SaaSHub helps you find the best software and product alternatives Learn more →
Top 23 Python Microservice Projects
-
falcon
The no-magic web data plane API and microservices framework for Python developers, with a focus on reliability, correctness, and performance at scale.
-
BentoML
The most flexible way to serve AI/ML models in production - Build Model Inference Service, LLM APIs, Inference Graph/Pipelines, Compound AI systems, Multi-Modal, RAG as a Service, and more!
-
InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
-
connexion
Connexion is a modern Python web framework that makes spec-first and api-first development easy.
-
opyrator
🪄 Turns your machine learning code into microservices with web API, interactive GUI, and more.
-
OPAL
Policy and data administration, distribution, and real-time updates on top of Policy Agents (OPA, Cedar, ...) (by permitio)
-
WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
-
aws-serverless-ecommerce-platform
Serverless Ecommerce Platform is a sample implementation of a serverless backend for an e-commerce website. This sample is not meant to be used as an e-commerce platform as-is, but as an inspiration on how to build event-driven serverless microservices on AWS.
-
apiron
:fried_egg: apiron is a Python package that helps you cook a tasty client for RESTful APIs. Just don't wash it with SOAP.
-
fastapi-microservice-template
A template for a FastAPI based Serverless Framework microservice running on AWS Lambda
-
observability-with-amazon-opensearch
This repository contains a microservice-based Sample App demonstrating observability capabilities in the Amazon OpenSearch Service.
-
mlToolKits
learningOrchestra is a distributed Machine Learning integration tool that facilitates and streamlines iterative processes in a Data Science project.
-
ecommerce
:shopping_cart: A e-commerce system using microservices concepts and architected with docker. (by nelsonwenner)
-
django-outbox-pattern
A django application to make it easier to use the transactional outbox pattern
-
b-rabbit
A thread safe library that aims to provide a simple API for interfacing with RabbitMQ. Built on top of rabbitpy, the library make it very easy to use the RabbitMQ message broker with just few lines of code. It implements all messaging pattern used by message brokers
-
django-rest-microservice
Provides OAuth2.0 Code Grant w/ PKCE authentication flow with third-party IDP (AWS Cognito), microservices architecture with Django, and out-of-box auth operation REST APIs for working with SPA.
-
py-inventa
A Python library for microservice registry and executing RPC (Remote Procedure Call) over Redis.
-
fuilder
An open-source dynamic and real-time form builder. (Microservices, Python, Django, PostgreSQL, Terraform, Google Cloud, Docker, Kubernetes)
-
SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
Link to GitHub -->
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).
Project mention: Opyrator: Turns your Python code into microservices with web API and webUI | news.ycombinator.com | 2023-10-30
Another tool that can help you deploy a Policy as Code-based solution in 2024 is OPAL, the Open Policy Administration Layer. OPAL is an open-source project that provides a comprehensive policy-based service for applications. With one click, you can deploy a full architecture of a Git-based centralized policy store with decentralized policy engines running as a sidecar with your applications. OPAL also provides a unified architecture to sync all the data you need with the policy engines.
Project mention: Observabilidade de microsserviços com OpenTelemetry e Amazon OpenSearch [Lab Session] | dev.to | 2024-01-29Referências/Reference: https://catalog.us-east-1.prod.workshops.aws/workshops/1abb648b-2ef8-442c-a731-efbcb69c1e1e/en-US https://github.com/aws-samples/observability-with-amazon-opensearch.git https://github.com/idealo/terraform-aws-opensearch.git
Project mention: walnats: Nats-powered event-driven background jobs and microservices framework for Python. | /r/coolgithubprojects | 2023-04-21
No python existe a biblioteca django-outbox-pattern que implementa o padrão outbox e também garante idempotência nos consumidores.
For example, in my latest project, I built a form builder using microservices architecture, and I needed to deploy the infrastructure on Google Cloud Platform (GCP). I had three services, each of which needed a Google Storage Bucket and a Google SQL Database. To accomplish this, I created modules for GCP to provision these common GCP services, and then created a separate module for each service under the services’ folder. These modules used the common GCP modules, as shown below:
Python Microservices related posts
- Opyrator: Turns your Python code into microservices with web API and webUI
- walnats: Nats-powered event-driven background jobs and microservices framework for Python.
- walnats: Nats-powered event-driven background jobs and microservices framework for Python.
- How to implement social login to django models?
- walnats: Nats-powered event-driven background jobs and microservices framework for Python.
- M3O: Serverless Micro services gateway
- walnats: Nats-powered event-driven background jobs and microservices framework for Python.
-
A note from our sponsor - SaaSHub
www.saashub.com | 19 Apr 2024
Index
What are some of the best open-source Microservice projects in Python? This list will help you:
Project | Stars | |
---|---|---|
1 | falcon | 9,379 |
2 | BentoML | 6,521 |
3 | Nameko | 4,649 |
4 | connexion | 4,414 |
5 | opyrator | 3,012 |
6 | OPAL | 2,271 |
7 | python-lambda | 1,479 |
8 | Zato | 1,070 |
9 | aws-serverless-ecommerce-platform | 1,053 |
10 | minos-python | 453 |
11 | apiron | 117 |
12 | fastapi-microservice-template | 80 |
13 | observability-with-amazon-opensearch | 79 |
14 | mlToolKits | 74 |
15 | ecommerce | 59 |
16 | walnats | 58 |
17 | django-outbox-pattern | 46 |
18 | b-rabbit | 26 |
19 | sdk-python | 23 |
20 | bunny-storm | 23 |
21 | django-rest-microservice | 8 |
22 | py-inventa | 7 |
23 | fuilder | 4 |