🌐 [translation-sync] Small edits

[mmcky]

Automated Translation Sync

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

Source PR

#526 - Small edits

Files Updated

• ✏️ lectures/numba.md
• ✏️ .translate/state/numba.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: 2026-04-13

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📝 Translation Quality

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

Summary: The translation of the modified sections is of high quality overall. The new Sharp Bits section and its subsections (Typing and Global Variables) are accurately and fluently translated. The Base Version and Acceleration via Numba subsections are well-handled. The How and When it Works section and Overview modifications are accurate. Minor considerations include the translation of the section heading 'Sharp Bits' which loses some of its colloquial 'gotcha' nuance, and the 'Typing' heading which is rendered as '类型推断' (Type Inference) rather than the broader '类型问题'. These are minor issues that don't significantly impact comprehension. All formatting, math, and code blocks are preserved correctly. Accurate translation of JIT compilation concepts, correctly rendering 'just-in-time compilation' as '即时编译' throughout The new Sharp Bits section (## 注意事项) and its subsections (### 类型推断, ### 全局变量) are well-structured and accurately convey the technical content about Numba limitations The Added sections 'Base Version' (#### 基础版本) and 'Acceleration via Numba' (#### 通过 Numba 加速) are clearly translated and maintain proper technical terminology Multithreaded Loops section accurately translates parallel computing concepts including 'prange' usage and the explanation of parallelization across households vs. time The admonition block 'Remark' is correctly translated as '备注' and the decorator syntax explanation is accurate Mathematical notation and LaTeX formatting are fully preserved throughout all modified sections The translation of the global variables gotcha explanation is accurate and preserves the warning emoji 😱

Suggestions:

• Sharp Bits section heading translation: 'Sharp Bits' → '注意事项' is acceptable but loses the nuance of 'sharp bits' implying specific pitfalls/gotchas. Consider '陷阱与注意事项' or keeping closer to the original intent with '潜在陷阱' to better capture that these are specific sharp edges users may hit.

• Typing section: The heading '类型推断' (Type Inference) is a reasonable translation, but the section is actually titled 'Typing' in the source, which covers broader typing issues. '类型问题' might be more accurate as it covers the broader concept of typing, not just inference.

• How and When it Works - 'on the fly' translation: '动态推断' correctly captures 'on the fly', which is good. No issue here.

• Overview - '内存消耗极大' for 'Highly memory-intensive': While accurate, '内存占用极高' is slightly more natural in Chinese technical writing for describing memory usage patterns.

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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 is correctly updated to reflect all structural changes from the English source, with the heading map accurately revised to match the new section hierarchy.

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

[Copilot]

Pull request overview

Automated translation sync for the zh-cn Numba lecture, aligning lectures/numba.md (and its translation state metadata) with the latest upstream edits from QuantEcon’s English source.

Changes:

• Updated translation frontmatter headings and internal anchors to match upstream structure.
• Refreshed several narrative/code sections (Numba intro, JIT usage examples, multithreading section) per upstream edits.
• Updated translation sync state (source-sha, synced-at, tool version, etc.).

Reviewed changes

Copilot reviewed 2 out of 2 changed files in this pull request and generated 1 comment.

File	Description
lectures/numba.md	Updates translated lecture content, headings mapping, and example code blocks to match upstream edits.
.translate/state/numba.md.yml	Updates translation-sync metadata (source commit, sync date, tool version, mode, section count).

Comments suppressed due to low confidence (1)

lectures/numba.md:118

• qm 的 for 循环体缩进不正确：for t in range(n): 下一行只有 2 个空格缩进，无法与外层缩进层级匹配，会导致 Python 抛出 IndentationError（或使循环体不在预期作用域内）。请将循环体缩进对齐到函数内的标准缩进层级。

def qm(x0, n, α=4.0):
    x = np.empty(n+1)
    x[0] = x0
    for t in range(n):
      x[t+1] = α * x[t] * (1 - x[t])
    return x

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[Copilot]

这里用 @jit 来演示“无法推断类型会抛错”不够可靠：jit 默认允许回退到 object mode，iterate(g, ...) 可能不会抛出错误，从而与上文叙述/注释（“This code throws an error”）不一致。若目标是稳定地产生类型推断失败的错误，请使用 @njit 或显式设置 nopython=True。