Master Python from variables to OOP with visual, step-by-step tutorials. Build real-world skills with hands-on code examples and detailed explanations.
Follow a structured path or jump to any topic. Each path builds on the previous one.
24 tutorials from beginner to advanced — more coming soon
Install Python, explore the REPL, write your first program, and set up your IDE.
Master int, float, str, bool, None — type conversion, f-strings, and dynamic typing.
Lists, tuples, sets, dictionaries — comprehensions and choosing the right structure.
Classes, inheritance, polymorphism, dunder methods, @property, and @dataclass.
Quick reference for syntax, types, control flow, functions, OOP, and common patterns.
if/elif/else, for and while loops, range, enumerate, zip, and match/case.
def, default arguments, *args, **kwargs, lambda, scope rules, and closures.
f-strings, string methods, slicing, encoding, and common string patterns.
Read and write files, JSON, CSV, and modern path handling with pathlib.
try/except, custom exceptions, EAFP vs LBYL, and context managers.
Imports, pip, virtual environments, package structure, and standard library.
Iterator protocol, yield, generator expressions, yield from, and itertools.
Closures, @wraps, decorator arguments, @dataclass, @lru_cache, and chaining.
pytest, fixtures, parametrize, mocking, coverage, and test organization.
Async routes, Pydantic models, dependency injection, middleware, and testing.
Threading, multiprocessing, asyncio, and when to use each approach.
Annotations, typing module, generics, Protocol, and mypy.
NumPy arrays, Pandas DataFrames, data cleaning, and matplotlib.
How algorithm performance scales with input size. Hover to compare.