知微
fa45d8aa5f
- 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
1319 lines
48 KiB
Python
1319 lines
48 KiB
Python
#!/usr/bin/env python
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# -*- coding:utf-8 -*-
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"""
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Date: 2025/3/10 19:00
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Desc: 东方财富网-数据中心-资金流向
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https://data.eastmoney.com/zjlx/detail.html
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"""
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import math
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import time
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from functools import lru_cache
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import pandas as pd
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import requests
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from akshare.utils.func import fetch_paginated_data
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from akshare.utils.tqdm import get_tqdm
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def stock_individual_fund_flow(
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stock: str = "600094", market: str = "sh"
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) -> pd.DataFrame:
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"""
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东方财富网-数据中心-资金流向-个股
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https://data.eastmoney.com/zjlx/detail.html
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:param stock: 股票代码
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:type stock: str
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:param market: 股票市场; 上海证券交易所: sh, 深证证券交易所: sz, 北京证券交易所: bj;
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:type market: str
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:return: 近期个股的资金流数据
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:rtype: pandas.DataFrame
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"""
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market_map = {"sh": 1, "sz": 0, "bj": 0}
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url = "https://push2his.eastmoney.com/api/qt/stock/fflow/daykline/get"
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headers = {
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"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 "
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"(KHTML, like Gecko) Chrome/81.0.4044.138 Safari/537.36",
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}
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params = {
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"lmt": "0",
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"klt": "101",
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"secid": f"{market_map[market]}.{stock}",
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"fields1": "f1,f2,f3,f7",
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"fields2": "f51,f52,f53,f54,f55,f56,f57,f58,f59,f60,f61,f62,f63,f64,f65",
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"ut": "b2884a393a59ad64002292a3e90d46a5",
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"_": int(time.time() * 1000),
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}
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r = requests.get(url, params=params, headers=headers)
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data_json = r.json()
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content_list = data_json["data"]["klines"]
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temp_df = pd.DataFrame([item.split(",") for item in content_list])
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temp_df.columns = [
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"日期",
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"主力净流入-净额",
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"小单净流入-净额",
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"中单净流入-净额",
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"大单净流入-净额",
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"超大单净流入-净额",
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"主力净流入-净占比",
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"小单净流入-净占比",
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"中单净流入-净占比",
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"大单净流入-净占比",
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"超大单净流入-净占比",
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"收盘价",
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"涨跌幅",
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"-",
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"-",
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]
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temp_df = temp_df[
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[
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"日期",
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"收盘价",
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"涨跌幅",
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"主力净流入-净额",
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"主力净流入-净占比",
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"超大单净流入-净额",
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"超大单净流入-净占比",
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"大单净流入-净额",
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"大单净流入-净占比",
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"中单净流入-净额",
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"中单净流入-净占比",
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"小单净流入-净额",
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"小单净流入-净占比",
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]
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]
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temp_df["日期"] = pd.to_datetime(temp_df["日期"], errors="coerce").dt.date
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temp_df["主力净流入-净额"] = pd.to_numeric(
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temp_df["主力净流入-净额"], errors="coerce"
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)
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temp_df["小单净流入-净额"] = pd.to_numeric(
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temp_df["小单净流入-净额"], errors="coerce"
