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Update build.py

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search-paths.js 中记录每篇笔记各小节在学习站中的面试题。
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CyC2018
2026-11-01 04:40:57 +08:00
parent 8355caaf4c
commit a4d7b6cf23
1 changed files with 10 additions and 2 deletions
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website/builder/build.py
+10 -2
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@@ -245,12 +245,19 @@ def build(optimize=True):
if learn_report['pending']:
print(prefix + '学习站：内容与 learn/content.lock.json 不一致，请在本机运行 python3 learn/maintain.py 查看并写入：'
+ json.dumps(learn_report['pending'], ensure_ascii=False), file=sys.stderr)
learn_topics = {}
learn_topics, learn_sections = {}, {}
if learn_report is not None:
# 每篇笔记在学习站中的题（题目的原文链接指向这篇笔记），文章末尾据此提示“读完练一练”，并按读者的记录写出练过几道
for question in json.loads((dist / 'learn' / 'data.json').read_text())['questions'].values():
for note in {link['note'] for link in question['links'] if link.get('note')}:
learn_topics.setdefault(note, []).append(question['id'])
# 小节标题下的“面试题”：笔记 → 小节锚点 → [题号, 题目, 热度]
for link in question['links']:
if link.get('note') and '?id=' in link['href']:
anchor = urllib.parse.unquote(link['href'].split('?id=', 1)[1])
entries = learn_sections.setdefault(link['note'], {}).setdefault(anchor, [])
if all(entry[0] != question['id'] for entry in entries):
entries.append([question['id'], question['text'], question['heat']])
copy_referenced_assets(dist, ROOT)
image_report = optimize_images(dist, CACHE) if optimize else {'converted': 0}
index_name, search_report = write_search_index(dist, sorted((dist / 'notes').glob('*.md')))
@@ -261,7 +268,8 @@ def build(optimize=True):
'window.CS_NOTES_LEGACY_ROUTES = ' + json.dumps(legacy, ensure_ascii=False, separators=(',', ':')) + ';\n'
'window.CS_NOTES_SEARCH_INDEX = "/' + index_name + '";\n'
'window.CS_NOTES_ANIMATIONS = ' + json.dumps(animations, ensure_ascii=False, separators=(',', ':')) + ';\n'
'window.CS_NOTES_LEARN_TOPICS = ' + json.dumps(learn_topics, ensure_ascii=False, separators=(',', ':')) + ';\n')
'window.CS_NOTES_LEARN_TOPICS = ' + json.dumps(learn_topics, ensure_ascii=False, separators=(',', ':')) + ';\n'
'window.CS_NOTES_LEARN_SECTIONS = ' + json.dumps(learn_sections, ensure_ascii=False, separators=(',', ':')) + ';\n')
generator = hashlib.sha256()
learn = [*LEARN_BUILD.parent.glob('*.py'), *(LEARN_BUILD.parent / 'src').rglob('*')] if LEARN_BUILD.is_file() else []
for resource in sorted([*Path(__file__).parent.glob('*.py'), *SITE.rglob('*'), *learn]):