search
HomeBackend DevelopmentPython TutorialWhat is Monkey Patching and How Does it Differ from Method Overloading and Delegation?

What is Monkey Patching and How Does it Differ from Method Overloading and Delegation?

Demystifying Monkey Patching

In the realm of programming, the term "monkey patching" often raises questions. What exactly does it entail? Is it akin to method/operator overloading or delegation?

Contrary to popular belief, monkey patching differs significantly from these concepts. Essentially, it involves the dynamic modification of attributes during runtime.

To illustrate, consider a class with a method called get_data. This method relies on external data sources, which can be problematic during unit testing. To address this, monkey patching allows you to replace get_data with a stub method that returns fixed data.

Since Python classes are mutable and methods are merely class attributes, monkey patching can be performed with ease. It extends to replacing classes and functions within a module using the same mechanism.

However, caution is advised when using this technique:

  1. Any other section of code aside from your test logic that references get_data will also call the modified method instead of the original.
  2. Existing variables or attributes referencing get_data will not be affected by the change and will continue to point to the original method.

In summation, monkey patching involves the dynamic alteration of attributes for testing or code alteration purposes, a practice that requires careful consideration.

The above is the detailed content of What is Monkey Patching and How Does it Differ from Method Overloading and Delegation?. For more information, please follow other related articles on the PHP Chinese website!

Statement
The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn
Python's Execution Model: Compiled, Interpreted, or Both?Python's Execution Model: Compiled, Interpreted, or Both?May 10, 2025 am 12:04 AM

Pythonisbothcompiledandinterpreted.WhenyourunaPythonscript,itisfirstcompiledintobytecode,whichisthenexecutedbythePythonVirtualMachine(PVM).Thishybridapproachallowsforplatform-independentcodebutcanbeslowerthannativemachinecodeexecution.

Is Python executed line by line?Is Python executed line by line?May 10, 2025 am 12:03 AM

Python is not strictly line-by-line execution, but is optimized and conditional execution based on the interpreter mechanism. The interpreter converts the code to bytecode, executed by the PVM, and may precompile constant expressions or optimize loops. Understanding these mechanisms helps optimize code and improve efficiency.

What are the alternatives to concatenate two lists in Python?What are the alternatives to concatenate two lists in Python?May 09, 2025 am 12:16 AM

There are many methods to connect two lists in Python: 1. Use operators, which are simple but inefficient in large lists; 2. Use extend method, which is efficient but will modify the original list; 3. Use the = operator, which is both efficient and readable; 4. Use itertools.chain function, which is memory efficient but requires additional import; 5. Use list parsing, which is elegant but may be too complex. The selection method should be based on the code context and requirements.

Python: Efficient Ways to Merge Two ListsPython: Efficient Ways to Merge Two ListsMay 09, 2025 am 12:15 AM

There are many ways to merge Python lists: 1. Use operators, which are simple but not memory efficient for large lists; 2. Use extend method, which is efficient but will modify the original list; 3. Use itertools.chain, which is suitable for large data sets; 4. Use * operator, merge small to medium-sized lists in one line of code; 5. Use numpy.concatenate, which is suitable for large data sets and scenarios with high performance requirements; 6. Use append method, which is suitable for small lists but is inefficient. When selecting a method, you need to consider the list size and application scenarios.

Compiled vs Interpreted Languages: pros and consCompiled vs Interpreted Languages: pros and consMay 09, 2025 am 12:06 AM

Compiledlanguagesofferspeedandsecurity,whileinterpretedlanguagesprovideeaseofuseandportability.1)CompiledlanguageslikeC arefasterandsecurebuthavelongerdevelopmentcyclesandplatformdependency.2)InterpretedlanguageslikePythonareeasiertouseandmoreportab

Python: For and While Loops, the most complete guidePython: For and While Loops, the most complete guideMay 09, 2025 am 12:05 AM

In Python, a for loop is used to traverse iterable objects, and a while loop is used to perform operations repeatedly when the condition is satisfied. 1) For loop example: traverse the list and print the elements. 2) While loop example: guess the number game until you guess it right. Mastering cycle principles and optimization techniques can improve code efficiency and reliability.

Python concatenate lists into a stringPython concatenate lists into a stringMay 09, 2025 am 12:02 AM

To concatenate a list into a string, using the join() method in Python is the best choice. 1) Use the join() method to concatenate the list elements into a string, such as ''.join(my_list). 2) For a list containing numbers, convert map(str, numbers) into a string before concatenating. 3) You can use generator expressions for complex formatting, such as ','.join(f'({fruit})'forfruitinfruits). 4) When processing mixed data types, use map(str, mixed_list) to ensure that all elements can be converted into strings. 5) For large lists, use ''.join(large_li

Python's Hybrid Approach: Compilation and Interpretation CombinedPython's Hybrid Approach: Compilation and Interpretation CombinedMay 08, 2025 am 12:16 AM

Pythonusesahybridapproach,combiningcompilationtobytecodeandinterpretation.1)Codeiscompiledtoplatform-independentbytecode.2)BytecodeisinterpretedbythePythonVirtualMachine,enhancingefficiencyandportability.

See all articles

Hot AI Tools

Undresser.AI Undress

Undresser.AI Undress

AI-powered app for creating realistic nude photos

AI Clothes Remover

AI Clothes Remover

Online AI tool for removing clothes from photos.

Undress AI Tool

Undress AI Tool

Undress images for free

Clothoff.io

Clothoff.io

AI clothes remover

Video Face Swap

Video Face Swap

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

Hot Tools

Safe Exam Browser

Safe Exam Browser

Safe Exam Browser is a secure browser environment for taking online exams securely. This software turns any computer into a secure workstation. It controls access to any utility and prevents students from using unauthorized resources.

SAP NetWeaver Server Adapter for Eclipse

SAP NetWeaver Server Adapter for Eclipse

Integrate Eclipse with SAP NetWeaver application server.

VSCode Windows 64-bit Download

VSCode Windows 64-bit Download

A free and powerful IDE editor launched by Microsoft

Atom editor mac version download

Atom editor mac version download

The most popular open source editor

SublimeText3 Mac version

SublimeText3 Mac version

God-level code editing software (SublimeText3)