semvec/pypi-packages huggingface dataset:
dash-chartist 0.0.5
Dash wrapper for chartist library
License: MIT

# dash-chartist

Minimal [Dash](https://dash.plot.ly/) wrapper for [react-chartist](https://github.com/fraserxu/react-chartist) library.

![](https://raw.githubusercontent.com/stevej2608/dash-chartist/master/docs/img/showcase.png)

**Code Snippet**
```
from dash_chartist import DashChartist
import dash
from dash import  html

external_stylesheets = [
    "https://cdnjs.cloudflare.com/ajax/libs/chartist/0.3.1/chartist.min.css",
    ]

app = dash.Dash(__name__, external_stylesheets=external_stylesheets)


data = {
    "labels": ['W1', 'W2', 'W3', 'W4', 'W5', 'W6', 'W7', 'W8', 'W9', 'W10'],
    "series": [ [1, 2, 4, 8, 6, -2, -1, -4, -6, -2] ]
}

options = {
    "high": 10,
    "low": -10,
}

chartType = 'Bar'

app.layout = html.Div([
    DashChartist(type=chartType, options=options, data=data)
])


if __name__ == '__main__':
    app.run_server(debug=False, host="0.0.0.0", port=5000)
```

## Installation

You can install *dash-chartist* with `pip`:

```
pip install dash-chartist
```

## Documentation

Head over to the [*README*][docs-homepage] for more details.

## Contributing

The source code for *dash-chartist* is available
[on GitHub][dash-chartist-repo]. If you find a bug or something is unclear, we encourage
you to raise an issue. We also welcome contributions, to contribute, fork the
repository and open a [pull request][dash-chartist-pulls].


[dash-homepage]: https://dash.plot.ly/
[dash-chartist-repo]: https://github.com/stevej2608/dash-chartist
[docs-homepage]: https://github.com/stevej2608/dash-chartist/blob/master/README.md
[dash-chartist-pulls]: https://github.com/stevej2608/dash-chartist/pulls
glrlm 0.1.0
Gray Level Run Length Matrix
License: MIT
Keywords: python,glrlm,feature extraction,image processing

# python-glrlm

This is library of Gray Level Run Length Matrix, feature extraction method of image processing

![GitHub](https://img.shields.io/github/license/eiproject/python-glrlm)
![GitHub top language](https://img.shields.io/github/languages/top/eiproject/python-glrlm)
![GitHub all releases](https://img.shields.io/github/downloads/eiproject/python-glrlm/total)
![GitHub release (latest by date)](https://img.shields.io/github/v/release/eiproject/python-glrlm)

## Installation

```console
pip install glrlm
```

## Usage Example

```python
from glrlm import GLRLM
import cv2

IMG_PATH = 'path_to_your/image'
img = cv2.imread(IMG_PATH)

app = GLRLM()
glrlm = app.get_features(img, 8)
```

## Features extracted

Feature extraction result from GLRLM library

- SRE = Short Run Emphasis
- LRE = Long Run Emphasis
- GLU = Grey Level Uniformity
- RLU = Run Length Uniformity
- RPC = Run Percentage

## Support

Reach me out on [Email](mailto:razifrizqullah@gmail.com "razifrizqullah@gmail.com")

## Contribution

If you find out this library as useful please give it a star to let everyone know. If you have idea on how to improve this library, I am always open for every contributors. Thank you!
namez 0.3.0
A package for accessing objects by name
License: MIT
Requires Python: >=3.8,<4.0

# namez

A package for accessing objects by name

## Installation

```bash
$ pip install namez
```

## Usage

- TODO

## Contributing

Interested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.

## License

`namez` was created by Shawn Presser. It is licensed under the terms of the MIT license.

## Credits

`namez` was created with [`cookiecutter`](https://cookiecutter.readthedocs.io/en/latest/) and the `py-pkgs-cookiecutter` [template](https://github.com/py-pkgs/py-pkgs-cookiecutter).
mocona 1.0.2
test
License: MIT

# data_xchg  (Data_Transfer)

data_xchg is the ultimate module to exchange data in any form (video or string) from one PC to another.

Installation
============

    pip install data-xchg

The following convention is used here: 
* the server is transmitting data
* the client is receiving data

Usage
============

server_video.py 

    import data_xcfg.server as server
    server_socket = server.conn('your ip address', 'port no')
    server.frame(server_socket, 0) 

client_video.py

    import cv2
    import data_xcfg.client as client
    client_socket = client.conn('your ip address', 'port no)
    while True:
        frame = client.frame(client_socket)
        cv2.imshow('frame', frame)
        cv2.waitKey(1)
        
 server_data.py
 
    import data_xcfg.server as server
    server_socket = server.conn('your ip address', 'port no)
    while True:
        addr = server.address(server_socket)
        for i in range(0, 10000):
            message = str(i)
            message = message.encode('utf-8')
            server_data.send(server_socket, message, addr)
            
            
client_data.py

    import data_xcfg.client as client
    client_socket = client.conn('your ip address', 'port no)
    while True:
      data = client.recv(client_socket)
      print(data)