https://github.com/anshajk/python-frameworks
Curated collection of powerful Python frameworks across different domains with examples
https://github.com/anshajk/python-frameworks
deep-learning machine-learning python python-library python3 tutorial
Last synced: 5 months ago
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Curated collection of powerful Python frameworks across different domains with examples
- Host: GitHub
- URL: https://github.com/anshajk/python-frameworks
- Owner: anshajk
- Created: 2025-02-28T08:14:02.000Z (10 months ago)
- Default Branch: main
- Last Pushed: 2025-07-09T07:59:14.000Z (6 months ago)
- Last Synced: 2025-07-09T09:02:11.087Z (6 months ago)
- Topics: deep-learning, machine-learning, python, python-library, python3, tutorial
- Language: Python
- Homepage:
- Size: 3.07 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Python Frameworks for Various Domains 🚀
Welcome to the Python Frameworks Repository! This repository serves as a curated collection of powerful Python frameworks across multiple domains, including backend engineering, machine learning operations (MLOps), deep learning, and more. Whether you're building scalable APIs, deploying machine learning models, or optimizing deep learning workflows, you'll find the right tools here. 🎯
## 📌 Why This Repository?
Python has a rich ecosystem of frameworks that simplify development, improve productivity, and enhance performance. Instead of searching for the right framework for your use case, this repository provides a well-organized reference to some of the most impactful Python frameworks in different domains.
### 🚀 Categories & Frameworks
#### 🔹 Backend Engineering
1. FastAPI – A high-performance web framework for building APIs with automatic OpenAPI and async support.
2. Django – The go-to framework for full-stack web applications with built-in admin and ORM.
3. Flask – A lightweight and flexible micro-framework for web development.
4. Sanic – A blazing-fast async web framework designed for high-throughput applications.
#### 🔹 Machine Learning & MLOps
1. Scikit-Learn – The standard for traditional machine learning algorithms and pipelines.
2. TensorFlow Extended (TFX) – A production-ready ML pipeline framework.
3. MLflow – A robust platform for managing ML experiments, models, and deployments.
4. Kubeflow – Kubernetes-native machine learning toolkit for scalable workflows.
#### 🔹 Deep Learning
1. TensorFlow – An industry-leading framework for deep learning research and deployment.
2. PyTorch – A flexible and dynamic deep learning framework with strong research adoption.
3. Keras – A high-level API for building neural networks on top of TensorFlow.
4. JAX – A powerful framework for high-performance machine learning research.
#### 🔹 Data Engineering & Processing
1. Pandas – The go-to library for data manipulation and analysis.
2. Dask – Parallel computing library that scales pandas and NumPy workflows.
3. Apache Airflow – A powerful workflow orchestration tool for ETL and automation.
4. PySpark – A Python API for Apache Spark, enabling big data processing.
#### 🔹 API & Microservices
1. GraphQL (Graphene) – A GraphQL framework for creating powerful APIs.
2. gRPC – A high-performance RPC framework for inter-service communication.
3. Celery – Distributed task queue framework for background processing.
## 📖 How to Use This Repository
Browse through the framework categories.
Check out official documentation links and examples.
Experiment with different frameworks to find the best fit for your project.
## 🤝 Contributions
Want to add a framework or improve this list? Contributions are welcome! Feel free to open a pull request or issue to suggest additions or improvements.
⭐ Stay Updated
If you find this repository useful, don't forget to star ⭐ it and share it with your fellow developers!
Happy coding! 🚀