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feat: 完成布局优化 - 操作列固定、批量按钮自适应、分类标签带数量

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优化内容:
1. 表格布局:
   - 使用 calc(100vw - 160px) 确保表格不超出视口
   - 操作列 fixed='right' 固定在右侧，宽度 300px
   - 按钮 3 个后自动换行 (max-width: 200px)
   - 恢复合理列宽，不再过度压缩

2. 批量操作区域:
   - 容器改为 inline-block，宽度自适应按钮内容
   - 背景宽度与按钮总宽度匹配

3. 分类标签:
   - 显示数量 (如 '待处理 (20)')
   - 点击切换筛选，去掉误导的 'X' 图标

4. 删除功能:
   - 操作列增加删除按钮
   - 删除前弹出确认对话框

5. 系统日志:
   - 修复后端日志路径 (parents[4])
   - 404 时显示友好提示

6. 其他:
   - 左侧菜单宽度 160px
   - 所有功能保留 (登录、用户管理、批量操作等)
This commit is contained in:
lt
2026-04-27 11:32:17 +08:00
parent 59d2a76df4
commit 277b13eaae
137 changed files with 8615 additions and 1213 deletions
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scripts/collector.py
+252 -140
View File
@@ -1,7 +1,7 @@
#!/usr/bin/env python3
"""
可持续性内容收集脚本
每天凌晨5:00运行，收集全球可持续性趋势信息，提炼选题和案例
每天凌晨5:00运行,收集全球可持续性趋势信息,提炼选题和案例
"""
import os
@@ -20,7 +20,8 @@ from dataclasses import dataclass, asdict
import subprocess
# 项目根目录
PROJECT_ROOT = Path(__file__).parent.parent
# scripts/collector.py 位于 <project_root>/scripts/,因此向上2级即可
PROJECT_ROOT = Path(__file__).resolve().parent.parent
sys.path.insert(0, str(PROJECT_ROOT))
# 配置路径
@@ -45,17 +46,18 @@ class SustainabilitySource:
"""可持续性信息源"""
name: str
type: str # rss, web, api, report, local
url: Optional[str] = None # 可为空（如本地源）
url: Optional[str] = None # 可为空(如本地源)
update_frequency: str = "daily"
credibility: str = "medium"
focus: str = "可持续性"
keywords: Optional[List[str]] = None # 源特定关键词
@dataclass
class SustainabilityCase:
"""可持续性案例"""
id: str
country: str
category: str # 子领域：城市农业、零浪费生活等
category: str # 子领域:城市农业、零浪费生活等
title: str
core_idea: str
data_facts: str
@@ -81,31 +83,47 @@ class SustainabilityTopic:
mvp_actions: str
estimated_length: int
priority_score: float
field: str = "可持续生活系统" # 内容领域
format: str = "趋势洞察 + 实操指南" # 内容形式
core_concept: str = "" # 核心理念
audience_pain: str = "" # 受众痛点
unique_angle: str = "" # 独特角度
priority: str = "中" # 优先级:高/中/低
total_score: Optional[float] = None # 总分
compliance_score: int = 100 # 合规分数
source_file: str = "automation/data/sustainability_topics.json" # 来源文件
ready_at: Optional[str] = None # 就绪时间
published_at: Optional[str] = None # 发布时间
platform_urls: dict = None # 平台发布链接
status: str = "待处理" # 待处理/待审查/待发布/已发布
lock_by: Optional[str] = None # 被哪个任务锁定
lock_at: Optional[str] = None # 锁定时间
created_at: Optional[str] = None # 创建时间
def __post_init__(self):
if self.platform_urls is None:
self.platform_urls = {}
class SustainabilityCollector:
"""可持续性内容收集器"""
def __init__(self):
self.load_config()
self.today_dir = DATA_DIR / "sustainability_raw" / TODAY
self.today_dir.mkdir(parents=True, exist_ok=True)
# 结果存储
self.new_cases: List[SustainabilityCase] = []
self.new_topics: List[SustainabilityTopic] = []
def load_config(self):
