Table of Contents

The Python List Method will allow you to built-in methods and will do operations on the Python list/ arrays. Read this article to learn more about Python list Methods.

What is Python List Methods?

Python consists of a set of built-in methods that will be used on lists.

How to add Elements to the List?

The built-in Python methods are used to add the element to the list.

1. Python append() method

This method is used to add the element to the end of the list.

Syntax: list.append (element)

Example

class CustomList:
    def __init__(self):
        self.data = []

    def append(self, value):
        self.data += [value]

    def __str__(self):
        return str(self.data)


# Example usage
custom_list = CustomList()
custom_list.append(1)
custom_list.append(2)
custom_list.append(3)

print("Custom list after appending elements:", custom_list)

Output

Custom list after appending elements: [1, 2, 3]

2. Python insert() method

The Python insert() method will allow you to insert the element at the specified position.

Syntax:

list.insert(<position, element)

Example

class CustomList:
    def __init__(self):
        self.data = []

    def insert(self, index, value):
        self.data = self.data[:index] + [value] + self.data[index:]

    def __str__(self):
        return str(self.data)


# Example usage
custom_list = CustomList()
custom_list.insert(0, 1)
custom_list.insert(1, 2)
custom_list.insert(1, 3)

print("Custom list after inserting elements:", custom_list)

Output

Custom list after inserting elements: [1, 3, 2]

3. Python extend() method

The Python extend method will add the items of the iterable to the end of the list.

Syntax: List1.extend(List2)

Example

class CustomList:
    def __init__(self):
        self.data = []

    def extend(self, iterable):
        self.data += iterable

    def __str__(self):
        return str(self.data)


# Example usage
custom_list = CustomList()
custom_list.extend([1, 2, 3])
custom_list.extend([4, 5, 6])

print("Custom list after extending elements:", custom_list)

Output

Custom list after extending elements: [1, 2, 3, 4, 5, 6]

What are the important functions of the Python List?

Some of the important functions of the Python list are given below:

1. Python sum() method

The Python sum method will allow you to calculate the sum of the elements of the list.

Syntax: sum(List)

Example

class CustomList:
    def __init__(self):
        self.data = []

    def append(self, value):
        self.data += [value]

    def sum(self):
        return sum(self.data)

    def __str__(self):
        return str(self.data)


# Example usage
custom_list = CustomList()
custom_list.append(1)
custom_list.append(2)
custom_list.append(3)

print("Custom list:", custom_list)
print("Sum of elements in custom list:", custom_list.sum())

Output

Custom list: [1, 2, 3]
Sum of elements in custom list: 6

2. Python count() method

This method will sum the total occurrence of the given element of the list.

Syntax: List.count(element)

Example

class CustomList:
    def __init__(self):
        self.data = []

    def append(self, value):
        self.data.append(value)

    def count(self, value):
        return self.data.count(value)

    def __str__(self):
        return str(self.data)


# Example usage
custom_list = CustomList()
custom_list.append(1)
custom_list.append(2)
custom_list.append(3)
custom_list.append(1)  # Adding one more 1

print("Custom list:", custom_list)
print("Number of occurrences of '1' in custom list:", custom_list.count(1))

Output

Custom list: [1, 2, 3, 1]
Number of occurrences of '1' in custom list: 2

3.Python index() method

This method will return the index of the first occurrence. So, the start and end indexes are not the required parameters.

Syntax: List.index(element[,start[,end]])

Example

class CustomList:
    def __init__(self):
        self.data = []

    def append(self, value):
        self.data.append(value)

    def index(self, value):
        return self.data.index(value)

    def __str__(self):
        return str(self.data)


# Example usage
custom_list = CustomList()
custom_list.append(1)
custom_list.append(2)
custom_list.append(3)

print("Custom list:", custom_list)
print("Index of '2' in custom list:", custom_list.index(2))

Output

Custom list: [1, 2, 3]
Index of '2' in custom list: 1

4. Python min() method

This method will find the minimum of all the elements of the list.

Syntax: min(iterable, *iterables[, key])

Example

class CustomList:
    def __init__(self):
        self.data = []

    def append(self, value):
        self.data.append(value)

    def min(self):
        return min(self.data)

    def __str__(self):
        return str(self.data)


# Example usage
custom_list = CustomList()
custom_list.append(3)
custom_list.append(1)
custom_list.append(5)
custom_list.append(2)

print("Custom list:", custom_list)
print("Minimum value in custom list:", custom_list.min())

Output

Custom list: [3, 1, 5, 2]
Minimum value in custom list: 1

5. Python max() method

The Python will calculate the maximum of all the elements of the list.

Syntax: max(iterable, *iterables[, key])

Example

class CustomList:
    def __init__(self):
        self.data = []

    def append(self, value):
        self.data.append(value)

    def max(self):
        return max(self.data)

    def __str__(self):
        return str(self.data)


# Example usage
custom_list = CustomList()
custom_list.append(3)
custom_list.append(1)
custom_list.append(5)
custom_list.append(2)

print("Custom list:", custom_list)
print("Maximum value in custom list:", custom_list.max())

Output

Custom list: [3, 1, 5, 2]
Maximum value in custom list: 5

6. Python sort() method

This method will allow us to sort the given data structure in ascending order. Whereas, the key and reverse flag won’t be considered as the necessary parameter and the reverse_ flag will be set to false when nothing is passed through the sorted().

