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What is the Maximum Possible Length of an Identifier in Python: Ever noticed how everything in Python has a name – like variables and functions? But have you wondered how long these names can be? That’s the puzzle we’re diving into!

Imagine we’re on a journey through Python’s rules to find out the maximum length allowed for these names. Get ready to uncover the secrets behind these naming limits. Together, we’ll discover how Python keeps its naming game in check and understand why it matters. So, let’s embark on this adventure and unravel the mystery of identifier lengths in Python! Read this article to know more on What is the Maximum Possible Length of an Identifier in Python?

Maximum Possible Length Of An Identifier In Python?

In Python, an identifier is limited to a maximum length of 79 characters. Python stands tall among the coding languages, boasting immense popularity since its creation by Guido van Rossum in 1991. Whether for web development, software creation, mathematical endeavors, or system scripting, Python’s prowess is unmatched.

The language’s flexibility extends to its underlying structure. Unlike some languages that rely heavily on C for their core, Python’s go-to implementation, CPython, is itself crafted in C. This uniqueness extends to its approachability – from seasoned coders to newcomers well-versed in C++, Java, or even Python itself, the language welcomes all.

FAQ- What is the Maximum Possible Length of an Identifier in Python?

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

How to Find Length of String in Java, Python, C++, Javascript, SQL, Shell script, Mysql, Oracle, and Perl

How To Find Length Of String in Java, Python, C++, Javascript, SQL, Shell script, Mysql, Oracle, and Perl: This article will offer you advanced knowledge of various computer languages. Strings are groups of characters that will represent a single word or an entire phase. It will summarise how to find the length of a string in Java, how to find the length of string in Python, how to find the length of a string in C++, how to find the length of the string in Javascript, how to find the length of the string in SQL, how to find length of string in Shellscript, how to find the length of the string in MySQL, how to find length of string in oracle, how to find the length of the string in Perl.

How to Find the Length of the String in Java?

The length of a string is calculated with the total number of characters it contains. Hence, to calculate the length of a string in Java, the in-built length method Java script class can be initiated. Moreover, in Java, strings are objects produced using the string class, and the length method is referred to as the public member method of the class. Therefore, any variable of type string can access the type string method through the.(dot )operation

In Java, you can find the length of a string using the length() method. Here’s how you can do it:

public class Main {
    public static void main(String[] args) {
        String myString = "Hello, World!";
        int length = myString.length(); // This gives the length of the string
        System.out.println("Length of the string: " + length);
    }
}

The length() method is a built-in function of the String class in Java. It returns the number of characters in the string, including spaces, punctuation, and any special characters.

In the example above, the output will be:

Length of the string: 13

So, the length of the string “Hello, World!” is 13 characters.

How to Find the Length of the String in Python?

Strings are simple to use in Python as they don’t have any explicit declaration ad can be defined with or without a specifier. However, python has a variety of in-built functions and methods for manipulating as well as accessing strings. Hence, Everything in Python is an object, a string is an object of string class which has several methods.

Example

In the program given below, we are taking a string as an input, and by using the len() function we are finding out the length of that string.

s1 ="Tutorialspoint"

length =len(s1)print("The Length of the string",s1,"is",length)

Output

The output of the above program is,

('The Length of the string', 'Tutorialspoint', 'is', 14)

How to Find the Length of the String in C++?

There are five different ways to calculate string length in C++. In C++, we can include traditional character array strings and C++ has String Class. We can calculate string length through different methods.

For C++ strings, using the length() or size() member functions is more convenient and safer, as they handle various complexities such as memory management and null termination automatically. For C-style strings, using strlen() or loop-based approaches is common, as they are more suited for character arrays with null-terminated strings.

Example

#include <iostream>
#include <string>

int main() {
    std::string myString = "Hello, World!";
    int length1 = myString.length(); // Using length() function
    int length2 = myString.size();   // Using size() function

    std::cout << "Length of the string using length(): " << length1 << std::endl;
    std::cout << "Length of the string using size(): " << length2 << std::endl;

    return 0;
}

Output

csharpCopy codeLength of the string using length(): 13
Length of the string using size(): 13

Both length() and size() functions give you the same result, which is the number of characters in the string, including spaces, punctuation, and any special characters. You can use either of them based on your preference.