"""加载配置文件"""
with open(CONFIG_DIR / "sources.yaml", "r", encoding='utf-8') as f:
self.config = yaml.safe_load(f)
with open(CONFIG_DIR / "wecom_config.yaml", "r", encoding='utf-8') as f:
self.wecom_config = yaml.safe_load(f)
self.sources = []
for source_group in self.config["sustainability_sources"].values():
for source_info in source_group:
@@ -116,22 +134,23 @@ class SustainabilityCollector:
# Provide defaults for missing optional fields
source_info.setdefault('update_frequency', 'daily')
source_info.setdefault('focus', '可持续性')
source_info.setdefault('keywords', None)
# Filter to only fields accepted by SustainabilitySource
allowed_keys = {'name', 'type', 'url', 'update_frequency', 'credibility', 'focus'}
allowed_keys = {'name', 'type', 'url', 'update_frequency', 'credibility', 'focus', 'keywords'}
filtered_info = {k: v for k, v in source_info.items() if k in allowed_keys}
self.sources.append(SustainabilitySource(**filtered_info))
logger.info(f"加载了 {len(self.sources)} 个信息源")
def load_local_cases_from_db(self) -> List[SustainabilityCase]:
"""从本地案例库加载历史案例，用于降级生成选题"""
"""从本地案例库加载历史案例,用于降级生成选题"""
local_cases = []
db_file = DATA_DIR / "sustainability_cases.json"
if db_file.exists():
try:
with open(db_file, 'r', encoding='utf-8') as f:
cases_data = json.load(f)
# 取最近50个案例（按日期倒序）
# 取最近50个案例(按日期倒序)
recent_cases = cases_data[-50:] if len(cases_data) > 50 else cases_data
for case_dict in recent_cases:
# 转换为 dataclass
@@ -143,15 +162,15 @@ class SustainabilityCollector:
return local_cases
def load_local_cases_from_markdown(self) -> List[SustainabilityCase]:
"""从 Markdown 案例文件解析案例（备用）"""
"""从 Markdown 案例文件解析案例(备用)"""
local_cases = []
md_file = PROJECT_ROOT / "strategy" / "全球案例数据库-v1.md"
if not md_file.exists():
return local_cases
try:
content = md_file.read_text(encoding='utf-8')
# 简单解析：按 "#### ID:" 分割案例
# 简单解析:按 "#### ID:" 分割案例
import re
blocks = re.split(r'#### ID:', content)
for block in blocks[1:]: # 第一个是引言
@@ -171,85 +190,115 @@ class SustainabilityCollector:
'china_applicability': '⭐⭐',
'collection_date': TODAY
}
# 提取字段
title_match = re.search(r'标题[：:]\s*(.+)\n', block)
title_match = re.search(r'(?:\*\*)?标题(?:\*\*)?[::]\s*(.+)\n', block)
if title_match:
case_data['title'] = title_match.group(1).strip()
case_data['id'] = f"LOCAL-{hashlib.md5(title_match.group(1).encode()).hexdigest()[:6].upper()}"
country_match = re.search(r'国家[：:]\s*(.+)\n', block)
else:
# 尝试从 ## 标题 格式提取
title_match2 = re.search(r'\*\*(?:标题|ID[::])\*\*[::]?\s*(.+)\n', block)
if title_match2:
case_data['title'] = title_match2.group(1).strip()
case_data['id'] = f"LOCAL-{hashlib.md5(title_match2.group(1).encode()).hexdigest()[:6].upper()}"
country_match = re.search(r'(?:\*\*)?国家(?:\*\*)?[::]\s*(.+)\n', block)
if country_match:
case_data['country'] = country_match.group(1).strip()
field_match = re.search(r'领域[：:]\s*(.+)\n', block)
