Sign In
Sign In

Creating a Web Application Using Python Flask

Creating a Web Application Using Python Flask
Hostman Team
Technical writer
Python
23.10.2024
Reading time: 14 min

In this tutorial, we will write a simple web application in Python with a database for user authentication. We will use Windows 10 and work in PyCharm using pipenv. The website will be built with HTML and CSS. The installation of Flask, PyCharm, and pipenv is described in detail in this article.

Throughout this article, we will use testing and educational examples that are not suitable for production implementation. For instance, to verify passwords in the database, you need to store password hashes and compare hashes, not plaintext passwords. Additionally, when working with databases, you should use an ORM rather than writing "raw" SQL (for more on ORM, see here).

To get started, we will create a project directory called Hostman. Within this directory, we will place the templates and static directories, and within the static directory, we will create a css directory. The project structure will look like this:

Hostman
|— templates
|— static
|    — css

Database for Logins and Passwords

Once you have installed Flask and the other tools, you can proceed to work. We will use the SQLite database management system (DBMS) to store user data. It is well-suited for small projects, and its main advantage is its standalone nature: it does not require a server to operate. Additionally, Python includes a built-in module, sqlite3, for working with SQLite. However, if you decide to work with a server-based DBMS, consider using cloud servers like Hostman.

In the project directory, we create a file named db.py. In this file, we will import the sqlite3 module and create a database and a table for logins and passwords:

import sqlite3
db_lp = sqlite3.connect('login_password.db')
cursor_db = db_lp.cursor()
sql_create = '''CREATE TABLE passwords(
login TEXT PRIMARY KEY,
password TEXT NOT NULL);'''

cursor_db.execute(sql_create)
db_lp.commit()
cursor_db.close()
db_lp.close()

Let’s break down what this code does:

  1. We connect to the database using the connect() method. This method will look for the file login_password.db in the project directory. If it does not find it, it will create one automatically.

  2. We create the cursor_db object for interacting with the database.

  3. sql_create is the SQL query for creating the table that holds the logins and passwords.

  4. We execute sql_create using the execute() method.

  5. We save changes to the database with the commit() method.

  6. Finally, we close the cursor_db and db_lp objects to avoid any database issues.

To create the database, run the command:

python db.py

Authentication

Now let’s work on the authentication for our Flask application.

Main Form

First, we will create a form that will be used for authentication into an abstract service. In the templates directory, we create a file named authorization.html with the following content:

<form method="POST">
  <div class="container">
    <label for="Login"><b>Login</b></label>
    <input type="text" placeholder="" name="Login" required>
    <label for="Password"><b>Password</b></label>
    <input type="password" placeholder="" name="Password" required>
    <button type="submit">Login</button>
    <div class="container">
      <span class="reg"><a href="/registration">Registration</a></span>
    </div>
  </div>
</form>

<link rel="stylesheet" href="{{ url_for('static', filename='css/auth.css') }}">

Here, there are three important points:

  1. <form method="POST"> — we indicate that we will be using POST requests.

  2. <label for="Login"> and <label for="Password"> — we mark the Login and Password fields that we will process later using the get() method from the request module.

  3. <link rel="stylesheet" href="{{ url_for('static', filename='css/auth.css') }}"> — we inform HTML where the CSS file is stored.

In the /static/css directory, we create a file named auth.css:

form {
    font: 14px Stem-Regular, arial, sans-serif; /* Choose font */
    border: 1px solid black; /* Color, size, and type of border */
    -webkit-border-radius: 20px; /* Round corners */
    color: #777991; /* Label color */
    width: 50%; /* Form width */
    margin-right: auto; /* Form positioning */
    margin-left: auto; /* Form positioning */
    text-align: center; /* Center text */
}


input[type=text], input[type=password] {
    text-align: center; /* Center text */
    -webkit-border-radius: 4px; /* Round corners */
    width: auto; /* Width */
    padding: 15px 20px; /* Internal padding size */
    margin: 10px 0; /* External margin size */
    margin-right: auto; /* External right margin size */
    margin-left: auto; /* External left margin size */
    display: block; /* Display type */
    border: 1px solid #050c26; /* Color, size, and type of border */
    box-sizing: border-box; /* Size of object relative to parent */
    font: 14px Stem-Regular, arial, sans-serif; /* Choose font */
    color: #777991; /* Text color in input */
}