How to Find the Length of the String In Javascript?

In JavaScript, you can find the length of a string using the length property of the string object, which returns the number of characters in the string. For example,

javascriptCopy codeconst myString = "Hello, World!";
const length = myString.length;

console.log("Length of the string: " + length);

Output

cCopy codeLength of the string: 13

How to Find Length of String in SQL?

Using LEN() function (for Microsoft SQL Server): If you are using Microsoft SQL Server, you can use the LEN() function instead of LENGTH().

SELECT LEN('Hello, World!') AS length;

Output:

markdownCopy codelength
-------
13

Both LENGTH() and LEN() functions return the number of characters in the specified string. The result represents the length of the string, including spaces, punctuation, and any special characters.

How to Find the Length of String in Shellscript?

In shell scripts, the length of the string can be calculated by the built-in shell parameter expansion feature or by using the expr command. Here are two common methods to find the length of a string in a shell script:

1. Using Shell Parameter Expansion: You can use the ${#variable} syntax to get the length of a string stored in a variable.

bashCopy code#!/bin/bash

myString="Hello, World!"
length=${#myString}

echo "Length of the string: $length"

Output

cCopy codeLength of the string: 13

2. Using expr the command: The expr a command is used for evaluating expressions in shell scripts. You can use it to find the length of a string as follows:

bashCopy code#!/bin/bash

myString="Hello, World!"
length=$(expr length "$myString")

echo "Length of the string: $length"

Output

cCopy codeLength of the string: 13

Both methods will give you the length of the string, including spaces and special characters. You can apply any approach based on your preference and the complexity of the task you are performing in your shell script

How to Find the Length of String in Mysql?

You can use the LENGTH() function in various scenarios, such as in SELECT queries, WHERE clauses, or in combination with other SQL functions to perform different operations on strings.

SELECT LENGTH('Hello, World!') AS length;

Output

markdownCopy codelength
-------
13

In the above example, the LENGTH() the function is applied to the string 'Hello, World!', and it returns 13, which is the length of the string.

How to Find the Length of String in Oracle?

To calculate the length of the string in Oracle, Choose LENGTH() to count bytes and CHAR_LENGTH() to count characters based on your needs.

Using LENGTH() function:

sqlCopy codeSELECT LENGTH('Hello, World!') AS length FROM DUAL;

Using CHAR_LENGTH() function:

sqlCopy codeSELECT CHAR_LENGTH('Hello, World!') AS length FROM DUAL;

Both queries will give the output:

markdownCopy codeLENGTH
------
13

How to Find the Length of String in Perl?

The Perl code to find the length of a string:

perlCopy codemy $length = length("Hello, world!");
print "Length: $length\n";

When you run this shorter Perl script, it will produce the same output:

makefileCopy codeLength: 13

This version removes the intermediate variable and directly prints the length of the string using the length() function.

FAQ – How To Find Length Of String in Java, Python, C++, Javascript, SQL, Shell Script, Mysql, Oracle, and Perl

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

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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 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

Python Bitwise operators are mostly used with integer-type objects. Hence, Bitwise operation will be executed through bitwise calculations on integers. Read this article to learn more about the Python Bitwise operator.

What is Python Bitwise Operator

Python Bitwise operators will work with integers. Whereas, they will consider the object as a string instead of treating it as a whole. Thus, different operations will be done on each bit in a string.

Moreover, Python has six bitwise operators such as &, |, ^, ~, << and >>. Each of these operators is mostly binary. This means they can work on the two operands. Each operand is referred to as a binary digit(bit) ie, 1 and 0.

Let us take a look at the table of the different operators of Bitwise

What is Bitwise And Operator?

The Bitwise AND operator works similarly to the logical AND operator. This will provide the result as true, if both the operands will come as 1. The combinations are given below

0 & 0 is 0
1 & 0 is 0
0 & 1 is 0
1 & 1 is 1

Example

a = 10 = 1010 (Binary)
b = 4 =  0100 (Binary)

a & b = 1010
         &
        0100
      = 0000
      = 0 (Decimal)

What is Bitwise OR Operator?

