Python Basics: Numbers, Strings, Functions, Data Structures, Classes, and Useful Tools

This guide walks through fundamental Python concepts with clear examples.

Numbers : absolute value ( abs(-6)), base conversions ( bin(10), oct(9), hex(15)), ASCII ↔ integer ( chr(65), ord('A')), logical checks ( all([1,0,3,6]), any([0,0,0,[]])), boolean casting, complex numbers, division with remainder ( divmod(10,3)), floating‑point conversion, rounding, exponentiation, and chained comparisons.

Strings : converting to bytes ( bytes(s, encoding='utf-8')), any object to string ( str(i)), compiling and executing code strings ( compile(...), exec(r)), evaluating expressions ( eval('1 + 3 + 5')), and advanced formatting with format specifications.

Functions : using sorted with custom keys, sum with optional start value, defining functions with positional, keyword, default, *args, and **kwargs parameters, lambda expressions, and creating callable objects via __call__.

Data Structures : creating dictionaries in several ways, immutable sets ( frozenset), regular sets, slices and slice objects for reusable slicing, tuples, and converting lists to sets.

Classes and Objects : checking callability ( callable(obj)), custom __repr__, making instances callable with __call__, using classmethod, dynamic attribute deletion ( delattr), introspection with dir, getattr, hasattr, identity ( id), type checking ( isinstance, issubclass), property creation via property decorator, and understanding metaclasses ( type).

Tools : enumeration ( enumerate), memory size ( sys.getsizeof), filtering ( filter), hashing ( hash), help documentation ( help), file I/O ( open(...).read()), range generation, reversed iteration, zip aggregation, chained operations, and object serialization to JSON using json.dump with a custom lambda to serialize object attributes.

Overall, the article serves as a practical reference for Python developers to master core language features and standard library utilities.