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
391 lines
11 KiB
Python
391 lines
11 KiB
Python
#!/usr/bin/env python
|
|
# -*- coding:utf-8 -*-
|
|
"""
|
|
Date: 2025/1/17 15:30
|
|
Desc: 东方财富-经济数据-澳大利亚
|
|
https://data.eastmoney.com/cjsj/foreign_5_0.html
|
|
"""
|
|
|
|
import pandas as pd
|
|
import requests
|
|
|
|
|
|
# 零售销售月率
|
|
def macro_australia_retail_rate_monthly() -> pd.DataFrame:
|
|
"""
|
|
东方财富-经济数据-澳大利亚-零售销售月率
|
|
https://data.eastmoney.com/cjsj/foreign_5_0.html
|
|
:return: 零售销售月率
|
|
:rtype: pandas.DataFrame
|
|
"""
|
|
url = "https://datacenter-web.eastmoney.com/api/data/v1/get"
|
|
params = {
|
|
"reportName": "RPT_ECONOMICVALUE_AUSTRALIA",
|
|
"columns": "ALL",
|
|
"filter": '(INDICATOR_ID="EMG00152903")',
|
|
"pageNumber": "1",
|
|
"pageSize": "2000",
|
|
"sortColumns": "REPORT_DATE",
|
|
"sortTypes": "-1",
|
|
"source": "WEB",
|
|
"client": "WEB",
|
|
"p": "1",
|
|
"pageNo": "1",
|
|
"pageNum": "1",
|
|
}
|
|
r = requests.get(url, params=params)
|
|
data_json = r.json()
|
|
temp_df = pd.DataFrame(data_json["result"]["data"])
|
|
temp_df.columns = [
|
|
"-",
|
|
"-",
|
|
"-",
|
|
"时间",
|
|
"-",
|
|
"发布日期",
|
|
"现值",
|
|
"前值",
|
|
]
|
|
temp_df = temp_df[
|
|
[
|
|
"时间",
|
|
"前值",
|
|
"现值",
|
|
"发布日期",
|
|
]
|
|
]
|
|
temp_df["前值"] = pd.to_numeric(temp_df["前值"], errors="coerce")
|
|
temp_df["现值"] = pd.to_numeric(temp_df["现值"], errors="coerce")
|
|
temp_df["发布日期"] = pd.to_datetime(temp_df["发布日期"], errors="coerce").dt.date
|
|
temp_df.sort_values(by="发布日期", ignore_index=True, inplace=True)
|
|
return temp_df
|
|
|
|
|
|
# 贸易帐
|
|
def macro_australia_trade() -> pd.DataFrame:
|
|
"""
|
|
东方财富-经济数据-澳大利亚-贸易帐
|
|
https://data.eastmoney.com/cjsj/foreign_5_1.html
|
|
:return: 贸易帐
|
|
:rtype: pandas.DataFrame
|
|
"""
|
|
url = "https://datacenter-web.eastmoney.com/api/data/v1/get"
|
|
params = {
|
|
"reportName": "RPT_ECONOMICVALUE_AUSTRALIA",
|
|
"columns": "ALL",
|
|
"filter": '(INDICATOR_ID="EMG00152793")',
|
|
"pageNumber": "1",
|
|
"pageSize": "2000",
|
|
"sortColumns": "REPORT_DATE",
|
|
"sortTypes": "-1",
|
|
"source": "WEB",
|
|
"client": "WEB",
|
|
"p": "1",
|
|
"pageNo": "1",
|
|
"pageNum": "1",
|
|
}
|
|
r = requests.get(url, params=params)
|
|
data_json = r.json()
|
|
temp_df = pd.DataFrame(data_json["result"]["data"])
|
|
temp_df.columns = [
|
|
"-",
|
|
"-",
|
|
"-",
|
|
"时间",
|
|
"-",
|
|
"发布日期",
|
|
"现值",
|
|
"前值",
|
|
]
|
|
temp_df = temp_df[
|
|
[
|
|
"时间",
|
|
"前值",
|
|
"现值",
