Learn Mutable and Immutable in Python | DataTrained

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Introduction to Mutable and Immutable In Python

Mutable and Immutable In Python, everything is an object. And, as any novice to Python should quickly discover, all Python objects can be either changeable or immutable. Let’s dive a little deeper into the details… Because everything mutable and immutable in Python is an Object, each variable contains an instance of that object. An object is given a unique object id when it is created. Its type is set at runtime and cannot be modified; however, if it is mutable, its state can be changed. A mutable object, on the other hand, can be altered after it is created, whereas an immutable object cannot. This is a key difference between mutable and immutable in python.

A quick aside about Python: The serpentine namesake isn’t an abbreviation or acronym; it’s merely the product of Python founder Guido van Rossum’s love of Monty Python. If you’re new to programming, the terms mutable and immutable in python objects will come up frequently. This article is for you if you are still perplexed or want to learn more about mutability and immutability. Everything in Python is an object. Every object has its own internal state and data type (data).

Python considers everything to be an object. A unique id is assigned to an item when it is created. We can’t change the object’s type, but we can change the object’s value. If we set variable a to be a list, we won’t be able to transform it to a tuple/dictionary, but we can modify the values in that list.

Mutable and immutable in Python, there are two sorts of objects. On the one hand, there are those objects that can modify their internal state (the data/content inside those objects) using predefined functions or methods, while on the other hand, there are those objects that cannot change their internal state (the data/content inside those objects).

What Is Python?

about python

Python is a programming language that is widely used to create websites and applications, automate operations, and perform data analysis. Python is a general-purpose programming language, which means it can be used to develop a wide range of applications and isn’t tailored to any particular problem. Because of its versatility and beginner-friendliness, it has become one of the most widely used programming languages today. It was the second-most popular programming language among developers in 2022, according to a survey performed by industry analyst firm RedMonk. There are two types of objects mutable and immutable in python.

Python is a dynamically structured, interpreted, object-oriented high-level programming language. Its high-level built-in data structures, together with dynamic typing and dynamic binding, make it ideal for Rapid Application Development and as a scripting or glue language for connecting existing components. Python’s concise, easy-to-learn syntax prioritizes readability, which lowers software maintenance costs. 

Python is a fantastic programming language. Many individuals chose it as their first programming language because of its simplicity. Python is also widely used by experienced programmers, because of its large community, variety of packages, and simple syntax. However, there is one issue that appears to be confusing both beginners and expert developers: Python objects. The distinction between mutable and immutable in python objects in particular.

Python is popular among programmers because of the enhanced productivity it offers. The edit-test-debug cycle is extraordinarily rapid because there is no compilation step. Python scripts are simple to debug: a bug or improper input will never result in a segmentation fault. Instead, when the interpreter finds a mistake, it throws an exception. The interpreter prints a stack trace if the application fails to catch the exception. Inspection of local and global variables, execution of arbitrary expressions, setting breakpoints, stepping through the code one line at a time, and so on are all possible with a source-level debugger. The debugger is written in Python, demonstrating Python’s introspective capabilities.

Different objects like mutable and immutable in Python are widely used for web and software development, task automation, data analysis, and data visualization. Python has been used by many non-programmers, such as accountants and scientists, for a variety of common tasks, such as arranging finances, due to its relative ease of learning.

What is a Mutable Object In Python?

Mutable Object In Python

Unlike other programming languages that enable objects, Python treats everything – including numbers, lists, and even functions – as an object. When something is mutable, it is changeable or capable of change. ‘Mutable’ in Python refers to objects’ capacity to change their values. Objects that store a collection of data are frequently these. The term “mutable” refers to items that can change after being created. We can alter mutable objects using a variety of methods and functions. The original objects are modified when certain methods and functions are used.

The memory where the changeable objects are kept remains unchanged while any modifications are made to them. This is broken down into sections. Objects that can be changed Continue reading to learn more.

Examples Of Mutable Objects:

  • List 
  • Dictionary
  • Set

Also Read: Blockchain Technology Complete Guide

Examples Of Mutable Objects

A. List

Lists are changeable in nature, which means we can change the items of a list using either the assignment or indexing operators.

