Sign In
Sign In

Loops in Python 3

Loops in Python 3
Hostman Team
Technical writer
Python
06.12.2023
Reading time: 8 min

You're probably already familiar with the if statement and the if-else and if-elif-else constructs. Now let's learn about loops. In this article, we will look at the simplest for and while loops, statements for interrupting and continuing them (break and continue, respectively), and examples of using if-elif-else statements to create additional conditions.

Loops in Python 3 and why you need them

Cyclic tasks are an integral part of our lives. Take shopping for groceries with a list. We look at the list, look for the desired product and put it in the cart, then go to the second item and repeat the same operation until the end of the list, after which we exit the program discard the list and move on to the next part of the code task. After the last item is executed, the list is discarded. Loops work in programming in the same way: the program will continue executing a certain piece of code as long as some condition specified for this piece or, as programmers say, for the loop body, is met.

The conditions are set with the special operators while or for, and a single execution of the loop body is called an iteration. There can be as many iterations as you want and they will be executed as long as the condition is true. If you make a logical mistake when writing the code, the iterations risk becoming infinite. In such cases, we speak of infinite loops, which, however, can be called intentionally.

For Loop in Python

The for statement is needed to loop through a known number of values in a list. for is one of the main helpers of a Python programmer; it saves a lot of time since you don't have to retype the same code many times. But enough theory, let's write some code to make it clearer what for does:

word = "hostman"
for letter in word:
   print (letter)

We get this result:

h
o
s
t
m
a
n

The program searches through all elements, in this case the characters that make up the string, and outputs them as a sequence. But they can also be elements of a list. A list is created using [] symbols, and its elements are enumerated using commas. For example, let's take our shopping list and display it on the screen:

products = ['milk', 'bread', 'eggs', 'sausage', 'sugar', 'flour']
for element in products:
   print (element)
milk
bread
eggs
sausage
sugar
flour

Now, a few remarks for beginners:

  • Do not forget the indentation in the loop body after the main lines with for and while operators.

  • You can use single or double quotes to correctly label strings and elements (in the examples above, we used both types), but in practice, it's better to use one of them so as not to worsen the code readability.

  • Programmers usually use variables i and j to denote counters, but it's possible to label them differently. In these examples, for the sake of clarity, we have intentionally labeled counters as letter and element to make it clear which values they search for.

While Loop in Python

The function of the while statement is different. As long as the condition entered by while is true, the loop body will continue to execute, and the number of iterations is not known in advance (unlike loops with the for statement). Example:

number = 1
while number < 10:
    print (number)
    number += 2
print ('The next value is greater than 10, so the count stopped.')

Here is the result of executing the code:

1
3
5
7
9
The next value is greater than 10, so the count stopped.

One of the features of Python is that the language is as visual as possible, and it's often clear what work the code is doing without detailed explanations. In this case, we have the following: we assigned the value 1 to the number variable and created a condition—as long as the value is less than 10, the loop body will be executed. In the body, we have created two instructions, one visible (to display the next value on the screen) and the other one adds the specified number to the variable value and overwrites this value. We could rewrite this line as follows:

number = number + 2

The entries x = x + 2 and x += 2 are equivalent (Python allows you to use different code to do the same thing in some cases).

As soon as the condition introduced by the while statement is no longer true (the number becomes greater than 10), the loop body stops executing, and the program moves to the final line (note that it is on a different level, so it is not indented), and a message is displayed:

The next value is greater than 10, so the count stopped

Using if-elif-else statements on loops

Now let's consider more complex and functional examples of constructs with while, which are created using the if, elif, and else statements. 

x = 0
while x < 10:
    if x == 0:
        print (x, "if statement is true")
        x += 1
    elif x <= 5:
        print (x, "First elif statement is true")
        x += 1
    elif x > 5 and x < 9:
        print (x, "Second elif statement is true")
        x += 1
    else:
        print (x, "else statement is true")
        x += 1
print ("That’s the count.")

Here’s the result:

0 if statement is true
1 first elif statement is true

6 second elif statement is true

9 else statement is true
That’s the count.