This symbol “|”  is referred to as Pipe and is also known as Bitwise OR Operator. Only if the bit operand is 1, then it will result in 1, or else it is 0

0 | 0 is 0
0 | 1 is 1
1 | 0 is 1
1 | 1 is 1

Example

a = 10 = 1010 (Binary)
b = 4 =  0100 (Binary)

a | b = 1010
         |
        0100
      = 1110
      = 14 (Decimal)

What is Bitwise NOT operator?

This bitwise operator is referred to as the binary equivalent of logical NOT operators. It will flip each bit, so, 1 will be replaced by 0 and 0 by 1. Hence, it will return the complement of the original number.

Moreover, python will use 2’s complement method. For example, positive integers can be achieved by reversing the bits. In contrast, negative numbers, -x will be written with the bit pattern for (x-1) along all the bits complemented ( switched from 1 to 0 or 0 to 1).

-1 is complement(1 - 1) = complement(0) = "11111111"
-10 is complement(10 - 1) = complement(9) = complement("00001001") = "11110110".

Example

a = 10 = 1010 (Binary)

In computers we usually represent numbers using 32 bits,
so binary representation of 10 is (....0000 1010)[32 bits]

~a is basically 1's complement of a 
i.e ~a should be ~10 = ~(....0000 1010) = (....1111 0101) = intermediate-result

Since bitwise negation inverts the sign bit,
we now have a negative number. And we represent a negative number
using 2's complement.

2's complement of intermediate-result is:
intermediate-res =  0101      //....1111 0101
      
                     1010      //....0000 1010 -(1's complement)

                         +1    
                 -----------
                   =  1011      //....0000 1011
                  -----------
                   =   -11 (Decimal)
                   
thus ~a = -11

What is Bitwise XOR Operator?

The full form of XOR is the exclusive OR. So, the result that is provided by the OR operator on two bits is 1, or else one of the bits is 1.

0 ^ 0 is 0
0 ^ 1 is 1
1 ^ 0 is 1
1 ^ 1 is 0

Example

a = 10 = 1010 (Binary)
b = 4 =  0100 (Binary)

a ^ b = 1010
         ^
        0100
      = 1110
      = 14 (Decimal)

Python Program on the bitwise operator will be given below

# Python program to show
# bitwise operators
 
a = 10
b = 4
 
# Print bitwise AND operation
print("a & b =", a & b)
 
# Print bitwise OR operation
print("a | b =", a | b)
 
# Print bitwise NOT operation
print("~a =", ~a)
 
# print bitwise XOR operation
print("a ^ b =", a ^ b)

Output

a & b = 0
a | b = 14
~a = -11
a ^ b = 14

What is a Shift Operator?

This Shift operator functions to shift the bits of a number left or right and then multiply or divide the number by two respectively. This operator is mainly used to multiply or divide a number by two.

Bitwise right shift

This operator is used to shift the bits of the number to the right and will fill 0 on the voids left as the result. Therefore, a similar effect can be achieved by dividing the number with some power of two.

Example

Example 1:
a = 10 = 0000 1010 (Binary)
a >> 1 = 0000 0101 = 5

Example 2:
a = -10 = 1111 0110 (Binary)
a >> 1 = 1111 1011 = -5 

Bitwise left shift

This operator will be used to shift the bits to the number to the left and that will fill 0 on voids right as the end result. Whereas, a similar effect can be achieved through multiplying the number with some power of two.

Example

Example 1:
a = 5 = 0000 0101 (Binary)
a << 1 = 0000 1010 = 10
a << 2 = 0001 0100 = 20 

Example 2:
b = -10 = 1111 0110 (Binary)
b << 1 = 1110 1100 = -20
b << 2 = 1101 1000 = -40 

Python program is illustrated below to show the shift operators.

# Python program to show
# shift operators
 
a = 10
b = -10
 
# print bitwise right shift operator
print("a >> 1 =", a >> 1)
print("b >> 1 =", b >> 1)
 
a = 5
b = -10
 
# print bitwise left shift operator
print("a << 1 =", a << 1)
print("b << 1 =", b << 1)

Output

a >> 1 = 5
b >> 1 = -5
a << 1 = 10
b << 1 = -20

What is Bitwise Operator Overloading?

Bitwise Operator Overloading is referred to as the extended meaning that is beyond the predefined operational meaning. For instance, operator
+ mostly functions to add the two integers and even join the two strings and combine the two lists.