Syntax: list.sort([key,[Reverse_flag]])

Example

class CustomList:
    def __init__(self):
        self.data = []

    def append(self, value):
        self.data.append(value)

    def sort(self):
        self.data.sort()

    def __str__(self):
        return str(self.data)


# Example usage
custom_list = CustomList()
custom_list.append(3)
custom_list.append(1)
custom_list.append(5)
custom_list.append(2)

print("Custom list before sorting:", custom_list)
custom_list.sort()
print("Custom list after sorting:", custom_list)

Output

Custom list before sorting: [3, 1, 5, 2]
Custom list after sorting: [1, 2, 3, 5]

7. Python reverse() method

The reverse method will reverse the order of the list.

Syntax: list. reverse()

Example

class CustomList:
    def __init__(self):
        self.data = []

    def append(self, value):
        self.data.append(value)

    def reverse(self):
        self.data = self.data[::-1]

    def __str__(self):
        return str(self.data)


# Example usage
custom_list = CustomList()
custom_list.append(1)
custom_list.append(2)
custom_list.append(3)

print("Custom list before reversing:", custom_list)
custom_list.reverse()
print("Custom list after reversing:", custom_list)

Output

Custom list before reversing: [1, 2, 3]
Custom list after reversing: [3, 2, 1]

Conclusion

Python lists are fundamental data structures that enable the storage and manipulation of collections of elements. For beginners learning Python, grasping basic list methods is crucial. These methods offer essential functionalities for managing lists effectively.

However, the append() method will allow adding elements to the end of a list, while extend() allows adding multiple elements from another iterable. insert() permits inserting elements at specific positions. For removing elements, students can utilize remove() to delete the first occurrence of a value or pop() to remove and return an element at a given index.

Python List Methods-FAQs

Hridhya Manoj

Hello, I’m Hridhya Manoj. I’m passionate about technology and its ever-evolving landscape. With a deep love for writing and a curious mind, I enjoy translating complex concepts into understandable, engaging content. Let’s explore the world of tech together

Table of Contents

In Python, there are many ways to join, or concatenate, two or more lists in Python. Check out the article below to learn more about Merge Two Lists in Python.

What is Python Join Two Lists?

Merging a list refers to adding or concatenating one list with another. Also, it refers to adding two lists. The methods that are used to join the Python list are given below:

a. Using the Naive Method

b.Using the + operator

c.Using the list comprehension

d.Using the extend () method

e.Using the * operator

f.Using the itertools.chains

g.Merge two List using reduce

How to Merge two lists in Python using Method

The list comprehension will help to accomplish the task of the list concatenation. Whereas, the new list will be created.

Example

# Method 1: Using extend() method
def merge_lists_method1(list1, list2):
    merged_list = list1.copy()  # Make a copy of list1 to preserve original data
    merged_list.extend(list2)  # Extend the list with elements from list2
    return merged_list

# Method 2: Using + operator
def merge_lists_method2(list1, list2):
    merged_list = list1 + list2  # Concatenate the two lists using the + operator
    return merged_list

# Example lists
list1 = [1, 2, 3]
list2 = [4, 5, 6]

# Output of Method 1
merged_list_method1 = merge_lists_method1(list1, list2)
print("Merged list using extend() method:", merged_list_method1)

# Output of Method 2
merged_list_method2 = merge_lists_method2(list1, list2)
print("Merged list using + operator:", merged_list_method2)

Output

Merged list using extend() method: [1, 2, 3, 4, 5, 6]
Merged list using + operator: [1, 2, 3, 4, 5, 6]

How to Merge two lists using the extend()

The extend() is a function that allows you to extend by list in Python and then perform the task. So, this function will do the in-place extension of the first list.

Example

def merge_lists(list1, list2):
    merged_list = list1.copy()  # Make a copy of list1 to preserve original data
    merged_list.extend(list2)  # Extend the list with elements from list2
    return merged_list

# Example lists
list1 = [1, 2, 3]
list2 = [4, 5, 6]

# Merge the lists using extend() method
merged_list = merge_lists(list1, list2)

# Output the merged list
print("Merged list using extend() method:", merged_list)

Output

Merged list using extend() method: [1, 2, 3, 4, 5, 6]

How to Join Two Lists Using * Operator in Python?

This method will be performed with the help of the * operator. It is the new addition to the list concatenation and will work only in Python 3.6+. So, any no of the list will be concatenated and returned to the new list using the operator.

Example

def join_lists(list1, list2):
    joined_list = [*list1, *list2]  # Concatenate the two lists using the * operator
    return joined_list

# Example lists
list1 = [1, 2, 3]
list2 = [4, 5, 6]

# Join the lists using * operator
joined_list = join_lists(list1, list2)

# Output the joined list
print("Joined list using * operator:", joined_list)

Output

Joined list using * operator: [1, 2, 3, 4, 5, 6]

How to join two lists using the itertools. chain() in Python?

itertools.chain() is a function in Python that combines multiple lists into a single iterable (something you can iterate over, like a list). Hence, it doesn’t create a new list by combining them, instead, it just gives you a way to access all the elements from all the lists one after the other without storing them in memory.

