Python uses a pass‑by‑object‑reference model, meaning functions receive references to objects; this article explains how mutable and immutable objects behave under this model, describes positional, keyword, default, *args and **kwargs argument types, and provides code examples illustrating each case.
This article examines a Python web‑crawler issue where the original script returns incorrect results, explains the underlying cause related to mutable data handling, and provides a corrected version of the code that successfully retrieves the desired price data from the Xinfadi website.
This article provides a comprehensive guide to Python's memory management and object assignment mechanisms, clearly explaining the differences between mutable and immutable objects, direct assignment, shallow copying, and deep copying through practical code examples and visual diagrams.
This article explains how Python implements function argument passing, distinguishing value passing—where a copy of the argument is used—from reference passing for mutable objects, illustrating both mechanisms with swap examples, memory diagrams, and concluding with best practices for modifying data inside functions.
This article explains three frequent Python pitfalls—using mutable objects as default arguments, unintentionally sharing class variables, and writing incorrect exception clauses—illustrates the problematic behavior with code examples, and provides the proper patterns to avoid each issue.
This article explains why Python’s augmented assignment (+=) can produce different results than regular assignment (=) when used with mutable objects like lists, illustrating the shared‑reference behavior and advising caution to avoid unexpected bugs.
This article explains why using a mutable object as a Python function's default value leads to unexpected behavior, illustrates the problem with concrete examples, and provides reliable solutions to avoid such subtle bugs.