Let’s look at an example of that:

list1 = [‘hi’,’bye’,52,True,2.3]

print(list1)

list1[1]=’see u later’

print(list1

Output:

[‘hi’, ‘bye,’ 52, True, 2.3]

[‘hi’,’see u later,’ 52, True, 2.3]

Explanation:

  1. We made a list and filled it with values.
  2. The value at the first index is then assigned using the assignment operator.
  3. Then we print the modified list (together with the old list) and notice that the value at index 1 has changed.
  4. This demonstrates that Lists are inherently changeable.

B. Dictionary

When it comes to mutable and immutable in python. Since dictionaries are mutable, we may use the built-in function to update them (update).

Let’s look at an example of that

dict1 = {1:’google’,2:’firefox’,3:’opera’}

print(dict1)

updateDict = {4:’Ms Edge’}

dict1.update(updateDict)

print(dict1)

Output:

{1: ‘google’, 2: ‘firefox’, 3: ‘opera’}

{1: ‘google’, 2: ‘firefox’, 3: ‘opera’, 4: ‘Ms Edge’}

Explanation:

  1. We made a dictionary and filled it with values.
  2. We make a variable and assign it a key:value pair.
  3. The update function is then used to update the dictionary with the newly produced key:value pair.
  4. Finally, we print the dictionary to see that the newly formed key:value pair is now included in t
    he original list.
  5. This demonstrates that dictionaries are inherently changeable.

C. Set

When it comes to mutable and immutable in python sets are considered mutable in nature, we can use the built-in function to update the mutable and immutable in python.

Let’s look at an example of that

set1 = {1,2}

print(set1)

updateSet = {‘a’,’b’,1}

set1.update(updateSet)

print(set1)

Output:

{1,2}

{1,2,’b’,’a’}

Explanation:

  1. We made a set and filled it with values.
  2. We make a variable and fill it with more set values.
  3. The update function is then used to add the newly formed set to the original set.
  4. Finally, we printed the set and discovered that the newly formed set had been added to the original set.
  5. This demonstrates that Sets are inherently changeable.

What is an Immutable Object In Python?

Immutable Object In Python

When no change is possible across time, it is said to be immutable. In Python, an object is said to be immutable if its value cannot be altered over time. The worth of these objects is infinite once they have been made. Immutable objects are those that cannot change after they have been initialized. These immutable objects have no methods or functions that can be used to change them. We must first change those immutable objects to mutable objects before we may edit them.

When you make changes to immutable objects, the memory where they were stored when they were first created is updated. This is broken down into sections. Immutable Objects are objects that cannot be changed. Continue reading to learn more.

Examples Of Immutable Objects:

  • Int
  • Float
  • String 
  • Tuple
  • Frozen Set

Examples Of Immutable Object In Python

A. Int

We can’t edit or update the int data type because it’s immutable. Immutable objects change their memory address when they are updated, as we saw earlier.

Let’s look at an example of that

intVariable = 20

print(‘memory address before updating: ‘, id(a))

# Updating an immutable object by assigning a new value to it.

# It will now refer to the new object and defer the previously created object.

intVariable=30

print(‘memory address after updating: ‘, id(a))

Output:

memory address before updating: 9789600

memory address after updating: 9789920

Explanation:

  1. To a variable, we assigned an integer value.
  2. The variable’s id is then printed.
  3. We print the variable’s id again after it has been updated.
  4. Both times, the output is different.
  5. This indicates that integers are immutable in nature, as another integer object was created and referenced when the value was changed.

B. Float

We can’t edit or update the float data type because it’s immutable. Immutable objects change their memory address when they are updated, as we saw earlier.

Let’s look at an example of that

floatVariable = 2.5

print(‘memory address before updating: ‘, id(floatVariable))

# Updating an immutable object by assigning a new value to it.

# It will now refer to the new object and defer the previously created object.

floatVariable = 10.0

print(‘memory address after updating: ‘, id(floatVariable))

Output:

memory address before updating: 140664386693680

memory address after updating: 140664386693712

Explanation:

  1. A variable was given some float values.
  2. The variable’s id is then printed.
  3. We print the variable’s id again after it has been updated.
  4. Both times, the output is different.
  5. This indicates that floats are immutable in nature, as another integer object was created and referenced when the value was updated.