After assigning the value 0 to the variable x, we create a condition for the while loop, and using the if, elif and else operators, we add a set of conditions that will cause a certain text to be displayed on the screen. The if condition triggers when x is 0, and the first elif triggers when x is less than or equal to 5. In the case of the second elif, we also used the and operator, which adds an extra condition so that the user also sees the text that is displayed when the else condition is met. Python checks the truth of conditions sequentially, so if any condition higher up on the list remains true until the last iteration, the directives for the conditions below will not be executed.

Break and Continue Statements

The break and continue statements provide additional ways to work with loops. Here's what they do:

  • break is used to interrupt a loop;

  • continue is used to skip a certain iteration and move on to the next one, but without terminating the loop.

For an example of how the break statement works, let's slightly modify the code from the previous chapter and try to execute it:

x = 0
while x < 10:
    if x == 0:
        print (x, "if statement is true")
        x += 1
    elif x <= 5:
        print (x, "first elif statement is true")
        x += 1
    elif x > 5 and x < 9:
        print (x, "second elif statement is true")
        x += 1
    else:
        print (x, "else statement is true")
print ("That’s the count.")

We removed the x += 1 line after the else operator and got into an infinite loop! Of course, we can just return the line, but we can also do it this way:

x = 0
while x < 10:

    else:
        print (x, "else statement is true")
        break
print ("That’s the count.")

Now, after adding the break statement, when the else condition is met, the loop will no longer be infinite, and the message will appear on the screen (That's the count).

Here is an example of how the continue statement works:

products = ['milk', 'bread', 'eggs', 'sausage', 'sugar', 'flour']
print ('Shopping list:')
print ()
for element in products:
    if element == 'sausage':
        continue
    print (element)
print ()
print ('And sausage is already bought.')

The result of the program:

Shopping list:
milk
bread
eggs
sugar
flour
And sausage is already bought.

As we can see, the sausage is no longer on the list: as soon as the program reaches it, the continue command comes into play, instructing it to ignore this item. But the loop is not interrupted, so the other products from the list are also displayed on the screen.

Nested Loops in Python

You can also use loop operators to create nested loops in Python 3. 

Example:

for i in range (1, 4):
    for j in range (1, 4):
        print (i * j, end=" ")
  print ()

The result of the program:

1 2 3
2 4 6
3 6 9

You have already guessed that this is the way to achieve consecutive multiplication of numbers (the i * j directive inside nested for loop is responsible for this, and the code end="" prints the obtained values with spaces). The last print() line, referring to the main for loop (this is implemented by indentation), is also necessary for clarity: in this case the program will print the obtained values in a column.

Beginners may also ask why there is no 4 8 12 line in the output? This is a peculiarity of the built-in range function that specifies the range of values: it does not include the last number, so for that line to appear, we should write the code like this:

for i in range (1, 5):
    for j in range (1, 4):
        print (i * j, end=" ")
  print ()
1 2 3 
2 4 6 
3 6 9
4 8 12 

Conclusion

In this short article, we got acquainted with for and while loops, learned how to use conditional if-elif-else constructs together with loops, and how to use break and continue statements. With a little practice, you will be able to write more complex code than presented in our examples. Good luck!

Check out our app platform to find a variety of Python applications, including Celery, Django, FastAPI and Flask. 

