connexion
flask-apscheduler
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connexion | flask-apscheduler | |
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23 | 7 | |
4,414 | 1,088 | |
0.5% | - | |
8.4 | 5.4 | |
1 day ago | 5 months ago | |
Python | Python | |
Apache License 2.0 | Apache License 2.0 |
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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.
flask-apscheduler
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Loading large amount of data - when is best?
I had to use it because I setup scheduled tasks in my init.py. Flask APScheduler
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Creating bots with OAuth 2.0 Authorization Code Flow with PKCE and V2 of the Twitter API
When I’ve previously made bots, I’ve typically used an external service such as Render’s cron job service or Google’s cloud scheduler to handle the timing of my bots. But for @noun__verb, I used flask-apscheduler to set up the timing. This might be better for smaller projects, but you may want to consider a cloud service as you scale.
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Handling Refresh Tokens in the OAuth 2.0 Authorization Code Flow with PKCE with Flask
Hopefully, this can be a starting point for you to get started with generating refresh tokens. As a next step, if you are using Flask you may want to consider using a schedular to update your refresh tokens regularly in an automated fashion. Additionally you may want to consider saving your tokens to a database in a secure fashion. This code sample can also be extended to allow you to connect to any of the endpoints that support v2 and can be deployed to a server as part of a more complete application.
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How can I run a while loop whilst flask is running?
Flask-APScheduler might be what you're looking for.
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Add Dynamically Job Scheduling
Any framework to add dynamically job scheduling like cron ? I find https://github.com/viniciuschiele/flask-apscheduler . Anything else like this?
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Wondering if I should use Celery vs threads for what I want to do
Flask-APSScheduler would work well for this.
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Call function every x minutes
To extend this, there is flask wrapper for apscheduler. I worked with this, and it's OK IMO. https://github.com/viniciuschiele/flask-apscheduler
What are some alternatives?
flask-restful - Simple framework for creating REST APIs
rq-dashboard - Flask-based web front-end for monitoring RQ queues
Flask RestPlus - Fully featured framework for fast, easy and documented API development with Flask
Quartz - Code for Quartz Scheduler
flasgger - Easy OpenAPI specs and Swagger UI for your Flask API
flower - Real-time monitor and web admin for Celery distributed task queue
django-rest-framework - Web APIs for Django. 🎸
django-apscheduler - APScheduler for Django
eve - REST API framework designed for human beings
Flask-RQ2 - A Flask extension for RQ.
falcon - The no-magic web data plane API and microservices framework for Python developers, with a focus on reliability, correctness, and performance at scale.
NiceHash-Mining-Scheduler - Schedule the start and stop of your NiceHash miners using this script.