Tweepy
connexion
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Tweepy | connexion | |
---|---|---|
29 | 23 | |
10,234 | 4,414 | |
1.0% | 0.5% | |
4.6 | 8.4 | |
8 days ago | 2 days ago | |
Python | Python | |
MIT License | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Tweepy
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Twitter API Reverse Engineered
How is this much different than what tweepy does?
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question about the excitability of a project
There are plenty of open source modules you can use, such as tweepy, which will make it a lot easier for you.
- How can do I grow my Newsletter?
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Measuring World Cup sentiment with Twitter and Tinybird
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.
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Creating a twitter bot to automatically post Bitcoin and Ethereum prices.
· Tweepy. An easy-to-use Python library for accessing the Twitter API.
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How to analyze edited Tweets with the Twitter API v2 using Python
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.
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Setting up AWS Code Pipeline to automate deployment of tweets streaming application
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.
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Deployment for Twitter bots: 3 Alternatives to Traditional Cloud
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.
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Is there a tool that can automatically extract information about posts on Twitter (content, likes, comments, etc) 24h after an account has posted it?
you can easily make a simple script with tweepy that scrapes the data and puts it into whatever file you need
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Analyzing images using the Twitter API v2 and AWS
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.
connexion
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Write OpenAPI with TypeSpec
I like the idea, especially the TS-like syntax around enums and union types. I've always preferred the SDL for GraphQL vs writing OpenAPI for similar reasons.
I echo the sentiment others have brought up, which is the trade-offs of a code-driven schema vs schema-driven code.
At work we use Pydantic and FastAPI to generate the OpenAPI contract, but there's some cruft and care needed around exposing those underlying Pydantic models through the API documentation. It's been easy to create schemas that have compatibility problems when run through other code generators. I know there are projects such as connexction[1] which attempt to inverse this, but I don't have much experience with it. In the GraphQL space it seems that code-first approaches are becoming more favored, though there's a different level of complexity needed to create a "typesafe" GraphQL server (eg. model mismatches between root query resolvers and field resolvers).
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Connexion 3 released!
Connexion is a popular Python web framework (~ 5 million downloads per month) that makes spec-first and api-first development easy. You describe your API in an OpenAPI (or swagger) specification with as much detail as you want and Connexion will guarantee that it works as you specified.
- Connexion 3.0 Released
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Show HN: REST Alternative to GraphQL and tRPC
> While REST APIs don't generally provide the same level of control to clients as GraphQL, many times this could be seen as a benefit especially in scenarios where strict control over data access and operations is crucial.
Rest is more secure, cacheable, and more performant on the server side as field resolution doesn't need to happen like it does with GraphQL. It is not more performant on the client side, and this is a trade-off, but I favor rest applications over GraphQL ones as a DevOps engineer. They are much easier to administer infrastructure-wise, I can cache the requests, etc.
Data at our company suggests that several small queries actually do better performance-wise than one large one. We switched to GraphQL a year and a half ago or so, but this piece of data seems to suggest that we might have been better off just sticking with REST. My suggestion to that effect was not met with optimism either on the client or server side. Apparently there are server-side benefits as well, allowing for more modular development or something like that.
I have used OpenAPI using connexion[1]. It was hard to understand at first, but I really liked that the single source of truth was one schema. It also made it really easy to develop against the API because it came with a UI that showed the documentation for all the rest end points and even had test buttons.
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Ask HN: Why is there no specification for Command Line Interfaces?
What's the use case? I was thinking about this exact issue because my product ships several CLI tools, but I wasn't convinced it would be worth the effort.
An OpenAPI specification describes an HTTP interface, and I see it as useful because it makes it easier to write code in language-of-choice to generate HTTP requests (by generating client libraries from the OpenAPI spec).
For a CLI, the interface is the command-line. Usually people type these commands, or they end up in bash scripts, or sometimes they get called from programming language of choice by shelling out to the CLI. So I could see a use case for a CLI spec, which would make it easier to generate client libraries (which would shell out to the CLI)... but it seems a little niche.
Or maybe, as input to a documentation tool (like Swagger docs). I would imagine if you're using a CLI library like Python's Click, most of that data is already there. Click Parameters documentation: https://click.palletsprojects.com/en/8.1.x/parameters/
Or maybe, you could start from the spec and then generate code which enforces it. So any changes pass through the spec, which would make it easy to write code (server and client-side) / documentation / changelogs. Some projects like this: Guardrail (Scala) https://github.com/guardrail-dev/guardrail , and Connexion (Python) https://github.com/spec-first/connexion .
But without this ecosystem of tooling, documenting your CLI in a specification didn't really seem worth the effort. Of course, that's a bootstrapping problem.
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Flask is Great!
Connexion is a framework on top of Flask that automagically handles HTTP requests defined using OpenAPI/Swagger.
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What is the best practice for mapping JSON requests to objects and back to JSON?
I recommend you create a OpenAPI Specification and implement a python module that you expose via connexion or on the cli via click(for easy testing).
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Flask-Powered APIs: Fast, Reliable, and Used by the World's Top Companies
I'm here because Swagger-CodeGen created flask-Connexion boilerplate for python.
- Python REST APIs With Flask, Connexion, and SQLAlchemy – Part 1 – Real Python
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Does anybody know any good resources I could use to study ISP architecture?
Personally we just prov them using librouteros and flask-connexion/openapi.
What are some alternatives?
twarc - A command line tool (and Python library) for archiving Twitter JSON
flask-restful - Simple framework for creating REST APIs
cornice - Build Web Services with Pyramid.
Flask RestPlus - Fully featured framework for fast, easy and documented API development with Flask
Python Blogs - A curated list of python programming language blogs
flasgger - Easy OpenAPI specs and Swagger UI for your Flask API
doccano - Open source annotation tool for machine learning practitioners.
django-rest-framework - Web APIs for Django. 🎸
eve - REST API framework designed for human beings
Geek-Jokes API - Random Geek Jokes REST API
falcon - The no-magic web data plane API and microservices framework for Python developers, with a focus on reliability, correctness, and performance at scale.