don't use ./input_folder . Just the name only
- output_folder: The name of the input folder where you want to save the files

**For Windows: To use this command without adding Python -m as the beginning, Make sure Python Script
is added to your PATH. [Refer Here](https://datatofish.com/add-python-to-windows-path/)**




The command would create folders in the output folder depending on the number of the images you have.

```bash
├── output_folder
│   ├── image_1
        ├── image_1_640_.jpeg
        ├── image_1_760_.jpeg
        
````
image_1_760_.jpeg represent the image with 760px for instance



#### Demo:

```bash
 resgen --input_folder input_folder --output_folder output_folder
```

## Contributing
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

## License
[MIT](https://choosealicense.com/licenses/mit/)
odap-adfrom-downloader 1.0.1
DataSentics adform downloader
License: MIT
Requires Python: >=3.7.1,<4.0.0

# DataSentics Python package for downloading adform data

**This package is distributed under the "DataSentics SW packages Terms of Use." See [license](https://github.com/DataSentics/odap-ga-downloader/blob/main/LICENSE)**

## Downloads data from adform in zip files

You need to specify:
  * Credentials (name, setup_id, client_id, secret)
  * Optionally you can specify scope, which data from Adform you would like to download, dates and file directory

```bash
$ pip install adform-downloader

from adform.Client import Client, FilePersistingHandler
from adform.Credentials import Credentials

setup_id = ""
client_id = ""
client_secret = ""

# optionally can be added into credentials. Written with default values
file = "/tmp/" # for state file
scopes = [
        "https://api.adform.com/scope/buyer.masterdata",
        "https://api.adform.com/scope/eapi",
        "https://api.adform.com/scope/buyer.rtb.lineitem",
    ]
tables = ["Click", "Event", "Impression", "Trackingpoint", "meta"]
start_day=today-8days, # format dd-mm-yyyy
end_day=today,
landing_file = "/tmp/" # for data, can be same as file

persisting_handler = FilePersistingHandler(location=file)
credentials = Credentials(setup_id=setup_id, client_id=client_id, client_secret=client_secret)
client = Client(credentials, persisting_handler)
client.download_masterdata_files_by_id()
```