Python httpx.stream_json() Guide: Stream JSON Data

Python's httpx library is a powerful tool for making HTTP requests. One of its standout features is the ability to stream JSON data using httpx.stream_json(). This method is particularly useful when dealing with large datasets that you don't want to load into memory all at once.

What is httpx.stream_json()?

The httpx.stream_json() method allows you to stream JSON data from an HTTP response. This is especially useful when you're working with large JSON files or APIs that return a lot of data. Instead of loading the entire JSON response into memory, you can process it in chunks.

This method is part of the httpx library, which is designed to be a fully featured HTTP client for Python. It supports both synchronous and asynchronous requests, making it a versatile choice for many different types of projects.

Why Use httpx.stream_json()?

When dealing with large JSON responses, loading the entire dataset into memory can be inefficient and may even cause your application to crash due to memory constraints. httpx.stream_json() solves this problem by allowing you to process the data in smaller, more manageable chunks.

This approach not only saves memory but also allows you to start processing the data as soon as the first chunk is received, rather than waiting for the entire response to be downloaded.

How to Use httpx.stream_json()

Using httpx.stream_json() is straightforward. Below is an example that demonstrates how to stream JSON data from an API:

import httpx

# Make a request to an API that returns a large JSON response
with httpx.stream("GET", "https://api.example.com/large-data") as response:
    # Stream the JSON data
    for chunk in response.stream_json():
        print(chunk)

In this example, we make a GET request to an API that returns a large JSON response. Instead of loading the entire response into memory, we use response.stream_json() to process the data in chunks.

Example Output

Here's what the output might look like when streaming JSON data:

{'id': 1, 'name': 'Item 1'}
{'id': 2, 'name': 'Item 2'}
{'id': 3, 'name': 'Item 3'}
...

Each chunk is a dictionary representing a part of the JSON response. You can process each chunk as it arrives, allowing you to handle large datasets efficiently.

Handling Errors

When streaming JSON data, it's important to handle errors gracefully. If the API returns an invalid JSON response, httpx.stream_json() will raise a httpx.JSONDecodeError. You can catch this exception and handle it appropriately:

import httpx

try:
    with httpx.stream("GET", "https://api.example.com/large-data") as response:
        for chunk in response.stream_json():
            print(chunk)
except httpx.JSONDecodeError:
    print("Invalid JSON response")

This ensures that your application doesn't crash if the API returns an invalid JSON response.

Conclusion

The httpx.stream_json() method is a powerful tool for efficiently handling large JSON responses in Python. By streaming the data in chunks, you can save memory and start processing the data as soon as it arrives. This makes it an ideal choice for working with large datasets or APIs that return a lot of data.

For more information on related topics, check out our guides on Python httpx.stream_text(), Python httpx.QueryParams(), and Python httpx.URL().