Skip to content

Latest commit

 

History

History
77 lines (55 loc) · 3.65 KB

README.md

File metadata and controls

77 lines (55 loc) · 3.65 KB

Twitter Automation flake8 flake8 wakatime

The official Twitter API with all features will cost you around $40,000/month. This framework is alternative for it. Twitter Automation is a robust and flexible automation framework, written in Python with stable, best system design architecture and is also easy-to-use. With Twitter Automation, users can automate tweet, retweet, like, and comment on tweets without using the Twitter's official APIs. This independence allows for greater customization and control over Twitter automation.

Key Features

  • Tweet a tweet using GPT-3 with a user-provided prompt and tags
  • Retweet and like tweets
  • Comment on tweets
  • Independent of Tweepy API
  • Utilizes Selenium for web automation, OpenCV for image processing, PyAutoGUI for GUI automation, and OpenAI GPT-3 for natural language processing.

Technical Details

Twitter Automation is built on top of cutting-edge technologies, including:

  • OpenAI GPT-3 for natural language processing, powering the tweet generation functionality
  • Selenium for web automation, allowing users to perform various actions on the Twitter website
  • OpenCV for image processing, enabling Twitter Automation to recognize specific elements on the Twitter website
  • PyAutoGUI for GUI automation, allowing Twitter Automation to simulate user input and interactions

Getting Started

cd twitter_automation

sudo apt update

install the python packages

python3 -m pip install -r requirements.txt

install the dependencies

sudo apt-get install $(cat package.txt)

install the chrome web-driver from https://chromedriver.chromium.org/downloads unzip and set the environment variable as DIVER_PATH as the path of the chromedriver binary-file like shown.

export DRIVER_PATH='/path/to/the/chromedriver'

also add the METADATA.json file path to your environment using

export METADATA='/path/to/metadata.json'

metadata.json is a file that you have to write it on your own, its a file that contains the credentials of the twitter userprofile/bots using which you are going to use this framework APIs just create a metadata.json file and use the format like below

  {
    "bot1": {
      "EMAIL_KEY": "username1.dummymail.com",
      "USERNAME_KEY": "twitterhandle1",
      "PASSWORD_KEY": "password1"
    },
    "bot2": {
      "EMAIL_KEY": "username2.dummymail.com",
      "USERNAME_KEY": "twitterhandle2",
      "PASSWORD_KEY": "password2"
    }
  }

NOTE: if you want to use Openai gpt-3's response as tweet content then you will also be needing a Openai API key, add the key to your environment using export API_KEY='your key'

Build guide

build

docker build -t <image_name:tag> .

run

docker run -v /path/to/host/bot_metadata.json:/root/bot_metadata.json -e METADATA='/root/bot_metadata.json' --name <contianer_name> -d -p 2222:22 <image_name:tag>

docker exec -it <container_name> bash

Conclusion

Overall, Twitter Automation is a powerful automation framework that allows for greater control and customization over Twitter automation. With its use of cutting-edge technologies, users can perform a variety of actions on Twitter without the limitations of the Tweepy API.