Example

import itertools

# Define the lists
list1 = [1, 2, 3]
list2 = [4, 5, 6]

# Use itertools.chain() to join the lists
joined_list = itertools.chain(list1, list2)

# Output the joined list
print("Joined list using itertools.chain():", list(joined_list))

Output

Joined list using itertools.chain(): [1, 2, 3, 4, 5, 6]

How to Concatenate two lists using the reduce () function in Python?

First, we import the reduce function from the functools library, which helps us perform operations on lists. Then, we create two lists, list1, and list2, each containing some elements. Next, we combine these lists into a nested list called nested_list. Using the reduce() function, we merge the lists within nested_list.

Within the reduce() function, we use a lambda function, which works similarly to the mini-function used for a single purpose, to concatenate each list in the nested list. Finally, the result of the concatenation is stored in the variable result, which holds the joined list. This joined list is then printed as the final output.

Conclusion

In Python, merging two lists can be achieved using different methods, such as the extend() method, the + operator, and itertools. chain(), or even the reduce() function from the functools library. Each method offers its way of combining lists, catering to different needs and preferences.

Whether you’re simply concatenating lists, chaining their elements together, or reducing them into a single list, Python provides versatile solutions to merge lists efficiently. By understanding these methods, you can choose the one that best fits your specific requirements when working with lists in Python.

Merge Two Lists in Python- FAQs

Hridhya Manoj

Hello, I’m Hridhya Manoj. I’m passionate about technology and its ever-evolving landscape. With a deep love for writing and a curious mind, I enjoy translating complex concepts into understandable, engaging content. Let’s explore the world of tech together

Table of Contents

Python consists of the built-in type which is referred to as List. The List literal will be written within the square brackets. The list will work similarly to the strings. It is required to use the len() function and square brackets to access data with the first element. Let us look into the article to learn more about Python List.

What is a Python List?

The list refers to the data structure in Python that will be mutable and will be an ordered sequence of elements.

What is FOR and IN?

Pythons for and it will be useful and are used in the Python lists. The *for construct — for var in the list will be the easy way to see each element in the list.

# Define a list of numbers
numbers = [1, 2, 3, 4, 5]

# Use a for loop to iterate over each number in the list
for num in numbers:
    # Calculate the square of each number
    square = num ** 2
    
    # Print the result
    print(f"The square of {num} is: {square}")

The in-construct will be the simple way to test if the element is visible in the list– value in the collection– and will test whether the value in the collection will return True or False.

The square of 1 is: 1
The square of 2 is: 4
The square of 3 is: 9
The square of 4 is: 16
The square of 5 is: 25

The for/ in constructs are mostly used in the Python code and will work on data types other than the list. It is important to important to memorize the syntax. It is possible to use the for/ in to work on the string. The string will take the place of chars and will print all the chars in the string.

What is Range?

In Python, the range() function helps us create a series of numbers that we can use in a loop. There are two common ways to use it:

1. range(n): This makes a series of numbers starting from 0 up to (but not including) n.

for i in range(5):
    print(i)
# Output: 0, 1, 2, 3, 4

2. range(a,b): This will make the series that will begin from a and go up to b.

for j in range(2, 6):
    print(j)
# Output: 2, 3, 4, 5

What is a While Loop?

Python consists of the standard while-loop, break, and continue statements that will operate for C++ and Java. So, this will alter the course of the innermost loop. The above for/ in loop will work to solve the common case of iterating over every element in the list. Thus, the while loop will provide you control over the index numbers. Check the loop that is given below:

  ## Access every 3rd element in a list
  i = 0
  while i < len(a):
    print(a[i])
    i = i + 3

What is List Methods?

The list of methods that are commonly used is given below:

1. list.append(elem):

• Adds a single element to the end of the list.
• Remember: It changes the original list and doesn’t give you a new one.

2.list.insert(index, elem):

• Puts an element at a specific spot in the list.
• Pushes other elements to make room for the new one.

3. list.extend(list2):

• Adds all elements from another list (list2) to the end of the original list.
• You can also use + or += for a similar result.

4. list.index(elem):

• Finds where a particular element is in the list.
• Be careful: It might cause an error if the element isn’t there. Use in to check first.

5.list.remove(elem):

• Locates and deletes the first occurrence of a specific element in the list.
• An error pops up if the element isn’t found.

6. list.sort():

• Put the list in order from smallest to largest.
• But usually, people prefer to use sorted().

7. list.reverse():

• Turns the list around, flipping the order of elements.
• It changes the original list; no new list is made.

8. list.pop(index):

• Takes out and gives you the element at a certain position.
• If you don’t say where it takes out and gives you the last one.
• Think of it as the opposite of append().

Thus, we can analyze the methods on the list object. Whereas, the lens () is referred to as a function that will consider the list as an argument.

Example:

def print_list(my_list):
    """
    Display the elements of a list.
    """
    print("List elements:")
    for item in my_list:
        print(item)

# Define an empty list
my_list = []

# Use the append() method to add elements to the list
my_list.append("apple")
my_list.append("banana")
my_list.append("orange")

# Display the original list
print("Original List:")
print_list(my_list)

# Use the insert() method to add an element at a specific index
my_list.insert(1, "grape")

# Display the list after insertion
print("\nList after insertion:")
print_list(my_list)

# Use the extend() method to add multiple elements to the list
more_fruits = ["kiwi", "melon"]
my_list.extend(more_fruits)

# Display the list after extension
print("\nList after extension:")
print_list(my_list)

# Use the remove() method to remove a specific element
my_list.remove("banana")

# Display the list after removal
print("\nList after removal:")
print_list(my_list)

# Use the pop() method to remove and return an element at a specific index
popped_item = my_list.pop(2)

# Display the list after popping an element
print(f"\nList after popping {popped_item}:")
print_list(my_list)

Note: The above methods cannot return the modified list but will modify the original list.

