Understanding HTTP Requests: Structure, Methods & Examples
Python
Network
04.10.2024
Reading time: 9 min
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HTTP is a key to communication on the internet. Methods of HTTP protocols allow clients to send requests to the servers and servers to send responses. Every website on the World Wide Web uses HTTP requests. So, it's necessary to understand them. This article explores the concept of HTTP requests, its structure, common methods, and real-life examples. This helps in understanding the functioning of the web.
What is an HTTP Request
An HTTP request is a message where a client, such as a web browser, asks the host located on the server for a specific resource. Clients use URLs in HTTP requests which show the resources they want to access from the server.
Components of an HTTP Request
Every HTTP request comprises three components namely; request line, headers and message body.
Request Line
A request line is the start line in an HTTP request command. It is used to initialize an action on the server. A request line would also indicate what kind of method and version of HTTP protocol the client is using. Apart from the HTTP method, a request line also consists of a URI or URL to the path or protocol.
Request line example:
GET /index.html HTTP/1.1Headers
Headers are right behind the request line. They offer client’s additional information to the server. Headers include data about the host, client’s user agent, language preferences and more. Server leverages this information to identify the browser and OS version of the client. HTTP request headers are case-sensitive, followed by a colon (:) and a value.
HTTP request Headers example:
Host: example.com
User-Agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/92.0.4515.107 Safari/537.36
Accept: application/json, text/plain, */*
Accept-Language: en-US,en;q=0.9
Accept-Encoding: gzip, deflate, br
Connection: keep-alive
Message body
The message body in an HTTP request is used to send data to the server. They are optional. So, not every HTTP request will have a message body. It depends on the HTTP request types the client uses. The HTTP requests that do have a message body, usually leverage POST to send information. Mainly, the server uses the message body to provide the requested data to the client.
Common HTTP Methods
An HTTP request is a way to connect the client with the server. There can be many reasons for pursuing this connection. It might be to retrieve specific resources or delete certain information on the server. The most common HTTP request methods used daily include:
GET: To Retrieve Resources
The biggest use case of an HTTP request is to ask the server for a specific set of data or resources. And that is done using the GET method. Every time a user wants to go to a website or any web page, the client browser first sends a request to retrieve the required data to load that page.
The GET in HTTP is a cacheable, safe, and idempotent method. However,, using a GET method multiple times can still impact server performance. The GET Method can only bring existing data from the server to the client. It can’t make any changes to it. So, the data or the resources would be in a read-only format.
POST: To Send Data
When a client wants to retrieve any information, they use the GET method, but when providing some information to the server, the client uses the HTTP POST request. Let’s say users need to submit a form or upload a file. In this case, the client’s browser has to execute the POST method in HTTP to send the data to the server.
The message body in an HTTP request contains the data. When a client browser sends a POST request, the server processes the data. Using a POST method multiple times would result in the creation of different resources on the server.
PUT: To Update Resources
Similar to the POST method, the PUT method also allows the client to add some information to the server. The only difference between both methods is that in POST, users submit new data whereas in PUT, they update the existing data.
When implementing the PUT request, the client has to specify the resource’s URL that it wants to update. The request also includes the updated representation of the resource in its message body. The server would simply replace the old representation with the new one.
The PUT method is idempotent so there is no harm in implementing multiple identical PUT requests as it would yield the same result.
DELETE: To Remove Resources
As the name suggests, the DELETE method helps the client delete any specific resource from the server. Employing the DELETE request helps the client instruct the server to delete the resource mentioned in the request.
Upon the DELETE request of the client, when the server successfully deletes the specified resource, it sends back a confirmation to the client. Sending multiple identical DELETE requests would yield the same result.
What is an HTTP Response?
When the server sends back a response to an HTTP request, it is called an HTTP response. The server acts upon the request it receives from the client browser. The HTTP response would then either consist of the requested resource or valuable information regarding the requested operation.
So, like an HTTP request, an HTTP response is also made up of three components with a slight difference. The response starts with a status line, and a request starts with a request line.
