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Python JSON serialization bug renders 1.6% of LLM interview reports unreadable

By PulseAugur Editorial · [1 sources] ·

A bug in the Preterview interview practice platform caused approximately 1.6% of user reports to become unreadable due to the handling of NaN values. Python's `json.dumps` function, by default, serializes `NaN` (Not a Number) values, which are not compliant with the JSON standard. JavaScript's `JSON.parse` function then fails to parse these reports, leading to an infinite loading state for users. The issue stemmed from an interviewer style that frequently omitted technical questions, resulting in all `NaN` values for the technical depth scoring category, which `numpy.nanmean` then returned as `NaN`. AI

IMPACT Highlights the critical need for robust data serialization and parsing in LLM-powered applications, especially when integrating with standard web technologies.

RANK_REASON A bug in a specific software product (Preterview) caused a functional issue.

Read on dev.to — LLM tag →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Python JSON serialization bug renders 1.6% of LLM interview reports unreadable

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26 / 100
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Tool
A bug in a specific software product (Preterview) caused a functional issue.
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Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
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product, infra
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High
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Breaking (< 6h)
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COVERAGE [1]

  1. dev.to — LLM tag TIER_1 English(EN) · jidonglab ·

    json.dumps Writes NaN by Default: 31 LLM Reports JSON.parse Rejected

    <p>Nine people emailed me the same screenshot: a spinner and the line "Your report is being prepared." One of them had been looking at it for 51 hours.</p> <p>The report was done. It had been done since about 40 seconds after their session ended. It was sitting in object storage …

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