APIs

On This Page

• 19.1  What is a REST API?
• 19.2  The requests Library
• 19.3  Working with JSON Responses
• 19.4  Authentication
• 19.5  Handling Errors & Status Codes
• 19.6  Mini Project — Weather Data Fetcher
• 19.7  Practical Exercises
• 19.8  Module Quiz (MCQs)
• 19.9  Module Assignment
• 19.10  Interview Questions — Module 19
• 19.11  Student Notes Page

Module 19: APIs

19.1  What is a REST API?

An API (Application Programming Interface) lets two different software systems talk to each other. A REST API is the most common type on the web — you send a request to a URL, and the server sends back data, usually in JSON format.

Think of an API like a restaurant waiter: you (the client) place an order (request), the kitchen (server) prepares it, and the waiter brings back your food (response).

19.2  The requests Library

The requests library is Python's most popular tool for making HTTP calls to APIs — simple, readable, and beginner-friendly.

pip install requests

import requests

response = requests.get("https://api.github.com/users/octocat")
print(response.status_code)   # 200 means success
print(response.json())        # convert response to a Python dict

19.3  Working with JSON Responses

API responses are almost always JSON — which converts directly into a Python dictionary or list, letting you extract exactly the fields you need.

data = response.json()
print(data["login"])         # username
print(data["public_repos"])  # number of public repos

# If the API returns a list of records:
# for item in data:
#     print(item["name"])

19.4  Authentication

Many APIs require authentication to identify who is making the request — most commonly via an API key passed in the URL, headers, or as a query parameter.

import requests

API_KEY = "your_api_key_here"
url = "https://api.openweathermap.org/data/2.5/weather"
params = {"q": "Delhi", "appid": API_KEY, "units": "metric"}

response = requests.get(url, params=params)
data = response.json()
temp = data["main"]["temp"]
print(f"Temperature in Delhi: {temp}°C")

19.5  Handling Errors & Status Codes

response = requests.get(url, params=params)

if response.status_code == 200:
    data = response.json()
    print("Success:", data)
else:
    print(f"Error {response.status_code}: Could not fetch data")

19.6  Mini Project — Weather Data Fetcher

import requests

def get_weather(city, api_key):
    url = "https://api.openweathermap.org/data/2.5/weather"
    params = {"q": city, "appid": api_key, "units": "metric"}
    response = requests.get(url, params=params)

    if response.status_code != 200:
        return None

    data = response.json()
    return {
        "city": city,
        "temperature": data["main"]["temp"],
        "condition": data["weather"][0]["description"]
    }

result = get_weather("Mumbai", "YOUR_API_KEY")
if result:
    print(f"{result['city']}: {result['temperature']}°C, {result['condition']}")

19.7  Practical Exercises

Basic (5 Questions)

1. Make a GET request to a free public API (e.g. https://api.github.com/users/github) and print the status code.

2. Convert an API response into a Python dictionary using .json().

3. Extract 3 specific fields from a JSON API response.

4. Print a friendly message combining 2 fields from an API response using an f-string.

5. Check if a response's status code is 200 before printing its data.

Intermediate (5 Questions)

1. Use the params argument in requests.get() to send a search query to an API.

2. Write a function that takes a city name and returns weather data from a public weather API.

3. Handle a 404 error gracefully by printing a custom 'not found' message.

4. Loop through a JSON response containing a list of items and print each one's name.

5. Save an API's JSON response directly to a local JSON file using the json module.

Advanced (5 Questions)

1. Build a 'Multi-City Weather Dashboard' that fetches and compares weather for 5 cities using a loop.

2. Fetch data from a public API and load the results directly into a Pandas DataFrame for analysis.

3. Build a function that retries a failed API request up to 3 times before giving up.

4. Combine API data with a local CSV (e.g. merge live currency exchange rates with a sales dataset).

5. Build a simple 'News Headline Fetcher' using a public news API, with graceful error handling for all status codes.

19.8  Module Quiz (MCQs)

19.9  Module Assignment

Assignment: Multi-City Weather Report Builder

• Choose a free public weather (or similar) API and get an API key.
• Write a function get_weather(city) that returns temperature and condition for any city.
• Fetch weather for 5 different cities using a loop and store results in a list of dictionaries.
• Convert the results into a Pandas DataFrame and export it as a CSV report.
• Handle any API errors (like an invalid city name) gracefully without crashing.

Expected Output: A working script that pulls live data from a real API for multiple cities and saves a clean, structured CSV report.

19.10  Interview Questions — Module 19

• Q: What is a REST API and why is it commonly used?
  A: A REST API allows two systems to communicate over HTTP using standard methods like GET and POST, and is widely used because it's simple, stateless, and works over any platform that supports web requests.
• Q: What is the difference between GET and POST requests?
  A: GET requests retrieve existing data from a server, while POST requests send new data to be created or processed on the server.
• Q: How do you handle authentication when calling an API?
  A: Most APIs require an API key, often passed as a query parameter or in the request headers, to identify and authorize the caller.
• Q: What would you do if an API call fails?
  A: Check the response's status code to understand the failure type, handle it gracefully with a try-except or conditional check, and avoid letting the program crash — potentially retrying for transient errors.

19.11  Student Notes Page

Use this space to write down key points, doubts, and your own examples from today's session.