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
248 lines
9.0 KiB
Python
248 lines
9.0 KiB
Python
#!/usr/bin/env python
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# -*- coding:utf-8 -*-
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"""
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Date: 2025/7/1 16:30
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Desc: 期货-仓单日报
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上海期货交易所-仓单日报
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https://tsite.shfe.com.cn/statements/dataview.html?paramid=dailystock
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郑州商品交易所-交易数据-仓单日报
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http://www.czce.com.cn/cn/jysj/cdrb/H770310index_1.htm
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大连商品交易所-行情数据-统计数据-日统计-仓单日报
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http://www.dce.com.cn/dalianshangpin/xqsj/tjsj26/rtj/cdrb/index.html
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广州期货交易所-行情数据-仓单日报
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http://www.gfex.com.cn/gfex/cdrb/hqsj_tjsj.shtml
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"""
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import re
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from io import BytesIO, StringIO
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import pandas as pd
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import requests
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def futures_warehouse_receipt_czce(date: str = "20251103") -> dict:
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"""
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郑州商品交易所-交易数据-仓单日报
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http://www.czce.com.cn/cn/jysj/cdrb/H770310index_1.htm
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:param date: 交易日, e.g., "20200702"
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:type date: str
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:return: 指定日期的仓单日报数据
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:rtype: dict
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"""
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import urllib3
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urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)
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if int(date) > 20251101:
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url = f"http://www.czce.com.cn/cn/DFSStaticFiles/Future/{date[:4]}/{date}/FutureDataWhsheet.xlsx"
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else:
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url = f"http://www.czce.com.cn/cn/DFSStaticFiles/Future/{date[:4]}/{date}/FutureDataWhsheet.xls"
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headers = {
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"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) "
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"Chrome/83.0.4103.116 Safari/537.36"
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}
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r = requests.get(url, verify=False, headers=headers)
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temp_df = pd.read_excel(BytesIO(r.content))
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index_list = temp_df[temp_df.iloc[:, 0].str.find("品种") == 0.0].index.to_list()
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index_list.append(len(temp_df))
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big_dict = {}
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for inner_index in range(len(index_list) - 1):
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inner_df = temp_df[index_list[inner_index] : index_list[inner_index + 1]]
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inner_key = re.findall(pattern=r"[a-zA-Z]+", string=inner_df.iloc[0, 0])[0]
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inner_df = inner_df.iloc[1:, :]
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inner_df.dropna(axis=0, how="all", inplace=True)
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inner_df.dropna(axis=1, how="all", inplace=True)
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inner_df.columns = inner_df.iloc[0, :].to_list()
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inner_df = inner_df.iloc[1:, :]
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inner_df.reset_index(inplace=True, drop=True)
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big_dict[inner_key] = inner_df
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return big_dict
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def futures_warehouse_receipt_dce(date: str = "20251027") -> pd.DataFrame:
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"""
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大连商品交易所-行情数据-统计数据-日统计-仓单日报
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http://www.dce.com.cn/dce/channel/list/187.html
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:param date: 交易日, e.g., "20200702"
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:type date: str
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:return: 指定日期的仓单日报数据
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:rtype: dict
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"""
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url = "http://www.dce.com.cn/dcereport/publicweb/dailystat/wbillWeeklyQuotes"
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payload = {
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"tradeDate": date,
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"varietyId": "all",
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}
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r = requests.post(url, json=payload)
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data_json = r.json()
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temp_df = pd.DataFrame(data_json["data"]["entityList"])
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temp_df.rename(
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columns={
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"variety": "品种名称",
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"whAbbr": "仓库/分库",
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"deliveryAbbr": "可选提货地点/分库-数量",
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"lastWbillQty": "昨日仓单量（手）",
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"wbillQty": "今日仓单量（手）",
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"diff": "增减（手）",
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"varietyOrder": "品种代码",
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},
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inplace=True,
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)
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temp_df = temp_df[
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[
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"品种代码",
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"品种名称",
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"仓库/分库",
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"可选提货地点/分库-数量",
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"昨日仓单量（手）",
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"今日仓单量（手）",
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"增减（手）",
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]
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]
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return temp_df
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def futures_shfe_warehouse_receipt(date: str = "20200702") -> dict:
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"""
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上海期货交易所指定交割仓库期货仓单日报
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https://tsite.shfe.com.cn/statements/dataview.html?paramid=dailystock¶mdate=20200703
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:param date: 交易日, e.g., "20200702"
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:type date: str
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:return: 指定日期的仓单日报数据
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:rtype: dict
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"""
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headers = {
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"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) "
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"Chrome/83.0.4103.116 Safari/537.36"
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}
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url = (
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f"https://www.shfe.com.cn/data/tradedata/future/dailydata/{date}dailystock.dat"
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)
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if date >= "20140519":
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r = requests.get(url, headers=headers)
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data_json = r.json()
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temp_df = pd.DataFrame(data_json["o_cursor"])
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temp_df["VARNAME"] = temp_df["VARNAME"].str.split(r"$", expand=True).iloc[:, 0]