field_match = re.search(r'(?:\*\*)?领域(?:\*\*)?[::]\s*(.+)\n', block)
if field_match:
field = field_match.group(1).strip()
# 映射到子领域
# 映射到子领域(扩展映射表)
category_map = {
'远程工作方式': '城市农业',
'数字游民政策': '低碳出行',
'AI副业服务': '环保科技产品',
'一人公司模式': '循环消费',
'未来技能趋势': '可持续饮食'
'未来技能趋势': '可持续饮食',
'可持续生活': '可持续饮食',
'零浪费生活': '零浪费生活',
'低碳出行': '低碳出行',
'循环消费': '循环消费',
'环保科技': '环保科技产品'
}
case_data['category'] = category_map.get(field, field[:4] if len(field) > 4 else field)
core_match = re.search(r'核心观点[：:]([\s\S]*?)(?=数据/事实|$)', block)
# 兼容新旧格式:字段可能带 **粗体**
core_match = re.search(r'(?:\*\*)?核心观点(?:\*\*)?[::]([\s\S]*?)(?=数据/事实|$)', block)
if core_match:
case_data['core_idea'] = core_match.group(1).strip()[:500]
data_match = re.search(r'数据/事实[：:]([\s\S]*?)(?=全球优势|$)', block)
else:
# 尝试从 - **核心观点** 格式
core_match2 = re.search(r'- \*\*核心观点\*\*[::]?\s*([\s\S]*?)(?=\n- |$)', block)
if core_match2:
case_data['core_idea'] = core_match2.group(1).strip()[:500]
data_match = re.search(r'(?:\*\*)?数据/事实(?:\*\*)?[::]([\s\S]*?)(?=全球优势|$)', block)
if data_match:
case_data['data_facts'] = data_match.group(1).strip()[:200]
global_match = re.search(r'全球优势[：:]([\s\S]*?)(?=中国痛点|$)', block)
global_match = re.search(r'(?:\*\*)?全球优势(?:\*\*)?[::]([\s\S]*?)(?=中国痛点|$)', block)
if global_match:
case_data['global_advantage'] = global_match.group(1).strip()[:200]
pain_match = re.search(r'中国痛点[：:]([\s\S]*?)(?=本土化建议|$)', block)
pain_match = re.search(r'(?:\*\*)?中国痛点(?:\*\*)?[::]([\s\S]*?)(?=本土化建议|$)', block)
if pain_match:
case_data['china_pain_point'] = pain_match.group(1).strip()[:200]
local_match = re.search(r'本土化建议[：:]([\s\S]*?)(?=MVP行动|$)', block)
local_match = re.search(r'(?:\*\*)?本土化建议(?:\*\*)?[::]([\s\S]*?)(?=MVP行动|$)', block)
if local_match:
case_data['localization_suggestion'] = local_match.group(1).strip()[:200]
mvp_match = re.search(r'MVP行动[：:]([\s\S]*?)(?=来源URL|$)', block)
mvp_match = re.search(r'(?:\*\*)?MVP行动(?:\*\*)?[::]([\s\S]*?)(?=来源URL|$)', block)
if mvp_match:
case_data['mvp_action'] = mvp_match.group(1).strip()[:200]
url_match = re.search(r'来源URL[：:]\s*(.+)\n', block)
url_match = re.search(r'(?:\*\*)?来源URL(?:\*\*)?[::]\s*(.+)\n', block)
if url_match:
case_data['source_url'] = url_match.group(1).strip()
else:
# 尝试从 URL: 或 来源URL 格式
url_match2 = re.search(r'[\*\s]*URL[::]?\s*(https?://[^\s]+)\n', block)
if url_match2:
case_data['source_url'] = url_match2.group(1).strip()
case = SustainabilityCase(**case_data)
local_cases.append(case)
logger.info(f"从 Markdown 案例库解析了 {len(local_cases)} 个案例")
except Exception as e:
logger.error(f"解析 Markdown 案例库失败: {e}")
return local_cases
def fetch_rss_feed(self, source: SustainabilitySource) -> List[Dict]:
"""获取RSS订阅内容"""
try:
feed = feedparser.parse(source.url)
articles = []
for entry in feed.entries[:10]: # 限制数量
# 检查是否包含可持续性关键词
content = entry.get('summary', entry.get('description', ''))
