How to Efficiently Load Large JSON Files without Overloading System Memory?

Efficient and Swift Loading of Voluminous JSON Files

Loading large JSON files can often strain system memory resources when using the straightforward json.load() method. This issue stems from the need to load the entire file's contents into memory at once.

A potential solution is to leverage partial file loading techniques. In the case of line-delimited text files, one can iterate over lines. Is there an analogous approach for JSON files?

ijson: A SAX-Like Parser for JSON

A solution to this problem is found in the ijson library. This library offers a SAX-like parsing approach, similar to how the SAX library handles XML. The following outlines a sample usage:

<code class="python">import ijson

for prefix, the_type, value in ijson.parse(open(json_file_name)):
    print(prefix, the_type, value)</code>

In this code, prefix represents the dot-separated index within the JSON tree, the_type specifies a SAX-style event type (e.g., start/end of map/array, null, string, etc.), and value is the object's value or None if the_type is an event.

Limitations and Tips

Note that ijson assumes key names don't contain dots. Additionally, its documentation is somewhat limited. It's recommended to explore the source code to gain a deeper understanding of its functionality.

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