Python
06.12.2023
Reading time: 8 min

Similar

Python

Python Static Method

A static method in Python is bound to the class itself rather than any instance of that class. So, you can call it without first creating an object and without access to instance data (self).  To create a static method we need to use a decorator, specifically @staticmethod. It will tell Python to call the method on the class rather than an instance. Static methods are excellent for utility or helper functions that are logically connected to the class but don't need to access any of its properties.  When To Use & Not to Use a Python Static Method Static methods are frequently used in real-world code for tasks like input validation, data formatting, and calculations—especially when that logic naturally belongs with a class but doesn't need its state. Here's an example from a User class that checks email format: class User: @staticmethod def is_valid_email(email): return "@" in email and "." in email This method doesn't depend on any part of the User instance, but conceptually belongs in the class. It can be used anywhere as User.is_valid_email(email), keeping your code cleaner and more organized. If the logic requires access to or modification of instance attributes or class-level data, avoid using a static method as it won't help here. For instance, if you are working with user settings or need to monitor object creation, you will require a class method or an instance method instead. class Counter: count = 0 @classmethod def increment(cls): cls.count += 1 In this example, using a static method would prevent access to cls.count, making it useless for this kind of task. Python Static Method vs Class Method Though they look similar, class and static methods in Python have different uses; so, let's now quickly review their differences. Defined inside a class, a class method is connected to that class rather than an instance. Conventionally called cls, the class itself is the first parameter; so, it can access and change class-level data. Factory patterns, alternate constructors, or any activity applicable to the class as a whole and not individual instances are often implemented via class methods. Conversely, a static method is defined within a class but does not start with either self or cls parameters. It is just a regular function that “lives” inside a class but doesn’t interact with the class or its instances. For utility tasks that are conceptually related to the class but don’t depend on its state, static methods are perfect. Here's a quick breakdown of the Python class/static methods differences: Feature Class Method Static Method Binding Bound to the class Not bound to class or instance First parameter cls (class itself) None (no self or cls) Access to class/instance data Yes No Common use cases Factory methods, class-level behavior Utility/helper functions Decorator @classmethod @staticmethod Python Static Method vs Regular Functions You might ask: why not just define a function outside the class instead of using a static method? The answer is structure. A static method keeps related logic grouped within the class, even if it doesn't interact with the class or its instances. # Regular function def is_even(n): return n % 2 == 0 # Static method inside a class class NumberUtils: @staticmethod def is_even(n): return n % 2 == 0 Both functions do the same thing, but placing is_even inside NumberUtils helps keep utility logic organized and easier to find later. Let’s proceed to the hands-on Python static method examples. Example #1 Imagine that we have a MathUtils class that contains a static method for calculating the factorial: class MathUtils: @staticmethod def factorial(n): if n == 0: return 1 else: return n * MathUtils.factorial(n-1) Next, let's enter: print(MathUtils.factorial(5))120 We get the factorial of 5, which is 120. Here, the factorial static method does not use any attributes of the class instance, only the input argument n. And we called it using the MathUtils.factorial(n) syntax without creating an instance of the MathUtils class. In Python, static methods apply not only in classes but also in modules and packages. The @staticmethod decorator marks a function you define inside a class if it does not interact with instance-specific data. The function exists on its own; it is related to the class logically but is independent of its internal state. Managed solution for Backend development Example #2 Let's say we're working with a StringUtils module with a static method for checking if a string is a palindrome. The code will be: def is_palindrome(string):    return string == string[::-1] This function doesn't rely on any instance-specific data — it simply performs a check on the input. That makes it a good candidate for a static method. To organize it within a class and signal that it doesn't depend on the class state, we can use the @staticmethod decorator like this: class StringUtils:    @staticmethod    def is_palindrome(string):       return string == string[::-1] Let's enter for verification: print(StringUtils.is_palindrome("deed"))True print(StringUtils.is_palindrome("deer"))False That's correct, the first word is a palindrome, so the interpreter outputs True, but the second word is not, and we get False. So, we can call the is_palindrome method through the StringUtils class using the StringUtils.is_palindrome(string) syntax instead of importing the is_palindrome function and calling it directly. - Python static method and class instance also differ in that the static cannot affect the state of an instance. Since they do not have access to the instance, they cannot alter attribute values, which makes sense. Instance methods are how one may modify the instance state of a class. Example #3 Let's look at another example. Suppose we have a Person class that has an age attribute and a static is_adult method that checks the value against the age of majority: class Person:    def __init__(self, age):        self.age = age    @staticmethod    def is_adult(age):       return age >= 21 Next, let's create an age variable with a value of 24, call the is_adult static method from the Person class with this value and store its result in the is_adult variable, like this: age = 24is_adult = Person.is_adult(age) Now to test this, let's enter: print(is_adult)True Since the age matches the condition specified in the static method, we get True. In the example, the is_adult static method serves as an auxiliary tool—a helper function—accepting the age argument but without access to the age attribute of the Person class instance. Conclusion Static methods improve code readability and make it possible to reuse it. They are also more convenient when compared to standard Python functions. Static methods are convenient as, unlike functions, they do not call for a separate import. Therefore, applying Python class static methods can help you streamline and work with your code greatly. And, as you've probably seen from the examples above, they are quite easy to master. On our app platform you can find Python applications, such as Celery, Django, FastAPI and Flask. 
16 April 2025 · 6 min to read
Python

