How to Process Sizeable JSON Files Without Memory Errors in Python?

Reading Sizeable JSON Files

Loading large JSON files into Python can pose memory challenges due to the default behavior of JSON decoders. These decoders typically load the entire file into memory, resulting in MemoryErrors for massive files.

The key to addressing this issue lies in utilizing a streaming approach rather than loading the entire file in one go. This involves reading and processing data in smaller chunks.

Solution: JSON Streaming

One effective solution is to implement the streaming approach with the ijson module. Ijson treats JSON as a stream, allowing for iterative processing of the data without holding the entire file in memory.

Code Example

<code class="python">from ijson import items

with open('file.json', 'r') as f:
    for event, value in items(f):
        # Process the current event and value
        pass</code>

In this example, the ijson module iterates over the JSON data, providing events and values for processing. This avoids loading the entire file into memory, resolving the initial memory error.

Alternative Solutions

Other notable solutions include:

• json-streamer: A library designed explicitly for streaming large JSON files.
• bigjson: A tool that converts JSON files into a binary format for more efficient processing.

By leveraging streaming techniques, you can effectively load and handle large JSON files without encountering memory constraints.

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