# 获取源配置的关键词(如果有)
source_keywords = getattr(source, 'keywords', None) or \
self.config.get('sustainability_sources', {}).get('global_keywords', [])
for entry in feed.entries[:15]: # 增加数量到15
title = entry.get('title', '')
# 可持续性关键词匹配
sustainability_keywords = [
'sustainable', 'green', 'eco', 'circular', 'climate',
'carbon', 'zero waste', 'renewable', 'recycle',
'环保', '可持续', '碳中和', '循环经济', '零浪费'
content = entry.get('summary', entry.get('description', ''))
# 确保 content 不为空
if not content:
content = title
# 关键词匹配(来源特定或全局)
keywords = source_keywords if source_keywords else [
'sustainable', 'green', 'eco', 'circular', 'climate', 'carbon',
'zero waste', 'renewable', 'recycle', '环保', '可持续', '碳中和',
'循环经济', '零浪费', '低碳', '生态'
]
if any(keyword.lower() in (title + content).lower() for keyword in sustainability_keywords):
search_text = (title + content).lower()
if any(keyword.lower() in search_text for keyword in keywords):
articles.append({
'title': title,
'url': entry.get('link', ''),
@@ -257,52 +306,52 @@ class SustainabilityCollector:
'published': entry.get('published', ''),
'source_name': source.name
})
logger.info(f"从 {source.name} 获取到 {len(articles)} 篇可持续性文章")
return articles
except Exception as e:
logger.error(f"获取RSS失败 {source.name}: {e}")
return []
def fetch_web_content(self, source: SustainabilitySource) -> List[Dict]:
"""获取网页内容（简化版，实际需要更复杂的抓取）"""
# 简化实现：只记录，不实际抓取
"""获取网页内容(简化版,实际需要更复杂的抓取)"""
# 简化实现:只记录,不实际抓取
logger.info(f"网页信息源 {source.name} 需要手动处理")
return []
def analyze_article(self, article: Dict) -> Optional[SustainabilityCase]:
"""分析文章内容，提炼案例"""
"""分析文章内容,提炼案例"""
try:
content = article['content']
title = article['title']
# 提取关键数据（简化版，实际可用NLP）
# 提取关键数据(简化版,实际可用NLP)
data_patterns = [
r'(\d+\.?\d*)\s*(?:percent|%|百分比)',
r'(\d+\.?\d*)\s*(?:million|billion|万|亿)',
r'(\d+\.?\d*)\s*(?:tons|tonnes|吨)',
r'(\d+\.?\d*)\s*(?:reduction|increase|减少|增加)'
]
data_points = []
for pattern in data_patterns:
matches = re.findall(pattern, content, re.IGNORECASE)
if matches:
data_points.extend(matches[:3]) # 限制数量
if len(data_points) < 2:
logger.info(f"文章数据不足: {title}")
return None
# 确定国家（简化判断）
# 确定国家(简化判断)
countries = ['China', 'Japan', 'Germany', 'US', 'UK', 'Sweden', 'Netherlands']
country = 'Global' # 默认
for c in countries:
if c.lower() in content.lower():
country = c
break
# 确定子领域
categories = self.config["sustainability_categories"]
category = categories[0] # 默认第一个
@@ -310,15 +359,15 @@ class SustainabilityCollector:
if any(keyword in content.lower() for keyword in [cat.lower(), cat[:4].lower()]):
category = cat
break
# 生成案例ID
case_id = f"SUS-{hashlib.md5(title.encode()).hexdigest()[:8].upper()}"
# 提取核心观点（简化版）
# 实际应用中可用AI提取，这里用前100字符
# 提取核心观点(简化版)
# 实际应用中可用AI提取,这里用前100字符
core_idea = content[:200] if len(content) > 200 else content
# 生成中国痛点（基于类别模板）
# 生成中国痛点(基于类别模板)
china_pains = {
"城市农业": "中国城市空间小、光照不足、怕邻居投诉",
