🌐 [translation-sync] [need_for_speed.md] Update np.random → Generator API

[mmcky]

Automated Translation Sync

This PR contains automated translations from QuantEcon/lecture-python-programming.

Source PR

#545 - [need_for_speed.md] Update np.random → Generator API

Files Updated

• ✏️ lectures/need_for_speed.md
• ✏️ .translate/state/need_for_speed.md.yml

Details

• Source Language: en
• Target Language: zh-cn
• Model: claude-sonnet-4-6

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This PR was created automatically by the translation action.

[github-actions]

✅ Translation Quality Review

Verdict: PASS | Model: claude-sonnet-4-6 | Date: 2026-05-05

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📝 Translation Quality

Criterion	Score
Accuracy	9/10
Fluency	9/10
Terminology	9/10
Formatting	10/10
Overall	9.2/10

Summary: The translation of the 'Vectorization vs pure Python loops' section is accurate, fluent, and well-formatted. The technical content is faithfully rendered, code comments are appropriately translated, and the list structure is preserved. No significant issues were found in this changed section. The three-step breakdown of vectorized operations (生成、求平方、求和) accurately mirrors the English source Code comment translation '# 将累加并存储总和' naturally conveys the meaning of '# Will accumulate and store sum' Technical term '批量算子' for 'batch operators' is appropriate in context The phrase '均匀分布的随机数' accurately conveys 'uniforms' in the statistical sense

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🔍 Diff Quality

Check	Status
Scope Correct	✅
Position Correct	✅
Structure Preserved	✅
Heading-map Correct	✅
Overall	10/10

Summary: The translation target document correctly mirrors the single source change: replacing np.random.uniform(0, 1, n) with rng = np.random.default_rng() / rng.uniform(0, 1, n) in the vectorized code cell, at the same relative position within the 'Vectorization vs pure Python loops' section, with no structural or metadata changes required.

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This review was generated automatically by action-translation review mode.

[Copilot]

Pull request overview

This automated translation-sync PR updates the zh-cn lecture content to match upstream changes that migrate from the legacy np.random global API to the newer NumPy Generator API, and refreshes the corresponding translation state metadata.

Changes:

• Updated the NumPy random sampling example to use rng = np.random.default_rng() and rng.uniform(...) instead of np.random.uniform(...).
• Updated .translate/state/need_for_speed.md.yml with the new upstream source-sha and synced-at date.

Reviewed changes

Copilot reviewed 2 out of 2 changed files in this pull request and generated no comments.

File	Description
lectures/need_for_speed.md	Switches the vectorization example from np.random.uniform to the Generator API (default_rng().uniform).
.translate/state/need_for_speed.md.yml	Updates translation-sync metadata (source-sha, synced-at) to reflect the new upstream source version.

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