Twitter Automation using Twitter API V2 with Python Tweepy



Description

This course is designed to teach you how to automate your Twitter account using Twitter API V2 with Python Tweepy. Twitter has become a powerful social media platform for businesses and individuals to connect and grow their brand. However, managing a Twitter account can be time-consuming and tedious, especially if you're trying to increase your reach and engagement.
In this course, you will learn how to automate your Twitter account using Python Tweepy and Twitter API V2. You'll learn how to create a Twitter app, obtain your API keys, and use Tweepy to access Twitter's API to automate various tasks such as posting tweets, following users, sending direct messages, and more.


What You will Learn?

  • Understand the basics of Twitter API V2 and Python Tweepy
  • Learn how to automate tasks such as posting tweets, following users, sending direct messages, and more

Pre-Requisites

  • A Twitter account
  • Basic understanding of APIs

Skills

  • SECTION 1: SETTING UP YOUR TWITTER DEVELOPER ACCOUNT AND EXPLORING TWEEPY
    In this section, you will learn how to set up your Twitter Developer account and explore Tweepy, the Python library for Twitter API. We'll start by applying for a developer account with Twitter and downloading Postman, a tool we'll use to test out APIs. Next, we'll go through the process of registering our app and project with Twitter and generating the necessary API keys that we'll use to access the API. We'll then dive into Tweepy documentation and learn how to use it to get user information and the user ID. We'll also cover how to get user information using Postman, a powerful tool for exploring APIs. Finally, we'll explore a Python script to follow users with the Twitter API, demonstrating how we can automate tasks to grow our Twitter following. By the end of this section, you'll have the foundational knowledge and tools needed to begin automating your Twitter account using Python Tweepy and the Twitter API.

  • SECTION 2: SEARCHING FOR TWEETS AND RETRIEVING TWEET URLS USING TWEEPY DOCUMENTATION
    In this section, you will learn how to use Tweepy documentation to write code for searching for tweets using the Twitter API. You will also learn how to retrieve the URL of a searched tweet. Tweepy is a Python library that allows you to access the Twitter API. The documentation provides detailed information on how to use Tweepy to perform various tasks, including searching for tweets. By the end of this section, you will have a solid understanding of how to use Tweepy to search for tweets and retrieve their URLs, which will enable you to analyze and share specific tweets with your audience.

  • SECTION 3: BUILDING A TWITTER SEARCH APP WITH FLASK AND BOOTSTRAP
    In this section, we will be building a Twitter search app using Flask and Bootstrap. We will begin by getting started with the Bootstrap documentation and exploring different ways to add CSS and JS libraries to our app, either via CDN or manually. We will also discuss Bootstrap cards and plan how the tweets will look like when displayed on our app. Next, we will grab the search tweets function from last week's tutorial and incorporate it into our Flask app. We will then view the searched tweets returned from the API call inside the Flask app. We will also add a re-tweet functionality to the search function, allowing users to re-tweet the tweets they find interesting. Additionally, we will refine the Twitter search query to only include English tweets and no-retweets.

  • SECTION 4: TWEET CLASSIFICATION: OPENAI AI API
    In this section, we will provide a summary and preview of the application we will be building. We will also provide a link to the Github repository with the starting file for the tutorial, which will include a Flask application with Twitter API V2 search functionality. We will then set up OpenAI and Text Classification documentation, and begin by searching for tweets that we will use to develop the classification training document. The classification training document is required to train the OpenAI API model. We will manually classify the training data tweets based on the selected use case. Next, we will upload the classification training document to OpenAI and obtain the File ID of the uploaded file to use in the later steps. We will then write the python code to classify a string based on the training document. Additionally, we will add an extra page to the Flask application for tweet classification and write the python code for the tweet classification functionality. Finally, we will render the new HTML page just created.


Tutor: Bertha Kgokong

Software Programmer And Tech Entrepreneur

Software Programmer and Tech Entrepreneur, i have extensive experience in Software Development - end-to-end in most platforms, Business Processes and Entrepreneurship. I am a fully qualified Engineer, with a Bachelors Degree and Masters in Business Administration - with over 17 years of professional experience. I am also an entrepreneur with a couple of award winning ventures and projects in Software Development.