C. String

We can’t insert or edit anything in a string because it’s immutable by nature. We received problems stating that strings are not changeable in nature when altering any section of the string.

Let’s look at an example of that

stringVariable = ‘hello geeks’

stringVariable[0] = ‘bye’

print(stringVariable)

Output:

stringVariable[0] = ‘bye’

TypeError: ‘str’ object does not support item assignment

Explanation:

  1. A variable was given some string values.
  2. Then, using the item assignment operator, we try to update the string.
  3. When we print the string after changing the variable, we get the error item assignment not supported.
  4. This means that strings are inherently immutable.

D. Tuple

Tuples are likewise immutable, which means we can’t append or update anything in them. We encountered several problems while updating any item in the tuple, such as strings are not mutable in nature. When it comes to Mutable and immutable in python, a tuple will be considered immutable.

Let’s look at an example of that

tupVariable = (1,2,3)

tupVariable[1] = 5

print(tupVariable)

Output:

tupVariable[1] = 5

TypeError: ‘tuple’ object does not support item assignment

Explanation:

  1. The tuple was given some values.
  2. The item assignment operator is then used to try to update the tuple.
  3. When we print the string after changing the variable, we get the error item assignment not supported.
  4. This means that tuples are inherently immutable.

E. Frozen Set

In Python, frozensets are similar to sets, but they are immutable in nature. While elements in a set can be changed at any moment, this is not possible with frozenset. As a result, we won’t be able to insert or update anything in the frozenSet. We got various problems while updating any item in frozenSet, When it comes to mutable and immutable in python such as frozenSet is not mutable in nature.

Let’s look at an example of that

nu = (1, 2, 3, 4, 5, 6, 7, 7, 8, 9)

fnum = frozenset(nu)

print(“frozenset Object is : “, fnum)

fnum[1] = 10

print(fnum)

Output:

frozenset Object is : frozenset({1, 2, 3, 4, 5, 6, 7, 8, 9})

fnum[1] = 10

TypeError: frozenset object does not support item assignment

Explanation:

  1. The tuple was given some values.
  2. The frozenset function is then used to transform the tuple into a frozenset.
  3. Then, using the item assignment operator, we try to update the frozenset.
  4. When we print the string after changing the variable, we get the error item assignment not supported.
  5. This demonstrates the immutability of frozensets in nature.

Examples Of Mutable and Immutable in Python

Examples Of Mutable and Immutable in Python

Although we’ve argued that everything mutable and immutable in Python is an object, there is a distinction to be made. Some objects can be changed, while others cannot. As I previously stated, many individuals who are new to Python are perplexed by this fact, so we’ll make sure it’s clear.

Imagine we need to construct an application to store information about the subjects chosen by students. We must keep in mind when developing such an application that we must employ objects that can be updated as needed afterward. Let’s look at the examples of mutable and immutable in python objects.

Let’s take an example of mutable and immutable in python: To record the names of all the subjects chosen by a student, we must utilize Mutable objects like List rather than Immutable objects like tuples in this application. We can’t modify the tuple if we use tuple(immutable object) here. If we need to update a student’s topic list, we must generate a new tuple, which consumes a lot of memory and is not a good practice.

Example:

student1=[‘subject1’, ‘subject2’, ‘subject3’]

#  now if we want to add a new subject to the list

student1.append(‘subject4’ptions 

print(student1)

Output:

[‘subject1’, ‘subject2’, ‘subject3’, ‘subject4’]

Exceptions In Immutability

Exceptions In Immutability

There are exceptions to mutable and immutable in Python, for now, let’s talk about immutability just as there are in any other language. Not all objects that appear to be immutable are actually mutable. This will cause you to have a lot of doubts. To further grasp this, let’s look at an example.

Take a look at the tuple ‘tup’.

Now, if we consider tuple tup = (‘DataTrained’,[4,3,1,2]);

The tuple has elements of several data kinds, as we can see. The first element is a string, which is immutable in nature as we all know. The second element is a list, which is mutable as we all know. We’ve established that the tuple is an immutable data type. It is unable to alter its contents. However, the contents of the list within it can alter. As a result, the value of immutable objects cannot be modified, but the value of their constituent objects can.

