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Python's json.dumps default increases LLM prompt tokens by 24%

By PulseAugur Editorial · [1 sources] ·

A Python developer discovered that the default `ensure_ascii=True` setting in Python's `json.dumps` function significantly increased token usage and reduced accuracy when used in LLM prompts. Unlike JavaScript's `JSON.stringify`, `json.dumps` with this default setting converts non-ASCII characters into hexadecimal escape sequences. This caused Claude to misinterpret Japanese customer names and increased input tokens by 24% on average for a 2,000-ticket dataset. The fix involves setting `ensure_ascii=False` in `json.dumps` and related functions like pandas' `to_json`. AI

IMPACT Default settings in programming libraries can have significant, unforeseen impacts on LLM token usage and accuracy.

RANK_REASON Developer discovers a common programming library's default behavior negatively impacts LLM prompt processing.

Read on dev.to — LLM tag →

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

Python's json.dumps default increases LLM prompt tokens by 24%

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34 / 100
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Developer discovers a common programming library's default behavior negatively impacts LLM prompt processing.
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product, infra
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COVERAGE [1]

  1. dev.to — LLM tag TIER_1 Français(FR) · jidonglab ·

    Python json.dumps ensure_ascii: 24% More Claude Tokens, Wrong Kanji

    <p>The Python port of my support-ticket classifier used 24% more input tokens than the TypeScript version it replaced. Same model. Same system prompt. Same 2,000 tickets in the replay set.</p> <p>I spent an afternoon diffing prompts before I saw it. The TypeScript prompt said <co…

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