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
940 lines
30 KiB
Python
940 lines
30 KiB
Python
import os
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import re
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import signal
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from typing import List, Union, Dict
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import threading
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from bs4 import BeautifulSoup
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import multitasking
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import pandas as pd
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import requests
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import rich
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from jsonpath import jsonpath
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from retry import retry
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from tqdm.auto import tqdm
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import time
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from ..utils import to_numeric
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from .config import EastmoneyFundHeaders
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from ..common.config import MagicConfig
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from ..shared import session, MAX_CONNECTIONS
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import warnings
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warnings.filterwarnings("module")
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if threading.current_thread() is threading.main_thread():
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signal.signal(signal.SIGINT, multitasking.killall)
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fund_session = session
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@retry(tries=3)
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@to_numeric
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def get_quote_history(fund_code: str, pz: int = 40000) -> pd.DataFrame:
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"""
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根据基金代码和要获取的页码抓取基金净值信息
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Parameters
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----------
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fund_code : str
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6 位基金代码
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pz : int, optional
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页码, 默认为 40000 以获取全部历史数据
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Returns
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-------
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DataFrame
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包含基金历史净值等数据
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Examples
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--------
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>>> import efinance as ef
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>>> ef.fund.get_quote_history('161725')
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日期 单位净值 累计净值 涨跌幅
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0 2021-06-11 1.5188 3.1499 -3.09
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1 2021-06-10 1.5673 3.1984 1.69
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2 2021-06-09 1.5412 3.1723 0.11
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3 2021-06-08 1.5395 3.1706 -6.5
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4 2021-06-07 1.6466 3.2777 1.61
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... ... ... ... ...
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1469 2015-06-08 1.0380 1.0380 2.5692
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1470 2015-06-05 1.0120 1.0120 1.5045
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1471 2015-06-04 0.9970 0.9970 --
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1472 2015-05-29 0.9950 0.9950 --
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1473 2015-05-27 1.0000 1.0000 --
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"""
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data = {
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"FCODE": f"{fund_code}",
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"IsShareNet": "true",
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"MobileKey": "1",
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"appType": "ttjj",
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"appVersion": "6.2.8",
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"cToken": "1",
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"deviceid": "1",
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"pageIndex": "1",
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"pageSize": f"{pz}",
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"plat": "Iphone",
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"product": "EFund",
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"serverVersion": "6.2.8",
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"uToken": "1",
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"userId": "1",
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"version": "6.2.8",
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}
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url = "https://fundmobapi.eastmoney.com/FundMNewApi/FundMNHisNetList"
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json_response = fund_session.get(
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url, headers=EastmoneyFundHeaders, data=data, verify=False
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).json()
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rows = []
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columns = ["日期", "单位净值", "累计净值", "涨跌幅"]
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if json_response is None:
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return pd.DataFrame(rows, columns=columns)
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datas = json_response["Datas"]
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if len(datas) == 0:
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return pd.DataFrame(rows, columns=columns)
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rows = []
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for stock in datas:
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date = stock["FSRQ"]
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rows.append(
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{
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"日期": date,
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"单位净值": stock["DWJZ"],
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"累计净值": stock["LJJZ"],
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"涨跌幅": stock["JZZZL"],
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}
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)
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df = pd.DataFrame(rows)
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return df
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def get_quote_history_multi(
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fund_codes: List[str], pz: int = 40000, **kwargs
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) -> Dict[str, pd.DataFrame]:
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dfs: Dict[str, pd.DataFrame] = {}
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pbar = tqdm(total=len(fund_codes))
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@multitasking.task
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@retry(tries=3, delay=1)
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def start(fund_code: str):