Output:

Original List:
List elements:
apple
banana
orange

List after insertion:
List elements:
apple
grape
banana
orange

List after extension:
List elements:
apple
grape
banana
orange
kiwi
melon

List after removal:
List elements:
apple
grape
orange
kiwi
melon

List after popping banana:
List elements:
apple
grape
kiwi
melon

• ‘Print list’ is a method that will take the list ( “my list”) as the parameter and provide each in the list as the output.

• An empty list my_list is defined.
• The append() method is used to add elements to the list.
• The print_list() method is called twice to display the original and modified lists.

What is List Build-Up

In List build-up, we can analyze that the pattern is to begin the list as an empty list, and use append() or extend() afterward to add the elements. Let us look into the code below:

list = []          ## Start as the empty list
  list.append('a')   ## Use append() to add elements
  list.append('b')

What is List Slice?

In List Slice, the slice will operate on the list and will work similarly to the strings. It will function to alter the sub-parts of the list.

  list = ['a', 'b', 'c', 'd']
  print(list[1:-1])   ## ['b', 'c']
  list[0:2] = 'z'    ## replace ['a', 'b'] with ['z']
  print(list)         ## ['z', 'c', 'd']

Conclusion

In conclusion, understanding Python lists is like gaining a valuable skill for organizing and managing collections of data in programming. Imagine a list as a versatile container capable of holding various items, acting as a dynamic tool to keep track of information. Adding elements is simplified with the append() method, while the insert(index, item) method allows precise placement of items within the list. For adding multiple elements swiftly, the extend() method proves handy.

In essence, a Python list is a powerful and flexible tool, and as you delve deeper into programming, you’ll uncover even more functionalities that make lists an indispensable part of your coding toolkit.

Python List – FAQs

Hridhya Manoj

Hello, I’m Hridhya Manoj. I’m passionate about technology and its ever-evolving landscape. With a deep love for writing and a curious mind, I enjoy translating complex concepts into understandable, engaging content. Let’s explore the world of tech together

Table of Contents

Python string exercises are necessary for a beginner to understand the program and to have regular practice. Check out the article to know more about Python String Excercise.

What is the Python String?

In Python, you can make words or sentences by using either single quotes (‘) or double quotes (“). So, ‘hello’ and “hello” mean the same thing. It’s like choosing between two different types of containers for your words in Python.

What are the examples of Python Strings?

Let us look into the Python program provided below:

Example 1

Python Program to find the number of vowels in the given string.

def count_vowels(input_string):
    vowels = "aeiouAEIOU"
    count = 0

    for char in input_string:
        if char in vowels:
            count += 1

    return count

# Example usage:
input_string = "Hello, World!"
result = count_vowels(input_string)
print(f'The number of vowels in "{input_string}" is: {result}')

Output

The number of vowels in "Hello, World!" is: 3

Example 2:

Check this example to illustrate how the Python Program will convert the string with the binary digits to an integer.

def binary_to_decimal(binary_string):
    decimal_value = int(binary_string, 2)
    return decimal_value

# Example usage:
binary_string = "1101"
decimal_result = binary_to_decimal(binary_string)
print(f'The decimal equivalent of binary "{binary_string}" is: {decimal_result}')

Output

The decimal equivalent of binary "1101" is: 13

Example 3:

The example below has provided the Python Program to drop all digits from the string.

def remove_digits(input_string):
    result_string = ''.join(char for char in input_string if not char.isdigit())
    return result_string

# Example usage:
input_string = "Hello123World456"
result = remove_digits(input_string)
print(f'The string without digits: "{result}"')

Output

The string without digits: "HelloWorld"

Conclusion

To conclude, navigating through the Python String Exercise will equip you with valuable skills in handling text effortlessly. From understanding the basics of string manipulation to mastering various methods, you’ve laid a strong foundation for your coding journey.

Python String Exercise-FAQs

Hridhya Manoj

Hello, I’m Hridhya Manoj. I’m passionate about technology and its ever-evolving landscape. With a deep love for writing and a curious mind, I enjoy translating complex concepts into understandable, engaging content. Let’s explore the world of tech together

Table of Contents

Python String Methods

Python consists of built-in methods that will be used on the strings. They will manipulate the strings. However, the string method won’t change the original string instead it will return the new string along with the changed attributes. Let us look into this article to learn more about Python String Methods.

What is Python String?

Python string consists of the sequence of the Unicode characters that will be enclosed in the quotation marks. Hence, you can find Python string methods below.

What are the Python String Methods?

Python functions will change the case of the strings. Check out the Python String Methods provided below:

a. lower()-It will convert all the uppercase characters in a string to the lowercase.

b.upper(): This string method in Python will turn all the lowercase characters in a string into the uppercase.

c.title(): It will change the string to the title case.

d.swapcase(): It will swap the cases of all the characters in the string.

e.capitalize(): capitalize will convert the first character of the string to the uppercase.

List of Python String Methods

Let us look into the table below to learn more about the Python String Methods list.