Conclusion

In this blog, we looked at what Python’s Mutable and Immutable in python objects are. Then we looked at changeable objects and examples of mutable things in detail. Then we’ll look into immutable objects and examine an example of immutable objects. Finally, we looked at several real-world examples of changeable versus immutable objects.

Immutable items are more quickly accessible than mutable objects. Modifying immutable things is inherently costly because it necessitates the creation of a duplicate; nevertheless, changing mutable objects is deemed inexpensive.

With easy-to-understand examples, we discussed mutable and immutable in Python. We hope you now understand what mutable and immutable in Python mean. Please let us know if you have any further queries.

Frequently Asked Question’s

1. What is Python?

Python is a multifunctional programming language that may be used almost everywhere data, mathematical computation, or lines of code are used. This means that, unlike Java, Python isn’t limited to web development. Python, like most programming languages, is accompanied by an interpreter that runs the finalized lines of code. There are many free resources available to help you learn Python, which is regarded as one of the easiest coding languages to learn and read because it is based on English syntax.

Python is a practical and accessible programming language for anybody from corporate software professionals to casual coders. Python can be used for simple tasks such as powering a Reddit moderator bot or for incredibly complicated programming such as analyzing enormous quantities of financial data for a hedge fund. Python’s scalability is one of its best features: Even if a small garage-based business grows into a high-rise corporate headquarters, a Python-based application can keep using the same coding language. Mutable and immutable in python.

2. Are sets mutable and immutable in Python?

A rigorous definition of a set in mathematics might be esoteric and difficult to grasp. In practice, though, a set can be conceived of as a well-defined collection of unique things, which are commonly referred to as elements or members. In programming, grouping things into a set can be beneficial, and Python has a built-in set type for this. The unique actions that may be performed on sets set them apart from other object types. When it comes to mutable and immutable in python the sets are considered as mutable.

Many of the operations that work with Python’s other composite data types don’t work with sets. Sets, for instance, cannot be indexed or sliced. Mutable and immutable in Python, on the other hand, provides a number of operations on set objects that closely resemble the operations provided for mathematical sets.

3. What is an immutable data type example?

Mutable and immutable In Python, a set is a data type that allows you to store multiple things in a single variable. It is one of the four built-in data types (List, Dictionary, Tuple, and Set) that differs from the other three in terms of attributes and usage. It’s an unindexed, unordered collection written using curly brackets. Mutable and immutable In Python, items in a set are immutable (unchangeable), have no duplicate values, and are unsorted. As a result, objects in a set do not always appear in the same order, and they may appear in a different order each time it is used. Set items cannot be referred to by key or index as a result of this.

Items in a set cannot be modified once it has been formed. New objects, on the other hand, can be added. As previously stated, every set item must be unique because copies are not permitted. A set’s elements can be of any data type. Mutable and immutable In Python, a set is an unordered, unindexed collection with unique members. Before you can use a collection type, you must first grasp its attributes. This can help your program’s security and efficiency.

4. What are types of mutable and immutable in Python?

In Python, mutable data types can have their values altered in place, but immutable data types cannot have their values changed in place. Here are some examples of mutable and immutable in python data types:

Here are Mutable data types:

  • Lists
  • Dictionaries
  • Sets

Immutable data types in Python:

  • Integers
  • Floating-Point numbers
  • Booleans
  • Strings
  • Tuples

Python The treatment of changeable and immutable objects differs. Because they require the production of a copy, immutable objects are easier to obtain and more expensive to alter. Mutable things, on the other hand, are simple to alter. Mutable and immutable In Python, each variable holds an instance of an object mutable and immutable in python.

Mutable and immutable In Python, there are two sorts of objects: mutable and immutable in python objects. When an object mutable and immutable in python is created, it is given a distinct object id. The object’s type is determined at runtime and cannot be modified subsequently. If it is a mutable object, though, its state can be modified.

5. What is mutability in Python?

When something is mutable, it is changeable or capable of change. Mutable and immutable in Python refers to objects’ capacity to change their values. Objects that store a collection of data are frequently these. The term “mutable” refers to an object’s internal state being modified or mutated. 

So, the most basic definition is: A mutable object is one whose internal state can be altered. Immutable, on the other hand, prevents changes to an object once it has been created. Python mutability refers to being able to change an object. Simply put, when it comes to mutable and immutable in python, a mutable object can be changed, but an immutable object cannot. For example, a tuple is an immutable data type. You cannot change its elements after creating it:

nums = (1, 2, 3)

nums[0] = 100 # ERROR!