button {
    font: 16px Stem-medium, arial, sans-serif; /* Choose button font */
    background-color: #454cee; /* Choose background color */
    -webkit-border-radius: 8px; /* Round edges */
    color: white; /* Choose text color */
    padding: 16px 20px; /* Internal padding size */
    margin: 8px 0; /* External margin size */
    border: none; /* No border */
    cursor: pointer; /* Change cursor on hover */
    width: auto; /* Width */
}


button:hover { 
    opacity: 0.9; /* Change button brightness on hover */
}


.container {
    padding: 20px; /* Internal padding size of the container */
}

As a result, our form will look like this:

Image5

Message for Successful Authentication

If the user enters the correct username-password pair, we will display a corresponding message. In the templates directory, we create a file named successfulauth.html with the following content:

<form method="POST">
  <div class="container">
    <label><b>You have successfully logged in</b></label>   
  </div>
</form>

<link rel="stylesheet" href="{{ url_for('static', filename='css/successfulauth.css') }}">

In the /static/css directory, we create a file named successfulauth.css:

form {
    font: 14px Stem-Regular, arial, sans-serif; /* Choose font */
    border: 1px solid black; /* Color, size, and type of border */
    -webkit-border-radius: 20px; /* Round corners */
    color: #777991; /* Label color */
    width: 40%; /* Form width */
    margin-right: auto; /* Form positioning */
    margin-left: auto; /* Form positioning */
    text-align: center; /* Center text */
}
.container {
    padding: 30px; /* Internal padding size of the container */
}

Image2

Message for Unsuccessful Authentication

In the templates directory, we create a file named auth_bad.html with the following content:

<form method="POST">
  <div class="container">
    <label><b>Incorrect username or password</b></label>   
  </div>
</form>  

<link rel="stylesheet" href="{{ url_for('static', filename='css/auth_bad.css') }}">

In the /static/css directory, we create a file named auth_bad.css:

form {
    font: 14px Stem-Regular, arial, sans-serif; /* Choose font */
    border: 1px solid black; /* Color, size, and type of border */
    -webkit-border-radius: 20px; /* Round corners */
    color: #777991; /* Label color */
    width: 40%; /* Form width */
    margin-right: auto; /* Form positioning */
    margin-left: auto; /* Form positioning */
    text-align: center; /* Center text */
}

.container {
    padding: 30px; /* Internal padding size of the container */
}

Image3

Now, we will create a registration form.

Registration

With the registration form, users will be able to create their own accounts. In the templates directory, create a file named registration.html with the following content:

<form method="POST">
  <div class="container">
    <label for="Login"><b>Username</b></label>
    <input type="text" placeholder="" name="Login" required>


    <label for="Password"><b>Password</b></label>
    <input type="password" placeholder="" name="Password" required>   


    <button type="submit">Register</button>
  </div>
</form>  

<link rel="stylesheet" href="{{ url_for('static', filename='css/regis.css') }}">

In the /static/css directory, create a file named regis.css:

form {
    font: 14px Stem-Regular, arial, sans-serif; /* Choose font */
    border: 1px solid black; /* Color, size, and type of border */
    -webkit-border-radius: 20px; /* Round corners */
    color: #777991; /* Label color */
    width: 50%; /* Form width */
    margin-right: auto; /* Form positioning */
    margin-left: auto; /* Form positioning */
    text-align: center; /* Center text */
}

input[type=text], input[type=password] {
    text-align: center; /* Center text */
    -webkit-border-radius: 4px; /* Round corners */
    width: auto; /* Width */
    padding: 15px 20px; /* Internal padding size */
    margin: 10px 0; /* External padding size */
    margin-right: auto; /* External padding size on the right */
    margin-left: auto; /* External padding size on the left */
    display: block; /* Display type */
    border: 1px solid #050c26; /* Color, size, and type of border */
    box-sizing: border-box; /* Size of the object relative to the parent */
    font: 14px Stem-Regular, arial, sans-serif; /* Choose font */
    color: #777991; /* Text color in input */
}

