How Can I Load and Parse Large JSON Files Without Overloading My Memory?

Memory-Efficient and Fast Loading of Large JSON Files

Loading large JSON files into memory using conventional methods can consume excessive resources. However, there exists an alternative approach that allows for efficient partial reading of JSON content.

Similar to iterating over lines in a text file, ijson provides an analogy for parsing JSON data incrementally. This library enables users to parse JSON objects without loading the gesamte file into memory.

To utilize ijson, one can employ the following approach:

<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-delimited path within the JSON tree, the_type indicates the event type ('start_map', 'end_map', etc.), and value contains the actual value associated with the event.

Using ijson, developers can effectively parse large JSON files incrementally, preserving memory while efficiently accessing data.

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