The glob module finds all pathnames matching a Unix shell-style pattern using wildcards like * (any characters), ? (single character), and [seq] (character ranges), making file discovery and batch operations simple.
Virtual environments create isolated Python installations to prevent package conflicts between projects using python -m venv.
Virtual environments solve the “dependency hell” problem - you can have different versions of the same library for different projects without conflicts!
The threading module enables concurrent execution through threads with synchronization primitives like Lock, Event, and Semaphore for safe resource sharing.
Python’s Global Interpreter Lock (GIL) means only one thread executes Python code at once - threading helps with I/O-bound tasks, not CPU-bound ones!
The sqlite3 module provides a lightweight, disk-based database interface that supports SQL queries without requiring a separate server process.
SQLite is the most widely deployed database engine in the world - it’s built into every smartphone, browser, and operating system!
PEP 585 made built-in collections generic, allowing list[int] instead of List[int] - eliminating duplicate type hierarchies in the typing module.
Before PEP 585, Python had two separate type systems - one for runtime and one for type hints. Now built-in collections work for both!
The heapq module provides heap queue (priority queue) operations using a binary heap implemented as a list, where heappush() and heappop() maintain the heap invariant with O(log n) complexity.
PEP 274 introduced dictionary comprehensions in Python 2.7/3.0 with syntax {key: value for item in iterable}, providing a concise way to create dictionaries similar to list comprehensions.
The unittest module provides TestCase classes, assertion methods, test discovery, and mock objects for comprehensive unit testing with setUp/tearDown methods and test runners.
Python’s standard library provides essential modules for OS operations, file handling, math, networking, dates, and performance measurement - “batteries included”!
Python’s standard library is so comprehensive that many tasks don’t require external dependencies - from web requests to compression, it’s all built-in!
Python’s interactive interpreter lets you experiment immediately with numbers, strings, and lists using intuitive syntax and meaningful indentation.
Python uses indentation instead of braces to define code blocks - making the visual structure of your code match its logical structure!
The subprocess module provides subprocess.run(), subprocess.Popen(), and subprocess.PIPE for secure process execution with proper input/output handling, error management, and cross-platform command execution.
The statistics module provides mathematical statistics functions for calculating averages, spread measures, and correlations without external dependencies.
Unlike floating-point calculations, the statistics module can work with Decimal and Fraction types for exact mathematical precision in statistical calculations!
PEP 492 introduced async def and await keywords, creating native coroutines that make asynchronous programming cleaner and more intuitive than generator-based approaches.
PEP 380 introduced yield from syntax for delegating to subgenerators, simplifying generator composition and enabling generators to return values.
yield from was the foundation that made async/await possible - it established the delegation pattern that coroutines needed!
The csv module provides csv.reader(), csv.writer(), csv.DictReader(), and csv.DictWriter() for robust CSV file processing with automatic dialect detection and proper handling of quotes, delimiters, and line endings.
The argparse module provides powerful command-line argument parsing with automatic help generation, type checking, subcommands, and error handling for building professional CLI applications.
The Python interpreter provides an interactive REPL (Read-Eval-Print Loop) for testing code, exploring APIs, and rapid prototyping, accessible via python command or enhanced with IPython for advanced features.
Python provides multiple string formatting methods (f-strings, .format(), manual), file operations with context managers, and JSON serialization for data exchange.
F-strings can execute any Python expression inside the braces - you can even call functions and perform calculations right inside the string!
The random module provides functions for generating random numbers, sampling from sequences, shuffling data, and seeding for reproducible randomness in simulations and games.
PEP 526 introduced variable annotations in Python 3.6, allowing type hints for variables using the syntax variable: type = value, extending PEP 484’s function annotations to all variables for better code documentation and static analysis.