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)
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temp_df["中单净流入-净额"] = pd.to_numeric(
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temp_df["中单净流入-净额"], errors="coerce"
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)
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temp_df["大单净流入-净额"] = pd.to_numeric(
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temp_df["大单净流入-净额"], errors="coerce"
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)
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temp_df["超大单净流入-净额"] = pd.to_numeric(
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temp_df["超大单净流入-净额"], errors="coerce"
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)
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temp_df["主力净流入-净占比"] = pd.to_numeric(
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temp_df["主力净流入-净占比"], errors="coerce"
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)
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temp_df["小单净流入-净占比"] = pd.to_numeric(
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temp_df["小单净流入-净占比"], errors="coerce"
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)
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temp_df["中单净流入-净占比"] = pd.to_numeric(
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temp_df["中单净流入-净占比"], errors="coerce"
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)
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temp_df["大单净流入-净占比"] = pd.to_numeric(
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temp_df["大单净流入-净占比"], errors="coerce"
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)
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temp_df["超大单净流入-净占比"] = pd.to_numeric(
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temp_df["超大单净流入-净占比"], errors="coerce"
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)
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temp_df["收盘价"] = pd.to_numeric(temp_df["收盘价"], errors="coerce")
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temp_df["涨跌幅"] = pd.to_numeric(temp_df["涨跌幅"], errors="coerce")
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return temp_df
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def stock_individual_fund_flow_rank(indicator: str = "5日") -> pd.DataFrame:
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"""
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东方财富网-数据中心-资金流向-排名
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https://data.eastmoney.com/zjlx/detail.html
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:param indicator: choice of {"今日", "3日", "5日", "10日"}
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:type indicator: str
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:return: 指定 indicator 资金流向排行
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:rtype: pandas.DataFrame
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"""
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indicator_map = {
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"今日": [
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"f62",
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"f12,f14,f2,f3,f62,f184,f66,f69,f72,f75,f78,f81,f84,f87,f204,f205,f124",
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],
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"3日": [
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"f267",
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"f12,f14,f2,f127,f267,f268,f269,f270,f271,f272,f273,f274,f275,f276,f257,f258,f124",
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],
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"5日": [
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"f164",
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"f12,f14,f2,f109,f164,f165,f166,f167,f168,f169,f170,f171,f172,f173,f257,f258,f124",
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],
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"10日": [
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"f174",
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"f12,f14,f2,f160,f174,f175,f176,f177,f178,f179,f180,f181,f182,f183,f260,f261,f124",
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],
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}
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url = "https://push2.eastmoney.com/api/qt/clist/get"
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params = {
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"fid": indicator_map[indicator][0],
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"po": "1",
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"pz": "100",
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"pn": "1",
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"np": "1",
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"fltt": "2",
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"invt": "2",
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"ut": "b2884a393a59ad64002292a3e90d46a5",
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"fs": "m:0+t:6+f:!2,m:0+t:13+f:!2,m:0+t:80+f:!2,m:1+t:2+f:!2,m:1+t:23+f:!2,m:0+t:7+f:!2,m:1+t:3+f:!2",
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"fields": indicator_map[indicator][1],
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}
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r = requests.get(url, params=params)
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data_json = r.json()
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total_page = math.ceil(data_json["data"]["total"] / 100)
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temp_list = []
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tqdm = get_tqdm()
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for page in tqdm(range(1, total_page + 1), leave=False):
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params.update(
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{
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"pn": page,
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}
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)
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r = requests.get(url, params=params, timeout=15)
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data_json = r.json()
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inner_temp_df = pd.DataFrame(data_json["data"]["diff"])
