Processing Lists of Data from APIs
APIs often return lists of data, especially when you request multiple results at once. Instead of a single value, the API response contains an array (or list) of items, such as a list of weather readings, several facts, or multiple images. The Cat Facts API, for example, has an endpoint /facts that returns a list of random cat facts. When you work with APIs like this, you need to know how to handle and process the lists they provide.
1234567891011import requests url = "https://catfact.ninja/facts?limit=5" response = requests.get(url) data = response.json() # The 'data' key contains a list of fact dictionaries facts = data["data"] for fact in facts: print(fact["fact"])
When the API returns a list of facts, you typically receive it as a list of dictionaries in Python after parsing the JSON response. To work with each fact individually, you can use a for loop to iterate through the list and print or process each item. This approach is common whenever you need to handle all items in a list, such as displaying them or performing calculations.
123456789101112131415import requests url = "https://catfact.ninja/facts?limit=5" response = requests.get(url) data = response.json() facts = data["data"] # Count how many facts contain the word 'cat' count = 0 for fact in facts: if "cat" in fact["fact"].lower(): count += 1 print(f"Number of facts containing the word 'cat': {count}")
Processing and analyzing lists of data from API responses is a crucial skill. Once you have the list, you can filter, count, or transform the items to extract meaningful insights. Whether you want to count facts mentioning a certain word, find the longest weather description, or summarize data, looping through the list allows you to perform these analyses efficiently.
1. Which Python structure is typically used to store a list of items from a JSON API response?
2. What is a common way to process each item in a list returned by an API?
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APIs often return lists of data, especially when you request multiple results at once. Instead of a single value, the API response contains an array (or list) of items, such as a list of weather readings, several facts, or multiple images. The Cat Facts API, for example, has an endpoint /facts that returns a list of random cat facts. When you work with APIs like this, you need to know how to handle and process the lists they provide.
1234567891011import requests url = "https://catfact.ninja/facts?limit=5" response = requests.get(url) data = response.json() # The 'data' key contains a list of fact dictionaries facts = data["data"] for fact in facts: print(fact["fact"])
When the API returns a list of facts, you typically receive it as a list of dictionaries in Python after parsing the JSON response. To work with each fact individually, you can use a for loop to iterate through the list and print or process each item. This approach is common whenever you need to handle all items in a list, such as displaying them or performing calculations.
123456789101112131415import requests url = "https://catfact.ninja/facts?limit=5" response = requests.get(url) data = response.json() facts = data["data"] # Count how many facts contain the word 'cat' count = 0 for fact in facts: if "cat" in fact["fact"].lower(): count += 1 print(f"Number of facts containing the word 'cat': {count}")
Processing and analyzing lists of data from API responses is a crucial skill. Once you have the list, you can filter, count, or transform the items to extract meaningful insights. Whether you want to count facts mentioning a certain word, find the longest weather description, or summarize data, looping through the list allows you to perform these analyses efficiently.
1. Which Python structure is typically used to store a list of items from a JSON API response?
2. What is a common way to process each item in a list returned by an API?
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