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
136 lines
3.8 KiB
Python
136 lines
3.8 KiB
Python
#!/usr/bin/env python
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# -*- coding:utf-8 -*-
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"""
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Date: 2023/4/5 22:05
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Desc: 乐咕乐股-基金仓位
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https://legulegu.com/stockdata/fund-position/pos-stock
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"""
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import pandas as pd
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import requests
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from akshare.stock_feature.stock_a_indicator import get_token_lg, get_cookie_csrf
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def fund_stock_position_lg() -> pd.DataFrame:
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"""
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乐咕乐股-基金仓位-股票型基金仓位
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https://legulegu.com/stockdata/fund-position/pos-stock
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:return: 股票型基金仓位
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:rtype: pandas.DataFrame
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"""
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url = "https://legulegu.com/api/stockdata/fund-position"
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token = get_token_lg()
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params = {
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"token": token,
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"type": "pos_stock",
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"category": "总仓位",
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"marketId": "5",
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}
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r = requests.get(
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url,
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params=params,
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**get_cookie_csrf(url="https://legulegu.com/stockdata/fund-position/pos-stock"),
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)
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data_json = r.json()
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temp_df = pd.DataFrame(data_json)
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temp_df["date"] = pd.to_datetime(temp_df["date"]).dt.date
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temp_df = temp_df[
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[
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"date",
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"close",
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"position",
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]
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]
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temp_df["date"] = pd.to_datetime(temp_df["date"]).dt.date
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temp_df["close"] = pd.to_numeric(temp_df["close"], errors="coerce")
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temp_df["position"] = pd.to_numeric(temp_df["position"], errors="coerce")
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return temp_df
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def fund_balance_position_lg() -> pd.DataFrame:
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"""
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乐咕乐股-基金仓位-平衡混合型基金仓位
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https://legulegu.com/stockdata/fund-position/pos-pingheng
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:return: 平衡混合型基金仓位
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:rtype: pandas.DataFrame
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"""
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url = "https://legulegu.com/api/stockdata/fund-position"
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token = get_token_lg()
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params = {
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"token": token,
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"type": "pos_pingheng",
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"category": "总仓位",
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"marketId": "5",
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}
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r = requests.get(
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url,
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params=params,
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**get_cookie_csrf(
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url="https://legulegu.com/stockdata/fund-position/pos-pingheng"
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),
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)
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data_json = r.json()
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temp_df = pd.DataFrame(data_json)
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temp_df["date"] = pd.to_datetime(temp_df["date"]).dt.date
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temp_df = temp_df[
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[
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"date",
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"close",
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"position",
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]
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]
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temp_df["date"] = pd.to_datetime(temp_df["date"]).dt.date
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temp_df["close"] = pd.to_numeric(temp_df["close"], errors="coerce")
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temp_df["position"] = pd.to_numeric(temp_df["position"], errors="coerce")
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return temp_df
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def fund_linghuo_position_lg() -> pd.DataFrame:
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"""
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乐咕乐股-基金仓位-灵活配置型基金仓位
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https://legulegu.com/stockdata/fund-position/pos-linghuo
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:return: 灵活配置型基金仓位
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:rtype: pandas.DataFrame
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"""
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url = "https://legulegu.com/api/stockdata/fund-position"
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token = get_token_lg()
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params = {
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"token": token,
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"type": "pos_linghuo",
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"category": "总仓位",
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"marketId": "5",
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}
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r = requests.get(
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url,
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params=params,
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**get_cookie_csrf(
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url="https://legulegu.com/stockdata/fund-position/pos-linghuo"
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),
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)
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data_json = r.json()
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temp_df = pd.DataFrame(data_json)
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temp_df["date"] = pd.to_datetime(temp_df["date"]).dt.date
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temp_df = temp_df[
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[
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"date",
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"close",
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"position",
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]
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]
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temp_df["date"] = pd.to_datetime(temp_df["date"]).dt.date
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temp_df["close"] = pd.to_numeric(temp_df["close"], errors="coerce")
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temp_df["position"] = pd.to_numeric(temp_df["position"], errors="coerce")
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return temp_df
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if __name__ == "__main__":
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fund_stock_position_lg_df = fund_stock_position_lg()
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print(fund_stock_position_lg_df)
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fund_balance_position_lg_df = fund_balance_position_lg()
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print(fund_balance_position_lg_df)
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fund_linghuo_position_lg_df = fund_linghuo_position_lg()
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print(fund_linghuo_position_lg_df)
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