semvec/pypi-packages huggingface dataset:
zakatqr 1.2.4
Django App to Create Zakat Invoice QR Code Image
License: MIT
Keywords: django zakat invoice qrcode qr base64 encode

<div align="center">
    <h1>Django Zakat QR Code </h1>
    <p><strong>Unofficial Python Package</strong> to create QR Code Image as Base64 or as PNG for e-invoice system by ZATCA</p>
</div>

## Installation

### PyPi

```bash
$ pip install zakatqr
```

### GitHub

```bash
$ git clone https://github.com/halmogbl/zakat_qr
$ cd zakat_qr
$ python3 setup.py install
```

## Usage

### Variables

**Zakatqr class's variables and descriptions**

| Variable Name| Description|
|--------------|:-----:|
| seller_name  | Seller’s name. |
|  tax_number  | Seller’ tax number, which is the VAT registration number. |
| timestamp | Invoice date, which is the timestamp of the electronic invoice.|
| total_with_vat |  Invoice total amount, which is the electronic invoice total **with VAT**.|
| total_vat   |  Tax amount, which is the VAT total. |

### Generate Base64

```python
from zakatqr import Zakatqr

invoice = Zakatqr(
    seller_name="Example",
    tax_number="123456789", 
    timestamp="2021-06-25 07:58:56.550604", 
    total_with_vat="115",
    total_vat="15",
)

print(invoice.tlv_to_base64())
# AQdNeSBuYW1lAgkxMjM0NTY3ODkDGjIwMjEtMDYtMjUgMDc6NTg6NTYuNTUwNjA0BAMxMTUFAjE1
```

### Generate A QR Code Image as Base64

```python
from zakatqr import Zakatqr

invoice = Zakatqr(
    seller_name="Example",
    tax_number="123456789", 
    timestamp="2021-06-25 07:58:56.550604", 
    total_with_vat="115",
    total_vat="15",
)

print(invoice.qr_image_encoded_uri())
# data:image/png;base64,/9j/4AAQSkZJRgABAQAAAQABAAD/...
```

### Create A QR Code Image


```python
from fatoora import Fatoora

invoice = Zakatqr(
    seller_name="Example",
    tax_number="123456789", 
    timestamp="2021-06-25 07:58:56.550604", 
    total_with_vat="115",
    total_vat="15",
)

image = invoice.qr_code()
image.save("qr_code_img.png")
```

![](https://user-images.githubusercontent.com/47291955/152148241-daaabd0f-3c16-4a58-8678-106e835eb488.png)
ptmv 1.0.2
An utf-8/truecolor image and video viewer for the terminal
License: MIT

<p align="center">
    <h1 align="center"><b>Python Terminal Media Viewer</b></h1>
    <p align="center"><b>View images and videos without leaving the console</b></p>
	<h2 align="center"><a href="https://github.com/kal39/ptmv">More info on GitHub</a></h2>
</p>




----

### Features

* View **images** form any terminal
* Watch **videos** from any terminal
* Watch **youtube** videos from any terminal (`-y`, `--youtube`)
* Play videos at **any fps** (`--fps`) with sound
* **Resize** images / videos (`--width`, `--height`)
* Easy to use

----

### Requirements

* A terminal that supports **truecolor** ([list](https://gist.github.com/XVilka/8346728)) and **utf-8** (most terminals should support utf-8).

----

### Usage

```shell
ptmv FILE [OPTIONS]
```

* **Required arguments**  

    * `FILE`

        File to display/play or youtube url

* **Optional arguments**  

  * `-y`. `--youtube` 
    View youtube videos

  * `--height` 
    Set height (setting both `width` and `height` will ignore original aspect ratio)

  * `--width` 
    Set width (setting both `width` and `height` will ignore original aspect ratio)

  * `--start-time`
    
    Set start position for video.

  * `-f`, `--fps` 
    Set fps (default 15 fps)

  * `-m`, `--mute` 
    Mute audio

  * `-h`, `--help ` 
    Display help
textcleaning 0.0.1
An open-source python package to clean raw text data
License: MIT

# cleantext


**cleantext** is a an open-source python package to clean raw text data


## Features 

cleantext has two main methods,
* **clean**: to clean raw text and return the cleaned text
* **clean_words**: to clean raw text and return a list of clean words

cleantext can apply all, or a selected combination of the following cleaning operations:
* Remove extra white spaces
* Convert the entire text into a uniform lowercase
* Remove digits from the text
* Remove punctuations from the text
* Remove or replace the part of text with custom regex
* Remove stop words, and choose a language for stop words
( Stop words are generally the most common words in a language with no significant meaning such as is, am, the, this, are etc.)
* Stem the words
(Stemming is a process of converting words with similar meaning into a single word. For example, stemming of words run, runs, running will result run, run, run)

## Installation

cleantext requires [Python 3](https://www.python.org/downloads/) and [NLTK](http://www.nltk.org/install.html) to execute. 

To install using pip, use

`pip install cleantext`

## Usage

* **Import the library**:

``` python
import cleantext
```

* **Choose a method:**

 To return the text in a string format, 
 
``` python
cleantext.clean("your_raw_text_here") 
```
 
 To return a list of words from the text,
 
``` python
cleantext.clean_words("your_raw_text_here") 
```
 
 To choose a specific set of cleaning operations,

``` python
cleantext.clean_words("your_raw_text_here",
clean_all= False # Execute all cleaning operations
extra_spaces=True ,  # Remove extra white spaces 
stemming=True , # Stem the words
stopwords=True ,# Remove stop words
lowercase=True ,# Convert to lowercase
numbers=True ,# Remove all digits 
punct=True ,# Remove all punctuations
reg: str = '<regex>', # Remove parts of text based on regex
reg_replace: str = '<replace_value>', # String to replace the regex used in reg
stp_lang='english'  # Language for stop words
)
```

## Examples

``` python
import cleantext
cleantext.clean('This is A s$ample !!!! tExt3% to   cleaN566556+2+59*/133', extra_spaces=True, lowercase=True, numbers=True, punct=True)
```

returns,

``` Python
'this is a sample text to clean'
```

----

``` Python
import cleantext
cleantext.clean_words('This is A s$ample !!!! tExt3% to   cleaN566556+2+59*/133')
```

returns,

``` Python
['sampl', 'text', 'clean']
```

----

``` Python
from cleantext import clean
text = "my id, name1@dom1.com and your, name2@dom2.in"
clean(text, reg=r"[a-z0-9\.\-+_]+@[a-z0-9\.\-+_]+\.[a-z]+", reg_replace='email', clean_all=False)

```

returns,

``` Python
"my id, email and your, email"
```

## License

##### MIT