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if len(multitasking.get_active_tasks()) >= MAX_CONNECTIONS:
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time.sleep(3)
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_df = get_quote_history(fund_code, pz)
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dfs[fund_code] = _df
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pbar.update(1)
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pbar.set_description_str(f"Processing => {fund_code}")
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for f in fund_codes:
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start(f)
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multitasking.wait_for_tasks()
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pbar.close()
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if kwargs.get(MagicConfig.RETURN_DF):
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return pd.concat(dfs, axis=0, ignore_index=True)
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return dfs
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@retry(tries=3)
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@to_numeric
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def get_realtime_increase_rate(fund_codes: Union[List[str], str]) -> pd.DataFrame:
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"""
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获取基金实时估算涨跌幅度
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Parameters
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----------
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fund_codes : Union[List[str], str]
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6 位基金代码或者 6 位基金代码构成的字符串列表
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Returns
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-------
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DataFrame
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单只或者多只基金实时估算涨跌情况
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Examples
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--------
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>>> import efinance as ef
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>>> # 单只基金
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>>> ef.fund.get_realtime_increase_rate('161725')
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基金代码 基金名称 最新净值 最新净值公开日期 估算时间 估算涨跌幅
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0 161725 招商中证白酒指数(LOF)A 2.8856 2021-09-07 2021-09-07 15:00 0.64
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>>> # 多只基金
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>>> ef.fund.get_realtime_increase_rate(['161725','005827'])
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基金代码 基金名称 最新净值 最新净值公开日期 估算时间 估算涨跌幅
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0 161725 招商中证白酒指数(LOF)A 2.8856 2021-09-07 2021-09-07 15:00 0.64
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1 005827 易方达蓝筹精选混合 2.5704 2021-09-07 2021-09-07 15:00 0.67
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"""
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if not isinstance(fund_codes, list):
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fund_codes = [fund_codes]
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data = {
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"pageIndex": "1",
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"pageSize": "300000",
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"Sort": "",
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"Fcodes": ",".join(fund_codes),
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"SortColumn": "",
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"IsShowSE": "false",
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"P": "F",
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"deviceid": "3EA024C2-7F22-408B-95E4-383D38160FB3",
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"plat": "Iphone",
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"product": "EFund",
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"version": "6.2.8",
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}
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columns = {
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"FCODE": "基金代码",
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"SHORTNAME": "基金名称",
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"ACCNAV": "最新净值",
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"PDATE": "最新净值公开日期",
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"GZTIME": "估算时间",
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"GSZZL": "估算涨跌幅",
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}
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url = "https://fundmobapi.eastmoney.com/FundMNewApi/FundMNFInfo"
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json_response = fund_session.get(
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url, headers=EastmoneyFundHeaders, data=data
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).json()
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rows = jsonpath(json_response, "$..Datas[:]")
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if not rows:
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df = pd.DataFrame(columns=columns.values())
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return df
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df = pd.DataFrame(rows).rename(columns=columns)[columns.values()]
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return df
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@retry(tries=3)
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def get_fund_codes(ft: str = None) -> pd.DataFrame:
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"""
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获取天天基金网公开的全部公墓基金名单
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Parameters
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----------
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ft : str, optional
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基金类型可选示例如下
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- ``'zq'`` : 债券类型基金
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- ``'gp'`` : 股票类型基金
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- ``'etf'`` : ETF 基金
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- ``'hh'`` : 混合型基金
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- ``'zs'`` : 指数型基金
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- ``'fof'`` : FOF 基金
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- ``'qdii'``: QDII 型基金
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- ``None`` : 全部
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Returns
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-------
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DataFrame
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天天基金网基金名单数据
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Examples
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--------
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>>> import efinance as ef
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>>> # 全部类型的基金
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>>> ef.fund.get_fund_codes()
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>>> # 股票型基金
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>>> ef.fund.get_fund_codes(ft = 'gp')
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基金代码 基金简称
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0 003834 华夏能源革新股票
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1 005669 前海开源公用事业股票
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2 004040 金鹰医疗健康产业A
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3 517793 1.20%
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4 004041 金鹰医疗健康产业C
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... ... ...
