螃蟹投研-股票行业Collector

收集A股某行业全部上市公司资料，包括代码、名称、交易所、行业、财务数据（ROE、毛利率、净利率、资产负债率、现金流、增长率）、控股股东及持股比例

Security Scan

The skill's code, runtime instructions, and requested packages are consistent with its stated purpose of collecting A‑share industry/company and financial data; nothing requested is disproportionate or unrelated.

Purpose & Capability

Name/description ask for A‑share industry/company and financial/holder data; SKILL.md requires akshare/baostock/pandas and the code uses akshare and network calls to fetch stock lists, shareholder info and market data. Required packages and external endpoints align with the stated data-collection purpose. Minor note: SKILL.md lists baostock as a data source but the provided __init__.py does not call baostock — likely harmless/incomplete documentation.

Instruction Scope

Runtime instructions and code only perform API calls (akshare functions and HTTP requests to Eastmoney), format and return data, and suggest clearing proxies for akshare. They do not instruct reading unrelated system files, environment variables, or sending data to unexpected third‑party endpoints beyond akshare/Eastmoney. The code uses subprocess to invoke curl for network calls, which is coherent with the stated intention to avoid proxy issues.

Install Mechanism

No install spec; SKILL.md lists pip dependencies (baostock, akshare, pandas). No downloads from arbitrary URLs or archive extraction; code is included directly. This is low-risk from an install-mechanism perspective, though users should still vet the pip packages and pin versions.

Credentials

The skill requests no environment variables, credentials, or config paths. That is proportional to the stated purpose. Network access is required for data retrieval, which is expected. No unrelated secrets or system config access is requested.

Persistence & Privilege

Skill does not request always:true and contains no installation steps that modify other skills or system-wide settings. It runs on demand and does not require persistent elevated privileges.

Assessment

This skill appears coherent for collecting A‑share company and financial data. Before installing: (1) review and pin versions for pip packages (akshare/baostock/pandas) to avoid supply‑chain risks; (2) be aware it performs network requests to akshare and Eastmoney (push2.eastmoney.com) — ensure these calls comply with your data/TOS constraints and run in an environment where outbound network access is acceptable; (3) note the code invokes curl via subprocess (used safely with a list of args here), so run in a controlled environment if you have strict execution policies; (4) the SKILL.md mentions baostock but the code doesn't call it — if you expect baostock data, verify the implementation or update requirements accordingly.

股票行业数据收集器 v2.3

功能

收集A股某行业的全部上市公司详细信息，包含完整财务数据和控股股东数据

【重要】获取行业全部公司的方法

本技能使用 akshare 行业分类 获取股票，确保不遗漏任何公司：

方法1：使用申万行业分类

c.collect(industry_name="煤炭")  # 自动转换为申万行业代码 BK0437
c.collect(industry_name="焦煤")  # BK1494
c.collect(industry_name="煤化工") # BK1419

方法2：直接使用申万行业代码

c.collect(industry_code="BK0437")   # 煤炭
c.collect(industry_code="BK1494")   # 焦煤
c.collect(industry_code="BK1493")   # 动力煤
c.collect(industry_code="BK1419")   # 煤化工

支持的行业

行业名称	申万代码	说明
煤炭	BK0437	煤炭开采
焦煤	BK1494	焦炭
动力煤	BK1493	动力煤
煤化工	BK1419	煤化工
石油	BK0411	石油开采
燃气	BK0501	燃气
电力	BK0502	电力
光伏	BK1033	光伏

输出字段

字段	说明	数据来源
代码	股票代码	基本信息
名称	公司名称	基本信息
交易所	沪市/深市	基本信息
行业	证监会行业分类	行业数据
ROE	净资产收益率(%)	利润表
毛利率	毛利率(%)	利润表
净利率	净利率(%)	利润表
营业收入	营业收入(元)	利润表
净利润	净利润(元)	利润表
总资产	总资产(元)	资产负债表
总负债	总负债(元)	资产负债表
资产负债率	负债/权益	资产负债表
经营现金流	经营现金流(元)	现金流量表
营收增长	营收增长率(%)	成长能力
净利润增长	净利润增长率(%)	成长能力
控股股东	控股股东名称	十大流通股东
控股比例	持股比例(%)	十大流通股东
股东性质	国企/民企	自动判断
所在地	省份	手动维护
产区	主要生产区	手动维护

数据来源

• baostock - 财务数据（免费无需注册）
• akshare - 股东数据、行业分类（需清除代理）

使用

from stock_industry_collector import IndustryCollector

c = IndustryCollector()

# 方法1：按行业名称
df = c.collect(industry_name="煤炭")

# 方法2：按申万行业代码
# df = c.collect(industry_code="BK0437")

print(f"找到 {len(df)} 只煤炭行业股票")

# 格式化
df['ROE'] = df['ROE'].apply(lambda x: str(round(float(x)*100, 2)) + '%' if x else '')
df['净利润'] = df['净利润'].apply(lambda x: str(round(float(x)/1e8, 2)) + '亿' if x else '')

print(df[['代码','名称','控股股东','ROE','净利润']].head())

# 保存Excel
df.to_excel("煤炭行业财务分析.xlsx", index=False)

注意事项

1. 行业股票获取：使用 akshare 申万/中证行业分类，不遗漏
2. 财报年份：默认获取2024年年报（year=2024, quarter=4）
3. 数据延迟：每年4月底发布上年年报
4. 请求限速：已内置延时，避免请求过快
5. 代理问题：akshare 需要清除系统代理才能正常工作