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temp_list.append(inner_temp_df)
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temp_df = pd.concat(temp_list, ignore_index=True)
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temp_df.reset_index(inplace=True)
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temp_df["index"] = range(1, len(temp_df) + 1)
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if indicator == "今日":
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temp_df.columns = [
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"序号",
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"最新价",
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"今日涨跌幅",
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"代码",
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"名称",
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"今日主力净流入-净额",
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"今日超大单净流入-净额",
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"今日超大单净流入-净占比",
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"今日大单净流入-净额",
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"今日大单净流入-净占比",
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"今日中单净流入-净额",
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"今日中单净流入-净占比",
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"今日小单净流入-净额",
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"今日小单净流入-净占比",
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"_",
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"今日主力净流入-净占比",
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"_",
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"_",
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"_",
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]
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temp_df = temp_df[
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[
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"序号",
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"代码",
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"名称",
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"最新价",
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"今日涨跌幅",
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"今日主力净流入-净额",
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"今日主力净流入-净占比",
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"今日超大单净流入-净额",
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"今日超大单净流入-净占比",
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"今日大单净流入-净额",
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"今日大单净流入-净占比",
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"今日中单净流入-净额",
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"今日中单净流入-净占比",
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"今日小单净流入-净额",
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"今日小单净流入-净占比",
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]
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]
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elif indicator == "3日":
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temp_df.columns = [
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"序号",
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"最新价",
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"代码",
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"名称",
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"_",
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"3日涨跌幅",
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"_",
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"_",
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"_",
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"3日主力净流入-净额",
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"3日主力净流入-净占比",
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"3日超大单净流入-净额",
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"3日超大单净流入-净占比",
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"3日大单净流入-净额",
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"3日大单净流入-净占比",
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"3日中单净流入-净额",
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"3日中单净流入-净占比",
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"3日小单净流入-净额",
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"3日小单净流入-净占比",
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]
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temp_df = temp_df[
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[
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"序号",
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"代码",
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"名称",
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"最新价",
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"3日涨跌幅",
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"3日主力净流入-净额",
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"3日主力净流入-净占比",
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"3日超大单净流入-净额",
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"3日超大单净流入-净占比",
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"3日大单净流入-净额",
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"3日大单净流入-净占比",
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"3日中单净流入-净额",
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"3日中单净流入-净占比",
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"3日小单净流入-净额",
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"3日小单净流入-净占比",
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]
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]
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elif indicator == "5日":
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temp_df.columns = [
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"序号",
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"最新价",
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"代码",
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"名称",
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"5日涨跌幅",
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"_",
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"5日主力净流入-净额",
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"5日主力净流入-净占比",
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"5日超大单净流入-净额",
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"5日超大单净流入-净占比",
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"5日大单净流入-净额",
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"5日大单净流入-净占比",
