How can I load large JSON files efficiently without consuming excessive memory?

Barbara Streisand
Release: 2024-10-27 00:53:02
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How can I load large JSON files efficiently without consuming excessive memory?

Delving into Memory-Efficient JSON File Loading

Loading large JSON files with memory constraints can pose a challenge. If using the standard json.load() function to read the entire file at once, memory consumption can surge. Fortunately, there are alternatives that enable partial file loading.

Introducing ijson: The SAX Parser for JSON

ijson, akin to SAX for XML, allows users to iteratively parse JSON files. This provides an analogy to line-by-line iteration in text files, addressing the memory concerns.

Using ijson to Load Portions of a JSON File

To utilize ijson for partial JSON file loading, follow these steps:

  1. Import the ijson library.
  2. Iterate over the file using ijson.parse(open(json_file_name)).
  3. For each prefix, type, and value, define the desired actions.

Example Code

Here is an example of using ijson to parse a JSON file:

<code class="python">import ijson
for prefix, the_type, value in ijson.parse(open(json_file_name)):
    print(prefix, the_type, value)</code>
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In this code, prefix represents the dot-separated index in the JSON tree, the_type indicates the SAX-like event, and value contains the object's value or None for event types.

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