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Top 23 Python Deployment Projects
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Ray
Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
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StackStorm
StackStorm (aka "IFTTT for Ops") is event-driven automation for auto-remediation, incident responses, troubleshooting, deployments, and more for DevOps and SREs. Includes rules engine, workflow, 160 integration packs with 6000+ actions (see https://exchange.stackstorm.org) and ChatOps. Installer at https://docs.stackstorm.com/install/index.html
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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.
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opyrator
🪄 Turns your machine learning code into microservices with web API, interactive GUI, and more.
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inference
Replace OpenAI GPT with another LLM in your app by changing a single line of code. Xinference gives you the freedom to use any LLM you need. With Xinference, you're empowered to run inference with any open-source language models, speech recognition models, and multimodal models, whether in the cloud, on-premises, or even on your laptop.
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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.
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transformer-deploy
Efficient, scalable and enterprise-grade CPU/GPU inference server for 🤗 Hugging Face transformer models 🚀
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runhouse
Fast, Pythonic AI services and workflows on your own infra. Unobtrusive, debuggable, PyTorch-like APIs.
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aws-deployment-framework
The AWS Deployment Framework (ADF) is an extensive and flexible framework to manage and deploy resources across multiple AWS accounts and regions based on AWS Organizations.
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sailor
Sailor is a tiny PaaS to install on your servers/VPS that uses git push to deploy micro-apps, micro-services, sites with SSL, on your own servers or VPS
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blindbox
BlindBox is a tool to isolate and deploy applications inside Trusted Execution Environments for privacy-by-design apps
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cookiecutter-django-ecs-github
Complete Walkthrough: Blue/Green Deployment to AWS ECS using Cookiecutter-Django using GitHub actions
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alto
Serverless for data practitioners. The fastest ⚡️ way to run your code in the cloud. Effortlessly run scripts, functions, and Jupyter notebooks in virtual machines. (by runprism)
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SaaSHub
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22. Ray | Github | tutorial
Project mention: Ask HN: What are some unpopular technologies you wish people knew more about? | news.ycombinator.com | 2023-12-02
Project mention: Opyrator: Turns your Python code into microservices with web API and webUI | news.ycombinator.com | 2023-10-30
Project mention: Cobbler: Allows for rapid setup of network installation environments | news.ycombinator.com | 2024-02-26
Project mention: GreptimeAI + Xinference - Efficient Deployment and Monitoring of Your LLM Applications | dev.to | 2024-01-24Xorbits Inference (Xinference) is an open-source platform to streamline the operation and integration of a wide array of AI models. With Xinference, you’re empowered to run inference using any open-source LLMs, embedding models, and multimodal models either in the cloud or on your own premises, and create robust AI-driven applications. It provides a RESTful API compatible with OpenAI API, Python SDK, CLI, and WebUI. Furthermore, it integrates third-party developer tools like LangChain, LlamaIndex, and Dify, facilitating model integration and development.
Project mention: [D] Object detection models that can be easily converted to CoreML | /r/MachineLearning | 2023-07-25
There are 3 courses that I usually recommend to folks looking to get into MLE/MLOps that already have a technical background. The first is a higher-level look at the MLOps processes, common challenges and solutions, and other important project considerations. It's one of Andrew Ng's courses from Deep Learning AI but you can audit it for free if you don't need the certificate: - Machine Learning in Production For a more hands-on, in-depth tutorial, I'd recommend this course from NYU (free on GitHub), including slides, scripts, full-code homework: - Machine Learning Systems And the title basically says it all, but this is also a really good one: - Hands-on Train and Deploy ML Pau Labarta, who made that last course, actually has a series of good (free) hands-on courses on GitHub. If you're interested in getting started with LLMs (since every company in the world seems to be clamoring for them right now), this course just came out from Pau and Paul Iusztin: - Hands-on LLMs For LLMs I also like this DLAI course (that includes Prompt Engineering too): - Generative AI with LLMs It can also be helpful to start learning how to use MLOps tools and platforms. I'll suggest Comet because I work there and am most familiar with it (and also because it's a great tool). Cloud and DevOps skills are also helpful. Make sure you're comfortable with git. Make sure you're learning how to actually deploy your projects. Good luck! :)
Project mention: [P] Secret Santa: Serve SantaCoder for code completion without exposing code IP using BlindBox | /r/MachineLearning | 2023-06-30GitHub: https://github.com/mithril-security/blindbox/
Project mention: Show HN: I created a CLI tool to run a Docker image in an EC2 instance | news.ycombinator.com | 2024-01-14
NOTE:
The open source projects on this list are ordered by number of github stars.
The number of mentions indicates repo mentiontions in the last 12 Months or
since we started tracking (Dec 2020).
Python Deployment related posts
- Cobbler: Allows for rapid setup of network installation environments
- FLaNK Stack Weekly 5 September 2023
- [D] Object detection models that can be easily converted to CoreML
- WDS equivalent for Linux
- Looking to help out with Flask web app projects!
- How to install programs for all users?
- Self-hosting in 2023: Nextcloud on Linode, or _?_ on _?_?
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A note from our sponsor - InfluxDB
www.influxdata.com | 26 Apr 2024
Index
What are some of the best open-source Deployment projects in Python? This list will help you:
| Project | Stars | |
|---|---|---|
| 1 | Ray | 31,101 |
| 2 | StackStorm | 5,896 |
| 3 | ByteTrack | 4,230 |
| 4 | opyrator | 3,014 |
| 5 | Cobbler | 2,536 |
| 6 | inference | 2,512 |
| 7 | mmdeploy | 2,502 |
| 8 | transformer-deploy | 1,615 |
| 9 | budgetml | 1,332 |
| 10 | AutoDMG | 1,215 |
| 11 | ecs-deploy | 827 |
| 12 | runhouse | 709 |
| 13 | hands-on-train-and-deploy-ml | 651 |
| 14 | aws-deployment-framework | 635 |
| 15 | FedScale | 365 |
| 16 | sailor | 277 |
| 17 | cfn-secret-provider | 142 |
| 18 | torchlambda | 123 |
| 19 | ansible-esxi | 93 |
| 20 | pypmml | 72 |
| 21 | blindbox | 54 |
| 22 | cookiecutter-django-ecs-github | 35 |
| 23 | alto | 35 |
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