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Welcome to Brad’s Python Notes (PyNotes!).
This is Brad’s Python Notes - a blog covering interesting aspects about Python, covering the Python Tutorial, the Python Standard Libraries and the Python Enhancement Proposals (PEPs).
Recent posts
http.client Module and Requests Library
TL;DR
The http.client module provides low-level HTTP protocol client functionality, but Python’s documentation recommends using the third-party Requests library instead for higher-level HTTP operations. Requests offers automatic connection pooling, elegant API design, and handles the complexities that make http.client fiddly to use directly.
PEP 525 - Asynchronous Generators
TL;DR
PEP 525 introduced asynchronous generators to Python 3.6, enabling functions that combine
async defwithyieldstatements. This feature simplifies creating asynchronous data sources by replacing verbose iterator classes with concise generator syntax, delivering approximately 2.3x better performance.Socket Module
TL;DR
The
socketmodule provides low-level access to BSD sockets for network programming. It supports TCP and UDP protocols across IPv4 and IPv6, offering both connection-oriented and connectionless communication patterns for building custom network applications.Built-in Types: str, list, dict, and set
TL;DR
Python’s built-in types (str, list, dict, set) come packed with dozens of methods for manipulation, searching, and transformation. Dictionaries maintain insertion order since Python 3.7, and many lesser-known methods like
dict.setdefault(),str.removeprefix(), and set operations on dictionary views can simplify common patterns.PEP 420 - Implicit Namespace Packages
TL;DR
PEP 420 introduced implicit namespace packages, allowing Python packages to be split across multiple directories without requiring an
__init__.pyfile. The import machinery automatically discovers and combines all portions of the package, enabling flexible distribution and avoiding file conflicts.gc Module - Garbage Collection Control
TL;DR
The
gcmodule provides an interface to Python’s garbage collector, allowing you to manually trigger collection, disable automatic collection, debug memory leaks, and tune performance. It’s particularly useful for finding reference cycles, optimizing memory usage in long-running processes, and understanding what objects are consuming memory.Context Managers: Mastering Python's Resource Management
TL;DR
Context managers handle setup and cleanup automatically using the
withstatement, implementing__enter__and__exit__methods to guarantee resource cleanup even when exceptions occur.PEP 448: Additional Unpacking Generalizations
TL;DR
PEP 448 extended Python’s unpacking operators (
*and**) in Python 3.5, allowing multiple unpackings in function calls and enabling unpacking directly within list, tuple, set, and dictionary literals. This eliminates verbose workarounds and makes code more concise and readable.Built-in Exceptions
TL;DR
Python’s built-in exceptions form a strict inheritance hierarchy rooted in
BaseException, with all user code exceptions inheriting fromException. Choose specific exception types likeValueError(wrong value) orTypeError(wrong type) rather than generic exceptions, and consider carefully before catchingBaseExceptionin user code as it will do things like capture keyboard interrupts (no Ctrl-C for you!).Codecs Module: Mastering Text Encoding and Decoding
TL;DR
The codecs module provides functions to encode and decode data between bytes and text using various character encodings (UTF-8, ASCII, etc.), with flexible error handling strategies for dealing with malformed data.