button {
    font: 16px Stem-medium, arial, sans-serif; /* Choose button font */
    background-color: #454cee; /* Choose background color */
    -webkit-border-radius: 8px; /* Round corners */
    color: white; /* Choose text color */
    padding: 16px 20px; /* Internal padding size */
    margin: 8px 0; /* External padding size */
    border: none; /* No border */
    cursor: pointer; /* Change cursor when hovering over the button */
    width: auto; /* Width */
}

button:hover { 
    opacity: 0.9; /* Change button brightness when hovering */
}

.container {
    padding: 20px; /* Internal padding size of the container */
}

The registration form will look like this:

Image4

Upon successful registration, the user will see a message like this:

Image1

To create this message, in the templates directory, create a file named successfulregis.html with the following content:

<form method="POST">
  <div class="container">
    <label><b>You have successfully registered</b></label>    


    <div class="container">
      <span class="reg"> <a href="/authorization">Return to login</a></span>
    </div>
  </div>
</form>  

<link rel="stylesheet" href="{{ url_for('static', filename='css/successfulregis.css') }}">

In the /static/css directory, create a file named successfulregis.css:

form {
    font: 14px Stem-Regular, arial, sans-serif; /* Choose font */
    border: 1px solid black; /* Color, size, and type of border */
    -webkit-border-radius: 20px; /* Round corners */
    color: #777991; /* Label color */
    width: 25%; /* Form width */
    margin-right: auto; /* Form positioning */
    margin-left: auto; /* Form positioning */
    text-align: center; /* Center text */
}

.container {
    padding: 20px; /* Internal padding size of the container */
}

Authorization Decorator

After creating all the forms and the database, we can start developing the Flask web application. To send an HTML document in response to a client request in Flask, the render_template() method must be used. This function from the Flask module is used to display templates from the templates folder.

The project directory now has the following structure:

Hostman
|— db.py
|— login_password.db
|— templates
|     — authorization.html
|     — auth_bad.html
|     — successfulauth.html
|     — successfulregis.html
|     — registration.html
|— static
|    — css
|         — auth_bad.css
|         — auth.css
|         — successfulauth.css
|         — regis.css
|         — successfulregis.css

In the /Hostman project directory, create a file named main.py, where we will import the necessary modules from Flask and add the code for user authorization. For more details on authentication, we recommend reading here.

from flask import Flask, request, render_template
import sqlite3


@app.route('/authorization', methods=['GET', 'POST'])
def form_authorization():
   if request.method == 'POST':
       Login = request.form.get('Login')
       Password = request.form.get('Password')


       db_lp = sqlite3.connect('login_password.db')
       cursor_db = db_lp.cursor()
       cursor_db.execute(('''SELECT password FROM passwords
                                               WHERE login = '{}';
                                               ''').format(Login))
       pas = cursor_db.fetchall()


       cursor_db.close()
       try:
           if pas[0][0] != Password:
               return render_template('auth_bad.html')
       except:
           return render_template('auth_bad.html')


       db_lp.close()
       return render_template('successfulauth.html')


   return render_template('authorization.html')

Here is the logic of how it works:

  1. The user navigates to /authorization — this is a GET request, and the decorator returns authorization.html.

  2. When the user enters their username and password and clicks the "Login" button, the server receives a POST request, which the decorator will handle. The decorator will retrieve the username and password entered by the user.

  3. Next, we connect to the database and execute an SQL query. Using cursor_db.execute() and cursor_db.fetchall(), we get the row with the password (which may be empty) corresponding to the entered username.

  4. We "extract" the password from the row, and:

    • If the row is empty, it will raise an error (array index out of bounds), which we handle with a try-except block, notifying the user of invalid input. The decorator completes its work.

    • If the password in the database does not match the received password, it simply returns a message about incorrect data and ends the operation.

    • If the password is correct, we display a message about successful authorization and conclude the work of the Flask decorator.