What are the examples for changing the Cases of Python Strings?

Example

Let us look into the example provided below for changing the case of the Python string.

# Define a sample string
sample_string = "Hello, World!"

# 1. len(): Get the length of the string
length = len(sample_string)
print(f"Length of the string: {length}")

# 2. upper(): Convert the string to uppercase
uppercase_string = sample_string.upper()
print(f"Uppercase string: {uppercase_string}")

# 3. lower(): Convert the string to lowercase
lowercase_string = sample_string.lower()
print(f"Lowercase string: {lowercase_string}")

# 4. capitalize(): Capitalize the first character of the string
capitalized_string = sample_string.capitalize()
print(f"Capitalized string: {capitalized_string}")

# 5. count(): Count the occurrences of a substring in the string
substring_count = sample_string.count("l")
print(f"Count of 'l' in the string: {substring_count}")

# 6. replace(): Replace a substring with another substring
replaced_string = sample_string.replace("Hello", "Hi")
print(f"String after replacement: {replaced_string}")

# 7. split(): Split the string into a list of substrings based on a delimiter
split_string = sample_string.split(",")
print(f"String after split: {split_string}")

# 8. strip(): Remove leading and trailing whitespaces from the string
whitespace_string = "    Hello, World!    "
stripped_string = whitespace_string.strip()
print(f"String after stripping whitespaces: {stripped_string}")

Output

Length of the string: 13
Uppercase string: HELLO, WORLD!
Lowercase string: hello, world!
Capitalized string: Hello, world!
Count of 'l' in the string: 3
String after replacement: Hi, World!
String after split: ['Hello', ' World!']
String after stripping whitespaces: Hello, World!

Conclusion

To conclude, a Python string is a sequence of characters enclosed by quotation marks. This article has also listed the various Python string methods and will help the students to improve their knowledge and skills in Python String Methods.

Python String Method- FAQs

Hridhya Manoj

Hello, I’m Hridhya Manoj. I’m passionate about technology and its ever-evolving landscape. With a deep love for writing and a curious mind, I enjoy translating complex concepts into understandable, engaging content. Let’s explore the world of tech together

Table of Contents

Python Escape Characters

An escape sequence is considered as a sequence of characters that is used inside the character or string. It is further converted into a character or series of characters. Read this article to learn more about Python Escape Character.

What is an Escape Character in Python?

A sequence is a set of two or more characters. Whereas, in Escape, the sequence will begin with the backlash(//) and other characters in the set follow that backlash.

However, an escape sequence is referred to as the sequence of characters that are used inside the character or string. It won’t represent itself whereas it will be turned into another character. Hence, the escape sequence will be created with two things: first is a backlash (\\) and the second refers to the set of one or more characters with the backlash(\\).

What is the List of Escape Sequences in Python?

Escape characters will be divided into non-printable characters when the backlash precedes them.

The list of Escape sequences in Python is given below:

What are the examples used to illustrate Escape single quotes in Python?

Using the single quote inside the string directly, thus the string will be closed inside the pair of single quotes. Hence, the interpreter will get confused and will produce an error output.

original_string = "This is a string with a single quote: 'Hello World'"
escaped_string = original_string.replace("'", "\\'")

print("Original String:", original_string)
print("Escaped String:", escaped_string)

In the example above, the replace method is used to replace each occurrence of a single quote (‘) with the escaped sequence (‘\\’).

Output

Original String: This is a string with a single quote: 'Hello World'
Escaped String: This is a string with a single quote: \'Hello World\'

What is an n Escape Sequence in Python?

”\n” tells the interpreter to print some characters in the new line separately. Check out the example given below:

def generate_sequence(n):
    sequence = [i for i in range(1, n + 1)]
    return sequence

# Replace '10' with your desired value of n
n = 10
result_sequence = generate_sequence(n)

print(f"The sequence up to {n} is: {result_sequence}")

Output

The sequence up to 10 is: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]

What is the Backlash Escape Sequence in Python?

The character that consists of the backlash (\) method that is followed by the letter or by the combination of digits are known as escape sequences.

Check out this example given below:

escaped_string = "This is a backslash: \\"
print(escaped_string)

Output

This is a backslash: \

What is the Python escape sequence for Space?

This Python escape sequence for space will allow us to add tab space between the words. Hence, this escape sequence will provide the tab space between the words of characters using the ”\t”.

Example

# Using \s escape sequence
escaped_string = "Hello\sWorld"
print(escaped_string)

# Using space character directly
space_string = "Hello World"
print(space_string)

Output

Hello World
Hello World

What is the Backspace Escape Sequence in Python?

The escape sequence will help to remove the space between the words. Check out the example given below

# Using \b escape sequence
escaped_string = "Hello\bWorld"
print(escaped_string)

# Without escape sequence
normal_string = "Hello\bWorld"
print(normal_string)

Output

HelloWorld
HelloWorld

What is the Python escape sequence for Hexa value?

We will use ”\xhh”, where the hh is referred to as the unique Hexa value of the alphabet

Example

# Using \xhh escape sequence
hex_value = "\x48\x65\x6C\x6C\x6F"
print("String with hex values:", hex_value)

# Converting hex values to characters
decoded_string = bytes.fromhex(hex_value[2:]).decode('utf-8')
print("Decoded String:", decoded_string)

Output

String with hex values: Hello
Decoded String: Hello

What is the Python escape sequence for Octal value?