Input in Python

Python provides interactive capabilities through various tools, one of which is the input() function. Its primary purpose is to receive user input. This function makes Python programs meaningful because without user interaction, applications would have limited utility. How the Python Input Works This function operates as follows: user_name = input('Enter your name: ') user_age = int(input('How old are you? ')) First, the user is asked to enter their name, then their age. Both inputs are captured using a special operator that stores the entered values in the variables user_name and user_age. These values can then be used in the program. For example, we can create an age-based access condition for a website (by converting the age input to an integer using int()) and display a welcome message using the entered name: if user_age < 18: print('Sorry, access is restricted to adults only') else: print('Welcome to the site,', user_name, '!') So, what happens when int() receives an empty value? If the user presses Enter without entering anything, let's see what happens by extending the program: user_name = input('Enter your name: ') user_age = int(input('How old are you? ')) if user_age < 18: print('Sorry, access is restricted to adults only') else: print('Welcome to the site,', user_name, '!') input('Press Enter to go to the menu') print('Welcome to the menu') Pressing Enter moves the program to the next line of code. If there is no next line, the program exits. The last line can be written as: input('Press Enter to exit') If there are no more lines in the program, it will exit. Here is the complete version of the program: user_name = input('Enter your name: ') user_age = int(input('How old are you? ')) if user_age < 18: print('Sorry, access is restricted to adults only') else: print('Welcome to the site,', user_name, '!') input('Press Enter to go to the menu') print('Welcome to the menu') input('Press Enter to exit') input('Press Enter to exit') If the user enters an acceptable age, they will see the message inside the else block. Otherwise, they will see only the if block message and the final exit prompt. The input() function is used four times in this program, and in the last two cases, it does not store any values but serves to move to the next part of the code or exit the program. input() in the Python Interpreter The above example is a complete program, but you can also execute it line by line in the Python interpreter. However, in this case, you must enter data immediately to continue: >>> user_name = input('Enter your name: ') Enter your name: Jamie >>> user_age = int(input('How old are you? ')) How old are you? 18 The code will still execute, and values will be stored in variables. This method allows testing specific code blocks. However, keep in mind that values are retained only until you exit the interactive mode. It is recommended to save your code in a .py file. Input Conversion Methods: int(), float(), split() Sometimes, we need to convert user input into a specific data type, such as an integer, a floating-point number, or a list. Integer conversion (int()) We've already seen this in a previous example: user_age = int(input('How old are you? ')) The int() function converts input into an integer, allowing Python to process it as a numeric type. By default, numbers entered by users are treated as strings, so Python requires explicit conversion. A more detailed approach would be: user_age = input('How old are you? ') user_age = int(user_age) The first method is shorter and more convenient, but the second method is useful for understanding function behavior. Floating-point conversion (float()) To convert user input into a floating-point number, use float(): height = float(input('Enter your height (e.g., 1.72): ')) weight = float(input('Enter your weight (e.g., 80.3): ')) Or using a more detailed approach: height = input('Enter your height (e.g., 1.72): ') height = float(height) weight = input('Enter your weight (e.g., 80.3): ') weight = float(weight) Now, the program can perform calculations with floating-point numbers. Converting Input into a List (split()) The split() method converts input text into a list of words: animals = input('Enter your favorite animals separated by spaces: ').split() print('Here they are as a list:', animals) Example output: Enter your favorite animals separated by spaces: cat dog rabbit fox bear Here they are as a list: ['cat', 'dog', 'rabbit', 'fox', 'bear'] Handling Input Errors Users often make mistakes while entering data or may intentionally enter incorrect characters. In such cases, incorrect input can cause the program to crash: >>> height = float(input('Enter your height (e.g., 1.72): ')) Enter your height (e.g., 1.72): 1m72 Traceback (most recent call last): File "<pyshell#2>", line 1, in <module> height = float(input('Enter your height (e.g., 1.72): ')) ValueError: could not convert string to float: '1m72' The error message indicates that Python cannot convert the string into a float. To prevent such crashes, we use the try-except block: try: height = float(input('Enter your height (e.g., 1.72): ')) except ValueError: height = float(input('Please enter your height in the correct format: ')) We can also modify our initial age-input program to be more robust: try: user_age = int(input('How old are you? ')) except ValueError: user_age = int(input('Please enter a number: ')) However, the program will still crash if the user enters incorrect data again. To make it more resilient, we can use a while loop: while True: try: height = float(input('Enter your height (e.g., 1.72): ')) break except ValueError: print('Let’s try again.') continue print('Thank you!') Here, we use a while loop with break and continue. The program works as follows: If the input is correct, the loop breaks, and the program proceeds to the final message: print('Thank you!'). If the program cannot convert input to a float, it catches an exception (ValueError) and displays the message "Let’s try again."  The continue statement prevents the program from crashing and loops back to request input again. Now, the user must enter valid data before proceeding. Here is the complete code for a more resilient program: user_name = input('Enter your name: ') while True: try: user_age = int(input('How old are you? ')) break except ValueError: print('Are you sure?') continue if user_age < 18: print('Sorry, access is restricted to adults only') else: print('Welcome to the site,', user_name, '!') input('Press Enter to go to the menu') print('Welcome to the menu') input('Press Enter to exit') This program still allows unrealistic inputs (e.g., 3 meters tall or 300 years old). To enforce realistic values, additional range checks would be needed, but that is beyond the scope of this article. 
08 April 2025 · 6 min to read
Python

