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
130 lines
5.0 KiB
Python
130 lines
5.0 KiB
Python
# -*- coding:utf-8 -*-
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# !/usr/bin/env python
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"""
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Date: 2023/6/19 17:00
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Desc: 沐甜科技数据中心-中国食糖指数
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https://www.msweet.com.cn/mtkj/sjzx13/index.html
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"""
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import requests
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import pandas as pd
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def index_sugar_msweet() -> pd.DataFrame:
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"""
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沐甜科技数据中心-中国食糖指数
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https://www.msweet.com.cn/mtkj/sjzx13/index.html
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:return: 中国食糖指数
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:rtype: pandas.DataFrame
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"""
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url = "https://www.msweet.com.cn/eportal/ui"
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params = {
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"struts.portlet.action": "/portlet/price!getSTZSJson.action",
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"moduleId": "cb752447cfe24b44b18c7a7e9abab048",
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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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temp_df = pd.concat(
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[pd.DataFrame(data_json["category"]), pd.DataFrame(data_json["data"])], axis=1
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)
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temp_df.columns = ["日期", "综合价格", "原糖价格", "现货价格"]
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temp_df.loc[3226, ["原糖价格"]] = 12.88 # 数据源错误
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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["综合价格"] = pd.to_numeric(temp_df["综合价格"], errors="coerce")
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temp_df["原糖价格"] = pd.to_numeric(temp_df["原糖价格"], errors="coerce")
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temp_df["现货价格"] = pd.to_numeric(temp_df["现货价格"], errors="coerce")
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return temp_df
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def index_inner_quote_sugar_msweet() -> pd.DataFrame:
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"""
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沐甜科技数据中心-配额内进口糖估算指数
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https://www.msweet.com.cn/mtkj/sjzx13/index.html
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:return: 配额内进口糖估算指数
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:rtype: pandas.DataFrame
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"""
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url = "https://www.msweet.com.cn/datacenterapply/datacenter/json/JinKongTang.json"
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r = requests.get(url)
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data_json = r.json()
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temp_df = pd.concat(
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[pd.DataFrame(data_json["category"]), pd.DataFrame(data_json["data"])], axis=1
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)
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temp_df.columns = [
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"日期",
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"利润空间",
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"泰国糖",
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"泰国MA5",
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"巴西MA5",
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"利润MA5",
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"巴西MA10",
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"巴西糖",
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"柳州现货价",
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"广州现货价",
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"泰国MA10",
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"利润MA30",
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"利润MA10",
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]
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temp_df.loc[988, ["泰国糖"]] = 4045.2 # 数据源错误
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temp_df["日期"] = temp_df["日期"].str.replace("/", "-")
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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["利润空间"] = pd.to_numeric(temp_df["利润空间"], errors="coerce")
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temp_df["泰国糖"] = pd.to_numeric(temp_df["泰国糖"], errors="coerce")
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temp_df["泰国MA5"] = pd.to_numeric(temp_df["泰国MA5"], errors="coerce")
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temp_df["巴西MA5"] = pd.to_numeric(temp_df["巴西MA5"], errors="coerce")
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temp_df["巴西MA10"] = pd.to_numeric(temp_df["巴西MA10"], errors="coerce")
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temp_df["巴西糖"] = pd.to_numeric(temp_df["巴西糖"], errors="coerce")
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temp_df["柳州现货价"] = pd.to_numeric(temp_df["柳州现货价"], errors="coerce")
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temp_df["广州现货价"] = pd.to_numeric(temp_df["广州现货价"], errors="coerce")
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temp_df["泰国MA10"] = pd.to_numeric(temp_df["泰国MA10"], errors="coerce")
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temp_df["利润MA30"] = pd.to_numeric(temp_df["利润MA30"], errors="coerce")
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temp_df["利润MA10"] = pd.to_numeric(temp_df["利润MA10"], errors="coerce")
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return temp_df
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def index_outer_quote_sugar_msweet() -> pd.DataFrame:
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"""
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沐甜科技数据中心-配额外进口糖估算指数
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https://www.msweet.com.cn/mtkj/sjzx13/index.html
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:return: 配额内进口糖估算指数
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:rtype: pandas.DataFrame
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"""
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url = "https://www.msweet.com.cn/datacenterapply/datacenter/json/Jkpewlr.json"
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r = requests.get(url)
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data_json = r.json()
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temp_df = pd.concat(
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[pd.DataFrame(data_json["category"]), pd.DataFrame(data_json["data"])], axis=1
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)
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temp_df.columns = [
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"日期",
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"巴西糖进口成本",
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"泰国糖进口利润空间",
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"巴西糖进口利润空间",
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"泰国糖进口成本",
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"日照现货价",
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]
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temp_df["日期"] = temp_df["日期"].str.replace("/", "-")
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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["巴西糖进口成本"] = pd.to_numeric(
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temp_df["巴西糖进口成本"], errors="coerce"
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)
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temp_df["泰国糖进口利润空间"] = pd.to_numeric(
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temp_df["泰国糖进口利润空间"], errors="coerce"
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)
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temp_df["巴西糖进口利润空间"] = pd.to_numeric(
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temp_df["巴西糖进口利润空间"], errors="coerce"
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)
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temp_df["泰国糖进口成本"] = pd.to_numeric(temp_df["泰国糖进口成本"])
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temp_df["日照现货价"] = pd.to_numeric(temp_df["日照现货价"], errors="coerce")
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return temp_df
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if __name__ == "__main__":
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index_sugar_msweet_df = index_sugar_msweet()
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print(index_sugar_msweet_df)
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index_inner_quote_sugar_msweet_df = index_inner_quote_sugar_msweet()
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print(index_inner_quote_sugar_msweet_df)
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index_outer_quote_sugar_msweet_df = index_outer_quote_sugar_msweet()
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print(index_outer_quote_sugar_msweet_df)
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