In Python escape sequence for an octal value, they use ”\ooo” and the ooo is the unique octal value of the alphabet.

Example

# Using \ooo escape sequence
octal_value = "\110\145\154\154\157"
print("String with octal values:", octal_value)

# Converting octal values to characters
decoded_string = bytes.fromhex(octal_value[1:]).decode('utf-8')
print("Decoded String:", decoded_string)

Output

String with octal values: Hello
Decoded String: Hello

How to remove the Python escape sequence?

Python escape sequence will be removed from the left to right of the argument string. Hence, it will use the string. strip () function.

def remove_escape_sequences(input_string):
    # Encode the string to bytes and then decode it
    decoded_string = input_string.encode('utf-8').decode('unicode_escape')
    return decoded_string

# Example usage
original_string = "This is a string with escape sequences: \\n\\t\\'"
removed_escape_string = remove_escape_sequences(original_string)

print("Original String:", original_string)
print("String with Escape Sequences Removed:", removed_escape_string)

Output

Original String: This is a string with escape sequences: \n\t\'
String with Escape Sequences Removed: This is a string with escape sequences: \n	'

Conclusion

Escape characters help manage the formatting and representation of special characters within strings, enabling more flexible and readable code. This article will allow the students to improve their knowledge and skills of the escape characters. It has also provided a list of the escape sequences in Python.

Python Escape Characters- FAQs

Hridhya Manoj

Hello, I’m Hridhya Manoj. I’m passionate about technology and its ever-evolving landscape. With a deep love for writing and a curious mind, I enjoy translating complex concepts into understandable, engaging content. Let’s explore the world of tech together

Table of Contents

Python Comments

Python Comments in lines are considered as the lines of code that will be neglected by the interpreter while the program is executed.

Therefore, comments will improve the readability of the code and could enable the programmers to understand the code. This article has listed the Python Comments and their types.

What are the Types of Comments in Python?

The three types of comments in Python are:

a. Single-line Comments

b. Multiline Comments

c. String Literals

d. Docstring Comments

What are the Examples for Comments in Python

The example below will tell us that the Python comments are neglected by the Python Interpreter during the program execution.

# sample comment 
name = "Skillvertex"
print(name) 

Output

Skillvertex

Why are Comments used in Python?

Comments play a vital role in programming, languages and every language has several ways of using comments.

Several uses of comments in Python are the following:

a. Improve the code readability

b. Explains code to others

c. Helps to analyze the code if known for some time

d. Note down the steps and the requirements for the function

e. Sharing the code with fellow developers

f. Collaboration with multiple people

What are the Types of Comments in Python

The different types of comments and their relevance are provided below:

1. Single -Line Comments

Python single-line comments will begin with the hashtag symbol and no white space is required. # will be needed until the end of the line. However, if the comment has gone beyond one line, it is necessary to put a hashtag on the next line and this will be carried on to the Python Comment.

Hence, python single-line comments will be very beneficial for providing short explanations for variables, functions, declarations, and expressions. Refer to the code snippet below to understand the single-line comment.

Example

# Print “Skillvertex !” to console 
print("Skillvertex") 

Output

Skillvertex

2. Multi-Line Mentions

Python won’t give the option for the multiline comments. So, there are several ways to write multiline comments.

a) Multiline comments using multiple hashtags (#)

It is possible to use the multiple hashtag # for writing multiline comments in Python. Each line will be denoted as a single-line comments

# Python program to demonstrate 
# multiline comments 
print("Multiline comments")

Output

Multiline comments

3. String Literals

Python will neglect the string literals and won’t be assigned to a variable. Thus, it is possible to use the string literals as Python Comments.

a. Single-line comments with the string literals

While executing the code, there won’t be any output, and use the strings with the triple quotes (”””) as the multiline comments

'This will be ignored by Python'

b. Multiline Comments using the string literals

""" Python program to demonstrate 
 multiline comments"""
print("Multiline comments")

Output

Multiline comments

4. Docstring

Python Docstring is referred to as the string literals along with the triple quotes and will be shown right after the function. Hence, it functions to associate documentation and will be written with the help of Python modules, classes, and methods.

Hence, it will be added below the functions, modules, or classes to describe what they do. The docstring will be created and then will be accessible through the  __doc__ attribute.

Example

def multiply(a, b): 
    """Multiplies the value of a and b"""
    return a*b 
  
  
# Print the docstring of multiply function 
print(multiply.__doc__) 

Output

Multiplies the value of a and b

Conclusion

In conclusion, comments in Python are like helpful notes you write in your code to explain things to yourself and others. They don’t affect how the program runs, but they make your code easier to understand.

Python Comments- FAQs

Hridhya Manoj

Hello, I’m Hridhya Manoj. I’m passionate about technology and its ever-evolving landscape. With a deep love for writing and a curious mind, I enjoy translating complex concepts into understandable, engaging content. Let’s explore the world of tech together

Table of Contents

The arithmetic operator will take precedence over the logical operator. Initially, python will check the arithmetic operators. Relational operators will be checked next. At the end, logical operators will be evaluated.

Therefore, if multiple operators are present in an expression, then the higher precedence will be checked first. However, the associativity will be given more importance while considering the order of evaluation in the operator. Let us look into this article to learn more about the precedence and Associativity of operators in Python.

What is Operator Precedence in Python?

