Files
MoFin/venv/lib/python3.12/site-packages/akshare/stock/stock_us_pink.py
T
知微 fa45d8aa5f fix: 小果地址统一node122(兼容LAN+EasyTier)
- health_checklist.json: 192.168.1.122→node122
- ocr_client.py: docstring IP→node122
- docs/market-data-requirements.md: IP→node122
- 所有API调用通过ProxyHandler({})绕过系统代理
  Privoxy对node122:18003返回500,直连正常
2026-06-30 02:56:35 +08:00

120 lines
3.4 KiB
Python

#!/usr/bin/env python
# -*- coding:utf-8 -*-
"""
Date: 2025/6/17 14:00
Desc: 东方财富网-行情中心-美股市场-粉单市场
https://quote.eastmoney.com/center/gridlist.html#us_pinksheet
"""
import pandas as pd
import requests
from akshare.utils.tqdm import get_tqdm
def stock_us_pink_spot_em() -> pd.DataFrame:
"""
东方财富网-行情中心-美股市场-粉单市场
https://quote.eastmoney.com/center/gridlist.html#us_pinksheet
:return: 粉单市场实时行情
:rtype: pandas.DataFrame
"""
url = "https://23.push2.eastmoney.com/api/qt/clist/get"
params = {
"np": "1",
"fltt": "1",
"invt": "1",
"fs": "m:153",
"fields": "f1,f2,f3,f4,f5,f6,f7,f8,f9,f10,f12,f13,f14,f15,f16,f17,f18,f20,f21,f23,f24,f25,"
"f26,f22,f33,f11,f62,f128,f136,f115,f152",
"fid": "f3",
"pn": "1",
"pz": "100",
"po": "1",
"dect": "1",
"ut": "bd1d9ddb04089700cf9c27f6f7426281",
}
r = requests.get(url, params=params)
data_json = r.json()
import math
total_page = math.ceil(data_json["data"]["total"] / 100)
tqdm = get_tqdm()
big_df = pd.DataFrame()
for page in tqdm(range(1, total_page + 1), leave=False):
params.update({"pn": page})
r = requests.get(url, params=params)
data_json = r.json()
temp_df = pd.DataFrame(data_json["data"]["diff"])
big_df = pd.concat(objs=[big_df, temp_df], ignore_index=True)
big_df.columns = [
"_",
"最新价",
"涨跌幅",
"涨跌额",
"_",
"_",
"_",
"_",
"_",
"_",
"_",
"简称",
"编码",
"名称",
"最高价",
"最低价",
"开盘价",
"昨收价",
"总市值",
"_",
"_",
"_",
"_",
"_",
"_",
"_",
"_",
"市盈率",
"_",
"_",
"_",
"_",
"_",
]
big_df.reset_index(inplace=True)
big_df["index"] = range(1, len(big_df) + 1)
big_df.rename(columns={"index": "序号"}, inplace=True)
big_df["代码"] = big_df["编码"].astype(str) + "." + big_df["简称"]
big_df = big_df[
[
"序号",
"名称",
"最新价",
"涨跌额",
"涨跌幅",
"开盘价",
"最高价",
"最低价",
"昨收价",
"总市值",
"市盈率",
"代码",
]
]
big_df["最新价"] = pd.to_numeric(big_df["最新价"], errors="coerce")
big_df["涨跌额"] = pd.to_numeric(big_df["涨跌额"], errors="coerce")
big_df["涨跌幅"] = pd.to_numeric(big_df["涨跌幅"], errors="coerce")
big_df["开盘价"] = pd.to_numeric(big_df["开盘价"], errors="coerce")
big_df["最高价"] = pd.to_numeric(big_df["最高价"], errors="coerce")
big_df["最低价"] = pd.to_numeric(big_df["最低价"], errors="coerce")
big_df["昨收价"] = pd.to_numeric(big_df["昨收价"], errors="coerce")
big_df["总市值"] = pd.to_numeric(big_df["总市值"], errors="coerce")
big_df["市盈率"] = pd.to_numeric(big_df["市盈率"], errors="coerce")
return big_df
if __name__ == "__main__":
stock_us_pink_spot_em_df = stock_us_pink_spot_em()
print(stock_us_pink_spot_em_df)