Using Lambda Functions to Process Data from an API with `requests` in Python

2 min read . June 26, 2021

Python offers a lot of flexibility in data processing, especially when working with data retrieved from APIs. One efficient way to process data quickly is by using lambda functions, which are small anonymous functions that can be used for simple tasks. How to use lambda functions in conjunction with the requests library to fetch and process data from an API.

1. Fetching Data from an API

The first step is to retrieve data from an API using the requests library. Here’s an example of how to fetch data from an API:

import requests

response = requests.get("https://jsonplaceholder.typicode.com/posts")
data = response.json()

In this example, we’re using the JSONPlaceholder API, which provides fake JSON data for testing and development. We’re fetching a list of posts.

2. Processing Data with Lambda Functions

Suppose we want to extract the titles (title) from each post. We can use a lambda function to do this simply and quickly.

Here’s how you can achieve this:

import requests

# Fetch data
response = requests.get("https://jsonplaceholder.typicode.com/posts")
data = response.json()

# Use lambda to extract titles
titles = list(map(lambda post: post['title'], data))

# Print titles
for title in titles:
    print(title)

3. Explanation of the Implementation

Lambda Function: A lambda function is an anonymous function used for small operations. In this case, we’re using a lambda function to extract the title value from each post object in the data list.
map() Function: The map() function applies a given function to each item in the data list (which consists of posts). The lambda function is applied to each item, resulting in a new list containing all the titles.
list(): The map() function returns a map object, so we need to convert it to a list using list() to access and display the results.

4. Example Output

With the above example, you will get a list of titles from all posts:

sunt aut facere repellat provident occaecati excepturi optio reprehenderit
qui est esse
ea molestias quasi exercitationem repellat qui ipsa sit aut
eum et est occaecati
... and so on

5. Another Example of Using Lambda

Lambda functions can be used for various operations. For instance, you might want to filter posts that contain a specific keyword in their title:

# Use lambda to filter posts with a certain keyword
keyword = "qui"
filtered_posts = list(filter(lambda post: keyword in post['title'], data))

# Print filtered post titles
for post in filtered_posts:
    print(post['title'])

In this example, we’re using filter() with a lambda function to filter posts where the title contains the keyword “qui”.

Conclusion

Lambda functions in Python are very useful for small and quick operations, especially when working with data from APIs. By using lambda functions, you can process and filter data more efficiently and cleanly. They are a powerful tool for data processing and are well-suited for simple yet frequently used operations in application development and data analysis.

Tags:

Python