semvec/pypi-packages huggingface dataset:
automation-engine 0.5.0
Automation Engine powered by MQTT
License: MIT
Requires Python: >=3.8,<4.0

# Automation Engine

A lightweight and flexible framework to automate things with MQTT.

## What is Automation Engine?

Automation Engine is a Python framework for building automations using MQTT. The most common use case for this is automating a smart home where devices publish their state to a MQTT broker.

The leading self-hosted solution for this at the time of writing is [Home Assistant](https://www.home-assistant.io), which is a great piece of open-source software. However, the automations framework in Home Assistant is quite limited, and you usually have to build multiple flows to achieve a single "automation".

Automation Engine is intended for home automation enthusiasts who prefer writing short snippets of Python, rather than building a large number of GUI "flows". As such, Automation Engine is similar to [NodeRED](https://nodered.org), but uses Python rather than a browser-based editor.

## Prometheus Metrics

Prometheus metrics are exposed on port `9832` by default. The port can be configured via the `metrics_port` config key.

## Contributions

This project is released under the MIT Licence. For more information, please see LICENSE.

The CONTRIBUTORS file can be generated by executing CONTRIBUTORS.gen. This generated file contains a list of people who have contributed to Automation Engine.
PDFTrueDiffV10 0.0.1
A PDF comparison tool which helps to view the differences side-by-side
License: MIT
Requires Python: >=3.8


### Project Description 
## PDF-TrueDiff

This is a python package which can be used to compare and highlight the differences between two PDFs.
### Installation
* Make sure your python version is >= 3.8 

* Make sure you have upgraded your pip version
``py -m pip install --upgrade pip``

### Requirements
* For virtual environments in windows, make sure poppler is installed 
``venv - pip install poppler``
* For linux
`sudo apt-get install poppler-utils`
* For conda
```conda install -c conda-forge poppler```

From Pypi

`pip install PDF-TrueDiff==0.0.17`

The input is two PDF files along with the path where the final image need to be saved. The output will have a folder which contain the equalized PDF and a horizontally stacked image of both PDFs to give a side-by-side comparison of each page. The image will be saved as 'Final.png'

Sample code
```
import PDF-TrueDiff
input1 = "path to first PDF"
input2 = "path to second PDF"
output = "path to the directory to save the equalized PDFs and final image"
PDF-TrueDiff.document_equalizer(input1, input2, output)   
```
linkedin-bot 1.0.3
This library allow to do automatisation actions like, share and comment on LinkedIn
License: MIT
Requires Python: >=3.5
Keywords: linkedin,bot,bot_linkedin,automatisation

# PACKAGE - LINKEDIN-BOT

### **But**
Ce packages permet d'automatiser les tâches de like, partage et commentaire sur linkedIn.

### **Pour importer**
    from bot_linkedin import automate_linkedin

### **Fonctions**

- **linkedin_test_driver_manager_chrome(self)**: 

    Allow to install chromedriver and out in PATH

- **linkedin_get_ip(self)**: 

    Allow to return proxy

- **linkedin_create_session_crawl(self)**: 

    Allow to add options of my driver

- **linkedin_launch_page(self, link: str)**: 

    Allow to create my driver

- **linkedin_connect_account(self, url:str)**: 

    Allow to connect on LinkedIn account with driver

- **linkedin_get_last_publication(self)**: 

    Allow to get a last publication. Here this function return a first 

- **linkedin_get_publications(self)**: 

    Allow to get a publication in list contains element de type object_selenium

- **linkedin_like_post(self, post)**: 

    Allow to like a post

- **linkedin_share_post(self, post, text_share="Merci pour ce post")**: 

    Allow to share a post
                    
- **linkedin_comment_post(self, post, text_comment="Très intéressant :)")**: 

    Allow to comment a post 

- **linkedin_close_session(self)**: 

     Allow to close session create for the driver
twitter-automate 1.0.3
This library allow to do automatisation actions like, share and comment on Twitter
License: MIT
Requires Python: >=3.5
Keywords: automate,twitter-automate,twitter,automatisation

# PACKAGE - TWITTER-AUTOMATE

### **But**
Ce packages permet d'automatiser les tâches de like, partage et commentaire sur Twitter.

### **Pour importer**

    from bot_twitter import automate_twitter as at

### **Fonctions**

- **twitter_auth_api(self)**: 

    This function allow to authentificate on Twitter API

- **twitter_auth_client(self)**: 

    This function allow to authentificate on Twitter Client

- **twitter_get_last_post(self, user_api: twitter_auth_api, pseudo_twitter: str)**: 

    This function return a dictionary contain id of last tweet and date creation

- **twitter_get_posts(self, user_api: twitter_auth_api, pseudo_twitter: str, nb_tweet: int)**: 

    This function return last tweets in function value of variable 'nb_tweet'

- **twitter_like (self, user_client: twitter_auth_client, id_post: str)**: 

    This function allow to like a tweet

- **twitter_retweet(self, user_client: twitter_auth_client, id_post: str)**: 

    This function allow to retweet a tweet

- **twitter_comment(self, user_client: twitter_auth_client, id_post: str, text_comment: str)**: 

    This function allow to comment a tweet
Nasdaq-Data-Link 1.0.4
Package for Nasdaq Data Link API access
License: MIT
Requires Python: >= 3.7
Keywords: nasdaq data link,nasdaq,datalink,API,data,financial,economic

Official Nasdaq Data Link API Client for Python
===============================================

A Python library for Nasdaq Data Link's RESTful API.


Setup
=====

You can install this package by using the pip tool and installing:

    $ pip install nasdaq-data-link
bahasa 1.0.1
Bahasa is natural language toolkit for bahasa indonesia
License: MIT
Keywords: NLP,Bahasa,Indonesia,Stemmer,Sastrawi,Stemming

BAHASA
======

Modul stemmer yang digunakan merupakan hasil _porting_ dari [Sastrawi](https://github.com/sastrawi/sastrawi) dengan beberapa perubahan.

INSTALASI
---------

Kita dapat menginstal bahasa dengan cara sebagai berikut:
```bash
pip install bahasa
```


PENGGUNAAN
----------

```python
from bahasa.stemmer import Stemmer

stemmer = Stemmer()

hasil = stemmer.stem("Saat ini pemerintah sedang memilih untuk menentukan rel yang digunakan.")
print(hasil)
saat ini perintah sedang pilih untuk tentu rel yang guna

hasil = stemmer.stem("membuang-buang waktu")
print(hasil)
buang waktu

# Menambahkan kata ke dalam kamus
stemmer.add_words("lauk", "nasi", "piring")

# Menghapus kata dalam kamus
stemmer.remove_words("ikan", "kucing")
```

TEST
----
```bash
python -m unittest discover
```