Here are a few title options, tailored to be question-based and reflecting the article\'s focus on handling large JSON files: Option 1 (More general): * How to Process Extremely Large JSON Files Wit

Reading Extremely Large JSON Files without Breaking Memory

Attempting to load substantial JSON files directly into memory using standard Python methods can result in a "MemoryError." This occurs because these methods attempt to read the entire file before parsing it, consuming excessive memory.

To overcome this issue, it is necessary to process the files incrementally as streams, reading portions at a time for immediate processing. ijson is a valuable library for this purpose, offering a streaming JSON parser.

Here is an example of how you can use ijson to stream a large JSON file:

<code class="python">import ijson

with open('large_file.json', 'r', encoding='utf-8') as f:
    parser = ijson.parse(f)

    for prefix, event, value in parser:
        # Process the current event and value
        if prefix and event == 'map_key':
            # Handle the key for a new object
            key = value
        elif event == 'string':
            # Handle the value for a string
            val = value</code>

As you iterate through the stream, you can process the data incrementally without exceeding memory limits. Other libraries mentioned in the discussion, such as json-streamer and bigjson, provide similar functionality. By utilizing these tools, you can effectively handle extremely large JSON files without encountering memory errors.

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