Registration Decorator

Users can access the /registration page from the authorization form. Here is the code for the decorator, which we will add to the end of main.py:

@app.route('/registration', methods=['GET', 'POST'])
def form_registration():
   if request.method == 'POST':
       Login = request.form.get('Login')
       Password = request.form.get('Password')


       db_lp = sqlite3.connect('login_password.db')
       cursor_db = db_lp.cursor()
       sql_insert = '''INSERT INTO passwords VALUES('{}','{}');'''.format(Login, Password)


       cursor_db.execute(sql_insert)
       db_lp.commit()


       cursor_db.close()
       db_lp.close()


       return render_template('successfulregis.html')


   return render_template('registration.html')

Initially, the GET request for /registration is processed, returning registration.html. When the user enters their data and clicks the "Register" button, the server receives a POST request, which extracts the Login and Password.

Next, we connect to the database. The sql_insert variable holds the SQL query for adding a new row with the user's data. We execute sql_insert and save the changes. Finally, we close the cursor_db and db_lp objects, returning a message indicating successful registration.

Full Program Code

from flask import Flask, request, render_template
import sqlite3


app = Flask(__name__)


@app.route('/authorization', methods=['GET', 'POST'])
def form_authorization():
   if request.method == 'POST':
       Login = request.form.get('Login')
       Password = request.form.get('Password')


       db_lp = sqlite3.connect('login_password.db')
       cursor_db = db_lp.cursor()
       cursor_db.execute(('''SELECT password FROM passwords
                                               WHERE login = '{}';
                                               ''').format(Login))
       pas = cursor_db.fetchall()


       cursor_db.close()
       try:
           if pas[0][0] != Password:
               return render_template('auth_bad.html')
       except:
           return render_template('auth_bad.html')


       db_lp.close()
       return render_template('successfulauth.html')


   return render_template('authorization.html')


@app.route('/registration', methods=['GET', 'POST'])
def form_registration():
   if request.method == 'POST':
       Login = request.form.get('Login')
       Password = request.form.get('Password')


       db_lp = sqlite3.connect('login_password.db')
       cursor_db = db_lp.cursor()
       sql_insert = '''INSERT INTO passwords VALUES('{}','{}');'''.format(Login, Password)

This completes the implementation of the user registration decorator and the overall application.

Conclusion

In this tutorial, we covered the essential steps to create a simple web application for user authentication and registration using Python framework Flask. We began by setting up the project structure and configuring SQLite for user data storage. We then developed HTML forms for authorization and registration, styling them with CSS. Through decorators, we implemented the logic to handle user input and interact with the database, ensuring secure processing of credentials. Finally, users receive feedback on successful or failed actions. This foundational knowledge equips you to build more complex Flask applications while enhancing user experience and security.

On our app platform you can deploy Flask and other Python applications. 

Python
23.10.2024
Reading time: 14 min

Similar

Python

How to Get the Length of a List in Python

Lists in Python are used almost everywhere. In this tutorial we will look at four ways to find the length of a Python list: by using built‑in functions, recursion, and a loop. Knowing the length of a list is most often required to iterate through it and perform various operations on it. len() function len() is a built‑in Python function for finding the length of a list. It takes one argument—the list itself—and returns an integer equal to the list’s length. The same function also works with other iterable objects, such as strings. Country_list = ["The United States of America", "Cyprus", "Netherlands", "Germany"] count = len(Country_list) print("There are", count, "countries") Output: There are 4 countries Finding the Length of a List with a Loop You can determine a list’s length in Python with a for loop. The idea is to traverse the entire list while incrementing a counter by  1 on each iteration. Let’s wrap this in a separate function: def list_length(list): counter = 0 for i in list: counter = counter + 1 return counter Country_list = ["The United States of America", "Cyprus", "Netherlands", "Germany", "Japan"] count = list_length(Country_list) print("There are", count, "countries") Output: There are 5 countries Finding the Length of a List with Recursion The same task can be solved with recursion: def list_length_recursive(list): if not list: return 0 return 1 + list_length_recursive(list[1:]) Country_list = ["The United States of America", "Cyprus", "Netherlands","Germany", "Japan", "Poland"] count = list_length_recursive(Country_list) print("There are", count, "countries") Output: There are 6 countries How it works. The function list_length_recursive() receives a list as input. If the list is empty, it returns 0—the length of an empty list. Otherwise it calls itself recursively with the argument list[1:], a slice of the original list starting from index 1 (i.e., the list without the element at index 0). The result of that call is added to 1. With each recursive step the returned value grows by one while the list shrinks by one element. length_hint() function The length_hint() function lives in the operator module. That module contains functions analogous to Python’s internal operators: addition, subtraction, comparison, and so on. length_hint() returns the length of iterable objects such as strings, tuples, dictionaries, and lists. It works similarly to len(): from operator import length_hint Country_list = ["The United States of America", "Cyprus", "Netherlands","Germany", "Japan", "Poland", "Sweden"] count = length_hint(Country_list) print("There are", count, "countries") Output: There are 7 countries Note that length_hint() must be imported before use. Conclusion In this guide we covered four ways to determine the length of a list in Python. Under equal conditions the most efficient method is len(). The other approaches are justified mainly when you are implementing custom classes similar to list.
17 July 2025 · 3 min to read
Python

