Python for the JVM Engineer

The Runtime Model

Understand how CPython executes your code — bytecode, the eval loop, and where it diverges from the JVM you already know.

Packaging and Dependency Hell

Navigate pip, Poetry, and uv with the same confidence you bring to Maven — once you understand what pyproject.toml is actually doing.

Async, Threading, and the GIL

Unpack Python's concurrency model — the GIL, asyncio's event loop, and when to use threads vs processes — through a JVM engineer's lens.

Type Hints in Real Code

Add Java-grade type safety to Python through gradual typing, mypy, and pyright — without rewriting your whole codebase.

Dataclasses, attrs, Pydantic

Pick the right data modelling tool for the job — validation, serialization, and immutability compared from a Java record and bean perspective.

Web Frameworks Compared

Pick between Flask, Django, and FastAPI with the same framework intuition you built around Spring — mapped concept by concept.

Background Jobs

Move work off the request thread with Celery, RQ, and Dramatiq — mapped to Quartz, Spring Batch, and the Java executor model you know.

Performance and Profiling

Find and fix Python bottlenecks using cProfile, py-spy, and flamegraphs — the same investigative workflow you apply with JFR and async-profiler.

Packaging for Distribution

Ship Python code as wheels, standalone executables, or Docker images — with the same discipline you apply to JAR and uber-JAR packaging.

Python in Containers

Build lean, production-ready Python container images with multi-stage builds and runtime configuration — applied from a JVM Docker experience base.