"零浪费生活": "中国垃圾分类执行难、环保产品溢价高",
@@ -328,8 +377,8 @@ class SustainabilityCollector:
"可持续饮食": "中国预制菜泛滥、有机食品价格高",
"环保科技产品": "中国消费者关注价格多于环保"
}
china_pain = china_pains.get(category, "中国相关数据不足，需本土化验证")
china_pain = china_pains.get(category, "中国相关数据不足,需本土化验证")
# 生成案例
case = SustainabilityCase(
id=case_id,
@@ -347,39 +396,39 @@ class SustainabilityCollector:
china_applicability="⭐⭐",
collection_date=TODAY
)
return case
except Exception as e:
logger.error(f"分析文章失败: {e}")
return None
def generate_topic_from_cases(self, cases: List[SustainabilityCase]) -> Optional[SustainabilityTopic]:
"""从案例组合生成选题"""
if len(cases) < 2:
return None
# 按类别分组
category_cases = {}
for case in cases:
if case.category not in category_cases:
category_cases[case.category] = []
category_cases[case.category].append(case)
# 选择案例数最多的类别
main_category = max(category_cases, key=lambda k: len(category_cases[k]))
main_cases = category_cases[main_category]
if len(main_cases) < 2:
return None
# 生成选题ID
topic_id = f"TOPIC-.{hashlib.md5((main_category + TODAY).encode()).hexdigest()[:6].upper()}"
topic_id = f"TOPIC-{hashlib.md5((main_category + TODAY).encode()).hexdigest()[:6].upper()}"
# 组合标题
case_titles = [case.title[:30] for case in main_cases[:2]]
topic_title = f"{main_category}新趋势: {case_titles[0]}与{case_titles[1]}的中国落地路径"
# 计算优先级分数
priority_weights = self.config["topic_priority"]
priority_score = (
@@ -389,67 +438,107 @@ class SustainabilityCollector:
priority_weights["executability"] * 0.6 + # 可执行性
priority_weights["brand_fit"] * 0.9 # 品牌契合度
)
# 计算优先级分数(转换为1-10整数)
priority_weights = self.config["topic_priority"]
score_float = (
priority_weights["audience_match"] * 0.8 +
priority_weights["data_availability"] * 0.9 +
priority_weights["uniqueness"] * 0.7 +
priority_weights["executability"] * 0.6 +
priority_weights["brand_fit"] * 0.9
)
# 转换为 1-10 的整数
score = round(score_float * 10)
topic = SustainabilityTopic(
id=topic_id,
title=topic_title,
cases=[case.id for case in main_cases],
audience="城市焦虑青年（26-35岁）",
audience="城市焦虑青年(26-35岁)",
china_pain_points=f"{main_category}在中国面临的主要问题",
localization_solution="国际案例中国化适配方案",
mvp_actions="读者可立即尝试的3个行动",
estimated_length=2500,
priority_score=round(priority_score, 2)
priority_score=round(score, 2),
field=self.map_category_to_field(main_category),
format="趋势洞察 + 实操指南",
core_concept=f"基于{len(main_cases)}个{main_category}案例,提炼本土化落地策略",
audience_pain=f"{main_category}领域常见的痛点与困惑",
unique_angle=f"国际案例本土化:{case_titles[0]}与{case_titles[1]}的中国实践",
priority="中",
total_score=round(score * 10, 1) if score is not None else None,
compliance_score=100,
source_file="automation/data/sustainability_topics.json",
status="待处理",
lock_by=None,
lock_at=None,
created_at=datetime.datetime.now().isoformat(),
ready_at=None,
published_at=None,
platform_urls={}
)
return topic
def map_category_to_field(self, category: str) -> str:
"""将案例类别映射到内容领域的字段"""
category_map = {
"城市农业": "可持续生活系统",
"零浪费生活": "可持续生活系统",
"低碳出行": "可持续生活系统",
"循环消费": "可持续生活系统",
"能源效率": "可持续生活系统",
"环保科技产品": "可持续生活系统"
}
return category_map.get(category, "可持续生活系统")
def save_results(self):
"""保存收集结果"""
# 保存案例
cases_file = self.today_dir / "new_cases.json"
with open(cases_file, 'w', encoding='utf-8') as f:
json.dump([asdict(case) for case in self.new_cases], f, ensure_ascii=False, indent=2)
# 保存选题
topics_file = self.today_dir / "new_topics.json"
with open(topics_file, 'w', encoding='utf-8') as f:
json.dump([asdict(topic) for topic in self.new_topics], f, ensure_ascii=False, indent=2)
# 更新主数据库
self.update_main_database()
logger.info(f"保存了 {len(self.new_cases)} 个案例和 {len(self.new_topics)} 个选题")
def update_main_database(self):
"""更新主数据库（简化版）"""
# 实际应更新Notion/数据库，这里仅保存到文件
"""更新主数据库(简化版)"""
# 实际应更新Notion/数据库,这里仅保存到文件
main_cases_file = DATA_DIR / "sustainability_cases.json"
main_topics_file = DATA_DIR / "sustainability_topics.json"
# 读取现有数据
existing_cases = []
existing_topics = []
if main_cases_file.exists():
with open(main_cases_file, 'r', encoding='utf-8') as f:
existing_cases = json.load(f)
if main_topics_file.exists():
with open(main_topics_file, 'r', encoding='utf-8') as f:
existing_topics = json.load(f)
# 合并新数据
all_cases = existing_cases + [asdict(case) for case in self.new_cases]
all_topics = existing_topics + [asdict(topic) for topic in self.new_topics]
# 保存（限制总数）
# 保存(限制总数)
with open(main_cases_file, 'w', encoding='utf-8') as f:
json.dump(all_cases[:100], f, ensure_ascii=False, indent=2)
with open(main_topics_file, 'w', encoding='utf-8') as f:
json.dump(all_topics[:50], f, ensure_ascii=False, indent=2)
def send_wecom_notification(self):
"""发送企业微信通知"""
try:
@@ -458,7 +547,7 @@ class SustainabilityCollector:
if not notification_script.exists():
logger.warning("企业微信通知脚本不存在")
return
# 准备通知数据
notification_data = {
"task": "sustainability_collection",
@@ -468,11 +557,11 @@ class SustainabilityCollector:
"source_count": len(self.sources),
"details_link": str(self.today_dir.relative_to(PROJECT_ROOT))
}
data_file = self.today_dir / "notification_data.json"
with open(data_file, 'w', encoding='utf-8') as f:
json.dump(notification_data, f, ensure_ascii=False)
# 运行通知脚本
result = subprocess.run(
[sys.executable, str(notification_script), str(data_file)],
@@ -480,19 +569,19 @@ class SustainabilityCollector:
text=True,
cwd=PROJECT_ROOT
)
if result.returncode == 0:
logger.info("企业微信通知发送成功")
else:
logger.error(f"通知发送失败: {result.stderr}")
except Exception as e:
logger.error(f"发送通知失败: {e}")
def run(self):
"""主运行流程"""
logger.info("开始可持续性内容收集")
# 1. 从所有信息源收集
all_articles = []
for source in self.sources:
@@ -506,54 +595,77 @@ class SustainabilityCollector:
# TODO: 实现API抓取
pass
elif source.type == 'local':
# 本地源不产生新文章，后续降级处理
# 本地源不产生新文章,后续降级处理
pass