|
|
"发布日期",
|
|
]
|
|
]
|
|
temp_df["前值"] = pd.to_numeric(temp_df["前值"], errors="coerce")
|
|
temp_df["现值"] = pd.to_numeric(temp_df["现值"], errors="coerce")
|
|
temp_df["发布日期"] = pd.to_datetime(temp_df["发布日期"], errors="coerce").dt.date
|
|
temp_df.sort_values(by="发布日期", ignore_index=True, inplace=True)
|
|
return temp_df
|
|
|
|
|
|
# 失业率
|
|
def macro_australia_unemployment_rate() -> pd.DataFrame:
|
|
"""
|
|
东方财富-经济数据-澳大利亚-失业率
|
|
https://data.eastmoney.com/cjsj/foreign_5_2.html
|
|
:return: 失业率
|
|
:rtype: pandas.DataFrame
|
|
"""
|
|
url = "https://datacenter-web.eastmoney.com/api/data/v1/get"
|
|
params = {
|
|
"reportName": "RPT_ECONOMICVALUE_AUSTRALIA",
|
|
"columns": "ALL",
|
|
"filter": '(INDICATOR_ID="EMG00101141")',
|
|
"pageNumber": "1",
|
|
"pageSize": "2000",
|
|
"sortColumns": "REPORT_DATE",
|
|
"sortTypes": "-1",
|
|
"source": "WEB",
|
|
"client": "WEB",
|
|
"p": "1",
|
|
"pageNo": "1",
|
|
"pageNum": "1",
|
|
}
|
|
r = requests.get(url, params=params)
|
|
data_json = r.json()
|
|
temp_df = pd.DataFrame(data_json["result"]["data"])
|
|
temp_df.columns = [
|
|
"-",
|
|
"-",
|
|
"-",
|
|
"时间",
|
|
"-",
|
|
"发布日期",
|
|
"现值",
|
|
"前值",
|
|
]
|
|
temp_df = temp_df[
|
|
[
|
|
"时间",
|
|
"前值",
|
|
"现值",
|
|
"发布日期",
|
|
]
|
|
]
|
|
temp_df["前值"] = pd.to_numeric(temp_df["前值"], errors="coerce")
|
|
temp_df["现值"] = pd.to_numeric(temp_df["现值"], errors="coerce")
|
|
temp_df["发布日期"] = pd.to_datetime(temp_df["发布日期"], errors="coerce").dt.date
|
|
temp_df.sort_values(by="发布日期", ignore_index=True, inplace=True)
|
|
return temp_df
|
|
|
|
|
|
# 生产者物价指数季率
|
|
def macro_australia_ppi_quarterly() -> pd.DataFrame:
|
|
"""
|
|
东方财富-经济数据-澳大利亚-生产者物价指数季率
|
|
https://data.eastmoney.com/cjsj/foreign_5_3.html
|
|
:return: 生产者物价指数季率
|
|
:rtype: pandas.DataFrame
|
|
"""
|
|
url = "https://datacenter-web.eastmoney.com/api/data/v1/get"
|
|
params = {
|
|
"reportName": "RPT_ECONOMICVALUE_AUSTRALIA",
|
|
"columns": "ALL",
|
|
"filter": '(INDICATOR_ID="EMG00152722")',
|
|
"pageNumber": "1",
|
|
"pageSize": "2000",
|
|
"sortColumns": "REPORT_DATE",
|
|
"sortTypes": "-1",
|
|
"source": "WEB",
|
|
"client": "WEB",
|
|
"p": "1",
|
|
"pageNo": "1",
|
|
"pageNum": "1",
|
|
}
|
|
r = requests.get(url, params=params)
|
|
data_json = r.json()
|
|
temp_df = pd.DataFrame(data_json["result"]["data"])
|
|
temp_df.columns = [
|
|
"-",
|
|
"-",
|
|
"-",
|
|
"时间",
|
|
"-",
|
|
"发布日期",
|
|
"现值",
|
|
"前值",
|
|
]
|
|
temp_df = temp_df[
|
|
[
|
|
"时间",
|
|
