Parsing large JSON files with Pydantic can lead to peak memory usage that exceeds 20 times the file size. For instance, a 100MB file could require about 2000MB of memory. To mitigate this issue, alternatives like the `ijson` library can be used for memory-efficient parsing by reading the JSON incrementally. Although this approach may slow down the parsing process, it significantly reduces memory consumption, making it feasible to handle larger datasets without running out of memory.
"Using Pydantic for large JSON files can lead to excessive memory usage, exceeding 20 times the file size. This poses significant challenges for handling large datasets efficiently."
"By switching to ijson, we can streamline the process of parsing JSON incrementally, reducing memory usage significantly, even though it may slow down the parsing speed."
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