Operators in Python

Python operators are tools used to perform various actions with variables, as well as numerical and other values called operands—objects on which operations are performed. There are several types of Python operators: Arithmetic Comparison Assignment Identity Membership Logical Bitwise This article will examine each of them in detail and provide examples. Arithmetic Operators For addition, subtraction, multiplication, and division, we use the Python operators +, -, *, and / respectively: >>> 24 + 28 52 >>> 24 - 28 -4 >>> 24 * 28 672 >>> 24 / 28 0.8571428571428571 For exponentiation, ** is used: >>> 5 ** 2 25 >>> 5 ** 3 125 >>> 5 ** 4 625 For floor division (integer division without remainder), // is used: >>> 61 // 12 5 >>> 52 // 22 2 >>> 75 // 3 25 >>> 77 // 3 25 The % operator returns the remainder (modulo division): >>> 62 % 6 2 >>> 65 % 9 2 >>> 48 % 5 3 >>> 48 % 12 0 Comparison Operators Python has six comparison operators: >, <, >=, <=, ==, !=. Note that equality in Python is written as ==, because a single = is used for assignment. The != operator is used for "not equal to." When comparing values, Python will return True or False depending on whether the expressions are true or false. >>> 26 > 58 False >>> 26 < 58 True >>> 26 >= 26 True >>> 58 <= 57 False >>> 50 == 50 True >>> 50 != 50 False >>> 50 != 51 True Assignment Operators A single = is used for assigning values to variables: >>> b = 5 >>> variants = 20 Python also provides convenient shorthand operators that combine arithmetic operations with assignment: +=, -=, *=, /=, //=, %=. For example: >>> cars = 5 >>> cars += 7 >>> cars 12 This is equivalent to: >>> cars = cars + 7 >>> cars 12 The first version is more compact. Other assignment operators work similarly: >>> train = 11 >>> train -= 2 >>> train 9 >>> moto = 3 >>> moto *= 7 >>> moto 21 >>> plain = 8 >>> plain /= 4 >>> plain 2.0 Notice that in the last case, the result is a floating-point number (float), not an integer (int). Identity Operators Python has two identity operators: is and is not. The results are True or False, similar to comparison operators. >>> 55 is 55 True >>> 55 is 56 False >>> 55 is not 55 False >>> 55 is not 56 True >>> 55 is '55' False >>> '55' is "55" True In the last two examples: 55 is '55' returned False because an integer and a string were compared. '55' is "55" returned True because both operands are strings. Python does not differentiate between single and double quotes, so the identity check was successful. Membership Operators There are only two membership operators in Python: in and not in. They check whether a certain value exists within a sequence. For example: >>> wordlist = ('assistant', 'streetcar', 'fraudster', 'dancer', 'heat', 'blank', 'compass', 'commerce', 'judgment', 'approach') >>> 'house' in wordlist False >>> 'assistant' in wordlist True >>> 'assistant' and 'streetcar' in wordlist True In the last case, a logical operator (and) was used, which leads us to the next topic. Logical Operators Python has three logical operators: and, or, and not. and returns True only if all operands are true. It can process any number of