Python Developer Path
A six-stage Python path built for developers coming from a typed language like TypeScript — idiom first, then backend, data, and the AI on-ramp.
Click a node to expand it — summary, free resources, and a checkbox to mark it complete. Progress is saved on this device only.
Python Developer Path
12 nodes · 0 marked complete
Core syntax & semantics
Variables and dynamic typing, list/tuple/dict/set, slicing, comprehensions, functions (*args/**kwargs), f-strings, truthiness, exceptions, file I/O, and venv/pip. For a TypeScript developer this is mostly idiom, not new concepts — about 1-2 weeks.
First projects: CLI tools
Apply Stage-1 syntax to two small real projects: a CLI expense tracker with JSON persistence, and a log-file parser that summarizes an Nginx/Express access log — the kind of tool you'd actually reach for on the job.
Idiomatic Python
Iterators/generators (yield), itertools, functools (lru_cache, partial), decorators, context managers (with, contextlib), and structural pattern matching (match). Writing "proper" Python, not just Python that runs — about 2-3 weeks.
Standard library & typing
pathlib, collections (Counter, defaultdict, deque), dataclasses, the enum module, the walrus operator, and type hints enforced with mypy — the closest analogue to the type discipline you already practice in TypeScript.
OOP & structural typing
Classes, dunder methods, properties, and — the closest analogue to a TS interface — ABCs vs. Protocol (structural typing). Covers inheritance vs. composition trade-offs for a domain model.
Testing & tooling
pytest (fixtures, parametrize, monkeypatch) with coverage, ruff for combined lint+format, uv or poetry for dependency management, and the src/ project layout with pyproject.toml — the modern, fast Python tooling stack.
Backend Python: FastAPI
asyncio and async/await (a mental model you already know from Node's event loop), httpx, and FastAPI itself — routing, Pydantic v2 validation, dependency injection, and JWT auth (a direct RBAC skill transfer). SQLAlchemy 2.0 + Alembic for the data layer. About 3-4 weeks leveraging existing Express experience.
Data & numerical Python
NumPy (arrays, broadcasting, vectorization) and pandas (DataFrames, groupby, joins, time series), plus matplotlib/seaborn and Jupyter notebooks. This is the prerequisite stage for any AI/ML work and the doorway into the AI/ML Engineer path. About 3-4 weeks.
Capstone: production API
Re-implement an existing Express+MySQL API in FastAPI + Postgres, with JWT/RBAC auth and pytest coverage, then containerize it with Docker — the project that proves the backend Python stage transferred.
Capstone: data pipeline
Exploratory analysis of a real Kaggle dataset, then an ETL script that moves data from MySQL through pandas into a cleaned Parquet file with summary charts — the project that proves the data stage transferred.
Performance & concurrency
Profiling (cProfile, timeit), the threads-vs-processes-vs-asyncio trade-off (the GIL is being removed in free-threaded 3.13+ builds but is still default-on in 2026), packaging, and Python design patterns — the ongoing "expert" track.
AI SDK on-ramp
The bridge into AI work: the openai/anthropic SDKs, and LangChain/LlamaIndex basics. Roughly 60% of your Node.js mental model transfers directly (event loop → asyncio, Express → FastAPI, npm → uv, Jest → pytest) — this node is where the Python path hands off to the AI/ML Engineer path.
Node list (accessible fallback)
| Tier | Node | Prerequisites |
|---|---|---|
| 0 | Core syntax & semantics | — |
| 1 | First projects: CLI tools | Core syntax & semantics |
| 1 | Idiomatic Python | Core syntax & semantics |
| 2 | Standard library & typing | Idiomatic Python |
| 3 | OOP & structural typing | Standard library & typing |
| 3 | Testing & tooling | Standard library & typing |
| 4 | Backend Python: FastAPI | OOP & structural typing, Testing & tooling |
| 4 | Data & numerical Python | OOP & structural typing, Testing & tooling |
| 5 | Capstone: production API | Backend Python: FastAPI |
| 5 | Capstone: data pipeline | Data & numerical Python |
| 6 | Performance & concurrency | Capstone: production API, Capstone: data pipeline |
| 6 | AI SDK on-ramp | Capstone: production API, Capstone: data pipeline |