In Python, an expression is of variables, operators, and values. The Python interpreter will come across an expression that has various operations and that will be evaluated with the ordered hierarchy. This process is defined as operator precedence.

The table below has provided all the operators from the highest precedence to the lowest precedence.

Precedence of Python Operators

It is commonly used in the expression that has more than one operator with different precedence for identifying which operator will be required to do first.

Example

10 + 20 * 30

output

10 + 20 * 30 is calculated as 10 + (20 * 30)
and not as (10 + 20) * 30

Python code for the above example

# Precedence of ‘+’ & ‘*’

print(expr)

Output

610

Precedence of logical operators in Python

The if block will be run in the code provided below even though the age is 0. The precedence of logical “and” will be greater than the logical “or“.

# Precedence of ‘or’ & ‘and’

name =”Alex”

age =0

ifname ==”Alex”orname ==”John”andage >=2:

    print(“Hello! Welcome.”)

else:

    print(“Good Bye!!”)

Output

Hello! Welcome.

Another way to execute the ‘else‘ block is the use of parenthesis (). It will be considered as their precedence and the highest among all the operators.

# Precedence of 'or' & 'and'
name = "John"
age = 0
 
if (name == " John" or name == " Albert") and age >= 2:
    print("Hello! Welcome.")
else:
    print("Good Bye!!")

Output

Good Bye!!

Associativity of the Python Operators

The expression has two or more operators with the same precedence, and then the operator associativity will determine it as either to be left or reft or from right to left.

Example

‘*’ and ‘ /’ consist of the same precedence and the associativity will be from Left to Right in the code below.

# Left-associative operators
a = 10 + 5 - 2  # Addition and subtraction are left-associative
print(a)  # Output: 13

b = 2 * 3 / 2  # Multiplication and division are left-associative
print(b)  # Output: 3.0

# Right-associative operators (only one example in Python, exponentiation)
c = 2 ** 3 ** 2  # Exponentiation is right-associative
print(c) 

Output

13
3.0
512

Operators’ Precedence and Associativity in Python

In Python, Operators’ precedence and Associativity are considered the two important characteristics of operators that will be used to check the order of subexpression in the absence of brackets.

Example

100 + 200 / 10 - 3 * 10

100 + 200 / 10 - 3 * 10 is calculated as 100 + (200 / 10) - (3 * 10)
and not as (100 + 200) / (10 - 3) * 10

Python code for the example above

expression = 100 + 200 / 10 - 3 * 10
print(expression)

Output

90.0

What are non-associative operators?

In Python, most of the operators have associativity and this indicates that it can be used to evaluate from left to right or right to left and have the same precedence.

Therefore, few operators are considered as non- associative and this means that they cannot be chained together.

a = 5
b = 10
c = 15
 
a = b = (a < b) += (b < c)

Output

a = b= (a < b) += (b < c)
                   ^^
SyntaxError: invalid syntax

Conclusion

To conclude, this article has listed about the operator precedence and associativity in Python. Moreover, several examples are also provided for a better understanding of the operator’s precedence. This can allow the students to improve their knowledge and skills regarding the topic.

Precedence and Associativity of Operators in Python- FAQs

Hridhya Manoj

Hello, I’m Hridhya Manoj. I’m passionate about technology and its ever-evolving landscape. With a deep love for writing and a curious mind, I enjoy translating complex concepts into understandable, engaging content. Let’s explore the world of tech together

Table of Contents

The Python Identity operator will compare the objects by checking if the object belongs to the same memory location. Read this article to learn more about Python Identity Operator.

What is Python Identity Operator

Python operator consists of two operators such as ‘is‘and ‘is not‘. Both the values will be returned with the Boolean values. The in-operators will check if the value comes true only if the operand object shares the same memory location.

Furthermore, the memory location of the object will be achieved with the help of the ”id()” function. Whereas, if both the variables id() are the same, then the in operator will return with the True.

# Identity Operator - 'is'
x = [1, 2, 3]
y = [1, 2, 3]
z = x

# 'is' operator checks if both variables refer to the same object in memory
print(x is y)  # False, because x and y refer to different objects
print(x is z)  # True, because x and z refer to the same object

# Identity Operator - 'is not'
print(x is not y)  # True, because x and y do not refer to the same object
print(x is not z)  # False, because x and z refer to the same object

Output

False
True
True
False

However, list and tuple will do operations very differently. The example given below contains two lists such as ”a” and ”b” with the same items and the id() varies.

a=[1,2,3]
b=[1,2,3]
print ("id(a), id(b):", id(a), id(b))
print ("a is b:", a is b)
print ("b is not a:", b is not a)

Output

id(a), id(b): 1552612704640 1552567805568
a is b: False
b is not a: True

The list or tuple has memory locations of individual items only and not the items themselves. Thus, ”a ” consists of an address of 10,20, or 30 integer objects that are located in a particular location and will be different from the of ”b”.

Output

140734682034984 140734682035016 140734682035048
140734682034984 140734682035016 140734682035048

Here, the ‘is’ operator will return with a false value even if it contains the same numbers. This happens due to the two different locations of a and b.

Conclusion

To conclude, this article will improve our knowledge of the Python Identity Operator. It has also provided examples of the ”is” and ”is not” operators.