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"5日中单净流入-净额",
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"5日中单净流入-净占比",
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"5日小单净流入-净额",
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"5日小单净流入-净占比",
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"_",
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"_",
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"_",
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]
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temp_df = temp_df[
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[
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"序号",
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"代码",
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"名称",
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"最新价",
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"5日涨跌幅",
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"5日主力净流入-净额",
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"5日主力净流入-净占比",
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"5日超大单净流入-净额",
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"5日超大单净流入-净占比",
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"5日大单净流入-净额",
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"5日大单净流入-净占比",
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"5日中单净流入-净额",
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"5日中单净流入-净占比",
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"5日小单净流入-净额",
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"5日小单净流入-净占比",
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]
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]
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elif indicator == "10日":
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temp_df.columns = [
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"序号",
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"最新价",
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"代码",
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"名称",
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"_",
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"10日涨跌幅",
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"10日主力净流入-净额",
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"10日主力净流入-净占比",
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"10日超大单净流入-净额",
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"10日超大单净流入-净占比",
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"10日大单净流入-净额",
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"10日大单净流入-净占比",
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"10日中单净流入-净额",
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"10日中单净流入-净占比",
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"10日小单净流入-净额",
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"10日小单净流入-净占比",
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"_",
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"_",
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"_",
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]
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temp_df = temp_df[
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[
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"序号",
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"代码",
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"名称",
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"最新价",
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"10日涨跌幅",
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"10日主力净流入-净额",
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"10日主力净流入-净占比",
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"10日超大单净流入-净额",
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"10日超大单净流入-净占比",
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"10日大单净流入-净额",
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"10日大单净流入-净占比",
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"10日中单净流入-净额",
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"10日中单净流入-净占比",
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"10日小单净流入-净额",
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"10日小单净流入-净占比",
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]
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]
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return temp_df
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|
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def stock_market_fund_flow() -> pd.DataFrame:
|
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"""
|
|
东方财富网-数据中心-资金流向-大盘
|
|
https://data.eastmoney.com/zjlx/dpzjlx.html
|
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:return: 近期大盘的资金流数据
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:rtype: pandas.DataFrame
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"""
|
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url = "https://push2his.eastmoney.com/api/qt/stock/fflow/daykline/get"
|
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headers = {
|
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"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 "
|
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"(KHTML, like Gecko) Chrome/81.0.4044.138 Safari/537.36",
|
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}
|
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params = {
|
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"lmt": "0",
|
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"klt": "101",
|
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"secid": "1.000001",
|
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"secid2": "0.399001",
|
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"fields1": "f1,f2,f3,f7",
|
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"fields2": "f51,f52,f53,f54,f55,f56,f57,f58,f59,f60,f61,f62,f63,f64,f65",
|
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"ut": "b2884a393a59ad64002292a3e90d46a5",
|
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"_": int(time.time() * 1000),
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}
|
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r = requests.get(url, params=params, headers=headers)
|
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data_json = r.json()
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content_list = data_json["data"]["klines"]