Understanding the main() Function in Python

In any complex program, it’s crucial to organize the code properly: define a starting point and separate its logical components. In Python, modules can be executed on their own or imported into other modules, so a well‑designed program must detect the execution context and adjust its behavior accordingly.  Separating run‑time code from import‑time code prevents premature execution, and having a single entry point makes it easier to configure launch parameters, pass command‑line arguments, and set up tests. When all important logic is gathered in one place, adding automated tests and rolling out new features becomes much more convenient.  For exactly these reasons it is common in Python to create a dedicated function that is called only when the script is run directly. Thanks to it, the code stays clean, modular, and controllable. That function, usually named main(), is the focus of this article. All examples were executed with Python 3.10.12 on a Hostman cloud server running Ubuntu 22.04. Each script was placed in a separate .py file (e.g., script.py) and started with: python script.py The scripts are written so they can be run just as easily in any online Python compiler for quick demonstrations. What Is the main() Function in Python The simplest Python code might look like: print("Hello, world!")  # direct execution Or a script might execute statements in sequence at file level: print("Hello, world!")       # action #1 print("How are you, world?") # action #2 print("Good‑bye, world...")  # action #3 That trivial arrangement works only for the simplest scripts. As a program grows, the logic quickly becomes tangled and demands re‑organization: # function containing the program’s main logic (entry point) def main():     print("Hello, world!") # launch the main logic if __name__ == "__main__":     main()                    # call the function with the main logic With more actions the code might look like: def main(): print("Hello, world!") print("How are you, world?") print("Good‑bye, world...") if __name__ == "__main__": main() This implementation has several important aspects, discussed below. The main() Function The core program logic lives inside a separate function. Although the name can be anything, developers usually choose main, mirroring C, C++, Java, and other languages.  Both helper code and the main logic are encapsulated: nothing sits “naked” at file scope. # greeting helper def greet(name): print(f"Hello, {name}!") # program logic def main(): name = input("Enter your name: ") greet(name) # launch the program if __name__ == "__main__": main() Thus main() acts as the entry point just as in many other languages. The if __name__ == "__main__" Check Before calling main() comes the somewhat odd construct if __name__ == "__main__":.  Its purpose is to split running from importing logic: If the script runs directly, the code inside the if block executes. If the script is imported, the block is skipped. Inside that block, you can put any code—not only the main() call: if __name__ == "__main__":     print("Any code can live here, not only main()") __name__ is one of Python’s built‑in “dunder” (double‑underscore) variables, often called magic or special. All dunder objects are defined and used internally by Python, but regular users can read them too. Depending on the context, __name__ holds: "__main__" when the module runs as a standalone script. The module’s own name when it is imported elsewhere. This lets a module discover its execution context. Advantages of Using  main() Organization Helper functions and classes, as well as the main function, are wrapped separately, making them easy to find and read. Global code is minimal—only initialization stays at file scope: def process_data(data): return [d * 2 for d in data] def main(): raw = [1, 2, 3, 4] result = process_data(raw) print("Result:", result) if __name__ == "__main__": main() A consistent style means no data manipulation happens at the file level. Even in a large script you can quickly locate the start of execution and any auxiliary sections. Isolation When code is written directly at the module level, every temporary variable, file handle, or connection lives in the global namespace, which can be painful for debugging and testing. Importing such a module pollutes the importer’s globals: # executes immediately on import values = [2, 4, 6] doubles = [] for v in values: doubles.append(v * 2) print("Doubled values:", doubles) With main() everything is local; when the function returns, its variables vanish: def double_list(items): return [x * 2 for x in items] # create a new list with doubled elements