semvec/pypi-packages huggingface dataset:
pbus 1.5.0
A simple application layer event-bus lib, support redis/mqtt/rabbitmq/kafka.
Keywords: pbus,bus,event,redis,rabbitmq,kafka

pbus
===============
A simple application layer event-bus lib, support redis/mqtt/rabbitmq.

Install
===============
```
 pip install pbus
```

Usage
===============
> 1. Use with Redis/MQTT/RabbitMQ Bus class.

Subscriber

```python
import pbus
bus = pbus.RedisBus(host='127.0.0.1')   # need "pip install redis"
# or
bus = pbus.MQTTBus(host='127.0.0.1')   # need "pip install paho-mqtt"
# or
bus = pbus.RabbitMQBus(host='127.0.0.1')   # need "pip install pika"
# or
bus = pbus.MemoryBus(exchange='ex1')    # with memory, can't use in multi-processing
# or
bus = pbus.KafkaBus(host='127.0.0.1') # with kafa, need "pip install kafka"
ps = bus.subscriber('test')
for data in ps.listen():
    print(data)
```

Publish
```Python
import pbus
bus = pbus.RedisBus(host='127.0.0.1')
# or
bus = pbus.MQTTBus(host='127.0.0.1')
# or
bus = pbus.RabbitMQBus(host='127.0.0.1')
bus.publish('test', 'Hello')

bus = pbus.MemoryBus(exchange='ex1')
bus.publish('test', 'Hello')
```

> 2. Use with URI(recommend)
```Python
import pbus
bus = pbus.connect("redis://:password@127.0.0.1:6379/2")    # with db 2
# or
bus = pbus.connect("mqtt://username:password@127.0.0.1:1883")    #
# or 
bus = pbus.connect("amqp://username:password@127.0.0.1:5672/myexchange")    #  with "myexchange" exchange
# or
bus = pbus.connect("memory:/ex1")    #  with "test" exchange

# ...... other code

```

> 3. Test event-bus speed.
- a. Run consumer client
```bash
python -m pbus -u redis://127.0.0.1
```

- b. Run producer client
```bash
python -m pbus -u redis://127.0.0.1 -p
```

You will see:
```
connecting to bus redis://127.0.0.1 ...
connecte success!
subscribing to pbus ...
subscribe success!
waiting data from pbus
1 :  count 27748 time: 5000ms speed: 5549/s total 27748
2 :  count 83135 time: 5000ms speed: 16627/s total 110883
3 :  count 86416 time: 5000ms speed: 17283/s total 197299
4 :  count 72546 time: 5000ms speed: 14509/s total 269845
```

Ctrl+C to stop test.

- c. Run both consumer and producer
```bash
python -m pbus -u redis://127.0.0.1 -l
```

You will see:
```
Consumer: connecting to bus redis://127.0.0.1 ...
Consumer: connecte success!
Consumer: subscribing to pbus ...
Consumer: subscribe success!
Consumer: waiting data from pbus
Producer: connecting to bus redis://127.0.0.1 ...
Producer: connecte success!
Producer: will publish "Hello World!" to pbus
--Press Ctrl+C to stop it!--
Consumer: 1 :  count 29119 time: 5000ms speed: 5823/s total 29119
Producer: 1 :  count 29642 time: 5000ms speed: 5928/s total 29642
```


[Click to view more information!](https://github.com/sintrb/pbus)


CHANGES
===============
1.0.0

- First version

1.1.0

- Support MQTT and RabbitMQ
- Support connect with URI


1.2.0

- Support Memory
polybiblioglot 0.2.0
A tool to translate scanned books
Requires Python: >=3.8,<4.0
Keywords: ocr,translation

[![CodeQL](https://github.com/bruno-robert/polybiblioglot/actions/workflows/codeql-analysis.yml/badge.svg?branch=master)](https://github.com/bruno-robert/polybiblioglot/actions/workflows/codeql-analysis.yml)
# polybiblioglot

A OCR tool to convert books scans into text and automatically translate them.

# Installation / Setup

## Requirements

### Tesseract

polybiblioglot uses tesseract for OCR, you will need to follow the steps described [here](https://github.com/tesseract-ocr/tesseract#installing-tesseract) to install tesseract.

On macos, you may find [this gist](https://gist.github.com/henrik/1967035) useful.

### Poppler

Poppler is a pdf renderer. In this case, we use it to convert pdf's to images for processing.
If you are only converting images, it isn't needed. Please note that the program may crash if you don't install poppler
and attempt to convert a pdf.

The [pdf2image](https://github.com/Belval/pdf2image) github explains how to install poppler depending on what platform you are on.
If you are on mac and have brew installed. It's as simple as `brew install poppler`

## Installation

Clone the repository:
`git clone https://github.com/bruno-robert/polybiblioglot.git`

cd into it:
`cd polybiblioglot`

(optional) create a python virtual environment:
`python -m venv env`
then
`source ./env/bin/activate`

install python dependancies
`pip install -r requirements.txt`

# Running polybiblioglot

To run polybiblioglot, simply execute the main.py file
`python main.py`

# Notes and limitation (for now)

## Limitations
- The OCR method used is optimized for high acuracy and not speed. I might add the functionality to change this in the future.

## Notes

- All computationally expensive or I/O intensive tasks are run asynchronously. This keeps the UI snappy. I'm currently using the DearPyGUI asynchronous call method wich will be depricated in the next version. A migration to python's out of the box threading library will be needed at that point.
rekishikon 0.3.2
A simple Language Detection Library
Requires Python: >=3.8,<4.0
Keywords: Language Detection,Language Classifier,Classifier,Multi-Language,n-gram

=================
rekishikon
=================
-------------------------------------------------
A simple, lightweight, language detection library
-------------------------------------------------

Simple Port of Nakatani Shuyo's Language Detection from Java to Python


With some fancy additions   

.. image:: https://travis-ci.com/K-Molloy/rekishikon.svg?branch=main
    :target: https://travis-ci.com/K-Molloy/rekishikon