Moreover, this can be gained a the + will be overloaded with the int class and str class. Operator Overloading consists of the same built-in operator or can work to demonstrate the different behavior of objects in the different classes.

An example to show the Bitwise Operator Overloading is given below

# Python program to demonstrate
# operator overloading
 
 
class Geek():
    def __init__(self, value):
        self.value = value
 
    def __and__(self, obj):
        print("And operator overloaded")
        if isinstance(obj, Geek):
            return self.value & obj.value
        else:
            raise ValueError("Must be a object of class  skillvertex")
 
    def __or__(self, obj):
        print("Or operator overloaded")
        if isinstance(obj, Geek):
            return self.value | obj.value
        else:
            raise ValueError("Must be a object of class  skillvertex")
 
    def __xor__(self, obj):
        print("Xor operator overloaded")
        if isinstance(obj, Geek):
            return self.value ^ obj.value
        else:
            raise ValueError("Must be a object of class Skilvertex")
 
    def __lshift__(self, obj):
        print("lshift operator overloaded")
        if isinstance(obj, Geek):
            return self.value << obj.value
        else:
            raise ValueError("Must be a object of class skillvertex")
 
    def __rshift__(self, obj):
        print("rshift operator overloaded")
        if isinstance(obj, Geek):
            return self.value >> obj.value
        else:
            raise ValueError("Must be a object of class  skill vertex")
 
    def __invert__(self):
        print("Invert operator overloaded")
        return ~self.value
 
 
# Driver's code
if __name__ == "__main__":
    a =  skillvertex(10)
    b =  skillvertex(12)
    print(a & b)
    print(a | b)
    print(a ^ b)
    print(a << b)
    print(a >> b)
    print(~a)

Output

And operator overloaded
8
Or operator overloaded
14
Xor operator overloaded
8
lshift operator overloaded
40960
rshift operator overloaded
8
Invert operator overloaded
-11

Conclusion

To conclude, this article will improve your knowledge of the different types of Python Bitwise operators. Those are Bitwise AND operator, Bitwise OR operator, Bitwise NOT operator, and several others are included.

Python Bitwise 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 logical operators are used to combine the conditional statements. Let us check out this to learn more about the Python logical operators in Python.

What is the Logical Operators in Python?

In Python, Logical operators will function on the conditional statements. They will work on Logical AND, Logical OR, and Logical NOT operations.

What is Truth Table for Logical Operators in Python?

What is the Logical AND operator in Python?

The Logical and AND operator will return True if both the operands are True otherwise, it will give the result as False.

Example

# Python program to demonstrate 
# logical and operator 
a = 10
b = 10
c = -10
if a > 0 and b > 0: 
    print("The numbers are greater than 0") 
if a > 0 and b > 0 and c > 0: 
    print("The numbers are greater than 0") 
else: 
    print("Atleast one number is not greater than 0")

Output

The numbers are greater than 0
Atleast one number is not greater than 0

Example 2

# Python program to demonstrate 
# logical and operator 
a = 10
b = 12
c = 0
if a and b and c: 
    print("All the numbers have boolean value as True") 
else: 
    print("Atleast one number has boolean value as False")

Output

Atleast one number has boolean value as False

What is the Logical OR operator in Python?

The logical OR operator will return a True value if the operands come true.

Example

# Python program to demonstrate 
# logical or operator 
a = 10
b = -10
c = 0
if a > 0 or b > 0: 
    print("Either of the number is greater than 0") 
else: 
    print("No number is greater than 0") 
if b > 0 or c > 0: 
    print("Either of the number is greater than 0") 
else: 
    print("No number is greater than 0")

Output

Either of the number is greater than 0
No number is greater than 0

What is the Logical NOT operator in Python?

The logical not operator will function with a single boolean value. Hence, if the boolean value will come True then it will return as False and Vice versa.

Example

# Python program to demonstrate 
# logical not operator 
a = 10
 
if not a: 
    print("Boolean value of a is True") 
if not (a%3 == 0 or a%5 == 0): 
    print("10 is not divisible by either 3 or 5") 
else: 
    print("10 is divisible by either 3 or 5")

Output

10 is divisible by either 3 or 5

What is Order of Precedence of Logical Operators?

