- Python 3 - Python is a programming language that lets you work more quickly and integrate your systems more effectively.
- Black - Uncompromising Python code formatter.
- Pylint - Code analysis for Python.
- Pytest - Framework that makes it easy to write small tests, yet scales to support complex functional testing for applications and libraries.
- Coverage.py - Tool for measuring code coverage of Python programs.
- Sphinx - Tool that makes it easy to create intelligent and beautiful documentation.
- SQLAlchemy - Python SQL toolkit and Object Relational Mapper that gives application developers the full power and flexibility of SQL.
- Jinja - Full featured template engine for Python.
- Pipenv - Tool that aims to bring the best of all packaging worlds (bundler, composer, npm, cargo, yarn, etc.) to the Python world.
- Celery - Asynchronous task queue/job queue based on distributed message passing.
- Protocol Buffers - Google's language-neutral, platform-neutral, extensible mechanism for serializing structured data – think XML, but smaller, faster, and simpler.
- PostgreSQL - The World's Most Advanced Open Source Relational Database.
- Redis - Open-source in-memory data structure store, used as a database, cache and message broker.
- SQLite - C-language library that implements a small, fast, self-contained, high-reliability, full-featured, SQL database engine.
- ScyllaDB - The real-time big data database.
- CockroachDB - Ultra-resilient SQL for global business.
Data Processing and Machine Learning
- ELK Stack - Elasticsearch, Logstash, and Kibana.
- Elasticsearch - Search and analytics engine.
- Logstash - Server‑side data processing pipeline that ingests data from multiple sources simultaneously, transforms it, and then sends it to a "stash" like Elasticsearch.
- Kibana - Data visualization with charts and graphs in Elasticsearch.
- NumPy - Fundamental package for scientific computing with Python.
- Seaborn - Statistical data visualization.
- Pandas - Python Data Analysis Library.
- Scikit-learn - Machine learning in Python.
- TensorFlow - End-to-end open source machine learning platform.
- PyTorch - Open-source deep learning platform that provides a seamless path from research prototyping to production deployment.
- Keras - The Python Deep Learning library.
Versioning and Continuous Integration
- GitLab - The first single application for the entire DevOps lifecycle.