logger.info(f"总共收集到 {len(all_articles)} 篇可持续性文章")
# 2. 分析文章，提炼案例
# 2. 分析文章,提炼案例
for article in all_articles[:20]: # 限制分析数量
case = self.analyze_article(article)
if case:
self.new_cases.append(case)
# 3. 降级策略：如果外部源没有收集到足够案例，使用本地案例库
# 3. 降级策略:如果外部源没有收集到足够案例,使用本地案例库
if len(self.new_cases) < 2:
logger.warning(f"外部源案例不足 ({len(self.new_cases)} < 2)，启动降级策略")
# 优先：从本地JSON数据库加载最近案例
logger.warning(f"外部源案例不足 ({len(self.new_cases)} < 2),启动降级策略")
# 从本地JSON数据库加载案例(按类别分组,选择案例最多的类别)
local_cases = self.load_local_cases_from_db()
if len(local_cases) < 2:
# 备用：从Markdown案例库解析
local_cases = self.load_local_cases_from_markdown()
if local_cases:
# 随机选取2-3个本地案例作为本次选题的案例基础
import random
selected = random.sample(local_cases, min(3, len(local_cases)))
self.new_cases.extend(selected)
logger.info(f"降级：使用了 {len(selected)} 个本地案例")
if local_cases and len(local_cases) >= 2:
# 按类别分组,选择案例最多的类别
category_cases = {}
for case in local_cases:
cat = case.category
if cat not in category_cases:
category_cases[cat] = []
category_cases[cat].append(case)
# 找出案例最多的类别
main_category = max(category_cases, key=lambda k: len(category_cases[k]))
main_cases = category_cases[main_category]
# 确保至少有2个案例
if len(main_cases) >= 2:
selected = main_cases[:min(3, len(main_cases))]
self.new_cases.extend(selected)
logger.info(f"降级:从类别'{main_category}'选取了 {len(selected)} 个案例")
else:
# 如果每个类别都少于2个,则随机选2个(可能类别不同,generate_topic_from_cases会合并)
import random
selected = random.sample(local_cases, min(3, len(local_cases)))
self.new_cases.extend(selected)
logger.info(f"降级:随机选取了 {len(selected)} 个本地案例")
else:
logger.error("降级失败：本地案例库为空")
# 备用:从Markdown案例库解析
local_cases = self.load_local_cases_from_markdown()
if local_cases:
import random
selected = random.sample(local_cases, min(3, len(local_cases)))
self.new_cases.extend(selected)
logger.info(f"降级(Markdown):使用了 {len(selected)} 个案例")
else:
logger.error("降级失败:本地案例库为空")
# 4. 生成选题
if self.new_cases:
topic = self.generate_topic_from_cases(self.new_cases)
if topic:
# 标记为今日创建，并添加锁字段（表示未被占用）
# 标记为今日创建,并添加锁字段(表示未被占用)
topic.created_at = datetime.datetime.now().isoformat()
topic.lock_by = None
topic.lock_at = None
# 确保状态为「待处理」
topic.status = "待处理"
self.new_topics.append(topic)
# 5. 保存结果
self.save_results()
# 6. 发送通知
self.send_wecom_notification()
# NOTE: 推送通知已禁用，由 publisher 统一发送最终日报
# self.send_wecom_notification()
logger.info(f"收集完成: {len(self.new_cases)} 案例, {len(self.new_topics)} 选题")
return len(self.new_cases), len(self.new_topics)
@@ -562,7 +674,7 @@ def main():
try:
collector = SustainabilityCollector()
case_count, topic_count = collector.run()
# 返回结果码
if case_count > 0 or topic_count > 0:
print(f"SUCCESS: Collected {case_count} cases and {topic_count} topics")
@@ -570,7 +682,7 @@ def main():
else:
print("WARNING: No new content found")
sys.exit(1)
except Exception as e:
logger.error(f"收集任务失败: {e}")
print(f"ERROR: {e}")