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temp_df = pd.DataFrame([item.split(",") for item in content_list])
|
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temp_df.columns = [
|
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"日期",
|
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"主力净流入-净额",
|
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"小单净流入-净额",
|
|
"中单净流入-净额",
|
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"大单净流入-净额",
|
|
"超大单净流入-净额",
|
|
"主力净流入-净占比",
|
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"小单净流入-净占比",
|
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"中单净流入-净占比",
|
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"大单净流入-净占比",
|
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"超大单净流入-净占比",
|
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"上证-收盘价",
|
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"上证-涨跌幅",
|
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"深证-收盘价",
|
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"深证-涨跌幅",
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]
|
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temp_df = temp_df[
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[
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"日期",
|
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"上证-收盘价",
|
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"上证-涨跌幅",
|
|
"深证-收盘价",
|
|
"深证-涨跌幅",
|
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"主力净流入-净额",
|
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"主力净流入-净占比",
|
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"超大单净流入-净额",
|
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"超大单净流入-净占比",
|
|
"大单净流入-净额",
|
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"大单净流入-净占比",
|
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"中单净流入-净额",
|
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"中单净流入-净占比",
|
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"小单净流入-净额",
|
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"小单净流入-净占比",
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]
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]
|
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temp_df["日期"] = pd.to_datetime(temp_df["日期"], errors="coerce").dt.date
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temp_df["上证-收盘价"] = pd.to_numeric(temp_df["上证-收盘价"], errors="coerce")
|
|
temp_df["上证-涨跌幅"] = pd.to_numeric(temp_df["上证-涨跌幅"], errors="coerce")
|
|
temp_df["深证-收盘价"] = pd.to_numeric(temp_df["深证-收盘价"], errors="coerce")
|
|
temp_df["深证-涨跌幅"] = pd.to_numeric(temp_df["深证-涨跌幅"], errors="coerce")
|
|
temp_df["主力净流入-净额"] = pd.to_numeric(
|
|
temp_df["主力净流入-净额"], errors="coerce"
|
|
)
|
|
temp_df["主力净流入-净占比"] = pd.to_numeric(
|
|
temp_df["主力净流入-净占比"], errors="coerce"
|
|
)
|
|
temp_df["超大单净流入-净额"] = pd.to_numeric(
|
|
temp_df["超大单净流入-净额"], errors="coerce"
|
|
)
|
|
temp_df["超大单净流入-净占比"] = pd.to_numeric(
|
|
temp_df["超大单净流入-净占比"], errors="coerce"
|
|
)
|
|
temp_df["大单净流入-净额"] = pd.to_numeric(
|
|
temp_df["大单净流入-净额"], errors="coerce"
|
|
)
|
|
temp_df["大单净流入-净占比"] = pd.to_numeric(
|
|
temp_df["大单净流入-净占比"], errors="coerce"
|
|
)
|
|
temp_df["中单净流入-净额"] = pd.to_numeric(
|
|
temp_df["中单净流入-净额"], errors="coerce"
|
|
)
|
|
temp_df["中单净流入-净占比"] = pd.to_numeric(
|
|
temp_df["中单净流入-净占比"], errors="coerce"
|
|
)
|
|
temp_df["小单净流入-净额"] = pd.to_numeric(
|
|
temp_df["小单净流入-净额"], errors="coerce"
|
|
)
|
|
temp_df["小单净流入-净占比"] = pd.to_numeric(
|
|
temp_df["小单净流入-净占比"], errors="coerce"
|
|
)
|
|
return temp_df
|
|
|
|
|
|
def stock_sector_fund_flow_rank(
|
|
indicator: str = "今日", sector_type: str = "行业资金流"
|
|
) -> pd.DataFrame:
|
|
"""
|
|
东方财富网-数据中心-资金流向-板块资金流-排名
|
|
https://data.eastmoney.com/bkzj/hy.html
|
|
:param indicator: choice of {"今日", "5日", "10日"}
|
|
:type indicator: str
|
|
:param sector_type: choice of {"行业资金流", "概念资金流", "地域资金流"}
|
|
:type sector_type: str
|
|
:return: 指定参数的资金流排名数据
|
|
:rtype: pandas.DataFrame
|
|
"""
|
|
sector_type_map = {"行业资金流": "2", "概念资金流": "3", "地域资金流": "1"}
|
|
indicator_map = {
|
|
"今日": [
|
|
"f62",
|
|
"1",
|
|
"f12,f14,f2,f3,f62,f184,f66,f69,f72,f75,f78,f81,f84,f87,f204,f205,f124",
|
|
],
|
|
"5日": [
|
|
"f164",
|
|
"5",
|
|
"f12,f14,f2,f109,f164,f165,f166,f167,f168,f169,f170,f171,f172,f173,f257,f258,f124",
|
|
],
|
|
"10日": [
|
|
"f174",
|
|
"10",
|
|
"f12,f14,f2,f160,f174,f175,f176,f177,f178,f179,f180,f181,f182,f183,f260,f261,f124",
|
|
],
|
|
}
|
|
url = "https://push2.eastmoney.com/api/qt/clist/get"
|
|
headers = {
|
|
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 "
|
|
"(KHTML, like Gecko) Chrome/81.0.4044.138 Safari/537.36",
|
|
}
|
|
params = {
|
|
"pn": "1",
|
|
"pz": "100",
|
|
"po": "1",
|
|
"np": "1",
|
|
"ut": "b2884a393a59ad64002292a3e90d46a5",
|
|
"fltt": "2",
|
|
"invt": "2",
|
|
"fid0": indicator_map[indicator][0],
|
|
"fs": f"m:90 t:{sector_type_map[sector_type]}",
|
|
"stat": indicator_map[indicator][1],
|
|
"fields": indicator_map[indicator][2],
|
|
"rt": "52975239",
|
|
"_": int(time.time() * 1000),
|
|
}
|
|
r = requests.get(url, params=params, headers=headers)
|
|
data_json = r.json()
|
|
total_page = math.ceil(data_json["data"]["total"] / 100)
|
|
temp_list = []
|
|
tqdm = get_tqdm()
|
|
for page in tqdm(range(1, total_page + 1), leave=False):
|
|
params.update(
|
|
{
|
|
"pn": page,
|
|
}
|
|
)
|
|
r = requests.get(url, params=params, timeout=15)
|
|
data_json = r.json()
|
|
inner_temp_df = pd.DataFrame(data_json["data"]["diff"])
|
|
temp_list.append(inner_temp_df)
|
|
temp_df = pd.concat(temp_list, ignore_index=True)
|
|
|
|
if indicator == "今日":
|
|
temp_df.columns = [
|
|
"-",
|
|
"今日涨跌幅",
|
|
"_",
|
|
"名称",
|
|
"今日主力净流入-净额",
|
|
"今日超大单净流入-净额",
|
|
"今日超大单净流入-净占比",
|
|
"今日大单净流入-净额",
|
|
"今日大单净流入-净占比",
|
|
"今日中单净流入-净额",
|
|
"今日中单净流入-净占比",
|
|
"今日小单净流入-净额",
|
|
"今日小单净流入-净占比",
|
|
"-",
|
|
"今日主力净流入-净占比",
|
|
"今日主力净流入最大股",
|
|
"今日主力净流入最大股代码",
|
|
"是否净流入",
|
|
]
|
|
|
|
temp_df = temp_df[
|
|
[
|
|
"名称",
|
|
"今日涨跌幅",
|
|
"今日主力净流入-净额",
|
|
"今日主力净流入-净占比",
|
|
"今日超大单净流入-净额",
|
|
"今日超大单净流入-净占比",
|
|
"今日大单净流入-净额",
|
|
"今日大单净流入-净占比",
|
|
"今日中单净流入-净额",
|
|
"今日中单净流入-净占比",
|
|
"今日小单净流入-净额",
|
|
"今日小单净流入-净占比",
|
|
"今日主力净流入最大股",
|
|
]
|
|
]
|
|
temp_df["今日主力净流入-净额"] = pd.to_numeric(
|
|
temp_df["今日主力净流入-净额"], errors="coerce"
|
|
)
|
|
temp_df.sort_values(["今日主力净流入-净额"], ascending=False, inplace=True)
|
|
temp_df.reset_index(inplace=True)
|
|
temp_df["index"] = range(1, len(temp_df) + 1)
|
|
temp_df.rename({"index": "序号"}, axis=1, inplace=True)
|
|
elif indicator == "5日":
|
|
temp_df.columns = [
|