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1981 012503 国泰中证环保产业50ETF联接A
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1982 012517 国泰中证细分机械设备产业主题ETF联接C
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1983 012600 中银内核驱动股票C
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1984 011043 国泰价值先锋股票C
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1985 012516 国泰中证细分机械设备产业主题ETF联接A
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"""
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params = [
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("op", "dy"),
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("dt", "kf"),
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("rs", ""),
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("gs", "0"),
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("sc", "qjzf"),
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("st", "desc"),
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("es", "0"),
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("qdii", ""),
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("pi", "1"),
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("pn", "50000"),
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("dx", "0"),
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]
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headers = {
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"Connection": "keep-alive",
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"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/87.0.4280.141 Safari/537.36 Edg/87.0.664.75",
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"Accept": "*/*",
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"Referer": "http://fund.eastmoney.com/data/fundranking.html",
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"Accept-Language": "zh-CN,zh;q=0.9,en;q=0.8,en-GB;q=0.7,en-US;q=0.6",
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}
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if ft is not None:
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params.append(("ft", ft))
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url = "http://fund.eastmoney.com/data/rankhandler.aspx"
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response = fund_session.get(url, headers=headers, params=params)
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columns = ["基金代码", "基金简称"]
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results = re.findall(r'"(\d{6}),(.*?),', response.text)
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df = pd.DataFrame(results, columns=columns)
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return df
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@retry(tries=3)
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def get_fund_manager(ft: str) -> pd.DataFrame:
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url = f"http://fundf10.eastmoney.com/jjjl_{ft}.html"
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response = fund_session.get(url)
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if not response:
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return pd.DataFrame()
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html = response.text
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soup = BeautifulSoup(html, "html.parser")
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contents = soup.find("div", class_="bs_gl").find_all("label")
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start_date = contents[0].span.text
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managers = ";".join([a.text for a in contents[1].find_all("a")])
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type_str = contents[2].span.text
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company = contents[3].find("a").text
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share = contents[4].span.text.replace("\r", "").replace("\n", "").replace(" ", "")
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return pd.DataFrame(
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data=[
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[
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ft,
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start_date,
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company,
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managers,
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type_str,
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share,