Python will calculate the expression from left to right in multiple operators.

Example

# Python program to demonstrate 
# order of evaluation of logical 
# operators 
def order(x): 
    print("Method called for value:", x) 
    return True if x > 0 else False  
a = order 
b = order 
c = order 
if a(-1) or b(5) or c(10): 
    print("Atleast one of the number is positive")

Output

Method called for value: -1
Method called for value: 5
Atleast one of the number is positive

Conclusion

To conclude, these Python logical operators provide a straightforward way to make decisions in your code. “AND” ensures both conditions must be true for the overall expression to be true, while “or” requires at least one condition to be true.

On the other hand, “not” negates the truth value of a condition. Several examples are illustrated in this for more clarity on Logical And, Logical, Logical Not operators.

Python Logical Operators- 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 comparison operators will compare two values. == or equal to, != or not equal to, > or greater than, >= or greater than or equal to, < or less than, and <= or less than or equal to are the six Python comparison operators. Read this article to learn more about Python Comparison Operators.

What is a Python Comparison Operator

Comparison Operators in Python play an essential role in Python’s conditional statements (if, else, and elif) and looping statements (while loops). These comparison operators are also known as relational operators. Hence, the known operators will stands for < and > will be for greater operators.

Furthermore, python will use two operators by adding the = symbol with these two. The <= symbol will be less than or equal to the operator and these >= symbols will stand for greater than or equal to the operator.

It is known that Python has two operators that are ”==” and ” !=”. The <= symbol will stand for less than or equal to the operator, whereas the ”>=” is referred to as the greater than or equal to the operator.

Look at the table below to learn more about six comparison operators in Python.

Comparison operators are mostly binary and need two operands. An expression that has a comparison operator is known as a Boolean expression. This will either come as true or false.

a=5
b=7
print (a>b)
print (a<b)

Output

False
True

Both the operands can either be Python literals, variables or expressions. As Python has mixed arithmetic it is possible to have any number-type operands.

The code provided below will show the use of Python comparison operators with integer numbers

print ("Both operands are integer")
a=5
b=7
print ("a=",a, "b=",b, "a>b is", a>b)
print ("a=",a, "b=",b,"a<b is",a<b)
print ("a=",a, "b=",b,"a==b is",a==b)
print ("a=",a, "b=",b,"a!=b is",a!=b)

Output

Both operands are integer
a= 5 b= 7 a>b is False
a= 5 b= 7 a<b is True
a= 5 b= 7 a==b is False
a= 5 b= 7 a!=b is True

Comparison of Float number

This example will show the comparison of an integer and float operand.

print ("comparison of int and float")
a=10
b=10.0
print ("a=",a, "b=",b, "a>b is", a>b)
print ("a=",a, "b=",b,"a<b is",a<b)
print ("a=",a, "b=",b,"a==b is",a==b)
print ("a=",a, "b=",b,"a!=b is",a!=b)

Output

comparison of int and float
a= 10 b= 10.0 a>b is False
a= 10 b= 10.0 a<b is False
a= 10 b= 10.0 a==b is True
a= 10 b= 10.0 a!=b is False

What is the Comparison of Complex numbers?

A complex object is considered as the number data type in Python. It will work differently from others in behavior. Python won’t support < and> operators as it cannot support the equality ( ==) and inequality (!=) operators.

print ("comparison of complex numbers")
a=10+1j
b=10.-1j
print ("a=",a, "b=",b,"a==b is",a==b)
print ("a=",a, "b=",b,"a!=b is",a!=b)

Output

comparison of complex numbers
a= (10+1j) b= (10-1j) a==b is False
a= (10+1j) b= (10-1j) a!=b is True

Here, it is possible to get a type error that is less than or greater than the operators.

print ("comparison of complex numbers")
a=10+1j
b=10.-1j
print ("a=",a, "b=",b,"a<b is",a<b)
print ("a=",a, "b=",b,"a>b is",a>b)

Output

comparison of complex numbers
Traceback (most recent call last):
  File "C:\Users\mlath\examples\example.py", line 5, in <module>
    print ("a=",a, "b=",b,"a<b is",a<b)
                                      ^^^
TypeError: '<' not supported between instances of 'complex' and
'complex