def main(): values = [2, 4, 6] result = double_list(values) print("Doubled values:", result) if __name__ == "__main__": main() That’s invaluable for unit testing, where you might run specific functions (including  main()) without triggering the whole program. Safety Without the __name__ check, top‑level code runs even on import—usually undesirable and potentially harmful. some.py: print("This code will execute even on import!") def useful_function(): return 42 main.py: import some print("The logic of the imported module executed itself...") Console: This code will execute even on import! The logic of the imported module executed itself... The safer some.py: def useful_function():     return 42 def main():     print("This code will not run on import") main() plus the __name__ check guard against accidental execution. Inside main() you can also verify user permissions or environment variables. How to Write main() in Python Remember: main() is not a language construct, just a regular function promoted to “entry point.” To ensure it runs only when the script starts directly: Tools – define helper functions with business logic. Logic – assemble them inside main() in the desired order. Check – add the if __name__ == "__main__" guard.  This template yields structured, import‑safe, test‑friendly code—excellent practice for any sizable Python project. Example Python Program Using main() # import the standard counter from collections import Counter # runs no matter how the program starts print("The text‑analysis program is active") # text‑analysis helper def analyze_text(text): words = text.split() # split text into words total = len(words) # total word count unique = len(set(words)) # unique word count avg_len = sum(len(w) for w in words) / total if total else 0 freq = Counter(words) # build frequency counter top3 = freq.most_common(3) # top three words return { 'total': total, 'unique': unique, 'avg_len': avg_len, 'top3': top3 } # program’s main logic def main(): print("Enter text (multiple lines). Press Enter on an empty line to finish:") lines = [] while True: line = input() if not line: break lines.append(line) text = ' '.join(lines) stats = analyze_text(text) print(f"\nTotal number of words: {stats['total']}") print(f"Unique words: {stats['unique']}") print(f"Average word length: {stats['avg_len']:.2f}") print("Top‑3 most frequent words:") for word, count in stats['top3']: print(f" {word!r}: {count} time(s)") # launch program if __name__ == "__main__": main() Running the script prints a prompt: Enter text (multiple lines). Press Enter on an empty line to finish: Input first line: Star cruiser Orion glided silently through the darkness of intergalactic space. Second line: Signals of unknown life‑forms flashed on the onboard sensors where the nebula glowed with a phosphorescent light. Third line: The cruiser checked the sensors, then the cruiser activated the defense system, and the cruiser returned to its course. Console output: The text‑analysis program is active Total number of words: 47 Unique words: 37 Average word length: 5.68 Top‑3 most frequent words: 'the': 7 time(s) 'cruiser': 4 time(s) 'of': 2 time(s) If you import this program (file program.py) elsewhere: import program         # importing program.py Only the code outside main() runs: The text‑analysis program is active So, a moderately complex text‑analysis utility achieves clear logic separation and context detection. When to Use main() and When Not To Use  main() (almost always appropriate) when: Medium/large scripts – significant code with non‑trivial logic, multiple functions/classes. Libraries or CLI utilities – you want parts of the module importable without side effects. Autotests – you need to test pure logic without extra boilerplate. You can skip main() when: Tiny one‑off scripts – trivial logic for a quick data tweak. Educational snippets – short examples illustrating a few syntax features. In short, if your Python program is a standalone utility or app with multiple processing stages, command‑line arguments, and external resources—introduce  main(). If it’s a small throw‑away script, omitting main() keeps things concise. Conclusion The  main() function in Python serves two critical purposes: Isolates the program’s core logic from the global namespace. Separates standalone‑execution logic from import logic. Thus, a Python file evolves from a straightforward script of sequential actions into a fully‑fledged program with an entry point, encapsulated logic, and the ability to detect its runtime environment.
14 July 2025 · 8 min to read
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

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