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
188 lines
5.7 KiB
Python
188 lines
5.7 KiB
Python
#!/usr/bin/env python
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# -*- coding:utf-8 -*-
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"""
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Date: 2022/11/5 17:08
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Desc: 东方财富-德国-经济数据
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"""
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import pandas as pd
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import requests
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def macro_germany_core(symbol: str = "EMG00179154") -> pd.DataFrame:
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"""
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东方财富-数据中心-经济数据一览-宏观经济-德国-核心代码
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https://data.eastmoney.com/cjsj/foreign_1_0.html
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:param symbol: 代码
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:type symbol: str
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:return: 指定 symbol 的数据
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:rtype: pandas.DataFrame
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"""
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url = "https://datacenter-web.eastmoney.com/api/data/v1/get"
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params = {
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"reportName": "RPT_ECONOMICVALUE_GER",
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"columns": "ALL",
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"filter": f'(INDICATOR_ID="{symbol}")',
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"pageNumber": "1",
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"pageSize": "5000",
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"sortColumns": "REPORT_DATE",
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"sortTypes": "-1",
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"source": "WEB",
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"client": "WEB",
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"p": "1",
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"pageNo": "1",
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"pageNum": "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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temp_df = pd.DataFrame(data_json["result"]["data"])
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temp_df.rename(
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columns={
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"COUNTRY": "-",
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"INDICATOR_ID": "-",
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"INDICATOR_NAME": "-",
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"REPORT_DATE_CH": "时间",
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"REPORT_DATE": "-",
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"PUBLISH_DATE": "发布日期",
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"VALUE": "现值",
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"PRE_VALUE": "前值",
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"INDICATOR_IDOLD": "-",
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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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"时间",
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"前值",
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"现值",
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"发布日期",
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]
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]
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temp_df["前值"] = pd.to_numeric(temp_df["前值"])
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temp_df["现值"] = pd.to_numeric(temp_df["现值"])
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temp_df["发布日期"] = pd.to_datetime(temp_df["发布日期"]).dt.date
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temp_df.sort_values(["发布日期"], inplace=True, ignore_index=True)
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return temp_df
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# 东方财富-德国-经济数据-IFO商业景气指数
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def macro_germany_ifo() -> pd.DataFrame:
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"""
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东方财富-数据中心-经济数据一览-德国-IFO商业景气指数
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https://data.eastmoney.com/cjsj/foreign_1_0.html
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:return: IFO商业景气指数
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:rtype: pandas.DataFrame
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"""
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temp_df = macro_germany_core(symbol="EMG00179154")
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return temp_df
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# 东方财富-德国-经济数据-消费者物价指数月率终值
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def macro_germany_cpi_monthly() -> pd.DataFrame:
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"""
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东方财富-数据中心-经济数据一览-德国-消费者物价指数月率终值
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https://data.eastmoney.com/cjsj/foreign_1_1.html
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:return: 消费者物价指数月率终值
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:rtype: pandas.DataFrame
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"""
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temp_df = macro_germany_core(symbol="EMG00009758")
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return temp_df
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# 东方财富-德国-经济数据-消费者物价指数年率终值
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def macro_germany_cpi_yearly() -> pd.DataFrame:
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"""
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东方财富-数据中心-经济数据一览-德国-消费者物价指数年率终值
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https://data.eastmoney.com/cjsj/foreign_1_2.html
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:return: 消费者物价指数年率终值
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:rtype: pandas.DataFrame
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"""
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temp_df = macro_germany_core(symbol="EMG00009756")
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return temp_df
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# 东方财富-德国-经济数据-贸易帐(季调后)
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def macro_germany_trade_adjusted() -> pd.DataFrame:
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"""
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东方财富-数据中心-经济数据一览-德国-贸易帐(季调后)
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https://data.eastmoney.com/cjsj/foreign_1_3.html
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:return: 贸易帐(季调后)
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:rtype: pandas.DataFrame
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"""
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temp_df = macro_germany_core(symbol="EMG00009753")
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return temp_df
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# 东方财富-德国-经济数据-GDP
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def macro_germany_gdp() -> pd.DataFrame:
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"""
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东方财富-数据中心-经济数据一览-德国-GDP
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https://data.eastmoney.com/cjsj/foreign_1_4.html
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:return: GDP
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:rtype: pandas.DataFrame
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"""
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temp_df = macro_germany_core(symbol="EMG00009720")
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return temp_df
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# 东方财富-德国-经济数据-实际零售销售月率
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def macro_germany_retail_sale_monthly() -> pd.DataFrame:
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"""
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东方财富-数据中心-经济数据一览-德国-实际零售销售月率
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https://data.eastmoney.com/cjsj/foreign_1_5.html
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:return: 实际零售销售月率
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:rtype: pandas.DataFrame
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"""
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temp_df = macro_germany_core(symbol="EMG01333186")
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return temp_df
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# 东方财富-德国-经济数据-实际零售销售年率
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def macro_germany_retail_sale_yearly() -> pd.DataFrame:
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"""
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东方财富-数据中心-经济数据一览-德国-实际零售销售年率
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https://data.eastmoney.com/cjsj/foreign_1_6.html
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:return: 实际零售销售年率
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:rtype: pandas.DataFrame
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"""
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temp_df = macro_germany_core(symbol="EMG01333192")
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return temp_df
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# 东方财富-德国-经济数据-ZEW 经济景气指数
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def macro_germany_zew() -> pd.DataFrame:
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"""
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东方财富-数据中心-经济数据一览-德国-ZEW 经济景气指数
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https://data.eastmoney.com/cjsj/foreign_1_7.html
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:return: ZEW 经济景气指数
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:rtype: pandas.DataFrame
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"""
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temp_df = macro_germany_core(symbol="EMG00172577")
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return temp_df
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if __name__ == "__main__":
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macro_germany_ifo_df = macro_germany_ifo()
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print(macro_germany_ifo_df)
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macro_germany_cpi_monthly_df = macro_germany_cpi_monthly()
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print(macro_germany_cpi_monthly_df)
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macro_germany_cpi_yearly_df = macro_germany_cpi_yearly()
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print(macro_germany_cpi_yearly_df)
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macro_germany_trade_adjusted_df = macro_germany_trade_adjusted()
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print(macro_germany_trade_adjusted_df)
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macro_germany_gdp_df = macro_germany_gdp()
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print(macro_germany_gdp_df)
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macro_germany_retail_sale_monthly_df = macro_germany_retail_sale_monthly()
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print(macro_germany_retail_sale_monthly_df)
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macro_germany_retail_sale_yearly_df = macro_germany_retail_sale_yearly()
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print(macro_germany_retail_sale_yearly_df)
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macro_germany_zew_df = macro_germany_zew()
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print(macro_germany_zew_df)
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