Python Deployment

Open-source Python projects categorized as Deployment

Top 23 Python Deployment Projects

  • 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.

  • Project mention: Open Source Advent Fun Wraps Up! | dev.to | 2024-01-05

    22. Ray | Github | tutorial

  • 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

  • Project mention: Ask HN: What are some unpopular technologies you wish people knew more about? | news.ycombinator.com | 2023-12-02
  • 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.

    InfluxDB logo
  • ByteTrack

    [ECCV 2022] ByteTrack: Multi-Object Tracking by Associating Every Detection Box

  • opyrator

    🪄 Turns your machine learning code into microservices with web API, interactive GUI, and more.

  • Project mention: Opyrator: Turns your Python code into microservices with web API and webUI | news.ycombinator.com | 2023-10-30
  • Cobbler

    Cobbler is a versatile Linux deployment server

  • Project mention: Cobbler: Allows for rapid setup of network installation environments | news.ycombinator.com | 2024-02-26
  • mmdeploy

    OpenMMLab Model Deployment Framework

  • Project mention: [D] Object detection models that can be easily converted to CoreML | /r/MachineLearning | 2023-07-25
  • 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.

  • Project mention: GreptimeAI + Xinference - Efficient Deployment and Monitoring of Your LLM Applications | dev.to | 2024-01-24

    Xorbits 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.

  • 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.

    WorkOS logo
  • transformer-deploy

    Efficient, scalable and enterprise-grade CPU/GPU inference server for 🤗 Hugging Face transformer models 🚀

  • budgetml

    Deploy a ML inference service on a budget in less than 10 lines of code.

  • AutoDMG

    Create deployable system images from OS X installer

  • ecs-deploy

    Powerful CLI tool to simplify Amazon ECS deployments, rollbacks & scaling (by fabfuel)

  • runhouse

    The fastest way to iterate and deploy AI workloads on your own infra. Unobtrusive, debuggable, PyTorch-like APIs.

  • Project mention: Better GPU Cluster Scheduling with Runhouse | dev.to | 2024-03-15

    With Runhouse, it’s easy to send code to your compute no matter where it lives, and efficiently utilize your resources across multiple callers scheduling jobs (e.g. researchers, pipelines, inference services, etc). We believe less is more when it comes to AI DevOps, so we don’t make any assumptions about the structure of your code or the infrastructure to which you’re sending it.

  • hands-on-train-and-deploy-ml

    Train and Deploy an ML REST API to predict crypto prices, in 10 steps

  • Project mention: Where to start | /r/mlops | 2023-09-13

    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! :)

  • 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.

  • FedScale

    FedScale is a scalable and extensible open-source federated learning (FL) platform.

  • 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

  • cfn-secret-provider

    A CloudFormation custom resource provider for deploying secrets and keys

  • torchlambda

    Lightweight tool to deploy PyTorch models to AWS Lambda

  • ansible-esxi

    Ansible management for stand-alone vmware esxi host

  • pypmml

    Python PMML scoring library

  • blindbox

    BlindBox is a tool to isolate and deploy applications inside Trusted Execution Environments for privacy-by-design apps

  • Project mention: [P] Secret Santa: Serve SantaCoder for code completion without exposing code IP using BlindBox | /r/MachineLearning | 2023-06-30

    GitHub: https://github.com/mithril-security/blindbox/

  • 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)

  • Project mention: Show HN: I created a CLI tool to run a Docker image in an EC2 instance | news.ycombinator.com | 2024-01-14
  • cookiecutter-django-ecs-github

    Complete Walkthrough: Blue/Green Deployment to AWS ECS using Cookiecutter-Django using GitHub actions

  • SaaSHub

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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). The latest post mention was on 2024-03-15.

Python Deployment related posts

Index

What are some of the best open-source Deployment projects in Python? This list will help you:

Project Stars
1 Ray 30,988
2 StackStorm 5,895
3 ByteTrack 4,216
4 opyrator 3,012
5 Cobbler 2,536
6 mmdeploy 2,502
7 inference 2,424
8 transformer-deploy 1,614
9 budgetml 1,332
10 AutoDMG 1,215
11 ecs-deploy 826
12 runhouse 702
13 hands-on-train-and-deploy-ml 651
14 aws-deployment-framework 632
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 alto 36
23 cookiecutter-django-ecs-github 35

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