Comparison of Booleans

Boolean objects are referred to as real integers such as true is 1 and false is 0. However, python will consider any non-zero numbers as true=. Hence, it is allowed to compare the boolean objects. False< True is True.

print ("comparison of Booleans")
a=True
b=False
print ("a=",a, "b=",b,"a<b is",a<b)
print ("a=",a, "b=",b,"a>b is",a>b)
print ("a=",a, "b=",b,"a==b is",a==b)
print ("a=",a, "b=",b,"a!=b is",a!=b)

Output

comparison of Booleans
a= True b= False a<b is False
a= True b= False a>b is True
a= True b= False a==b is False
a= True b= False a!=b is True

What is the Comparison of Sequence Types?

The comparison of one similar sequence object will be operated in Python. A string object can be compared with another string only. A list can’t be compared with a tuple even if it holds the same items.

print ("comparison of different sequence types")
a=(1,2,3)
b=[1,2,3]
print ("a=",a, "b=",b,"a<b is",a<b)

Output

comparison of different sequence types
Traceback (most recent call last):
  File "C:\Users\mlath\examples\example.py", line 5, in <module>
    print ("a=",a, "b=",b,"a<b is",a<b)
                                       ^^^
TypeError: '<' not supported between instances of 'tuple' and 'list'

From the example provided above, it is understood that the sequence objects will be compared with the help of a lexicographical ordering mechanism. This comparison will begin with the item at the 0th index. Hence, if they come as equal, this comparison will move to the next index until they get the items at the certain index unequal or the sequence is exhausted.

However, if one sequence is considered as the initial sub-sequence of the other, then the shorter sequence will be the lesser one.

The operators will be considered greater and that will depend on the difference in the values of items when they are not equal. An example of this is BAT’>’BAR’ is True, if the T comes after R in Unicode order.

All the items in the two sequences will be compared for equity. Thus, the sequence will be equal while comparison.

print ("comparison of strings")
a='BAT'
b='BALL'
print ("a=",a, "b=",b,"a<b is",a<b)
print ("a=",a, "b=",b,"a>b is",a>b)
print ("a=",a, "b=",b,"a==b is",a==b)
print ("a=",a, "b=",b,"a!=b is",a!=b)

Output

comparison of strings
a= BAT b= BALL a<b is False
a= BAT b= BALL a>b is True
a= BAT b= BALL a==b is False
a= BAT b= BALL a!=b is True

Another example given below illustrates the two tuple objects.

print ("comparison of tuples")
a=(1,2,4)
b=(1,2,3)
print ("a=",a, "b=",b,"a<b is",a<b)
print ("a=",a, "b=",b,"a>b is",a>b)
print ("a=",a, "b=",b,"a==b is",a==b)
print ("a=",a, "b=",b,"a!=b is",a!=b)

Output

a= (1, 2, 4) b= (1, 2, 3) a<b is False
a= (1, 2, 4) b= (1, 2, 3) a>b is True
a= (1, 2, 4) b= (1, 2, 3) a==b is False
a= (1, 2, 4) b= (1, 2, 3) a!=b is True

What is the Comparison of Dictionary objects?

While comparing the dictionary objects, “< ” and “>” operators are used in the Python dictionary and they are not defined. Whereas, in operands, this type error “<” cannot be supported in between the instances of ‘dict’ and ‘dict’ will be reported.

Whereas. the equality comparison will monitor if the length of both the dict items is the same. The length of the dictionary will be considered as the number of key-value pairs in it.

However, python dictionaries will be compared with the length. The dictionaries that have fewer elements won’t be referred to as dictionaries. Since dictionaries require more elements.

print ("comparison of dictionary objects")
a={1:1,2:2}
b={2:2, 1:1, 3:3}
print ("a=",a, "b=",b,"a==b is",a==b)
print ("a=",a, "b=",b,"a!=b is",a!=b)

Output

comparison of dictionary objects
a= {1: 1, 2: 2} b= {2: 2, 1: 1, 3: 3} a==b is False
a= {1: 1, 2: 2} b= {2: 2, 1: 1, 3: 3} a!=b is True

Conclusion

Comparison Operators in Python is a relevant topic for beginners to learn. Learning these operators will be useful during coding and writing Python.

Python Comparison Operators- 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