Getting Started with APIs and Handling JSON Data

pip install requests

import requests

response = requests.get("https://api.open-notify.org/this-api-doesnt-exist")
print(response.status_code)  # Output: 404

import requests

response = requests.get("https://api.open-notify.org/astros.json")
astronaut_data = response.json()

# Display the JSON response in a readable format
print(json.dumps(astronaut_data, indent=4))

In this example, we retrieve information about astronauts currently in space. The response.json() method converts the API response (in JSON format) into a Python dictionary, making it easy to work with.

JSON Structure

JSON data is hierarchical and consists of key-value pairs. Understanding the structure of the JSON response is crucial for extracting relevant information. Let's break down the structure of the astronaut data we retrieved.

{
    "message": "success",
    "number": 6,
    "people": [
        {"craft": "ISS", "name": "Alexey Ovchinin"},
        {"craft": "ISS", "name": "Nick Hague"},
        {"craft": "ISS", "name": "Christina Koch"},
        {"craft": "ISS", "name": "Alexander Skvortsov"},
        {"craft": "ISS", "name": "Luca Parmitano"},
        {"craft": "ISS", "name": "Andrew Morgan"}
    ]
}

• message: Indicates the status of the API request.
• number: Represents the total number of people in space.
• people: A list containing information about each person, including their craft (in this case, the ISS) and name.

Using the json Library in Python

Python's built-in json library provides methods for encoding Python objects into JSON format (serialization) and decoding JSON data into Python objects (deserialization).

Serialization with json.dumps()

The json.dumps() function takes a Python object and returns a JSON-formatted string. This is particularly useful for displaying JSON data in a readable format.

import json

def jprint(obj):
    # Create a formatted string of the Python JSON object
    text = json.dumps(obj, sort_keys=True, indent=4)
    print(text)

# Display the formatted JSON response
jprint(astronaut_data)

The sort_keys=True argument sorts the keys in the output for better readability.

Deserialization with json.loads()

Conversely, the json.loads() function takes a JSON-formatted string and returns a Python object.

json_string = '{"message": "success", "number": 6, "people": [...]}'
python_object = json.loads(json_string)

Now that we've covered the basics, let's explore a practical example of working with JSON data retrieved from an API.

Practical Example: ISS Pass Times

We'll use the Open Notify API to get the next times the ISS will pass over a specific location. The API endpoint requires latitude (lat) and longitude (lon) parameters. Here's how we can achieve this.

import requests
from datetime import datetime

# Parameters for New York City
parameters = {"lat": 40.71, "lon": -74}

# Make a request to the API with parameters
response = requests.get("https://api.open-notify.org/iss-pass.json", params=parameters)
pass_times = response.json()["response"]

# Extract and print the pass times
for pass_time in pass_times:
    timestamp = pass_time["risetime"]
    formatted_time = datetime.fromtimestamp(timestamp)
    print(f"ISS will pass over at: {formatted_time}")

In this example, we extract the pass times and convert the timestamps into human-readable datetime objects.

Conclusion

Working with JSON data is an essential skill when interacting with APIs in Python. The requests library combined with the built-in json library provides a powerful toolset for making API requests, handling JSON responses, and extracting meaningful information.