Working with APIs in Python – Fetching & Handling Data Using requests

Working with APIs in Python – Fetching & Handling Data Using requests

If you are learning Python and want to build real-world applications, understanding APIs is very important.

Almost every modern application — from weather apps to payment gateways — uses APIs.

In this blog, you’ll learn:

  • What an API is

  • What the requests library does

  • How to fetch data from an API

  • How to handle JSON responses

  • How to handle errors properly

  • A real example project

What is an API?

API stands for Application Programming Interface.It allows two applications to communicate with each other.

For example:

  • A weather app gets data from a weather API

  • A payment app connects to a bank’s API

  • A website fetches data from a backend server

When you work as a Python developer (especially in web development with frameworks like Django or Flask), APIs are everywhere.

What is the requests Library?

requests is a popular Python library used to:

  • Send HTTP requests

  • Fetch data from APIs

  • Send data to servers

  • Handle responses easily

It is simple and beginner-friendly.

Install requests

pip install requests

Making Your First API Request

Let’s fetch sample data from a free API.

We’ll use:
https://jsonplaceholder.typicode.com/posts

import requests

url = "https://jsonplaceholder.typicode.com/posts"

response = requests.get(url)

print(response.status_code)
print(response.text)

Output:

  • 200 → Success

  • response.text → Raw data from the API

Understanding JSON Data

Most APIs return data in JSON format.Instead of using response.text, we use:

data = response.json()
print(data[0])

Now the response becomes a Python list or dictionary.

Example output:

{
  'userId': 1,
  'id': 1,
  'title': '...',
  'body': '...'
}

Now you can access values like:

print(data[0]['title'])

Handling Errors Properly

Good developers always handle errors.

import requests

url = "https://jsonplaceholder.typicode.com/posts"

try:
    response = requests.get(url)
    response.raise_for_status()
    data = response.json()
    print("First title:", data[0]['title'])

except requests.exceptions.HTTPError as err:
    print("HTTP Error:", err)

except requests.exceptions.ConnectionError:
    print("Connection Error")

except requests.exceptions.Timeout:
    print("Timeout Error")

except requests.exceptions.RequestException:
    print("Something went wrong")

This makes your application safe and professional.

Sending Data to an API (POST Request)

You can also send data.

import requests

url = "https://jsonplaceholder.typicode.com/posts"

payload = {
    "title": "My Post",
    "body": "This is my content",
    "userId": 1
}

response = requests.post(url, json=payload)

print(response.status_code)
print(response.json())

Common HTTP Methods:

  • GET → Fetch data

  • POST → Create data

  • PUT → Update data

  • DELETE → Remove data

Real-World Example – Weather App

You can build:

  • Weather checker

  • Crypto price tracker

  • News headline app

  • Movie search app

  • Job listing fetcher

All of these use APIs.

Working with API Keys

Many APIs require an API key for authentication.

Example:

url = "https://api.example.com/data?apikey=YOUR_API_KEY"

Never share your API key publicly.

Best Practices

✔ Always check status_code
✔ Use try-except
✔ Keep API keys secret
✔ Use .json() instead of .text
✔ Read API documentation carefully


Why Learning APIs is Important for Your Career

If you want to become:

  • Python Developer

  • Backend Developer

  • Data Analyst

  • Automation Engineer

APIs are a must-know skill.Companies expect developers to:

  • Integrate third-party services

  • Build REST APIs

  • Handle JSON data

Working with APIs using requests is simple and powerful.

Once you master this:

  • You can build real-world applications

  • You can connect your projects to live data

  • You become industry-ready


Comments

Post a Comment

Popular posts from this blog

Database Integration in FastAPI (SQLAlchemy CRUD)

  Introduction So far, we’ve built APIs without storing data.But real-world applications need a database to: Store user data. Manage products. Persist application state. In this blog, we’ll connect FastAPI with a database using SQLAlchemy and perform CRUD operations . What is SQLAlchemy? SQLAlchemy is a powerful Python ORM (Object Relational Mapper) that allows you to: Interact with databases using Python code. Avoid writing raw SQL queries. Work with models instead of tables. Step 1: Install Dependencies pip install sqlalchemy (For SQLite, no extra driver needed) Project Structure Update app/ ├── main.py ├── database/ │ ├── connection.py ├── models/ │ ├── item.py ├── schemas/ │ ├── item.py ├── routes/ │ ├── item.py Step 2: Database Connection app/database/connection.py from sqlalchemy import create_engine from sqlalchemy . orm import sessionmaker , declarative_base DATABASE_URL = "sqlite:///./test.db" engine = create_engine ( DAT...
Read more

Middleware & CORS in FastAPI

  Introduction As your API grows, you may need to: Log requests Modify responses Handle cross-origin requests This is where Middleware and CORS (Cross-Origin Resource Sharing) come into play.They help control how requests and responses flow through your application. What is Middleware? Middleware is a function that runs: Before a request reaches your route After a response is returned Think of it as a pipeline layer between client and server. Request Flow with Middleware Client → Middleware → Route → Middleware → Response Creating Custom Middleware from fastapi import FastAPI , Request import time app = FastAPI () @ app . middleware ( "http" ) async def log_requests ( request : Request , call_next ): start_time = time . time() response = await call_next ( request ) process_time = time . time() - start_time print ( f"Request: { request . url} | Time: { process_time } " ) return response What This Middle...
Read more

Python Data Handling

Python Data Handling for Beginners In Python, data handling means storing, changing, and using data in different ways. In this post, you will learn: Lists Tuples Dictionaries Sets String Methods Type Conversion 1. Python Lists :Lists store many values in one variable.                fruits = ["apple", "banana", "mango"]                                                                       Method                          Use                                            append()          ...
Read more