values. Using an example from the previous section: >>> wordlist = ('assistant', 'streetcar', 'fraudster', 'dancer', 'heat', 'blank', 'compass', 'commerce', 'judgment', 'approach') >>> 'assistant' and 'streetcar' in wordlist True >>> 'fraudster' and 'dancer' and 'heat' and 'blank' in wordlist True >>> 'fraudster' and 'dancer' and 'heat' and 'blank' and 'house' in wordlist False Since 'house' is not in the sequence, the result is False. These operations also work with numerical values: >>> numbers = 54 > 55 and 22 > 21 >>> print(numbers) False One of the expressions is false, and and requires all conditions to be true. or works differently: it returns True if at least one operand is true. If we replace and with or in the previous example, we get: >>> numbers = 54 > 55 or 22 > 21 >>> print(numbers) True Here, 22 > 21 is true, so the overall expression evaluates to True, even though 54 > 55 is false. not reverses logical values: >>> first = True >>> second = False >>> print(not first) False >>> print(not second) True As seen in the example, not flips True to False and vice versa. Bitwise Operators Bitwise operators are used in Python to manipulate objects at the bit level. There are five of them (shift operators belong to the same type, as they differ only in shift direction): & (AND) | (OR) ^ (XOR) ~ (NOT) << and >> (shift operators) Bitwise operators are based on Boolean logic principles and work as follows: & (AND) returns 1 if both operands contain 1; otherwise, it returns 0: >>> 1 & 1 1 >>> 1 & 0 0 >>> 0 & 1 0 >>> 0 & 0 0 | (OR) returns 1 if at least one operand contains 1, otherwise 0: >>> 1 | 1 1 >>> 1 | 0 1 >>> 0 | 1 1 >>> 0 | 0 0 ^ (XOR) returns 1 if the operands are different and 0 if they are the same: >>> 1 ^ 1 0 >>> 1 ^ 0 1 >>> 0 ^ 1 1 >>> 0 ^ 0 0 ~ (NOT) inverts bits, turning positive values into negative ones with a shift of one: >>> ~5 -6 >>> ~-5 4 >>> ~7 -8 >>> ~-7 6 >>> ~9 -10 >>> ~-9 8 << and >> shift bits by a specified number of positions: >>> 1 << 1 2 >>> 1 >> 1 0 To understand shifts, let’s break down values into bits: 0 = 00 1 = 01 2 = 10 Shifting 1 left by one bit gives 2, while shifting right results in 0. What happens if we shift by two positions? >>> 1 << 2 4 >>> 1 >> 2 0 1 = 001 2 = 010 4 = 100 Shifting 1 two places to the left results in 4 (100 in binary). Shifting right always results in zero because bits are discarded. For more details, refer to our article on bitwise operators. Difference Between Operators and Functions You may have noticed that we have included no functions in this overview. The confusion between operators and functions arises because both perform similar actions—transforming objects. However: Functions are broader and can operate on strings, entire blocks of code, and more. Operators work only with individual values and variables. In Python, a function can consist of a block of operators, but operators can never contain functions.
08 April 2025 · 6 min to read

Do you have questions,
comments, or concerns?

Our professionals are available to assist you at any moment,
whether you need help or are just unsure of where to start.
Email us
Hostman's Support