|
"-",
|
|
"_",
|
|
"名称",
|
|
"5日涨跌幅",
|
|
"_",
|
|
"5日主力净流入-净额",
|
|
"5日主力净流入-净占比",
|
|
"5日超大单净流入-净额",
|
|
"5日超大单净流入-净占比",
|
|
"5日大单净流入-净额",
|
|
"5日大单净流入-净占比",
|
|
"5日中单净流入-净额",
|
|
"5日中单净流入-净占比",
|
|
"5日小单净流入-净额",
|
|
"5日小单净流入-净占比",
|
|
"5日主力净流入最大股",
|
|
"_",
|
|
"_",
|
|
]
|
|
|
|
temp_df = temp_df[
|
|
[
|
|
"名称",
|
|
"5日涨跌幅",
|
|
"5日主力净流入-净额",
|
|
"5日主力净流入-净占比",
|
|
"5日超大单净流入-净额",
|
|
"5日超大单净流入-净占比",
|
|
"5日大单净流入-净额",
|
|
"5日大单净流入-净占比",
|
|
"5日中单净流入-净额",
|
|
"5日中单净流入-净占比",
|
|
"5日小单净流入-净额",
|
|
"5日小单净流入-净占比",
|
|
"5日主力净流入最大股",
|
|
]
|
|
]
|
|
temp_df.sort_values(["5日主力净流入-净额"], ascending=False, inplace=True)
|
|
temp_df.reset_index(inplace=True)
|
|
temp_df["index"] = range(1, len(temp_df) + 1)
|
|
temp_df.rename({"index": "序号"}, axis=1, inplace=True)
|
|
elif indicator == "10日":
|
|
temp_df.columns = [
|
|
"-",
|
|
"_",
|
|
"名称",
|
|
"_",
|
|
"10日涨跌幅",
|
|
"10日主力净流入-净额",
|
|
"10日主力净流入-净占比",
|
|
"10日超大单净流入-净额",
|
|
"10日超大单净流入-净占比",
|
|
"10日大单净流入-净额",
|
|
"10日大单净流入-净占比",
|
|
"10日中单净流入-净额",
|
|
"10日中单净流入-净占比",
|
|
"10日小单净流入-净额",
|
|
"10日小单净流入-净占比",
|
|
"10日主力净流入最大股",
|
|
"_",
|
|
"_",
|
|
]
|
|
|
|
temp_df = temp_df[
|
|
[
|
|
"名称",
|
|
"10日涨跌幅",
|
|
"10日主力净流入-净额",
|
|
"10日主力净流入-净占比",
|
|
"10日超大单净流入-净额",
|
|
"10日超大单净流入-净占比",
|
|
"10日大单净流入-净额",
|
|
"10日大单净流入-净占比",
|
|
"10日中单净流入-净额",
|
|
"10日中单净流入-净占比",
|
|
"10日小单净流入-净额",
|
|
"10日小单净流入-净占比",
|
|
"10日主力净流入最大股",
|
|
]
|
|
]
|
|
temp_df.sort_values(["10日主力净流入-净额"], ascending=False, inplace=True)
|
|
temp_df.reset_index(inplace=True)
|
|
temp_df["index"] = range(1, len(temp_df) + 1)
|
|
temp_df.rename({"index": "序号"}, axis=1, inplace=True)
|
|
return temp_df
|
|
|
|
|
|
@lru_cache()
|
|
def _get_stock_sector_fund_flow_summary_code() -> dict:
|
|
"""
|
|
东方财富网-数据中心-资金流向-行业板块
|
|
https://data.eastmoney.com/bkzj/gn.html
|
|
:return: 行业板块与代码字典
|
|
:rtype: dict
|
|
"""
|
|
url = "https://push2.eastmoney.com/api/qt/clist/get"
|
|
params = {
|
|
"fid": "f62",
|
|
"po": "1",
|
|
"pz": "100",
|
|
"pn": "1",
|
|
"np": "1",
|
|
"fltt": "2",
|
|
"invt": "2",
|
|
"ut": "8dec03ba335b81bf4ebdf7b29ec27d15",
|
|
"fs": "m:90 t:2",
|
|
"fields": "f12,f14,f2,f3,f62,f184,f66,f69,f72,f75,f78,f81,f84,f87,f204,f205,f124,f1,f13",
|
|
}
|
|
temp_df = fetch_paginated_data(url, params)
|
|
name_code_map = dict(zip(temp_df["f14"], temp_df["f12"]))
|
|
return name_code_map
|
|
|
|
|
|
def stock_sector_fund_flow_summary(
|
|
symbol: str = "电源设备", indicator: str = "今日"
|
|
) -> pd.DataFrame:
|
|
"""
|
|
东方财富网-数据中心-资金流向-行业资金流-xx行业个股资金流
|
|
https://data.eastmoney.com/bkzj/BK1034.html
|
|
:param symbol: 行业名称
|
|
:type symbol: str
|
|
:param indicator: choice of {"今日", "5日", "10日"}
|
|
:type indicator: str
|
|
:return: xx行业个股资金流
|
|
:rtype: pandas.DataFrame
|
|
"""
|
|
code_name_map = _get_stock_sector_fund_flow_summary_code()
|
|
url = "https://push2.eastmoney.com/api/qt/clist/get"
|
|
if indicator == "今日":
|
|
params = {
|
|
"fid": "f62",
|
|
"po": "1",
|
|
"pz": "5000",
|
|
"pn": "1",
|
|
"np": "2",
|
|
"fltt": "2",
|
|
"invt": "2",
|
|
"fs": f"b:{code_name_map[symbol]}",
|
|
"fields": "f12,f14,f2,f3,f62,f184,f66,f69,f72,f75,f78,f81,f84,f87,f204,f205,f124,f1,f13",
|
|
}
|
|
r = requests.get(url, params=params)
|
|
data_json = r.json()
|
|
temp_df = pd.DataFrame(data_json["data"]["diff"]).T
|
|
temp_df.reset_index(inplace=True)
|
|
temp_df["index"] = temp_df["index"].astype(int) + 1
|
|
temp_df.rename(
|
|
columns={
|
|
"index": "序号",
|
|
"f12": "代码",
|
|
"f14": "名称",
|
|
"f2": "最新价",
|
|
"f3": "今天涨跌幅",
|
|
"f62": "今日主力净流入-净额",
|
|
"f184": "今日主力净流入-净占比",
|
|
"f66": "今日超大单净流入-净额",
|
|
"f69": "今日超大单净流入-净占比",
|
|
"f72": "今日大单净流入-净额",
|
|
"f75": "今日大单净流入-净占比",
|
|
"f78": "今日中单净流入-净额",
|
|
"f81": "今日中单净流入-净占比",
|
|
"f84": "今日小单净流入-净额",
|
|
"f87": "今日小单净流入-净占比",
|
|
},
|
|
inplace=True,
|
|
)
|
|
temp_df = temp_df[
|
|
[
|
|
"序号",
|
|
"代码",
|
|
"名称",
|
|
"最新价",
|
|
"今天涨跌幅",
|
|
"今日主力净流入-净额",
|
|
"今日主力净流入-净占比",
|
|
"今日超大单净流入-净额",
|
|
"今日超大单净流入-净占比",
|
|
"今日大单净流入-净额",
|
|
"今日大单净流入-净占比",
|
|
"今日中单净流入-净额",
|
|
"今日中单净流入-净占比",
|
|
"今日小单净流入-净额",
|
|
"今日小单净流入-净占比",
|
|
]
|
|
]
|
|
temp_df["最新价"] = pd.to_numeric(temp_df["最新价"], errors="coerce")
|
|
temp_df["今天涨跌幅"] = pd.to_numeric(temp_df["今天涨跌幅"], errors="coerce")
|
|
temp_df["今日主力净流入-净额"] = pd.to_numeric(
|
|
temp_df["今日主力净流入-净额"], errors="coerce"
|
|
)
|
|
temp_df["今日主力净流入-净占比"] = pd.to_numeric(
|
|
temp_df["今日主力净流入-净占比"], errors="coerce"
|
|
)
|
|
temp_df["今日超大单净流入-净额"] = pd.to_numeric(
|
|
temp_df["今日超大单净流入-净额"], errors="coerce"
|
|
)
|
|
temp_df["今日超大单净流入-净占比"] = pd.to_numeric(
|
|
temp_df["今日超大单净流入-净占比"], errors="coerce"
|
|
)
|
|
temp_df["今日大单净流入-净额"] = pd.to_numeric(
|
|
temp_df["今日大单净流入-净额"], errors="coerce"
|
|
)
|
|
temp_df["今日大单净流入-净占比"] = pd.to_numeric(
|
|
temp_df["今日大单净流入-净占比"], errors="coerce"
|
|
)
|
|
temp_df["今日中单净流入-净额"] = pd.to_numeric(
|
|
temp_df["今日中单净流入-净额"], errors="coerce"
|
|
)
|
|
temp_df["今日中单净流入-净占比"] = pd.to_numeric(
|
|
temp_df["今日中单净流入-净占比"], errors="coerce"
|
|
)
|
|
temp_df["今日小单净流入-净额"] = pd.to_numeric(
|
|
temp_df["今日小单净流入-净额"], errors="coerce"
|
|
)
|
|
temp_df["今日小单净流入-净占比"] = pd.to_numeric(
|
|
temp_df["今日小单净流入-净占比"], errors="coerce"
|
|
)
|
|
return temp_df
|
|
if indicator == "5日":
|
|
params = {
|
|
"fid": "f164",
|
|
"po": "1",
|
|
"pz": "50000",
|
|
"pn": "1",
|
|
"np": "2",
|
|
"fltt": "2",
|
|
"invt": "2",
|
|
"fs": f"b:{code_name_map[symbol]}",
|
|
"fields": "f12,f14,f2,f109,f164,f165,f166,f167,f168,f169,f170,f171,f172,f173,f257,f258,f124,f1,f13",
|
|
}
|
|
r = requests.get(url, params=params)
|
|
data_json = r.json()
|
|
temp_df = pd.DataFrame(data_json["data"]["diff"]).T
|
|
temp_df.reset_index(inplace=True)
|
|
temp_df["index"] = temp_df["index"].astype(int) + 1
|
|
temp_df.rename(
|
|
columns={
|
|
"index": "序号",
|
|
"f12": "代码",
|
|
"f14": "名称",
|
|
"f2": "最新价",
|
|
"f109": "5日涨跌幅",
|
|
"f164": "5日主力净流入-净额",
|
|
"f165": "5日主力净流入-净占比",
|
|
"f166": "5日超大单净流入-净额",
|
|
"f167": "5日超大单净流入-净占比",
|
|
"f168": "5日大单净流入-净额",
|
|
"f169": "5日大单净流入-净占比",
|
|
"f170": "5日中单净流入-净额",
|
|
"f171": "5日中单净流入-净占比",
|
|
"f172": "5日小单净流入-净额",
|
|
"f173": "5日小单净流入-净占比",
|
|
},
|
|
inplace=True,
|
|
)
|
|
temp_df = temp_df[
|
|
[
|
|
"序号",
|
|
"代码",
|
|
"名称",
|
|
"最新价",
|
|
"5日涨跌幅",
|
|
"5日主力净流入-净额",
|
|
"5日主力净流入-净占比",
|
|
"5日超大单净流入-净额",
|
|
"5日超大单净流入-净占比",
|
|
"5日大单净流入-净额",
|
|
"5日大单净流入-净占比",
|
|
"5日中单净流入-净额",
|
|
"5日中单净流入-净占比",
|
|
"5日小单净流入-净额",
|
|
"5日小单净流入-净占比",
|
|
]
|
|
]
|
|
temp_df["最新价"] = pd.to_numeric(temp_df["最新价"], errors="coerce")
|
|
temp_df["5日涨跌幅"] = pd.to_numeric(temp_df["5日涨跌幅"], errors="coerce")
|
|
