Tweepy VS django-rest-framework

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 GitHub Discussion: link

Django’s "batteries-included" philosophy makes it an excellent choice for API development. With Django REST Framework (DRF), you get:

I am maintaining a Python codebase that is based on Django and Django REST Framework (DRF). The codebase uses Nix for development, testing, CI/CD and packaging.

Django Rest framework

Explore the Django REST Framework Documentation for advanced topics.

I've seen some companies using React with Django REST Framework [1], to keep the benefits of Django (I'm not a Django dev so I will have to guess, the ORM and project structure?) while having a strong separation between front and back (separate projects, teams, deploys, etc).

[1] https://www.django-rest-framework.org

Django REST Framework is a powerful and flexible toolkit for building Web APIs using Django, the popular high-level Python web framework. Zuplo proudly sponsors the DRF project to continue improving the Django API development ecosystem.

I think people tend to consider Django either for building old-school, industrial-strength monolith apps or for APIs and using something like React for the front-end. I’m here to tell you that plain old Django is a great option even for your personal websites! In my opinion, if you need a database, you should use Django1.

This post will extend Django REST Framework's ViewSet and SimpleRouter to provide a Rails-like request handler class + resource routing in server-render Django applications. It also features form-level method spoofing for PUT, PATCH and DELETE requests via custom middleware.

Django Rest Framework