Working with APIs in Python

June 28, 2025

Modern applications often need to connect to external services—fetching weather forecasts, stock prices, sending emails, or integrating with social media platforms. These interactions are usually done via APIs (Application Programming Interfaces), which enable software to exchange data and functionality over the web. Python, with its rich ecosystem of libraries, makes working with APIs straightforward and efficient.

Understanding APIs and HTTP Requests

Most web APIs today follow the REST architecture, using HTTP methods like GET, POST, PUT, and DELETE to perform operations. When working with APIs, you send HTTP requests and parse the responses, which are usually in JSON or XML format.

Using the Requests Library

The go-to tool for HTTP requests in Python is the requests library. It offers a simple interface for making calls to APIs. Here’s an example of a GET request to fetch data from a public API:

import requests

response = requests.get("https://api.coindesk.com/v1/bpi/currentprice.json")

if response.status_code == 200:

data = response.json()

print("Bitcoin Price (USD):", data["bpi"]["USD"]["rate"])

else:

print("API request failed with status code:", response.status_code)

This example fetches the current Bitcoin price from the CoinDesk API, parses the JSON response, and prints the price in USD.

Sending Data with POST Requests

APIs often require you to send data, such as creating new records or submitting forms. Here’s how you might send a POST request with a JSON payload:

url = "https://api.example.com/tasks"

payload = {"title": "Buy groceries", "due": "2025-07-01"}

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

if response.status_code == 201:

print("Task created successfully!")

else:

print("Failed to create task:", response.text)

Adding Headers and Authentication

Many APIs require API keys, tokens, or other forms of authentication. You can include them in the request headers:

headers = {

"Authorization": "Bearer YOUR_ACCESS_TOKEN",

"Accept": "application/json"

}

response = requests.get("https://api.example.com/user", headers=headers)

Handling Errors Gracefully

Always check the status code and handle potential errors, such as timeouts or invalid responses. You can also set a timeout to avoid hanging requests:

try:

response = requests.get("https://api.example.com/data", timeout=5)

response.raise_for_status() # Raises HTTPError for bad responses

except requests.exceptions.RequestException as e:

print("Error:", e)

Working with Pagination

Some APIs limit the number of results per request and use pagination. You’ll need to loop through pages until all data is fetched:

url = "https://api.example.com/items?page=1"

while url:

response = requests.get(url).json()

for item in response["data"]:

print(item)

url = response.get("next") # Next page URL or None

Conclusion

Python’s intuitive syntax and powerful libraries make it ideal for working with APIs. By mastering the basics of sending requests, handling responses, managing authentication, and dealing with errors, you can integrate your Python applications with a vast array of services and data sources—unlocking countless possibilities for automation, data analysis, and dynamic web development.

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