This repository holds a machine-generated draft of the QuantEcon Python Programming lectures in Chinese. Individual lectures have been reviewed as they were synced, but the edition has never had an end-to-end read by a Chinese speaker. That is what this issue tracks.
There is no deadline. Work through it whenever there is time, at whatever pace suits. One lecture a month is genuinely useful. Tick lectures off below as they are done.
What you are looking at
The precedent that matters: when the Persian edition was reviewed, the native speaker found meaning-inverting mistranslations that read perfectly fluently. A machine translation that reads well can still say the opposite of what the English says. A careful reading is the only thing that catches that.
Where to read
Unlike the French edition, this one is published — so read the live pages, linked in the checklist below. They render figures, maths and executed code output as a reader actually sees them, which the raw .md files do not.
To read the English side by side, the same file lives at lectures/<name>.md in the English repo.
How to submit feedback: one PR per lecture
- Create a branch, e.g.
review/numpy
- Edit
lectures/<name>.md directly — fix the Chinese as you would write it
- Open a PR titled e.g.
Review: numpy.md, referencing this issue
- Tick the lecture off in the checklist below
One PR per lecture, please — not one big PR. Smaller PRs are easier to discuss, and a disagreement about one lecture then does not hold up the other twenty-five.
Commenting rather than editing is completely fine too — a PR with notes, or a comment on this issue. Do not let the mechanics get in the way of the feedback.
What is most valuable
In rough order:
- Meaning errors. The Chinese says something the English does not. These matter most and are the ones only a human reader finds.
- Wrong technical terms. A term rendered in a way a Chinese economist or programmer would not recognise.
- Terminology that should be consistent but is not — the same English term rendered differently across lectures.
- Unnatural Chinese. Grammatically correct but not how anyone would write it. Academic register, please — these are teaching materials.
- Anything in the code that looks wrong. Code should not have been translated at all, but comments inside it were. The Persian review caught a genuine code bug this way.
Please do not spend time on these
- Anything wrong in the English. That is a source issue — raise it upstream instead and it will flow back here. Fixing it only in the Chinese makes the two editions diverge.
translation: blocks in the file header. Machine bookkeeping — please leave them alone.- Punctuation spacing around
—— and full-width marks. Convention in this edition is no space adjacent to ——; where the tooling has got that wrong it is a known class being fixed at the source rather than per-file.
Terminology is worth more than a file fix
If a term is wrong, it is probably wrong in several lectures. Rather than fixing each occurrence, say so and it can be pinned in the glossary — then every future translation gets it right automatically, including lectures nobody has reviewed yet.
What to check in each lecture
Condensed from the per-lecture checklists this issue replaces:
| Area |
What to look for |
| Prose |
accuracy against the English, fluency, consistent key terms, nothing left untranslated |
| Maths |
formulas render, notation matches the source, symbols agree with the surrounding text |
| Figures |
figures render, axis labels and captions translated where appropriate |
| Code |
cells run, comments translated accurately, prose variable names match the code |
| Links |
cross-references resolve, external links live, bibliography intact |
| Structure |
headings match the source, admonitions and directives render, no broken MyST |
| Edge cases |
proper nouns, numbers and units, full-width punctuation（，。；：！？）, stray English |
Lectures
status.md is excluded deliberately — it is an auto-generated {nb-exec-table} page with no translatable prose.
This repository holds a machine-generated draft of the QuantEcon Python Programming lectures in Chinese. Individual lectures have been reviewed as they were synced, but the edition has never had an end-to-end read by a Chinese speaker. That is what this issue tracks.
There is no deadline. Work through it whenever there is time, at whatever pace suits. One lecture a month is genuinely useful. Tick lectures off below as they are done.
What you are looking at
lecture-python-programming(English).translate/state/<name>.md.ymlThe precedent that matters: when the Persian edition was reviewed, the native speaker found meaning-inverting mistranslations that read perfectly fluently. A machine translation that reads well can still say the opposite of what the English says. A careful reading is the only thing that catches that.
Where to read
Unlike the French edition, this one is published — so read the live pages, linked in the checklist below. They render figures, maths and executed code output as a reader actually sees them, which the raw
.mdfiles do not.To read the English side by side, the same file lives at
lectures/<name>.mdin the English repo.How to submit feedback: one PR per lecture
review/numpylectures/<name>.mddirectly — fix the Chinese as you would write itReview: numpy.md, referencing this issueOne PR per lecture, please — not one big PR. Smaller PRs are easier to discuss, and a disagreement about one lecture then does not hold up the other twenty-five.
Commenting rather than editing is completely fine too — a PR with notes, or a comment on this issue. Do not let the mechanics get in the way of the feedback.
What is most valuable
In rough order:
Please do not spend time on these
translation:blocks in the file header. Machine bookkeeping — please leave them alone.——and full-width marks. Convention in this edition is no space adjacent to——; where the tooling has got that wrong it is a known class being fixed at the source rather than per-file.Terminology is worth more than a file fix
If a term is wrong, it is probably wrong in several lectures. Rather than fixing each occurrence, say so and it can be pinned in the glossary — then every future translation gets it right automatically, including lectures nobody has reviewed yet.
What to check in each lecture
Condensed from the per-lecture checklists this issue replaces:
Lectures
about_py.md— 关于本系列讲座autodiff.md— 自动微分探险debugging.md— 调试与错误处理functions.md— 函数getting_started.md— 入门指南intro.md— 面向经济学与金融学的Python编程jax_intro.md— JAXmatplotlib.md— Matplotlibnames.md— 名称与命名空间need_for_speed.md— 科学计算中的 Pythonnumba.md— Numbanumpy.md— NumPynumpy_vs_numba_vs_jax.md— NumPy vs Numba vs JAXoop_intro.md— OOP I：对象与方法pandas.md— Pandaspandas_panel.md— Pandas 面板数据polars.md— Polarspython_advanced_features.md— 更多语言特性python_by_example.md— 入门示例python_essentials.md— Python 基础要点python_oop.md— OOP II：构建类scipy.md— SciPysympy.md— SymPytroubleshooting.md— 故障排除workspace.md— 编写较长的程序writing_good_code.md— 编写高质量代码status.mdis excluded deliberately — it is an auto-generated{nb-exec-table}page with no translatable prose.