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str(pd.to_datetime("today").date()),
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]
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],
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columns=[
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"基金代码",
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"基金经理任职日期",
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"基金公司",
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"基金经理",
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"基金种类",
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"基金规模",
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"当前日期",
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],
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)
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@retry(tries=3)
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@to_numeric
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def get_invest_position(
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fund_code: str, dates: Union[str, List[str]] = None
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) -> pd.DataFrame:
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"""
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获取基金持仓占比数据
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Parameters
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----------
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fund_code : str
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基金代码
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dates : Union[str, List[str]], optional
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日期或者日期构成的列表
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可选示例如下
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- ``None`` : 最新公开日期
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- ``'2020-01-01'`` : 一个公开持仓日期
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- ``['2020-12-31' ,'2019-12-31']`` : 多个公开持仓日期
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Returns
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-------
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DataFrame
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基金持仓占比数据
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Examples
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--------
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>>> import efinance as ef
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>>> # 获取最新公开的持仓数据
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>>> ef.fund.get_invest_position('161725')
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基金代码 股票代码 股票简称 持仓占比 较上期变化 公开日期
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0 161725 600519 贵州茅台 16.78 1.36 2022-03-31
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1 161725 600809 山西汾酒 15.20 0.52 2022-03-31
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2 161725 000568 泸州老窖 14.57 -0.89 2022-03-31
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3 161725 000858 五粮液 12.83 -1.26 2022-03-31
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4 161725 002304 洋河股份 11.58 0.91 2022-03-31
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5 161725 603369 今世缘 3.75 -0.04 2022-03-31
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6 161725 000799 酒鬼酒 3.40 -0.91 2022-03-31
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7 161725 000596 古井贡酒 3.27 -0.24 2022-03-31
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8 161725 600779 水井坊 2.59 -0.26 2022-03-31
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9 161725 603589 口子窖 2.30 -0.38 2022-03-31
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>>> # 获取近 2 个公开持仓日数据
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>>> public_dates = ef.fund.get_public_dates('161725')
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>>> ef.fund.get_invest_position('161725',public_dates[:2])
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基金代码 股票代码 股票简称 持仓占比 较上期变化 公开日期
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0 161725 600519 贵州茅台 16.78 1.36 2022-03-31
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1 161725 600809 山西汾酒 15.20 0.52 2022-03-31
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2 161725 000568 泸州老窖 14.57 -0.89 2022-03-31
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3 161725 000858 五粮液 12.83 -1.26 2022-03-31
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4 161725 002304 洋河股份 11.58 0.91 2022-03-31
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5 161725 603369 今世缘 3.75 -0.04 2022-03-31