"前值",
|
|
"现值",
|
|
"发布日期",
|
|
]
|
|
]
|
|
temp_df["前值"] = pd.to_numeric(temp_df["前值"], errors="coerce")
|
|
temp_df["现值"] = pd.to_numeric(temp_df["现值"], errors="coerce")
|
|
temp_df["发布日期"] = pd.to_datetime(temp_df["发布日期"], errors="coerce").dt.date
|
|
temp_df.sort_values(by="发布日期", ignore_index=True, inplace=True)
|
|
return temp_df
|
|
|
|
|
|
# 消费者物价指数季率
|
|
def macro_australia_cpi_quarterly() -> pd.DataFrame:
|
|
"""
|
|
东方财富-经济数据-澳大利亚-消费者物价指数季率
|
|
https://data.eastmoney.com/cjsj/foreign_5_4.html
|
|
:return: 消费者物价指数季率
|
|
:rtype: pandas.DataFrame
|
|
"""
|
|
url = "https://datacenter-web.eastmoney.com/api/data/v1/get"
|
|
params = {
|
|
"reportName": "RPT_ECONOMICVALUE_AUSTRALIA",
|
|
"columns": "ALL",
|
|
"filter": '(INDICATOR_ID="EMG00101104")',
|
|
"pageNumber": "1",
|
|
"pageSize": "2000",
|
|
"sortColumns": "REPORT_DATE",
|
|
"sortTypes": "-1",
|
|
"source": "WEB",
|
|
"client": "WEB",
|
|
"p": "1",
|
|
"pageNo": "1",
|
|
"pageNum": "1",
|
|
}
|
|
r = requests.get(url, params=params)
|
|
data_json = r.json()
|
|
temp_df = pd.DataFrame(data_json["result"]["data"])
|
|
temp_df.columns = [
|
|
"-",
|
|
"-",
|
|
"-",
|
|
"时间",
|
|
"-",
|
|
"发布日期",
|
|
"现值",
|
|
"前值",
|
|
]
|
|
temp_df = temp_df[
|
|
[
|
|
"时间",
|
|
"前值",
|
|
"现值",
|
|
"发布日期",
|
|
]
|
|
]
|
|
temp_df["前值"] = pd.to_numeric(temp_df["前值"], errors="coerce")
|
|
temp_df["现值"] = pd.to_numeric(temp_df["现值"], errors="coerce")
|
|
temp_df["发布日期"] = pd.to_datetime(temp_df["发布日期"], errors="coerce").dt.date
|
|
temp_df.sort_values(by="发布日期", ignore_index=True, inplace=True)
|
|
return temp_df
|
|
|
|
|
|
# 消费者物价指数年率
|
|
def macro_australia_cpi_yearly() -> pd.DataFrame:
|
|
"""
|
|
东方财富-经济数据-澳大利亚-消费者物价指数年率
|
|
https://data.eastmoney.com/cjsj/foreign_5_5.html
|
|
:return: 消费者物价指数年率
|
|
:rtype: pandas.DataFrame
|
|
"""
|
|
url = "https://datacenter-web.eastmoney.com/api/data/v1/get"
|
|
params = {
|
|
"reportName": "RPT_ECONOMICVALUE_AUSTRALIA",
|
|
"columns": "ALL",
|
|
"filter": '(INDICATOR_ID="EMG00101093")',
|
|
"pageNumber": "1",
|
|
"pageSize": "2000",
|
|
"sortColumns": "REPORT_DATE",
|
|
"sortTypes": "-1",
|
|
"source": "WEB",
|
|
"client": "WEB",
|
|
"p": "1",
|
|
"pageNo": "1",
|
|
"pageNum": "1",
|
|
}
|
|
r = requests.get(url, params=params)
|
|
data_json = r.json()
|
|
temp_df = pd.DataFrame(data_json["result"]["data"])
|
|
temp_df.columns = [
|
|
"-",
|
|
"-",
|
|
"-",
|
|
"时间",
|
|
"-",
|
|
"发布日期",
|
|
"现值",
|
|
"前值",
|
|
]
|
|
temp_df = temp_df[