-
Status Line: As the request line does in an HTTP request, the status line in the HTTP response also indicates which version of HTTP is used along with the status code and the message specifying the outcome of the request.
-
Headers: Headers in the HTTP response offer additional information like the date and time of response, the type of content that is sent in the
message body, details of the server and instructions on how to cache the content. -
Body: The actual message or response data that the server sends to the client browser is placed in the
message body. The content could be anything fromXML,JSONorHTMLfor the web page, an image, or any other kind of requested resource.
Status Codes and Their Meanings
HTTP status codes represent the status of the client’s HTTP requests. They come as a part of an HTTP server response. Every status code consists of three digital numbers where the first digit of the code indicates the class or category of the response. There are five types of code groups.
|
Status code group |
Description |
|
1xx |
Informational responses, continuing processing. |
|
2xx |
Success responses, requests are processed, understood and accepted. |
|
3xx |
Redirecting responses, suggests further action to complete the request. |
|
4xx |
Error responses, show what’s wrong with the request on client-side. |
|
5xx |
Error responses, state what went wrong with processing request on server-side. |
HTTP Headers and Their Importance
HTTP headers provide additional information about requests and responses. This information is critical for communication between client and server. Headers are fundamental for web browsing and app functionality. They play an important role in the following web operations:
- Host Identification
Headers bear the identification of a server’s domain that is hosting the resources. It is helpful in scenarios where a server hosts multiple domains.
-
Caching
Headers likeExpiresandCache-Controlhandle how browsers cache responses and intermediate proxies. It helps minimize loading time and server requests by determining how long a response needs to be stored. -
Cookie Management
Headers likeSet-CookieandCookiehelp save and send cookies respectively. They assist in tracking user behavior and maintain user sessions. -
Security
Headers also play a critical role in securing web applications. An Authorization header helps with user authentication whereas a Content-Security-Policy is used for mitigating XSS and other security risks.
-
Response Control
Headers likeStatusinform whether the request was a success or a failure. It also provides the necessary details so the client can manage responses appropriately.
Practical Examples of HTTP Requests
Here are a few real-life examples of how different HTTP requests are commonly used in day-to-day operations. All the examples are in Python with the use of the requests library.
GET
From entering a simple URL for the website to asking for a specific record from the web server, fetching data requires an HTTP GET request. Let’s say, the client wants to get the weather data of London. The implementation of GET requests in this use case would look like:
import requests
response = requests.get("https://api.example.com/data", params={"param1": "value1", "param2": "value2"})
# Print the response
print(response.status_code)
print(response.json()) # Assuming the response is in JSON format
POST
When a user wants to create a new user in a hypothetical API. And wants to send the following JSON data:
{
"username": "newuser",
"email": "newuser@example.com",
"password": "securepassword"
}
The following Python code sends a POST request with the specified data:
import requests
url = "https://api.example.com/users"
data = {
"username": "newuser",
"email": "newuser@example.com",
"password": "securepassword"
}
# Make the POST request
response = requests.post(url, json=data)
if response.status_code == 201:
print("User created successfully:", response.json())
else:
print("Error:", response.status_code, response.text)
PUT
When a client wants to update the information of a user with a specific ID.
import requests
url = "https://api.example.com/users/123"
data = {
"username": "updateduser",
"email": "updateduser@example.com"
}
# Make the PUT request
response = requests.put(url, json=data)
if response.status_code == 200:
print("User updated successfully:", response.json())
else:
print("Error:", response.status_code, response.text)
DELETE
When a client wants to delete a specific user. Here’s how it will look like in Python.
import requests
url = "https://api.example.com/users/123"
# Make the DELETE request
response = requests.delete(url)
if response.status_code == 204:
print("User deleted successfully.")
else:
print("Error:", response.status_code, response.text)
Conclusion
HTTP requests play a critical role in web interactions. Hence, it is essential to understand various request methods and how they work. However, the key to seamless communication lies in picking a suitable method. This also enhances the efficiency of web applications.
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Python
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04.10.2024
Reading time: 9 min
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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.
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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
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