{"id":25110,"date":"2018-08-19T04:15:28","date_gmt":"2018-08-18T22:45:28","guid":{"rendered":"https:\/\/data-flair.training\/blogs\/?p=25110"},"modified":"2026-04-23T16:08:56","modified_gmt":"2026-04-23T10:38:56","slug":"copy-in-python-deep-shallow-copy","status":"publish","type":"post","link":"https:\/\/data-flair.training\/blogs\/copy-in-python-deep-shallow-copy\/","title":{"rendered":"Copy in Python – Python Deep Copy and Shallow Copy"},"content":{"rendered":"

Today, in this Python Tutorial, we will see the copy in Python. Moreover, we will define Deep Copy and Shallow Copy in Python. <\/span><\/p>\n

Also, we will see a difference between Shallow Copy vs Deep Copy. Along with this, we will discuss Copy Module and Shallow Copying Dictionaries.<\/span><\/p>\n

So, let’s start Copy in Python.<\/p>\n

\"Copy<\/a>

Copy in Python – Shallow Copy and Deep Copy<\/p><\/div>\n

What is Python Copy Module?<\/h3>\n

When we perform an assignment in Python, it does not copy the object we assign. All it does is create bindings between a target and an object. <\/span><\/p>\n

But sometimes, we may need to change one Python copy without changing the other for a mutable collection.<\/span><\/p>\n

In this Python Copy tutorial, we discuss the module <\/span>copy<\/span><\/i> in Python. It has the following members-<\/span><\/p>\n

    \n
  • copy.copy(x): <\/strong>This returns a shallow copy of x.<\/li>\n
  • copy.deepcopy(x): <\/strong>This returns a deep copy of x.<\/li>\n
  • exception copy.error:<\/strong> <\/span>This is the exception it raises for module-specific errors.<\/li>\n<\/ul>\n

    Before we can begin explaining shallow copy and deep copy, we think it is necessary to tell you that these concepts apply to compound objects only- those that hold other objects, like lists or class instances.<\/span><\/p>\n

    Comparison between deep copy and shallow copy in Python:<\/strong><\/p>\n

    Shallow copy in Python:<\/strong><\/p>\n

      \n
    • It creates a new outer object but takes references from the original element.<\/li>\n
    • Any changes made in the mutable element can affect both the original and the copy object.<\/li>\n
    • It is fast in speed as it copies only the top-level objects.<\/li>\n
    • It uses less memory.<\/li>\n<\/ul>\n

      Deep copy in Python:<\/strong><\/p>\n

        \n
      • It also creates a new outer object but copies all the nested objects.<\/li>\n
      • Changes made in any part of the copy do not affect the original object.<\/li>\n
      • It is slower because it copies all the internal data.<\/li>\n
      • It uses more memory as it duplicates the whole data structure.<\/li>\n<\/ul>\n

        Python Deep Copy<\/h3>\n

        When a deep copy in Python creates a new object, it inserts into the new object copies of the objects in the original object. In other words, it copies an object into another. <\/span><\/p>\n

        This means any changes we make to the copy do not reflect in the original.<\/span><\/p>\n

        1. Example of Deep Copy in Python<\/h4>\n

        Let\u2019s try implementing this in Python. We use the deepcopy() function.<\/span><\/p>\n