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6 161725 000799 酒鬼酒 3.40 -0.91 2022-03-31
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7 161725 000596 古井贡酒 3.27 -0.24 2022-03-31
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8 161725 600779 水井坊 2.59 -0.26 2022-03-31
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9 161725 603589 口子窖 2.30 -0.38 2022-03-31
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10 161725 000568 泸州老窖 15.46 0.57 2021-12-31
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11 161725 600519 贵州茅台 15.42 0.63 2021-12-31
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12 161725 600809 山西汾酒 14.68 -1.72 2021-12-31
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13 161725 000858 五粮液 14.09 0.87 2021-12-31
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14 161725 002304 洋河股份 10.67 -1.34 2021-12-31
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15 161725 000799 酒鬼酒 4.31 0.09 2021-12-31
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16 161725 603369 今世缘 3.79 0.81 2021-12-31
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17 161725 000596 古井贡酒 3.51 -0.69 2021-12-31
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18 161725 600779 水井坊 2.85 -0.41 2021-12-31
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19 161725 603589 口子窖 2.68 2.68 2021-12-31
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"""
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columns = {
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"GPDM": "股票代码",
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"GPJC": "股票简称",
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"JZBL": "持仓占比",
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"PCTNVCHG": "较上期变化",
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}
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df = pd.DataFrame(columns=columns.values())
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if not isinstance(dates, List):
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dates = [dates]
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if dates is None:
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dates = [None]
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dfs: List[pd.DataFrame] = []
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for date in dates:
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params = [
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("FCODE", fund_code),
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("appType", "ttjj"),
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("deviceid", "3EA024C2-7F22-408B-95E4-383D38160FB3"),
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("plat", "Iphone"),
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("product", "EFund"),
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("serverVersion", "6.2.8"),
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("version", "6.2.8"),
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]
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if date is not None:
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params.append(("DATE", date))
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url = "https://fundmobapi.eastmoney.com/FundMNewApi/FundMNInverstPosition"
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json_response = fund_session.get(
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url, headers=EastmoneyFundHeaders, params=params
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).json()
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stocks = jsonpath(json_response, "$..fundStocks[:]")
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if not stocks:
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continue
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date = json_response["Expansion"]
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_df = pd.DataFrame(stocks)
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_df["公开日期"] = date
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_df.insert(0, "基金代码", fund_code)
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dfs.append(_df)
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fields = ["基金代码"] + list(columns.values()) + ["公开日期"]
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if not dfs:
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return pd.DataFrame(columns=fields)
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df = pd.concat(dfs, axis=0, ignore_index=True).rename(columns=columns)[fields]