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temp_df["REGNAME"] = temp_df["REGNAME"].str.split(r"$", expand=True).iloc[:, 0]
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temp_df["WHABBRNAME"] = (
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temp_df["WHABBRNAME"].str.split(r"$", expand=True).iloc[:, 0]
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)
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big_dict = {}
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for item in set(temp_df["VARNAME"]):
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big_dict[item] = temp_df[temp_df["VARNAME"] == item]
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else:
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url = f"https://www.shfe.com.cn/data/tradedata/future/dailydata/{date}dailystock.html"
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r = requests.get(url, headers=headers)
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temp_df = pd.read_html(StringIO(r.text))[0]
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index_list = temp_df[
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temp_df.iloc[:, 3].str.contains("单位：") == 1
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].index.to_list()
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big_dict = {}
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for inner_index in range(len(index_list)):
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temp_index_start = index_list[inner_index]
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if (inner_index + 1) >= len(index_list):
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if temp_df.iloc[-1, 0].startswith("注："):
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temp_index_end = len(temp_df) - 1
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else:
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temp_index_end = len(temp_df)
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else:
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temp_index_end = index_list[inner_index + 1]
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inner_df = temp_df[temp_index_start:temp_index_end]
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inner_df.reset_index(inplace=True, drop=True)
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inner_key = inner_df.iloc[0, 0]
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inner_df.columns = inner_df.iloc[1].to_list()
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inner_df = inner_df[2:]
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inner_df.reset_index(inplace=True, drop=True)
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big_dict[inner_key] = inner_df
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return big_dict
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def futures_gfex_warehouse_receipt(date: str = "20240122") -> dict:
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"""
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广州期货交易所-行情数据-仓单日报
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http://www.gfex.com.cn/gfex/cdrb/hqsj_tjsj.shtml
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:param date: 交易日, e.g., "20240122"
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:type date: str
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:return: 指定日期的仓单日报数据
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:rtype: dict
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"""
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url = "http://www.gfex.com.cn/u/interfacesWebTdWbillWeeklyQuotes/loadList"
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headers = {
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"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) "
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"Chrome/83.0.4103.116 Safari/537.36"
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}
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payload = {"gen_date": date}
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r = requests.post(url=url, data=payload, headers=headers)
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data_json = r.json()
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temp_df = pd.DataFrame(data_json["data"])
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symbol_list = list(
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set([item.upper() for item in temp_df["varietyOrder"].tolist() if item != ""])
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)
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temp_df.rename(
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columns={
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"varietyOrder": "symbol",
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"variety": "品种",
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"whAbbr": "仓库/分库",
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"lastWbillQty": "昨日仓单量",
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"wbillQty": "今日仓单量",
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"regWbillQty": "增减",
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},
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inplace=True,
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)
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temp_df = temp_df[
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[
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"symbol",
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"whType",
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"品种",
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"仓库/分库",
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"昨日仓单量",
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"今日仓单量",
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"增减",
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]
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]
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temp_df["whType"] = pd.to_numeric(temp_df["whType"], errors="coerce")
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temp_df.dropna(
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subset=["whType"], how="any", axis=0, ignore_index=True, inplace=True
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)
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big_dict = dict()
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for symbol in symbol_list:
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inner_temp_df = temp_df[temp_df["symbol"] == symbol.lower()].copy()
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inner_temp_df = inner_temp_df[
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[
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"品种",
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"仓库/分库",
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"昨日仓单量",
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"今日仓单量",
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"增减",
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]
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]
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inner_temp_df["昨日仓单量"] = pd.to_numeric(
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inner_temp_df["昨日仓单量"], errors="coerce"
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)
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inner_temp_df["今日仓单量"] = pd.to_numeric(
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inner_temp_df["今日仓单量"], errors="coerce"
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)
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inner_temp_df["增减"] = pd.to_numeric(inner_temp_df["增减"], errors="coerce")
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inner_temp_df.reset_index(inplace=True, drop=True)
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big_dict[symbol] = inner_temp_df
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return big_dict
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if __name__ == "__main__":
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futures_warehouse_receipt_czce_df = futures_warehouse_receipt_czce(date="20251014")
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print(futures_warehouse_receipt_czce_df)
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futures_warehouse_receipt_dce_df = futures_warehouse_receipt_dce(date="20251014")
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print(futures_warehouse_receipt_dce_df)
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futures_shfe_warehouse_receipt_df = futures_shfe_warehouse_receipt(date="20200702")
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print(futures_shfe_warehouse_receipt_df)
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futures_shfe_warehouse_receipt_df = futures_shfe_warehouse_receipt(date="20140516")
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print(futures_shfe_warehouse_receipt_df)
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futures_gfex_warehouse_receipt_df = futures_gfex_warehouse_receipt(date="20240122")
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print(futures_gfex_warehouse_receipt_df)
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futures_gfex_warehouse_receipt_df = futures_gfex_warehouse_receipt(date="20260226")
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print(futures_gfex_warehouse_receipt_df)
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