Goal: Master Python’s language features beyond basics.
- Advanced data structures: sets, frozensets, deque, defaultdict, namedtuple, OrderedDict, ChainMap
- Comprehensions and generator expressions — nested and complex cases
- Decorators — function decorators, class decorators, parameterized decorators
- Context managers — custom implementations using
contextlib - Iterators and generators — advanced usage with
yield from, generator delegation - Python data model — dunder methods, customizing behavior (
__call__,__getitem__, etc.) - Variable scopes and closures,
nonlocalkeyword - Exception hierarchy, custom exceptions, exception chaining
Goal: Build complex abstractions with elegant code.
- Advanced OOP: multiple inheritance, MRO, mixins, abstract base classes (
abcmodule) - Properties, descriptors, and attribute management
- Metaclasses — creating and modifying classes dynamically
- Functional programming:
functools(partial, wraps, lru_cache),itertools,operatormodule - Coroutines & asynchronous generators (
async def,await,async for) - Type hinting: Generics, protocols, type aliases,
TypedDict,NewType
Goal: Understand how Python works and optimize code.
- Python bytecode and the interpreter (
dismodule) - Memory management, garbage collection, reference counting
- Profiling:
cProfile,profile,timeit,line_profiler - Optimizing bottlenecks, algorithmic efficiency
- C extensions with
ctypesorcffibasics - Using
multiprocessing,concurrent.futures, andasynciofor concurrency
Goal: Write bulletproof code with effective testing and debugging.
- Writing comprehensive tests with
pytest: fixtures, parametrization, mocks - Property-based testing with
hypothesis - Debugging with
pdb,ipdb, and remote debugging tools - Logging best practices (
loggingmodule) and structured logging - Using linters (
flake8), formatters (black), and type checkers (mypy)
Goal: Use Python’s rich ecosystem to build professional projects.
- Web frameworks: Deep dive into FastAPI or Django internals
- Async programming with
asyncio, event loops, and async libraries - Data manipulation with NumPy and pandas, efficient data pipelines
- Automation:
subprocess,pathlib,shutil, scripting best practices - Database interfacing: ORM (SQLAlchemy core & ORM, async ORM like Tortoise)
- Messaging and queueing: RabbitMQ (
pika), Kafka (confluent-kafka-python) - Packaging & deployment:
setuptools,poetry,wheel, publishing to PyPI
Goal: Architect scalable, maintainable Python systems.
- Design patterns in Python (Singleton, Factory, Observer, Decorator, Strategy)
- Clean Architecture and SOLID principles applied in Python
- Microservices: REST APIs, gRPC with
grpcio - Event-driven architecture, reactive programming concepts
- Distributed computing: Celery, Dask, or Ray basics
- Building CLI tools with
argparseorclick
Goal: Apply knowledge in complex projects and open source.
- Contribute to Python projects on GitHub or Python itself
- Build a full-stack app (API + frontend + DB + CI/CD)
- Create libraries or frameworks for niche use-cases
- Optimize open-source code with performance improvements
- Write technical blog posts or tutorials on advanced Python topics
| Resource / Tool | Purpose |
|---|---|
| Fluent Python by Luciano Ramalho | Deep dive into idiomatic Python |
| Python docs & typing docs | Reference & advanced typing |
pytest, hypothesis |
Testing & property-based testing |
black, flake8, mypy |
Formatting, linting, typing checks |
dis module |
Bytecode inspection |
asyncio docs & trio |
Async programming |
cProfile, line_profiler |
Profiling & performance tuning |
| Real Python / Talk Python podcast | Tutorials & interviews |
| Frequency | Activity |
|---|---|
| Daily | Solve a medium-to-hard Python coding challenge |
| Weekly | Build/refactor part of a project using advanced features |
| Monthly | Write a technical article or contribute code to OSS |