When it comes to mutable and immutable In Python, everything is an object. Every object falls into one of two categories: changeable or immutable. A Python object is given a unique object id when it is created. The state of a type can be modified depending on whether it is mutable or immutable. Mutability in Python refers to an object’s ability to alter. A mutable object, unlike an immutable object, can change. A list, for example, is mutable, whereas a tuple is not. To put it another way, you can alter the elements of a list but not the elements of a tuple.

6. Which Python types are immutable with examples?

Immutability has a wide range of applications in sensitive operations that we perform in a networked setting with parallel processing. You seal the values and ensure that no threads can replace or update your data by constructing immutable objects. This is also handy in cases where you want to write a piece of code that cannot be changed. A debug code that tries to find the value of an immutable object, for example.

Tuples are immutable, which means they can’t be changed once they’ve been generated mutable and immutable in Python. This is due to the fact that they may perform the same sequence operations as strings. Strings are immutable, as we all know. The index operator, like the string operator, selects an element from a tuple. As a result, they are unchangeable.

7. Why is list mutable in Python?

Many Python types are immutable. Immutable data types include integers, floats, strings, and (as you’ll see later in this course) tuples. Once you’ve created one of these objects, you can’t change it unless you reassign it to a new value. When it comes to mutable and immutable in python list will always be considered as mutable.

The list is a changeable data type. After you’ve made a list, do the following:

  • It is possible to change the elements.
  • Individual values can be swapped in and out.
  • It is possible to rearrange the elements.

The term “container” refers to items that hold references to other objects. A tuple, list, or dictionary are examples of containers. If a mutable object is updated, the value of an immutable container that contains a reference to it can be changed. However, the container is still regarded as immutable since only the IDs of the contained objects are assumed when we talk about the mutability of a container.

8. Why are strings called immutable?

When writing any application software, a String is an inescapable type of variable. Various properties such as usernames, passwords, and so on are stored via string references. Whenever we talk of mutable and immutable in python String objects are immutable in Java. Immutable simply means that it cannot be changed or modified. The data or state of a String object can’t be modified once it’s been formed; instead, a new String object is produced.

The reference variable still refers to “Sachin” rather than “Sachin Tendulkar.” However, if we assign it to the reference variable explicitly, it will correspond to the object “Sachin Tendulkar.”

9. Are Python strings mutable or immutable?

When it comes to mutable and immutable in python. String data types in Python are immutable. This signifies that a string value can’t be changed. We may test this by updating a portion of the string, which will result in an error.

# Can not reassign 

t= “Tutorialspoint”

print type(t)

t[0] = “M”

When we run the program given above, we get the following output −

t[0] = “M”

TypeError: ‘str’ object does not support item assignment

We may double-check this by looking at the memory location address of the string’s letter positions.

x = ‘banana’

for idx in range (0,5):

    print x[idx], “=”, id(x[idx])

We receive the following output when we run the aforesaid programme. As you can see in mutable and immutable in python, a and b both point to the same place. N and N are also pointing to the same place.

b = 91909376

a = 91836864

n = 91259888

a = 91836864

n = 91259888

10. What is the difference between immutable & final?

In our blog on mutable and immutable in python. Let’s throw some light on immutable & final too

final: final is a modifier in Java that can be applied to a class, method, or variable. When a variable is declared using the final keyword, the value of the variable cannot be changed, making it a constant.

Immutability: Immutability simply means that something does not change through time or that it cannot be changed. In Java, we know that String objects are immutable, which means we can’t edit them once they’ve been created.

  1. final indicates that you cannot alter the object’s reference to point to another reference or object, but you can change its state (using setter methods e.g). Immutable means that you can’t modify the object’s real value, but you can change its reference to another one.
  2. Immutability is applicable to an object but not to variables, whereas the final modifier is applicable to variables but not to objects.
  3. We won’t acquire any immutability by defining a reference variable as final, even when the reference variable is final. In the appropriate Object, we can make any change we want. However, we are unable to reassign that variable.
  4. final ensures that the object’s address remains constant, whereas Immutable implies that we can’t change the object’s state once it’s been created.

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