|
|
[
|
|
"时间",
|
|
"前值",
|
|
"现值",
|
|
"发布日期",
|
|
]
|
|
]
|
|
temp_df["前值"] = pd.to_numeric(temp_df["前值"], errors="coerce")
|
|
temp_df["现值"] = pd.to_numeric(temp_df["现值"], errors="coerce")
|
|
temp_df["发布日期"] = pd.to_datetime(temp_df["发布日期"], errors="coerce").dt.date
|
|
temp_df.sort_values(by="发布日期", ignore_index=True, inplace=True)
|
|
return temp_df
|
|
|
|
|
|
# 央行公布利率决议
|
|
def macro_australia_bank_rate() -> pd.DataFrame:
|
|
"""
|
|
东方财富-经济数据-澳大利亚-央行公布利率决议
|
|
https://data.eastmoney.com/cjsj/foreign_5_6.html
|
|
:return: 央行公布利率决议
|
|
:rtype: pandas.DataFrame
|
|
"""
|
|
url = "https://datacenter-web.eastmoney.com/api/data/v1/get"
|
|
params = {
|
|
"reportName": "RPT_ECONOMICVALUE_AUSTRALIA",
|
|
"columns": "ALL",
|
|
"filter": '(INDICATOR_ID="EMG00342255")',
|
|
"pageNumber": "1",
|
|
"pageSize": "2000",
|
|
"sortColumns": "REPORT_DATE",
|
|
"sortTypes": "-1",
|
|
"source": "WEB",
|
|
"client": "WEB",
|
|
"p": "1",
|
|
"pageNo": "1",
|
|
"pageNum": "1",
|
|
}
|
|
r = requests.get(url, params=params)
|
|
data_json = r.json()
|
|
temp_df = pd.DataFrame(data_json["result"]["data"])
|
|
temp_df.columns = [
|
|
"-",
|
|
"-",
|
|
"-",
|
|
"时间",
|
|
"-",
|
|
"发布日期",
|
|
"现值",
|
|
"前值",
|
|
]
|
|
temp_df = temp_df[
|
|
[
|
|
"时间",
|
|
"前值",
|
|
"现值",
|
|
"发布日期",
|
|
]
|
|
]
|
|
temp_df["前值"] = pd.to_numeric(temp_df["前值"], errors="coerce")
|
|
temp_df["现值"] = pd.to_numeric(temp_df["现值"], errors="coerce")
|
|
temp_df["发布日期"] = pd.to_datetime(temp_df["发布日期"], errors="coerce").dt.date
|
|
temp_df.sort_values(by="发布日期", ignore_index=True, inplace=True)
|
|
return temp_df
|
|
|
|
|
|
if __name__ == "__main__":
|
|
macro_australia_retail_rate_monthly_df = macro_australia_retail_rate_monthly()
|
|
print(macro_australia_retail_rate_monthly_df)
|
|
|
|
macro_australia_trade_df = macro_australia_trade()
|
|
print(macro_australia_trade_df)
|
|
|
|
macro_australia_unemployment_rate_df = macro_australia_unemployment_rate()
|
|
print(macro_australia_unemployment_rate_df)
|
|
|
|
macro_australia_ppi_quarterly_df = macro_australia_ppi_quarterly()
|
|
print(macro_australia_ppi_quarterly_df)
|
|
|
|
macro_australia_cpi_quarterly_df = macro_australia_cpi_quarterly()
|
|
print(macro_australia_cpi_quarterly_df)
|
|
|
|
macro_australia_cpi_yearly_df = macro_australia_cpi_yearly()
|
|
print(macro_australia_cpi_yearly_df)
|
|
|
|
macro_australia_bank_rate_df = macro_australia_bank_rate()
|
|
print(macro_australia_bank_rate_df)
|