temp_df["5日主力净流入-净额"] = pd.to_numeric(
|
|
temp_df["5日主力净流入-净额"], errors="coerce"
|
|
)
|
|
temp_df["5日主力净流入-净占比"] = pd.to_numeric(
|
|
temp_df["5日主力净流入-净占比"], errors="coerce"
|
|
)
|
|
temp_df["5日超大单净流入-净额"] = pd.to_numeric(
|
|
temp_df["5日超大单净流入-净额"], errors="coerce"
|
|
)
|
|
temp_df["5日超大单净流入-净占比"] = pd.to_numeric(
|
|
temp_df["5日超大单净流入-净占比"], errors="coerce"
|
|
)
|
|
temp_df["5日大单净流入-净额"] = pd.to_numeric(
|
|
temp_df["5日大单净流入-净额"], errors="coerce"
|
|
)
|
|
temp_df["5日大单净流入-净占比"] = pd.to_numeric(
|
|
temp_df["5日大单净流入-净占比"], errors="coerce"
|
|
)
|
|
temp_df["5日中单净流入-净额"] = pd.to_numeric(
|
|
temp_df["5日中单净流入-净额"], errors="coerce"
|
|
)
|
|
temp_df["5日中单净流入-净占比"] = pd.to_numeric(
|
|
temp_df["5日中单净流入-净占比"], errors="coerce"
|
|
)
|
|
temp_df["5日小单净流入-净额"] = pd.to_numeric(
|
|
temp_df["5日小单净流入-净额"], errors="coerce"
|
|
)
|
|
temp_df["5日小单净流入-净占比"] = pd.to_numeric(
|
|
temp_df["5日小单净流入-净占比"], errors="coerce"
|
|
)
|
|
return temp_df
|
|
if indicator == "10日":
|
|
params = {
|
|
"fid": "f174",
|
|
"po": "1",
|
|
"pz": "50000",
|
|
"pn": "1",
|
|
"np": "2",
|
|
"fltt": "2",
|
|
"invt": "2",
|
|
"fs": f"b:{code_name_map[symbol]}",
|
|
"fields": "f12,f14,f2,f160,f174,f175,f176,f177,f178,f179,f180,f181,f182,f183,f260,f261,f124,f1,f13",
|
|
}
|
|
r = requests.get(url, params=params)
|
|
data_json = r.json()
|
|
temp_df = pd.DataFrame(data_json["data"]["diff"]).T
|
|
temp_df.reset_index(inplace=True)
|
|
temp_df["index"] = temp_df["index"].astype(int) + 1
|
|
temp_df.rename(
|
|
columns={
|
|
"index": "序号",
|
|
"f12": "代码",
|
|
"f14": "名称",
|
|
"f2": "最新价",
|
|
"f160": "10日涨跌幅",
|
|
"f174": "10日主力净流入-净额",
|
|
"f175": "10日主力净流入-净占比",
|
|
"f176": "10日超大单净流入-净额",
|
|
"f177": "10日超大单净流入-净占比",
|
|
"f178": "10日大单净流入-净额",
|
|
"f179": "10日大单净流入-净占比",
|
|
"f180": "10日中单净流入-净额",
|
|
"f181": "10日中单净流入-净占比",
|
|
"f182": "10日小单净流入-净额",
|
|
"f183": "10日小单净流入-净占比",
|
|
},
|
|
inplace=True,
|
|
)
|
|
temp_df = temp_df[
|
|
[
|
|
"序号",
|
|
"代码",
|
|
"名称",
|
|
"最新价",
|
|
"10日涨跌幅",
|
|
"10日主力净流入-净额",
|
|
"10日主力净流入-净占比",
|
|
"10日超大单净流入-净额",
|
|
"10日超大单净流入-净占比",
|
|
"10日大单净流入-净额",
|
|
"10日大单净流入-净占比",
|
|
"10日中单净流入-净额",
|
|
"10日中单净流入-净占比",
|
|
"10日小单净流入-净额",
|
|
"10日小单净流入-净占比",
|
|
]
|
|
]
|
|
temp_df["最新价"] = pd.to_numeric(temp_df["最新价"], errors="coerce")
|
|
temp_df["10日涨跌幅"] = pd.to_numeric(temp_df["10日涨跌幅"], errors="coerce")
|
|
temp_df["10日主力净流入-净额"] = pd.to_numeric(
|
|
temp_df["10日主力净流入-净额"], errors="coerce"
|
|
)
|
|
temp_df["10日主力净流入-净占比"] = pd.to_numeric(
|
|
temp_df["10日主力净流入-净占比"], errors="coerce"
|
|
)
|
|
temp_df["10日超大单净流入-净额"] = pd.to_numeric(
|
|
temp_df["10日超大单净流入-净额"], errors="coerce"
|
|
)
|
|
temp_df["10日超大单净流入-净占比"] = pd.to_numeric(
|
|
temp_df["10日超大单净流入-净占比"], errors="coerce"
|
|
)
|
|
temp_df["10日大单净流入-净额"] = pd.to_numeric(
|
|
temp_df["10日大单净流入-净额"], errors="coerce"
|
|
)
|
|
temp_df["10日大单净流入-净占比"] = pd.to_numeric(
|
|
temp_df["10日大单净流入-净占比"], errors="coerce"
|
|
)
|
|
temp_df["10日中单净流入-净额"] = pd.to_numeric(
|
|
temp_df["10日中单净流入-净额"], errors="coerce"
|
|
)
|
|
temp_df["10日中单净流入-净占比"] = pd.to_numeric(
|
|
temp_df["10日中单净流入-净占比"], errors="coerce"
|
|
)
|
|
temp_df["10日小单净流入-净额"] = pd.to_numeric(
|
|
temp_df["10日小单净流入-净额"], errors="coerce"
|
|
)
|
|
temp_df["10日小单净流入-净占比"] = pd.to_numeric(
|
|
temp_df["10日小单净流入-净占比"], errors="coerce"
|
|
)
|
|
return temp_df
|
|
else:
|
|
return pd.DataFrame()
|
|
|
|
|
|
def stock_sector_fund_flow_hist(symbol: str = "汽车服务") -> pd.DataFrame:
|
|
"""
|
|
东方财富网-数据中心-资金流向-行业资金流-行业历史资金流
|
|
https://data.eastmoney.com/bkzj/BK1034.html
|
|
:param symbol: 行业名称
|
|
:type symbol: str
|
|
:return: xx行业个股资金流
|
|
:rtype: pandas.DataFrame
|
|
"""
|
|
code_name_map = _get_stock_sector_fund_flow_summary_code()
|
|
url = "https://push2his.eastmoney.com/api/qt/stock/fflow/daykline/get"
|
|
params = {
|
|
"lmt": "0",
|
|
"klt": "101",
|
|
"fields1": "f1,f2,f3,f7",
|
|
"fields2": "f51,f52,f53,f54,f55,f56,f57,f58,f59,f60,f61,f62,f63,f64,f65",
|
|
"secid": f"90.{code_name_map[symbol]}",
|
|
}
|
|
r = requests.get(url, params=params)
|
|
data_json = r.json()
|
|
temp_df = pd.DataFrame([item.split(",") for item in data_json["data"]["klines"]])
|
|
temp_df.columns = [
|
|
"日期",
|
|
"主力净流入-净额",
|
|
"小单净流入-净额",
|
|
"中单净流入-净额",
|
|
"大单净流入-净额",
|
|
"超大单净流入-净额",
|
|
"主力净流入-净占比",
|
|
"小单净流入-净占比",
|
|
"中单净流入-净占比",
|
|
"大单净流入-净占比",
|
|
"超大单净流入-净占比",
|
|
"-",
|
|
"-",
|
|
"-",
|
|
"-",
|
|
]
|
|
temp_df = temp_df[
|
|
[
|
|
"日期",
|
|
"主力净流入-净额",
|
|
"主力净流入-净占比",
|
|
"超大单净流入-净额",
|
|
"超大单净流入-净占比",
|
|
"大单净流入-净额",
|
|
"大单净流入-净占比",
|
|
"中单净流入-净额",
|
|
"中单净流入-净占比",
|
|
"小单净流入-净额",
|
|
"小单净流入-净占比",
|
|
]
|
|
]
|
|
temp_df["主力净流入-净额"] = pd.to_numeric(
|
|
temp_df["主力净流入-净额"], errors="coerce"
|
|
)
|
|
temp_df["主力净流入-净占比"] = pd.to_numeric(
|
|
temp_df["主力净流入-净占比"], errors="coerce"
|
|
)
|
|
temp_df["超大单净流入-净额"] = pd.to_numeric(
|
|
temp_df["超大单净流入-净额"], errors="coerce"
|
|
)
|
|
temp_df["超大单净流入-净占比"] = pd.to_numeric(
|
|
temp_df["超大单净流入-净占比"], errors="coerce"
|
|
)
|
|
temp_df["大单净流入-净额"] = pd.to_numeric(
|
|
temp_df["大单净流入-净额"], errors="coerce"
|
|
)
|
|
temp_df["大单净流入-净占比"] = pd.to_numeric(
|
|
temp_df["大单净流入-净占比"], errors="coerce"
|
|
)
|
|
temp_df["中单净流入-净额"] = pd.to_numeric(
|
|
temp_df["中单净流入-净额"], errors="coerce"
|
|
)
|
|
temp_df["中单净流入-净占比"] = pd.to_numeric(
|
|
temp_df["中单净流入-净占比"], errors="coerce"
|
|
)
|
|
temp_df["小单净流入-净额"] = pd.to_numeric(
|
|
temp_df["小单净流入-净额"], errors="coerce"
|
|
)
|
|
temp_df["小单净流入-净占比"] = pd.to_numeric(
|
|
temp_df["小单净流入-净占比"], errors="coerce"
|
|
)
|
|
temp_df["日期"] = pd.to_datetime(temp_df["日期"], errors="coerce").dt.date
|
|
return temp_df
|
|
|
|
|
|
@lru_cache()
|
|
def _get_stock_concept_fund_flow_summary_code() -> dict:
|
|
"""
|
|
东方财富网-数据中心-资金流向-概念资金流
|
|
https://data.eastmoney.com/bkzj/gn.html
|
|
:return: 概念与代码字典
|
|
:rtype: dict
|
|
"""
|
|
url = "https://push2.eastmoney.com/api/qt/clist/get"
|
|
params = {
|
|
"pn": "1",
|
|
"pz": "100",
|
|
"po": "1",
|
|
"np": "1",
|
|
"fields": "f3,f12,f13,f14,f62",
|
|
"fid": "f62",
|
|
"fs": "m:90+t:3",
|
|
"ut": "b2884a393a59ad64002292a3e90d46a5",
|
|
"_": int(time.time() * 1000),
|
|
}
|
|
temp_df = fetch_paginated_data(url, params)
|
|
name_code_map = dict(zip(temp_df["f14"], temp_df["f12"]))
|
|
return name_code_map
|
|
|
|
|
|
def stock_concept_fund_flow_hist(symbol: str = "数据要素") -> pd.DataFrame:
|
|
"""
|
|
东方财富网-数据中心-资金流向-概念资金流-概念历史资金流
|
|
https://data.eastmoney.com/bkzj/BK0574.html
|
|
:param symbol: 概念名称
|
|
:type symbol: str
|
|
:return: 概念历史资金流
|
|
:rtype: pandas.DataFrame
|
|
"""
|
|
code_name_map = _get_stock_concept_fund_flow_summary_code()