Python Identity Operator- FAQs

Hridhya Manoj

Hello, I’m Hridhya Manoj. I’m passionate about technology and its ever-evolving landscape. With a deep love for writing and a curious mind, I enjoy translating complex concepts into understandable, engaging content. Let’s explore the world of tech together

Table of Contents

The membership operators in Python will allow us to know if an item is available in the given container-type object. Let us look at this article to learn more about Python Membership Operator

What is a Python Membership Operator?

Python will provide two membership operators for checking the membership value. It will check for membership in a string, list, or tuples sequence.

What is In operator?

The in-operator will monitor whether a character or substring will be present in the sequence. So, this operator will be considered true only if it can find the specified element, or else it will be false.

Example

'S' in 'Skillvertex'   # Checking 'S' in String
True
's' in 'Skillvertex'   #Checking 's' in string since Python is case-sensitive,returns False
False
'Skill' in ['Skill','Vertex']   #Checking 'Skill' in list of strings
True
10 in [10000,1000,100,10]        #Checking 10 in list of integers
True
dict1={1:'Skill,2:'For',3:'Skill'}     # Checking 3 in keys of dictionary
3 in dict1
True

Python Program to find the common member is provided below

# Membership operator example
fruits = ['apple', 'banana', 'orange', 'grape']

# Using 'in' operator
search_fruit = 'banana'
if search_fruit in fruits:
    print(f"{search_fruit} is present in the list.")
else:
    print(f"{search_fruit} is not present in the list.")

# Using 'not in' operator
search_fruit = 'kiwi'
if search_fruit not in fruits:
    print(f"{search_fruit} is not present in the list.")
else:
    print(f"{search_fruit} is present in the list.")

Output

banana is present in the list.
kiwi is not present in the list.

Now, the Python Program below will use the same example without an operator.

# Membership operator example without using operators
fruits = ['apple', 'banana', 'orange', 'grape']

# Without using 'in' operator
search_fruit = 'banana'
found = False
for fruit in fruits:
    if fruit == search_fruit:
        found = True
        break
if found:
    print(f"{search_fruit} is present in the list.")
else:
    print(f"{search_fruit} is not present in the list.")

# Without using 'not in' operator
search_fruit = 'kiwi'
not_found = True
for fruit in fruits:
    if fruit == search_fruit:
    not_found = False
        break
if not_found:
    print(f"{search_fruit} is not present in the list.")
else:
    print(f"{search_fruit} is present in the list.")

Output

banana is present in the list.
kiwi is not present in the list.

The execution speed of the in-operator will mainly depend on the target object type. The average time complexity of the in operator for the list is 0(n). Hence, it will get slow due to the number of elements increasing.

Moreover, the average time complexity of the in-operator for sets is 0(1). Hence, it won’t rely on the number of elements.

Whereas in dictionaries, the keys in the dictionary are unique values such as set. It is possible to repeat the value as similar to the list. So, the ‘in’ for values () will be executed as similar to the lists.

What is NOT in the operator?

This NOT in operator can run the program to get the true value if it can’t find the variable in the specified sequence or else, it will be declared as false.

Take a look at the Python Program to illustrate the not-in operator.

# Membership operator 'not in' example with output
fruits = ['apple', 'banana', 'orange', 'grape']

# Using 'not in' operator
search_fruit = 'kiwi'
if search_fruit not in fruits:
    print(f"{search_fruit} is not present in the list.")
else:
    print(f"{search_fruit} is present in the list.")

Output

kiwi is not present in the list.

This example mentions that the not-in operator will be used to evaluate the value such as kiwi is not present in the list of fruits.

What is an Identity Operator?

The identity operator functions to compare the objects as both the objects are the same data type and will share the same memory location.

What ‘is’ operator

This ‘is’ operator will be used to check if the value can come true, only if the variable on either side of the operator points to the same object or else it will be false.

# Using 'is' operator for membership-like testing
fruits = ['apple', 'banana', 'orange', 'grape']

# Object to test for membership
search_fruit = 'banana'

# Check using 'is' operator
is_member = any(fruit is search_fruit for fruit in fruits)

if is_member:
    print(f"{search_fruit} is in the list.")
else:
    print(f"{search_fruit} is not in the list.")

Output

banana is in the list.

What is ‘Is not’ operator

This ‘Is not’ operator will check if the values come true, only if both variables are not in the same object.

# Using 'is not' operator for membership-like testing
fruits = ['apple', 'banana', 'orange', 'grape']

# Object to test for non-membership
search_fruit = 'kiwi'

# Check using 'is not' operator
is_not_member = all(fruit is not search_fruit for fruit in fruits)

if is_not_member:
    print(f"{search_fruit} is not in the list.")
else:
    print(f"{search_fruit} is in the list.")

Output

kiwi is not in the list.

Conclusion

To conclude, in Python membership operators (in and not in) will allow us to check if something is part of a group, such as looking if a specific word is in a list.

If it’s on the list, it will give us True, otherwise False. On the other hand, not in does the opposite; it gives us True if the thing is not in the group, and False. This article has also discussed the different operators of the membership operator. Those operators include ‘In’ operator, ‘not in’ operator, and several other identity operators.

Python Membership Operator- FAQs

Hridhya Manoj

Hello, I’m Hridhya Manoj. I’m passionate about technology and its ever-evolving landscape. With a deep love for writing and a curious mind, I enjoy translating complex concepts into understandable, engaging content. Let’s explore the world of tech together