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return df
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@retry(tries=3)
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@to_numeric
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def get_period_change(fund_code: str) -> pd.DataFrame:
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"""
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获取基金阶段涨跌幅度
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Parameters
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----------
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fund_code : str
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6 位基金代码
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Returns
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-------
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DataFrame
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指定基金的阶段涨跌数据
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Examples
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--------
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>>> import efinance as ef
|
|
>>> ef.fund.get_period_change('161725')
|
|
基金代码 收益率 同类平均 同类排行 同类总数 时间段
|
|
0 161725 -6.28 0.07 1408 1409 近一周
|
|
1 161725 10.85 5.82 178 1382 近一月
|
|
2 161725 25.32 7.10 20 1332 近三月
|
|
3 161725 22.93 10.39 79 1223 近六月
|
|
4 161725 103.76 33.58 7 1118 近一年
|
|
5 161725 166.59 55.42 9 796 近两年
|
|
6 161725 187.50 48.17 2 611 近三年
|
|
7 161725 519.44 61.62 1 389 近五年
|
|
8 161725 6.46 5.03 423 1243 今年以来
|
|
9 161725 477.00 成立以来
|
|
"""
|
|
|
|
params = (
|
|
("AppVersion", "6.3.8"),
|
|
("FCODE", fund_code),
|
|
("MobileKey", "3EA024C2-7F22-408B-95E4-383D38160FB3"),
|
|
("OSVersion", "14.3"),
|
|
("deviceid", "3EA024C2-7F22-408B-95E4-383D38160FB3"),
|
|
("passportid", "3061335960830820"),
|
|
("plat", "Iphone"),
|
|
("product", "EFund"),
|
|
("version", "6.3.6"),
|
|
)
|
|
url = "https://fundmobapi.eastmoney.com/FundMNewApi/FundMNPeriodIncrease"
|
|
json_response = fund_session.get(
|
|
url, headers=EastmoneyFundHeaders, params=params
|
|
).json()
|
|
columns = {
|
|
"syl": "收益率",
|
|
"avg": "同类平均",
|
|
"rank": "同类排行",
|
|
"sc": "同类总数",
|
|
"title": "时间段",
|
|
}
|
|
titles = {
|
|
"Z": "近一周",
|
|
"Y": "近一月",
|
|
"3Y": "近三月",
|
|
"6Y": "近六月",
|
|
"1N": "近一年",
|
|
"2Y": "近两年",
|
|
"3N": "近三年",
|
|
"5N": "近五年",
|
|
"JN": "今年以来",
|
|
"LN": "成立以来",
|
|
}
|
|
# 发行时间
|
|
ESTABDATE = json_response["Expansion"]["ESTABDATE"]
|
|
df = pd.DataFrame(json_response["Datas"])
|
|
|
|
df = df[list(columns.keys())].rename(columns=columns)
|
|
df["时间段"] = titles.values()
|
|
df.insert(0, "基金代码", fund_code)
|
|
return df
|
|
|
|
|
|
def get_public_dates(fund_code: str) -> List[str]:
|
|
"""
|
|
获取历史上更新持仓情况的日期列表
|
|
|
|
Parameters
|
|
----------
|
|
fund_code : str
|
|
6 位基金代码
|
|
|
|
Returns
|
|
-------
|
|
List[str]
|
|
指定基金公开持仓的日期列表
|
|
|
|
Examples
|
|
--------
|
|
>>> import efinance as ef
|
|
>>> public_dates = ef.fund.get_public_dates('161725')
|
|
>>> # 展示前 5 个
|
|
>>> public_dates[:5]
|
|
['2021-03-31', '2021-01-08', '2020-12-31', '2020-09-30', '2020-06-30']
|
|
|
|
"""
|
|
|
|
params = (
|
|
("FCODE", fund_code),
|
|
("appVersion", "6.3.8"),
|
|
("deviceid", "3EA024C2-7F22-408B-95E4-383D38160FB3"),
|
|
("plat", "Iphone"),
|
|
("product", "EFund"),
|
|
("serverVersion", "6.3.6"),
|
|
("version", "6.3.8"),
|
|
)
|
|
url = "https://fundmobapi.eastmoney.com/FundMNewApi/FundMNIVInfoMultiple"
|
|
json_response = fund_session.get(
|
|
url, headers=EastmoneyFundHeaders, params=params
|
|
).json()
|
|
if json_response["Datas"] is None:
|
|
return []
|
|
return json_response["Datas"]
|
|
|
|
|
|
@retry(tries=3)
|
|
@to_numeric
|
|
def get_types_percentage(
|
|
fund_code: str, dates: Union[List[str], str, None] = None
|
|
) -> pd.DataFrame:
|
|
"""
|
|
获取指定基金不同类型占比信息
|
|
|
|
Parameters
|
|
----------
|
|
fund_code : str
|
|
6 位基金代码
|
|
dates : Union[List[str], str, None]
|
|
可选值类型示例如下(后面有获取 dates 的例子)
|
|
|
|
- ``None`` : 最新公开日期
|
|
- ``'2020-01-01'`` : 一个公开持仓日期
|
|
- ``['2020-12-31' ,'2019-12-31']`` : 多个公开持仓日期
|
|
|
|
|
|
Returns
|
|
-------
|
|
DataFrame
|
|
指定基金的在不同日期的不同类型持仓占比信息
|
|
|
|
Examples
|
|
--------
|
|
>>> import efinance as ef
|
|
>>> # 获取持仓公开日期
|
|
>>> public_dates = ef.fund.get_public_dates('005827')
|
|
>>> # 取前两个公开持仓日期
|
|
>>> dates = public_dates[:2]
|
|
>>> ef.fund.get_types_percentage('005827',dates)
|
|
基金代码 股票比重 债券比重 现金比重 总规模(亿元) 其他比重
|
|
0 005827 94.4 -- 6.06 880.1570625231 0
|
|
0 005827 94.09 -- 7.63 677.007455712 0
|
|
|
|
"""
|
|
|
|
columns = {
|