|
|
url = "https://push2his.eastmoney.com/api/qt/stock/fflow/daykline/get"
|
|
params = {
|
|
"lmt": "0",
|
|
"klt": "101",
|
|
"fields1": "f1,f2,f3,f7",
|
|
"fields2": "f51,f52,f53,f54,f55,f56,f57,f58,f59,f60,f61,f62,f63,f64,f65",
|
|
"secid": f"90.{code_name_map[symbol]}",
|
|
}
|
|
r = requests.get(url, params=params)
|
|
data_json = r.json()
|
|
temp_df = pd.DataFrame([item.split(",") for item in data_json["data"]["klines"]])
|
|
temp_df.columns = [
|
|
"日期",
|
|
"主力净流入-净额",
|
|
"小单净流入-净额",
|
|
"中单净流入-净额",
|
|
"大单净流入-净额",
|
|
"超大单净流入-净额",
|
|
"主力净流入-净占比",
|
|
"小单净流入-净占比",
|
|
"中单净流入-净占比",
|
|
"大单净流入-净占比",
|
|
"超大单净流入-净占比",
|
|
"-",
|
|
"-",
|
|
"-",
|
|
"-",
|
|
]
|
|
temp_df = temp_df[
|
|
[
|
|
"日期",
|
|
"主力净流入-净额",
|
|
"主力净流入-净占比",
|
|
"超大单净流入-净额",
|
|
"超大单净流入-净占比",
|
|
"大单净流入-净额",
|
|
"大单净流入-净占比",
|
|
"中单净流入-净额",
|
|
"中单净流入-净占比",
|
|
"小单净流入-净额",
|
|
"小单净流入-净占比",
|
|
]
|
|
]
|
|
temp_df["主力净流入-净额"] = pd.to_numeric(
|
|
temp_df["主力净流入-净额"], errors="coerce"
|
|
)
|
|
temp_df["主力净流入-净占比"] = pd.to_numeric(
|
|
temp_df["主力净流入-净占比"], errors="coerce"
|
|
)
|
|
temp_df["超大单净流入-净额"] = pd.to_numeric(
|
|
temp_df["超大单净流入-净额"], errors="coerce"
|
|
)
|
|
temp_df["超大单净流入-净占比"] = pd.to_numeric(
|
|
temp_df["超大单净流入-净占比"], errors="coerce"
|
|
)
|
|
temp_df["大单净流入-净额"] = pd.to_numeric(
|
|
temp_df["大单净流入-净额"], errors="coerce"
|
|
)
|
|
temp_df["大单净流入-净占比"] = pd.to_numeric(
|
|
temp_df["大单净流入-净占比"], errors="coerce"
|
|
)
|
|
temp_df["中单净流入-净额"] = pd.to_numeric(
|
|
temp_df["中单净流入-净额"], errors="coerce"
|
|
)
|
|
temp_df["中单净流入-净占比"] = pd.to_numeric(
|
|
temp_df["中单净流入-净占比"], errors="coerce"
|
|
)
|
|
temp_df["小单净流入-净额"] = pd.to_numeric(
|
|
temp_df["小单净流入-净额"], errors="coerce"
|
|
)
|
|
temp_df["小单净流入-净占比"] = pd.to_numeric(
|
|
temp_df["小单净流入-净占比"], errors="coerce"
|
|
)
|
|
temp_df["日期"] = pd.to_datetime(temp_df["日期"]).dt.date
|
|
return temp_df
|
|
|
|
|
|
def stock_main_fund_flow(symbol: str = "全部股票") -> pd.DataFrame:
|
|
"""
|
|
东方财富网-数据中心-资金流向-主力净流入排名
|
|
https://data.eastmoney.com/zjlx/list.html
|
|
:param symbol: 全部股票; choice of {"全部股票", "沪深A股", "沪市A股", "科创板", "深市A股", "创业板", "沪市B股", "深市B股"}
|
|
:type symbol: str
|
|
:return: 主力净流入排名
|
|
:rtype: pandas.DataFrame
|
|
"""
|
|
symbol_map = {
|
|
"全部股票": "m:0+t:6+f:!2,m:0+t:13+f:!2,m:0+t:80+f:!2,m:1+t:2+f:!2,m:1+t:23+f:!2,m:0+t:7+f:!2,m:1+t:3+f:!2",
|
|
"沪深A股": "m:0+t:6+f:!2,m:0+t:13+f:!2,m:0+t:80+f:!2,m:1+t:2+f:!2,m:1+t:23+f:!2",
|
|
"沪市A股": "m:1+t:2+f:!2,m:1+t:23+f:!2",
|
|
"科创板": "m:1+t:23+f:!2",
|
|
"深市A股": "m:0+t:6+f:!2,m:0+t:13+f:!2,m:0+t:80+f:!2",
|
|
"创业板": "m:0+t:80+f:!2",
|
|
"沪市B股": "m:1+t:3+f:!2",
|
|
"深市B股": "m:0+t:7+f:!2",
|
|
}
|
|
url = "https://push2.eastmoney.com/api/qt/clist/get"
|
|
params = {
|
|
"fid": "f184",
|
|
"po": "1",
|
|
"pz": "100",
|
|
"pn": "1",
|
|
"np": "1",
|
|
"fltt": "2",
|
|
"invt": "2",
|
|
"fields": "f2,f3,f12,f13,f14,f62,f184,f225,f165,f263,f109,f175,f264,f160,f100,f124,f265,f1",
|
|
"ut": "b2884a393a59ad64002292a3e90d46a5",
|
|
"fs": symbol_map[symbol],
|
|
}
|
|
temp_df = fetch_paginated_data(url, params)
|
|
temp_df.rename(
|
|
columns={
|
|
"index": "序号",
|
|
"f12": "代码",
|
|
"f14": "名称",
|
|
"f2": "最新价",
|
|
"f184": "今日排行榜-主力净占比",
|
|
"f225": "今日排行榜-今日排名",
|
|
"f3": "今日排行榜-今日涨跌",
|
|
"f165": "5日排行榜-主力净占比",
|
|
"f263": "5日排行榜-5日排名",
|
|
"f109": "5日排行榜-5日涨跌",
|
|
"f175": "10日排行榜-主力净占比",
|
|
"f264": "10日排行榜-10日排名",
|
|
"f160": "10日排行榜-10日涨跌",
|
|
"f100": "所属板块",
|
|
},
|
|
inplace=True,
|
|
)
|
|
temp_df = temp_df[
|
|
[
|
|
"序号",
|
|
"代码",
|
|
"名称",
|
|
"最新价",
|
|
"今日排行榜-主力净占比",
|
|
"今日排行榜-今日排名",
|
|
"今日排行榜-今日涨跌",
|
|
"5日排行榜-主力净占比",
|
|
"5日排行榜-5日排名",
|
|
"5日排行榜-5日涨跌",
|
|
"10日排行榜-主力净占比",
|
|
"10日排行榜-10日排名",
|
|
"10日排行榜-10日涨跌",
|
|
"所属板块",
|
|
]
|
|
]
|
|
temp_df["最新价"] = pd.to_numeric(temp_df["最新价"], errors="coerce")
|
|
temp_df["今日排行榜-主力净占比"] = pd.to_numeric(
|
|
temp_df["今日排行榜-主力净占比"], errors="coerce"
|
|
)
|
|
temp_df["今日排行榜-今日排名"] = pd.to_numeric(
|
|
temp_df["今日排行榜-今日排名"], errors="coerce"
|
|
)
|
|
temp_df["今日排行榜-今日涨跌"] = pd.to_numeric(
|
|
temp_df["今日排行榜-今日涨跌"], errors="coerce"
|
|
)
|
|
temp_df["5日排行榜-主力净占比"] = pd.to_numeric(
|
|
temp_df["5日排行榜-主力净占比"], errors="coerce"
|
|
)
|
|
temp_df["5日排行榜-5日排名"] = pd.to_numeric(
|
|
temp_df["5日排行榜-5日排名"], errors="coerce"
|
|
)
|
|
temp_df["5日排行榜-5日涨跌"] = pd.to_numeric(
|
|
temp_df["5日排行榜-5日涨跌"], errors="coerce"
|
|
)
|
|
temp_df["10日排行榜-主力净占比"] = pd.to_numeric(
|
|
temp_df["10日排行榜-主力净占比"], errors="coerce"
|
|
)
|
|
temp_df["10日排行榜-10日排名"] = pd.to_numeric(
|
|
temp_df["10日排行榜-10日排名"], errors="coerce"
|
|
)
|
|
temp_df["10日排行榜-10日涨跌"] = pd.to_numeric(
|
|
temp_df["10日排行榜-10日涨跌"], errors="coerce"
|
|
)
|
|
return temp_df
|
|
|
|
|
|
if __name__ == "__main__":
|
|
stock_individual_fund_flow_df = stock_individual_fund_flow(
|
|
stock="600094", market="sh"
|
|
)
|
|
print(stock_individual_fund_flow_df)
|
|
|
|
stock_individual_fund_flow_rank_df = stock_individual_fund_flow_rank(
|
|
indicator="今日"
|
|
)
|
|
print(stock_individual_fund_flow_rank_df)
|
|
|
|
stock_individual_fund_flow_rank_df = stock_individual_fund_flow_rank(
|
|
indicator="3日"
|
|
)
|
|
print(stock_individual_fund_flow_rank_df)
|
|
|
|
stock_individual_fund_flow_rank_df = stock_individual_fund_flow_rank(
|
|
indicator="5日"
|
|
)
|
|
print(stock_individual_fund_flow_rank_df)
|
|
|
|
stock_individual_fund_flow_rank_df = stock_individual_fund_flow_rank(
|
|
indicator="10日"
|
|
)
|
|
print(stock_individual_fund_flow_rank_df)
|
|
|
|
stock_market_fund_flow_df = stock_market_fund_flow()
|
|
print(stock_market_fund_flow_df)
|
|
|
|
stock_sector_fund_flow_rank_df = stock_sector_fund_flow_rank(
|
|
indicator="今日", sector_type="地域资金流"
|
|
)
|
|
print(stock_sector_fund_flow_rank_df)
|
|
|
|
stock_sector_fund_flow_rank_df = stock_sector_fund_flow_rank(
|
|
indicator="今日", sector_type="行业资金流"
|
|
)
|
|
print(stock_sector_fund_flow_rank_df)
|
|
|
|
stock_sector_fund_flow_rank_df = stock_sector_fund_flow_rank(
|
|
indicator="今日", sector_type="概念资金流"
|
|
)
|
|
print(stock_sector_fund_flow_rank_df)
|
|
|
|
stock_sector_fund_flow_summary_df = stock_sector_fund_flow_summary(
|
|
symbol="文化传媒", indicator="今日"
|
|
)
|
|
print(stock_sector_fund_flow_summary_df)
|
|
|
|
stock_sector_fund_flow_hist_df = stock_sector_fund_flow_hist(symbol="汽车服务")
|
|
print(stock_sector_fund_flow_hist_df)
|
|
|
|
stock_concept_fund_flow_hist_df = stock_concept_fund_flow_hist(symbol="半导体概念")
|
|
print(stock_concept_fund_flow_hist_df)
|
|
|
|
stock_main_fund_flow_df = stock_main_fund_flow(symbol="全部股票")
|
|
print(stock_main_fund_flow_df)
|