autokeras
fastapi
Our great sponsors
autokeras | fastapi | |
---|---|---|
5 | 465 | |
9,065 | 70,779 | |
0.2% | - | |
5.3 | 9.8 | |
about 1 month ago | 4 days ago | |
Python | Python | |
Apache License 2.0 | MIT License |
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.
autokeras
- Machine Learning Algorithms Cheat Sheet
-
Ask HN: Which piece of tech is underutilized?
I think the interfaces aren't high level enough for the average programmer to adopt it. It needs what https://autokeras.com is for neural nets.
- Technical documentation that just works
- SVM training taking forever on my local machine. Will using AWS Sagemaker be faster for training SVM (Linear) models?
-
[D] [P] How do you use tools like AutoML?
AutoKeras time_series_forecaster.py
fastapi
-
FastAPI Got Me an OpenAPI Spec Really... Fast
That’s when I found FastAPI.
-
How to Deploy a Fast API Application to a Kubernetes Cluster using Podman and Minikube
FastAPI & Uvicorn
-
Analysing FastAPI Middleware Performance
Discussion at FastAPI GitHub: https://github.com/tiangolo/fastapi/issues/2696
-
LangChain, Python, and Heroku
An API application framework (such as FastAPI)
-
Litestar – powerful, flexible, and highly performant Python ASGI framework
It’s been my experience that async Python frameworks tend to turn IO bound problems into CPU bound problems with a high enough request rate, because due to their nature they act as unbounded queues.
This ends up made worse if you’re using sync routes.
If you’re constrained on a resource such as a database connection pool, your framework will continue to pull http requests off the wire that a sane client will cancel and retry due to timeouts because it takes too long to get a connection out of the pool. Since there isn’t a straightforward way to cancel the execution of a route handler in every Python http framework I’ve seen exhibit this problem, the problem quickly snowballs.
This is an issue with fastapi, too- https://github.com/tiangolo/fastapi/issues/5759
-
AI-Powered Image Search with CLIP, pgvector, and Fast API
Fast API.
- Ask HN: What is your go-to stack for the web?
-
Fun with Avatars: Crafting the core engine | Part. 1
We will create our API using FastAPI, a modern high-performance web framework for building fast APIs with Python. It is designed to be easy to use, efficient, and highly scalable. Some key features of FastAPI include:
-
Building Fast APIs with FastAPI: A Comprehensive Guide
FastAPI is a modern, fast, web framework for building APIs with Python 3.7+ based on standard Python type hints. It is designed to be easy to use, fast to run, and secure. In this blog post, we’ll explore the key features of FastAPI and walk through the process of creating a simple API using this powerful framework.
-
Effortless API Documentation: Accelerating Development with FastAPI, Swagger, and ReDoc
FastAPI is a modern, fast web framework for building APIs with Python 3.7+ that automatically generates OpenAPI and JSON Schema documentation. While FastAPI simplifies API development, manually creating and updating API documentation can still be a time-consuming task. In this blog post, we’ll explore how to leverage FastAPI’s automatic documentation generation capabilities, specifically focusing on Swagger and ReDoc, and how to streamline the process of documenting your APIs.
What are some alternatives?
autogluon - AutoGluon: Fast and Accurate ML in 3 Lines of Code
AIOHTTP - Asynchronous HTTP client/server framework for asyncio and Python
mljar-supervised - Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
HS-Sanic - Async Python 3.6+ web server/framework | Build fast. Run fast. [Moved to: https://github.com/sanic-org/sanic]
adanet - Fast and flexible AutoML with learning guarantees.
Tornado - Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed.
tf-keras-vis - Neural network visualization toolkit for tf.keras
django-ninja - 💨 Fast, Async-ready, Openapi, type hints based framework for building APIs
automlbenchmark - OpenML AutoML Benchmarking Framework
Flask - The Python micro framework for building web applications.
AutoViz - Automatically Visualize any dataset, any size with a single line of code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.
swagger-ui - Swagger UI is a collection of HTML, JavaScript, and CSS assets that dynamically generate beautiful documentation from a Swagger-compliant API.