|
"GP": "股票比重",
|
|
"ZQ": "债券比重",
|
|
"HB": "现金比重",
|
|
"JZC": "总规模(亿元)",
|
|
"QT": "其他比重",
|
|
}
|
|
df = pd.DataFrame(columns=columns.values())
|
|
if not isinstance(dates, List):
|
|
dates = [dates]
|
|
elif dates is None:
|
|
dates = [None]
|
|
for date in dates:
|
|
params = [
|
|
("FCODE", fund_code),
|
|
("OSVersion", "14.3"),
|
|
("appVersion", "6.3.8"),
|
|
("deviceid", "3EA024C2-7F21-408B-95E4-383D38160FB3"),
|
|
("plat", "Iphone"),
|
|
("product", "EFund"),
|
|
("serverVersion", "6.3.6"),
|
|
("version", "6.3.8"),
|
|
]
|
|
if date is not None:
|
|
params.append(("DATE", date))
|
|
params = tuple(params)
|
|
url = "https://fundmobapi.eastmoney.com/FundMNewApi/FundMNAssetAllocationNew"
|
|
json_response = fund_session.get(
|
|
url, params=params, headers=EastmoneyFundHeaders
|
|
).json()
|
|
|
|
if len(json_response["Datas"]) == 0:
|
|
continue
|
|
_df = pd.DataFrame(json_response["Datas"])[columns.keys()]
|
|
_df = _df.rename(columns=columns)
|
|
df = pd.concat([df, _df], axis=0, ignore_index=True)
|
|
df.insert(0, "基金代码", fund_code)
|
|
return df
|
|
|
|
|
|
@retry(tries=3)
|
|
@to_numeric
|
|
def get_base_info_single(fund_code: str) -> pd.Series:
|
|
"""
|
|
获取基金的一些基本信息
|
|
|
|
Parameters
|
|
----------
|
|
fund_code : str
|
|
6 位基金代码
|
|
|
|
Returns
|
|
-------
|
|
Series
|
|
基金的一些基本信息
|
|
"""
|
|
|
|
params = (
|
|
("FCODE", fund_code),
|
|
("deviceid", "3EA024C2-7F22-408B-95E4-383D38160FB3"),
|
|
("plat", "Iphone"),
|
|
("product", "EFund"),
|
|
("version", "6.3.8"),
|
|
)
|
|
url = "https://fundmobapi.eastmoney.com/FundMNewApi/FundMNNBasicInformation"
|
|
json_response = fund_session.get(
|
|
url, headers=EastmoneyFundHeaders, params=params
|
|
).json()
|
|
columns = {
|
|
"FCODE": "基金代码",
|
|
"SHORTNAME": "基金简称",
|
|
"ESTABDATE": "成立日期",
|
|
"RZDF": "涨跌幅",
|
|
"DWJZ": "最新净值",
|
|
"JJGS": "基金公司",
|
|
"FSRQ": "净值更新日期",
|
|
"COMMENTS": "简介",
|
|
}
|
|
items = json_response["Datas"]
|
|
if not items:
|
|
rich.print("基金代码", fund_code, "可能有误")
|
|
return pd.Series(index=columns.values())
|
|
|
|
s = pd.Series(json_response["Datas"]).rename(index=columns)[columns.values()]
|
|
|
|
s = s.apply(lambda x: x.replace("\n", " ").strip() if isinstance(x, str) else x)
|
|
return s
|
|
|
|
|
|
def get_base_info_muliti(fund_codes: List[str]) -> pd.Series:
|
|
"""
|
|
获取多只基金基本信息
|
|
|
|
Parameters
|
|
----------
|
|
fund_codes : List[str]
|
|
6 位基金代码列表
|
|
|
|
Returns
|
|
-------
|
|
Series
|
|
多只基金基本信息
|
|
"""
|
|
|
|
ss = []
|
|
|
|
@multitasking.task
|
|
@retry(tries=3, delay=1)
|
|
def start(fund_code: str) -> None:
|
|
s = get_base_info_single(fund_code)
|
|
ss.append(s)
|
|
pbar.update()
|
|
pbar.set_description(f"Processing => {fund_code}")
|
|
|
|
pbar = tqdm(total=len(fund_codes))
|
|
for fund_code in fund_codes:
|
|
start(fund_code)
|
|
multitasking.wait_for_tasks()
|
|
df = pd.DataFrame(ss)
|
|
return df
|
|
|
|
|
|
def get_base_info(fund_codes: Union[str, List[str]]) -> Union[pd.Series, pd.DataFrame]:
|
|
"""
|
|
获取基金的一些基本信息
|
|
|
|
Parameters
|
|
----------
|
|
fund_codes : Union[str, List[str]]
|
|
6 位基金代码 或多个 6 位 基金代码构成的列表
|
|
|
|
Returns
|
|
-------
|
|
Union[Series, DataFrame]
|
|
基金的一些基本信息
|
|
|
|
- ``Series`` : 包含单只基金基本信息(当 ``fund_codes`` 是字符串时)
|
|
- ``DataFrane`` : 包含多只股票基本信息(当 ``fund_codes`` 是字符串列表时)
|
|
|
|
Raises
|
|
------
|
|
TypeError
|
|
当 fund_codes 类型不符合要求时
|
|
|
|
Examples
|
|
--------
|
|
>>> import efinance as ef
|
|
>>> ef.fund.get_base_info('161725')
|
|
基金代码 161725
|
|
基金简称 招商中证白酒指数(LOF)A
|
|
成立日期 2015-05-27
|
|
涨跌幅 -6.03
|
|
最新净值 1.1959
|
|
基金公司 招商基金
|
|
净值更新日期 2021-07-30
|
|
简介 产品特色：布局白酒领域的指数基金，历史业绩优秀，外资偏爱白酒板块。
|
|
dtype: object
|
|
|
|
>>> # 获取多只基金基本信息
|
|
>>> ef.fund.get_base_info(['161725','005827'])
|
|
基金代码 基金简称 成立日期 涨跌幅 最新净值 基金公司 净值更新日期 简介00:00, 6.38it/s]
|
|
0 005827 易方达蓝筹精选混合 2018-09-05 -2.98 2.4967 易方达基金 2021-07-30 明星消费基金经理另一力作，A+H股同步布局，价值投资典范，适合长期持有。
|
|
1 161725 招商中证白酒指数(LOF)A 2015-05-27 -6.03 1.1959 招商基金 2021-07-30 产品特色：布局白酒领域的指数基金，历史业绩优秀，外资偏爱白酒板块。
|
|
|
|
"""
|
|
|
|
if isinstance(fund_codes, str):
|
|
return get_base_info_single(fund_codes)
|
|
elif hasattr(fund_codes, "__iter__"):
|
|
return get_base_info_muliti(fund_codes)
|
|
raise TypeError(f"所给的 {fund_codes} 不符合参数要求")
|
|
|
|
|
|
@to_numeric
|
|
def get_industry_distribution(
|
|
fund_code: str, dates: Union[str, List[str]] = None
|
|
) -> pd.DataFrame:
|
|
"""
|
|
获取指定基金行业分布信息
|
|
|
|
Parameters
|
|
----------
|
|
fund_code : str
|
|
6 位基金代码
|
|
dates : Union[str, List[str]], optional
|
|
日期
|
|
可选示例如下
|
|
|
|
- ``None`` : 最新公开日期
|
|
- ``'2020-01-01'`` : 一个公开持仓日期
|
|
- ``['2020-12-31' ,'2019-12-31']`` : 多个公开持仓日期