        >>> import copy\r\n>>> list1=[1,3,[7,4],6]\r\n>>> list2=copy.deepcopy(list1) #Making a deep copy\r\n>>> list1<\/pre>\n
        Output<\/strong><\/p>\n
        [1, 3, [7, 4], 6]<\/div>\n
        >>> list2<\/pre>\n
        Output<\/strong><\/p>\n
        [1, 3, [7, 4], 6]<\/div>\n
        >>> list2[2][0]=5 #Modifying the element at index 2,0\r\n>>> list1<\/pre>\n
        Output<\/strong><\/p>\n
        [1, 3, [7, 4], 6]<\/div>\n
        >>> list2<\/pre>\n
        Output<\/strong><\/p>\n
        [1, 3, [5, 4], 6]<\/div>\n
        As you can see, this did not change anything for the original object.<\/span><\/p>\n
        2. Problems with Python Deep Copy<\/h4>\n
          \n
        • It is possible that recursive objects cause a recursive loop; these are compound objects that directly or indirectly reference themselves.<\/span><\/li>\n
        • It is possible that a deep copy may copy too much.<\/span><\/li>\n<\/ul>\n
          To deal with these problems, deepcopy():<\/span><\/p>\n
            \n
          • Keeps a memo dictionary of objects is copied during the current copying pass.<\/span><\/li>\n
          • Allows user-defined classes to override the copying operation or the copied component set.<\/span><\/li>\n<\/ul>\n
            Python Shallow Copy<\/h3>\n
            With a Shallow Copy in Python, we create a new object of which we recursively put copies of objects into the original. <\/span><\/p>\n
            In other words, we copy a reference of an object into another. Any changes we make to the copy do reflect in the original.<\/span><\/p>\n
            Let\u2019s implement this with Python. We\u2019ll use the copy() function.<\/span><\/p>\n
            >>> import copy\r\n>>> list1=[1,3,[7,4],6]\r\n>>> list2=copy.copy(list1) #Making a shallow copy\r\n>>> list1<\/pre>\n
            Output<\/strong><\/p>\n
            [1, 3, [7, 4], 6]<\/div>\n
            >>> list2<\/pre>\n
            Output<\/strong><\/p>\n
            [1, 3, [7, 4], 6]<\/div>\n
            >>> list2[2][0]=5 #Modifying the element at index 2,0\r\n>>> list1<\/pre>\n
            Output<\/strong><\/p>\n
            [1, 3, [5, 4], 6]<\/div>\n
            >>> list2<\/pre>\n
            Output<\/strong><\/p>\n
            [1, 3, [5, 4], 6]<\/div>\n
            It is apparent that making changes to a shallow copy does change the original object.<\/span><\/p>\n
            Shallow Copying Dictionaries in Python<\/h3>\n
            Let\u2019s first create a dictionary in Shallow Copy in Python.<\/span><\/p>\n
            >>> dict1={'a':1,'b':2,'c':[1,2,3]}<\/pre>\n
            Now, we\u2019ll make a copy of it.<\/span><\/p>\n
            >>> dict2=dict1.copy()<\/pre>\n
            Finally, we\u2019ll append a new element to this.<\/span><\/p>\n
            >>> dict2['c'].append(7)\r\n>>> dict1<\/pre>\n
            Output<\/strong><\/p>\n
            {‘a’: 1, ‘b’: 2, ‘c’: [1, 2, 3, 7]}<\/div>\n
            >>> dict2<\/pre>\n
            Output<\/strong><\/p>\n
            {‘a’: 1, ‘b’: 2, ‘c’: [1, 2, 3, 7]}<\/div>\n
            Other ways to create a shallow copy of a dictionary are dict(dict1) and copy.copy(dict1). <\/span><\/p>\n
            As you can see, altering the mutable in the copy changed the original too. To prevent this, we can do a deep copy in Python.<\/span><\/p>\n
            >>> import copy\r\n>>> dict1={'a':1,'b':2,'c':[1,2,3]}\r\n>>> dict2=copy.deepcopy(dict1)\r\n>>> dict2['c'].append(7)\r\n>>> dict1<\/pre>\n
            Output<\/strong><\/p>\n
            {‘a’: 1, ‘b’: 2, ‘c’: [1, 2, 3]}<\/div>\n
            >>> dict2<\/pre>\n
            Output<\/strong><\/p>\n
            {‘a’: 1, ‘b’: 2, ‘c’: [1, 2, 3, 7]}<\/div>\n
            So, this was all in Copy in Python. Hope you like our explanation of Shallow Copy and Deep Copy.<\/p>\n
            Python Interview Questions on Deep Copy and Shallow Copy<\/h3>\n
              \n
            1. What is Copy in Python?<\/li>\n
            2. What does Copy() do in Python?<\/li>\n
            3. How do you make a Copy in Python?<\/li>\n
            4. What is the difference between a deep copy and a shallow copy?<\/li>\n
            5. How do Deep Copy and Shallow Copy work in Python?<\/li>\n<\/ol>\n
              Conclusion<\/h3>\n
              Hence, today, in this Copy in Python Tutorial, we discussed Shallow copy and Deep copy with Python. <\/span><\/p>\n
              Where shallow copy changes reflect in the original object, deep copy changes don\u2019t. <\/span><\/p>\n
              Moreover, we understood the difference between Shallow Copy vs Deep Copy in Python. Also, we saw Shallow Copy Dictionaries.\u00a0<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"
              Today, in this Python Tutorial, we will see the copy in Python. Moreover, we will define Deep Copy and Shallow Copy in Python. Also, we will see a difference between Shallow Copy vs Deep...<\/p>\n","protected":false},"author":5,"featured_media":25133,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[46],"tags":[2990,3650,10337,10448,10449,10475,10476,10477,10837,12815,12816,12818,12819],"class_list":["post-25110","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-python","tag-copy-in-python","tag-deep-copy","tag-python-3-deep-copy","tag-python-copy-list","tag-python-copy-module","tag-python-deep-copy","tag-python-deep-copy-dictionary","tag-python-deep-copy-example","tag-python-shallow-copy-dictionary","tag-shallow-copy","tag-shallow-copy-and-deep-copy","tag-shallow-copy-vs-deep-copy","tag-shallow-copy-vs-deep-copy-python"],"yoast_head":"\nCopy in Python - Python Deep Copy and Shallow Copy - DataFlair<\/title>\n<meta name=\"description\" content=\"Copy in Python,shallow copy vs deep copy,Python copy module,shallow copy and deep copy,Shallow copy dictionary, Python Copy list\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/data-flair.training\/blogs\/copy-in-python-deep-shallow-copy\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Copy in Python - 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