


Default Argument Binding Anomaly
Python's default arguments, when bound at function definition instead of execution, can perplex programmers. For instance, consider this function:
def foo(a=[]): a.append(5) return a
It returns a list with a single element, [5], for the first call. However, subsequent calls increment this element count, resulting in an unexpected pattern:
>>> foo() [5] >>> foo() [5, 5] >>> foo() [5, 5, 5]
This seemingly illogical behavior stems from the fundamental concept of Python functions as first-class objects. Upon function definition, Python evaluates the function and its default parameters as "member data" of the function object. Consequently, these parameters retain their state across function invocations, just like regular class attributes.
This binding at definition time has a clear rationale: it ensures that all aspects of function definition are resolved upfront. If binding were performed at function execution, the function signature would become "hybrid," with part of the binding occurring at definition and part at invocation. This inconsistency could introduce potential errors and confusion.
By binding default arguments at definition, Python maintains the integrity of function objects as immutable entities. This behavior provides a consistent and comprehensible framework for working with Python functions and their associated default parameters.
The above is the detailed content of Why Do Subsequent Calls to a Python Function with a Mutable Default Argument Produce Unexpected Results?. For more information, please follow other related articles on the PHP Chinese website!

The article discusses Python's new "match" statement introduced in version 3.10, which serves as an equivalent to switch statements in other languages. It enhances code readability and offers performance benefits over traditional if-elif-el

Exception Groups in Python 3.11 allow handling multiple exceptions simultaneously, improving error management in concurrent scenarios and complex operations.

Function annotations in Python add metadata to functions for type checking, documentation, and IDE support. They enhance code readability, maintenance, and are crucial in API development, data science, and library creation.

The article discusses unit tests in Python, their benefits, and how to write them effectively. It highlights tools like unittest and pytest for testing.

Article discusses access specifiers in Python, which use naming conventions to indicate visibility of class members, rather than strict enforcement.

Article discusses Python's \_\_init\_\_() method and self's role in initializing object attributes. Other class methods and inheritance's impact on \_\_init\_\_() are also covered.

The article discusses the differences between @classmethod, @staticmethod, and instance methods in Python, detailing their properties, use cases, and benefits. It explains how to choose the right method type based on the required functionality and da

InPython,youappendelementstoalistusingtheappend()method.1)Useappend()forsingleelements:my_list.append(4).2)Useextend()or =formultipleelements:my_list.extend(another_list)ormy_list =[4,5,6].3)Useinsert()forspecificpositions:my_list.insert(1,5).Beaware


Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Hot Tools

Dreamweaver CS6
Visual web development tools

EditPlus Chinese cracked version
Small size, syntax highlighting, does not support code prompt function

SAP NetWeaver Server Adapter for Eclipse
Integrate Eclipse with SAP NetWeaver application server.

ZendStudio 13.5.1 Mac
Powerful PHP integrated development environment

Zend Studio 13.0.1
Powerful PHP integrated development environment
