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Roadmap · Updated May 2026

The Python Developer trek

From Python basics to production-grade services. Async, testing, packaging, web frameworks, databases, Docker, and the tooling modern teams actually use.

Stages
13
Estimated time
5 months
Level
Beginner → Advanced
Maintained by
3 practitioners
01
Stage 01

Python foundations

Variables, types, control flow, functions, and the standard library you will reach for every day. Idiomatic Python from day one.

PythonBeginner
02
Stage 02

Object-oriented Python

Classes, protocols, dataclasses, composition vs inheritance, and when to prefer plain functions over objects.

OOPIntermediate
03
Stage 03

Type hints & static analysis

mypy, pyright, and writing code that editors and CI can verify. Generics, TypeVar, and the difference between static and runtime checking.

Typesmypypyright
04
Stage 04

Testing with pytest

Unit tests, fixtures, parametrize, mocking, property-based testing, and coverage-driven development.

pytestTestingTDD
05
Stage 05

Async Python

The event loop, coroutines, asyncio primitives, and building I/O-bound services that handle thousands of concurrent connections.

AsyncasyncioConcurrent
06
Stage 06

Web APIs with FastAPI

Build, document, and deploy REST APIs with FastAPI, Pydantic v2, dependency injection, background tasks, and proper error handling.

FastAPIPydanticREST
07
Stage 07

Databases & ORMs

SQLAlchemy 2.0, Alembic migrations, connection pooling, and writing queries that survive 10x traffic.

SQLAlchemyPostgresAlembic
08
Stage 08

Caching & performance

Redis for caching, profiling Python code, and the techniques that actually move the needle on latency.

RedisCachingPerformance
09
Stage 09

Security best practices

Input validation, secrets management, SQL injection, XSS, dependency auditing, and writing Python code that doesn't get you breached.

SecurityOWASPSecrets
10
Stage 10

Packaging & tooling

uv, ruff, pyproject.toml, publishing to PyPI, and reproducible builds that work on any machine.

uvruffPyPIPackaging
11
Stage 11

Docker & deployment

Containerize Python services correctly. Multi-stage builds, secrets handling, health checks, and production-ready images.

DockerDeploymentContainers
12
Stage 12

CI/CD & observability

GitHub Actions pipelines, structured logging, distributed tracing, and the feedback loops that let you ship with confidence.

CI/CDGitHub ActionsObservability
13
Stage 13

Capstone — ship a production service

Plan, build, deploy, and document a complete production Python service. Open-source it. Get one engineer review.

CapstoneAdvancedPortfolio

Trek complete. What's next?

You've walked the full roadmap. Now ship the capstone, write about it, and share the path with the next engineer who needs it.

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