|
|
|
|
Returns
|
|
-------
|
|
DataFrame
|
|
指定基金行业持仓信息
|
|
|
|
Examples
|
|
--------
|
|
>>> import efinance as ef
|
|
>>> # 获取持仓公开日期
|
|
>>> public_dates = ef.fund.get_public_dates('161725')
|
|
>>> # 取前一个公开持仓日期
|
|
>>> dates = public_dates[:1]
|
|
>>> ef.fund.get_industry_distribution('161725',dates)
|
|
0 161725 制造业 93.07 2021-06-30 6492580.019556
|
|
1 161725 金融业 0.01 2021-06-30 485.060688
|
|
2 161725 农、林、牧、渔业 0 2021-06-30 0.585078
|
|
3 161725 电力、热力、燃气及水生产和供应业 0 2021-06-30 1.302039
|
|
4 161725 建筑业 0 2021-06-30 2.537137
|
|
5 161725 批发和零售业 0 2021-06-30 5.888394
|
|
6 161725 信息传输、软件和信息技术服务业 0 2021-06-30 157.037536
|
|
7 161725 水利、环境和公共设施管理业 0 2021-06-30 4.443833
|
|
8 161725 教育 0 2021-06-30 1.626203
|
|
9 161725 科学研究和技术服务业 0 2021-06-30 48.30805
|
|
10 161725 采矿业 -- 2021-06-30 --
|
|
11 161725 交通运输、仓储和邮政业 -- 2021-06-30 --
|
|
12 161725 租赁和商务服务业 -- 2021-06-30 --
|
|
13 161725 住宿和餐饮业 -- 2021-06-30 --
|
|
14 161725 房地产业 -- 2021-06-30 --
|
|
15 161725 居民服务、修理和其他服务业 -- 2021-06-30 --
|
|
16 161725 卫生和社会工作 -- 2021-06-30 --
|
|
17 161725 文化、体育和娱乐业 -- 2021-06-30 --
|
|
18 161725 综合 -- 2021-06-30 --
|
|
19 161725 合计 93.08 2021-06-30 6493286.808514
|
|
|
|
"""
|
|
|
|
columns = {
|
|
"HYMC": "行业名称",
|
|
"ZJZBL": "持仓比例",
|
|
"FSRQ": "公布日期",
|
|
"SZ": "市值",
|
|
}
|
|
df = pd.DataFrame(columns=columns.values())
|
|
if isinstance(dates, str):
|
|
dates = [dates]
|
|
elif dates is None:
|
|
dates = [None]
|
|
for date in dates:
|
|
|
|
params = [
|
|
("FCODE", fund_code),
|
|
("OSVersion", "14.4"),
|
|
("appVersion", "6.3.8"),
|
|
("deviceid", "3EA024C2-7F22-408B-95E4-383D38160FB3"),
|
|
("plat", "Iphone"),
|
|
("product", "EFund"),
|
|
("serverVersion", "6.3.6"),
|
|
("version", "6.3.8"),
|
|
]
|
|
if date is not None:
|
|
params.append(("DATE", date))
|
|
url = "https://fundmobapi.eastmoney.com/FundMNewApi/FundMNSectorAllocation"
|
|
response = fund_session.get(url, headers=EastmoneyFundHeaders, params=params)
|
|
datas = response.json()["Datas"]
|
|
|
|
_df = pd.DataFrame(datas)
|
|
_df = _df.rename(columns=columns)
|
|
df = pd.concat([df, _df], axis=0, ignore_index=True)
|
|
df.insert(0, "基金代码", fund_code)
|
|
df = df.drop_duplicates()
|
|
return df
|
|
|
|
|
|
def get_pdf_reports(fund_code: str, max_count: int = 12, save_dir: str = "pdf") -> None:
|
|
"""
|
|
根据基金代码获取其全部 pdf 报告
|
|
|
|
Parameters
|
|
----------
|
|
fund_code : str
|
|
6 位基金代码
|
|
max_count : int, optional
|
|
要获取的最大个数个 pdf (从最新的的开始数), 默认为 ``12``
|
|
save_dir : str, optional
|
|
pdf 保存的文件夹路径, 默认为 ``'pdf'``
|
|
|
|
Examples
|
|
--------
|
|
>>> import efinance as ef
|
|
>>> # 获取基金代码为 161725 的基金最新的两个 pdf 报道文件
|
|
>>> ef.fund.get_pdf_reports('161725',max_count = 2)
|
|
161725 的 pdf 文件已存储到文件夹 pdf/161725 中
|
|
"""
|
|
|
|
headers = {
|
|
"Connection": "keep-alive",
|
|
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/89.0.4389.128 Safari/537.36 Edg/89.0.774.77",
|
|
"Accept": "*/*",
|
|
"Referer": "http://fundf10.eastmoney.com/",
|
|
"Accept-Language": "zh-CN,zh;q=0.9,en;q=0.8,en-GB;q=0.7,en-US;q=0.6",
|
|
}
|
|
|
|
@multitasking.task
|
|
@retry(tries=3, delay=1)
|
|
def download_file(
|
|
fund_code: str, url: str, filename: str, file_type=".pdf"
|
|
) -> None:
|
|
"""
|
|
根据文件名、文件直链等参数下载文件
|
|
|
|
Parameters
|
|
----------
|
|
fund_code : str
|
|
6 位基金代码
|
|
url : str
|
|
下载连接
|
|
filename : str
|
|
文件后缀名
|
|
file_type : str, optional
|
|
文件类型, 默认为 '.pdf'
|
|
"""
|
|
|
|
pbar.set_description(f"Processing => {fund_code}")
|
|
fund_code = str(fund_code)
|
|
if not os.path.exists(save_dir + "/" + fund_code):
|
|
os.mkdir(save_dir + "/" + fund_code)
|
|
response = fund_session.get(url, headers=headers)
|
|
path = f"{save_dir}/{fund_code}/{filename}{file_type}"
|
|
with open(path, "wb") as f:
|
|
f.write(response.content)
|
|
if os.path.getsize(path) == 0:
|
|
os.remove(path)
|
|
return
|
|
pbar.update(1)
|
|
|
|
params = (
|
|
("fundcode", fund_code),
|
|
("pageIndex", "1"),
|
|
("pageSize", "200000"),
|
|
("type", "3"),
|
|
)
|
|
|
|
json_response = fund_session.get(
|
|
"http://api.fund.eastmoney.com/f10/JJGG", headers=headers, params=params
|
|
).json()
|
|
|
|
base_link = "http://pdf.dfcfw.com/pdf/H2_{}_1.pdf"
|
|
|
|
pbar = tqdm(total=min(max_count, len(json_response["Data"])))
|
|
if not os.path.exists(save_dir):
|
|
os.mkdir(save_dir)
|
|
for item in json_response["Data"][-max_count:]:
|
|
|
|
title = item["TITLE"]
|
|
download_url = base_link.format(item["ID"])
|
|
download_file(fund_code, download_url, title)
|
|
multitasking.wait_for_tasks()
|
|
pbar.close()
|
|
print(f"{fund_code} 的 pdf 文件已存储到文件夹 {save_dir}/{fund_code} 中")
|