HTTP, JSON, REST APIs, and Python Requests

Overview

Modern software applications rarely operate in isolation. Web applications, mobile apps, AI systems, dashboards, and data pipelines frequently need to communicate with external services to exchange information.

This communication is typically built upon four core components:

1. HTTP – The communication protocol used to transmit data.
2. JSON – A lightweight format used to represent data.
3. REST – A common architectural style for designing APIs.
4. Requests – A Python library used to interact with APIs.

Understanding how these components work together is fundamental for backend development, data science, machine learning, automation, and AI engineering.

1. HTTP (HyperText Transfer Protocol)

Definition

HTTP is a communication protocol that enables clients and servers to exchange information over a network.

A client sends an HTTP request, and a server responds with an HTTP response.

Client  ─── Request ───► Server
Client ◄── Response ─── Server

Common Use Cases

• Loading web pages
• Accessing APIs
• Downloading files
• Sending form data
• Communicating with cloud services

Request Structure

An HTTP request typically contains:

Method
URL
Headers
Body (optional)

Example:

GET /users/101 HTTP/1.1
Host: api.example.com

Response Structure

An HTTP response typically contains:

Status Code
Headers
Body

Example:

HTTP/1.1 200 OK
Content-Type: application/json

2. JSON (JavaScript Object Notation)

Definition

JSON is a lightweight, language-independent data format used to exchange information between systems.

Although it originated from JavaScript syntax, it is now supported by virtually every modern programming language.

JSON Data Types

JSON TypePython EquivalentObjectDictionaryArrayListStringStringNumberint / floatBooleanTrue / FalseNullNone

Example JSON

{
    "id": 101,
    "name": "Anunaya",
    "role": "AI Engineer",
    "active": true
}

Working with JSON in Python

import json

user = {
    "name": "Anu",
    "role": "AI Engineer"
}

json_string = json.dumps(user)
python_object = json.loads(json_string)

Conversion Functions

FunctionPurposejson.dumps()Python Object → JSON Stringjson.loads()JSON String → Python Object3. APIs (Application Programming Interfaces)

Definition

An API is a set of rules that allows one software application to communicate with another.

APIs act as intermediaries between systems.

Application A
      │
      ▼
     API
      │
      ▼
Application B

Examples

• Weather APIs
• Payment APIs
• Social Media APIs
• AI Model APIs
• Mapping APIs

Examples:

• OpenAI API
• Google Maps API
• GitHub API
• Stripe API

APIs define:

• Available operations
• Required inputs
• Expected outputs
• Authentication requirements

4. REST (Representational State Transfer)

Definition

REST is an architectural style commonly used for designing web APIs.

REST treats information as resources that can be identified using URLs.

Examples:

/users
/products
/orders

Individual resources are typically represented as:

/users/101
/products/55
/orders/9001

Characteristics of RESTful APIs

• Resource-oriented
• Stateless
• Uses standard HTTP methods
• Supports predictable URL structures

5. HTTP Methods in REST APIs

GET

Retrieve data.

GET /users/101

Expected outcome:

{
    "id": 101,
    "name": "Anunaya"
}

POST

Create a new resource.

POST /users

Request Body:

{
    "name": "John"
}

PUT

Replace an existing resource.

PUT /users/101

PATCH

Partially update a resource.

PATCH /users/101

DELETE

Remove a resource.

DELETE /users/101

6. Relationship Between HTTP, JSON, and REST

These technologies solve different problems.

TechnologyResponsibilityHTTPData TransportRESTAPI Design StyleJSONData Representation

Example Flow:

Python Application
        │
        ▼
HTTP Request
        │
        ▼
REST API
        │
        ▼
JSON Response
        │
        ▼
Python Object

7. The Requests Library

Why Requests?

Python's standard library contains modules such as urllib for making HTTP requests.

However, handling requests manually can become verbose.

The requests library provides a simpler and more readable interface.

Installation:

pip install requests

8. Making GET Requests

Basic Example

import requests

response = requests.get(
    "https://jsonplaceholder.typicode.com/users"
)

print(response.status_code)

Output:

200

9. Understanding Response Objects

A response object contains several useful attributes.

response.status_code
response.headers
response.text
response.json()

Common Attributes

AttributeDescriptionstatus_codeHTTP status codeheadersResponse metadatatextRaw response contentjson()Parsed JSON response

Example:

users = response.json()

print(users[0]["name"])

10. Common HTTP Status Codes

CodeMeaning200Success201Resource Created204Success (No Content)400Bad Request401Unauthorized403Forbidden404Not Found500Internal Server Error11. Sending Data Using POST Requests

Example

import requests

payload = {
    "name": "Anu",
    "role": "AI Engineer"
}

response = requests.post(
    "https://api.example.com/users",
    json=payload
)

What json= Does

The json= parameter automatically:

1. Converts Python dictionaries into JSON.
2. Sets the Content-Type: application/json header.
3. Sends the JSON data in the request body.

12. End-to-End API Workflow

The complete interaction follows a simple sequence.

Step 1:
Python Application

Step 2:
requests Library Sends HTTP Request

Step 3:
REST API Receives Request

Step 4:
Server Processes Request

Step 5:
Server Returns JSON Response

Step 6:
requests Converts JSON Into Python Objects

Step 7:
Application Uses Returned Data

Key Takeaways

• HTTP is the protocol used for communication.
• JSON is the format used to exchange data.
• APIs enable communication between applications.
• REST is a popular style for designing APIs.
• Requests is Python's most widely used HTTP client library.
• Most modern applications rely on the combination of HTTP, REST APIs, JSON, and Requests.

Understanding these concepts provides the foundation for working with web development, automation, data engineering, AI systems, and modern software integrations.