search
HomeBackend DevelopmentPython TutorialWhy does `dict.fromkeys()` create shared mutable objects in Python?

 Why does `dict.fromkeys()` create shared mutable objects in Python?

Dictionary Creation and Mutable Objects: Surprising Behavior with fromkeys

When creating dictionaries using dict.fromkeys() in Python, an unexpected situation may arise when mutable objects are employed as values. Consider the following example:

<code class="python">xs = dict.fromkeys(range(2), [])
xs[0].append(1)
print(xs)</code>

Despite creating two separate list objects as values for the dictionary keys 0 and 1, adding an element to the list at index 0 also adds it to the list at index 1. This occurs because fromkeys binds each key to the same reference of the mutable object, resulting in shared modifications.

In contrast, dictionary comprehensions in Python 3.2 exhibit different behavior:

<code class="python">xs = {i: [] for i in range(2)}
xs[0].append(1)
print(xs)</code>

Here, each key is bound to a distinct list object. Appending an element to the list at index 0 does not affect the list at index 1.

Why the Difference?

The behavior of fromkeys can be understood by considering the following equivalent code:

<code class="python">a = []
xs = dict.fromkeys(range(2), a)</code>

Each key in the resulting dictionary references the same a object, leading to the observed shared modifications.

To achieve the desired behavior of distinct mutable objects for each key, use dictionary comprehensions or, for Python 2.6 and earlier without dictionary comprehensions, use dict() with a generator expression:

<code class="python">xs = dict((i, []) for i in range(2))</code>

The above is the detailed content of Why does `dict.fromkeys()` create shared mutable objects in Python?. 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
What are some common operations that can be performed on Python arrays?What are some common operations that can be performed on Python arrays?Apr 26, 2025 am 12:22 AM

Pythonarrayssupportvariousoperations:1)Slicingextractssubsets,2)Appending/Extendingaddselements,3)Insertingplaceselementsatspecificpositions,4)Removingdeleteselements,5)Sorting/Reversingchangesorder,and6)Listcomprehensionscreatenewlistsbasedonexistin

In what types of applications are NumPy arrays commonly used?In what types of applications are NumPy arrays commonly used?Apr 26, 2025 am 12:13 AM

NumPyarraysareessentialforapplicationsrequiringefficientnumericalcomputationsanddatamanipulation.Theyarecrucialindatascience,machinelearning,physics,engineering,andfinanceduetotheirabilitytohandlelarge-scaledataefficiently.Forexample,infinancialanaly

When would you choose to use an array over a list in Python?When would you choose to use an array over a list in Python?Apr 26, 2025 am 12:12 AM

Useanarray.arrayoveralistinPythonwhendealingwithhomogeneousdata,performance-criticalcode,orinterfacingwithCcode.1)HomogeneousData:Arrayssavememorywithtypedelements.2)Performance-CriticalCode:Arraysofferbetterperformancefornumericaloperations.3)Interf

Are all list operations supported by arrays, and vice versa? Why or why not?Are all list operations supported by arrays, and vice versa? Why or why not?Apr 26, 2025 am 12:05 AM

No,notalllistoperationsaresupportedbyarrays,andviceversa.1)Arraysdonotsupportdynamicoperationslikeappendorinsertwithoutresizing,whichimpactsperformance.2)Listsdonotguaranteeconstanttimecomplexityfordirectaccesslikearraysdo.

How do you access elements in a Python list?How do you access elements in a Python list?Apr 26, 2025 am 12:03 AM

ToaccesselementsinaPythonlist,useindexing,negativeindexing,slicing,oriteration.1)Indexingstartsat0.2)Negativeindexingaccessesfromtheend.3)Slicingextractsportions.4)Iterationusesforloopsorenumerate.AlwayschecklistlengthtoavoidIndexError.

How are arrays used in scientific computing with Python?How are arrays used in scientific computing with Python?Apr 25, 2025 am 12:28 AM

ArraysinPython,especiallyviaNumPy,arecrucialinscientificcomputingfortheirefficiencyandversatility.1)Theyareusedfornumericaloperations,dataanalysis,andmachinelearning.2)NumPy'simplementationinCensuresfasteroperationsthanPythonlists.3)Arraysenablequick

How do you handle different Python versions on the same system?How do you handle different Python versions on the same system?Apr 25, 2025 am 12:24 AM

You can manage different Python versions by using pyenv, venv and Anaconda. 1) Use pyenv to manage multiple Python versions: install pyenv, set global and local versions. 2) Use venv to create a virtual environment to isolate project dependencies. 3) Use Anaconda to manage Python versions in your data science project. 4) Keep the system Python for system-level tasks. Through these tools and strategies, you can effectively manage different versions of Python to ensure the smooth running of the project.

What are some advantages of using NumPy arrays over standard Python arrays?What are some advantages of using NumPy arrays over standard Python arrays?Apr 25, 2025 am 12:21 AM

NumPyarrayshaveseveraladvantagesoverstandardPythonarrays:1)TheyaremuchfasterduetoC-basedimplementation,2)Theyaremorememory-efficient,especiallywithlargedatasets,and3)Theyofferoptimized,vectorizedfunctionsformathematicalandstatisticaloperations,making

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

VSCode Windows 64-bit Download

VSCode Windows 64-bit Download

A free and powerful IDE editor launched by Microsoft

MinGW - Minimalist GNU for Windows

MinGW - Minimalist GNU for Windows

This project is in the process of being migrated to osdn.net/projects/mingw, you can continue to follow us there. MinGW: A native Windows port of the GNU Compiler Collection (GCC), freely distributable import libraries and header files for building native Windows applications; includes extensions to the MSVC runtime to support C99 functionality. All MinGW software can run on 64-bit Windows platforms.

EditPlus Chinese cracked version

EditPlus Chinese cracked version

Small size, syntax highlighting, does not support code prompt function

SAP NetWeaver Server Adapter for Eclipse

SAP NetWeaver Server Adapter for Eclipse

Integrate Eclipse with SAP NetWeaver application server.

Dreamweaver Mac version

Dreamweaver Mac version

Visual web development tools