Tweepy VS AWS-CICD

How is this much different than what tweepy does?

There are plenty of open source modules you can use, such as tweepy, which will make it a lot easier for you.

I chose Python as a language to handle the streaming, because a) it’s the language I’m strongest in, and b) because of tweepy.

· Tweepy. An easy-to-use Python library for accessing the Twitter API.

As announced in this blog post, the Twitter API v2 supports the ability to get metadata about edited Tweets. In this short guide, I will showcase how developers and researchers can get information about edited Tweets from the Twitter API v2 in Python using Tweepy.

In this tutorial, we will configure AWS CodePipeline to build an ECR image and deploy the latest version to lambda container. The application code will stream tweets using Tweepy, a Python library for accessing the Twitter API. First we need to setup CodePipeline and the various stages to deploy application code to lambda image which will stream tweets when invoked. The intended devops architecture is as below.

That means you need a requirements.txt file in your repo somewhere, and it needs to list the dependencies for your project. A good way of knowing what the dependencies are is to check what you imported at the beginning of your python file. For my bots, I need Tweepy, config, and Python-dotenv Requirements.txt looks like this for Divas, my Twitter Bot Collection.

you can easily make a simple script with tweepy that scrapes the data and puts it into whatever file you need

In order to use the Twitter API v2, you need to apply for a Twitter developer account. Once you have an approved Twitter developer account, follow the instruction here to obtain your BEARER TOKEN that you will use to connect to the Twitter API v2 in you code in Python. We will be using the Tweepy package in Python to get images from the Twitter API v2, so you will need to have Python as well as the Tweepy package installed on your machine. Instructions on installing the Tweepy package can be found in this tutorial.

The stages described above are just an example and could be fewer or more depending on the application. For example, we could have more environments for testing before deploying to production. For the rest of the blog, we will describe how some of these stages can be configured for deploying the twitter streaming application. All source code referenced in the rest of the article can be accessed here.