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
279 lines
11 KiB
Python
279 lines
11 KiB
Python
#!/usr/bin/env python
|
|
# -*- coding:utf-8 -*-
|
|
"""
|
|
Date: 2024/3/18 14:00
|
|
Desc: 玄田数据
|
|
https://zhujia.zhuwang.com.cn
|
|
"""
|
|
|
|
import pandas as pd
|
|
import requests
|
|
|
|
|
|
def futures_hog_core(symbol: str = "外三元") -> pd.DataFrame:
|
|
"""
|
|
玄田数据-核心数据
|
|
https://zhujia.zhuwang.com.cn
|
|
:param symbol: choice of {"外三元", "内三元", "土杂猪"}
|
|
:type symbol: str
|
|
:return: 玄田数据-核心数据
|
|
:rtype: pandas.DataFrame
|
|
"""
|
|
if symbol == "外三元":
|
|
url = "https://xt.yangzhu.vip/data/getzhujiahitsdata"
|
|
params = {"ptype": "1", "areano": "-1", "datetype": "0"}
|
|
r = requests.post(url, params=params)
|
|
data_json = r.json()
|
|
temp_df = pd.DataFrame(data_json["data"])
|
|
temp_df.columns = ["value", "date"]
|
|
temp_df = temp_df[["date", "value"]]
|
|
temp_df["date"] = pd.to_datetime(temp_df["date"], errors="coerce").dt.date
|
|
temp_df["value"] = pd.to_numeric(temp_df["value"], errors="coerce")
|
|
return temp_df
|
|
elif symbol == "内三元":
|
|
url = "https://xt.yangzhu.vip/data/getzhujiahitsdata"
|
|
params = {"ptype": "2", "areano": "-1", "datetype": "0"}
|
|
r = requests.post(url, params=params)
|
|
data_json = r.json()
|
|
temp_df = pd.DataFrame(data_json["data"])
|
|
temp_df.columns = ["value", "date"]
|
|
temp_df = temp_df[["date", "value"]]
|
|
temp_df["date"] = pd.to_datetime(temp_df["date"], errors="coerce").dt.date
|
|
temp_df["value"] = pd.to_numeric(temp_df["value"], errors="coerce")
|
|
return temp_df
|
|
elif symbol == "土杂猪":
|
|
url = "https://xt.yangzhu.vip/data/getzhujiahitsdata"
|
|
params = {"ptype": "3", "areano": "-1", "datetype": "0"}
|
|
r = requests.post(url, params=params)
|
|
data_json = r.json()
|
|
temp_df = pd.DataFrame(data_json["data"])
|
|
temp_df.columns = ["value", "date"]
|
|
temp_df = temp_df[["date", "value"]]
|
|
temp_df["date"] = pd.to_datetime(temp_df["date"], errors="coerce").dt.date
|
|
temp_df["value"] = pd.to_numeric(temp_df["value"], errors="coerce")
|
|
return temp_df
|
|
|
|
|
|
def futures_hog_cost(symbol: str = "玉米") -> pd.DataFrame:
|
|
"""
|
|
玄田数据-成本维度
|
|
https://zhujia.zhuwang.com.cn
|
|
:param symbol: choice of {"玉米", "豆粕", "二元母猪价格", "仔猪价格"}
|
|
:type symbol: str
|
|
:return: 玄田数据-成本维度
|
|
:rtype: pandas.DataFrame
|
|
"""
|
|
if symbol == "玉米":
|
|
url = "https://xt.yangzhu.vip/data/getzhujiahitsdata"
|
|
params = {"ptype": "4", "areano": "-1", "datetype": "0"}
|
|
r = requests.post(url, params=params)
|
|
data_json = r.json()
|
|
temp_df = pd.DataFrame(data_json["data"])
|
|
temp_df.columns = ["value", "date"]
|
|
temp_df = temp_df[["date", "value"]]
|
|
temp_df["date"] = pd.to_datetime(temp_df["date"], errors="coerce").dt.date
|
|
temp_df["value"] = pd.to_numeric(temp_df["value"], errors="coerce")
|
|
return temp_df
|
|
elif symbol == "豆粕":
|
|
url = "https://xt.yangzhu.vip/data/getzhujiahitsdata"
|
|
params = {"ptype": "5", "areano": "-1", "datetype": "0"}
|
|
r = requests.post(url, params=params)
|
|
data_json = r.json()
|
|
temp_df = pd.DataFrame(data_json["data"])
|
|
temp_df.columns = ["value", "date"]
|
|
temp_df = temp_df[["date", "value"]]
|
|
temp_df["date"] = pd.to_datetime(temp_df["date"], errors="coerce").dt.date
|
|
temp_df["value"] = pd.to_numeric(temp_df["value"], errors="coerce")
|
|
return temp_df
|
|
elif symbol == "二元母猪价格":
|
|
url = "https://xt.yangzhu.vip/data/getmapdata"
|
|
params = {
|
|
"ptype": "1",
|
|
"areano": "-1",
|
|
}
|
|
r = requests.post(url, params=params)
|
|
data_json = r.json()
|
|
temp_df = pd.DataFrame(data_json["data"])
|
|
temp_df.columns = ["date", "value"]
|
|
temp_df["date"] = pd.to_datetime(temp_df["date"], errors="coerce").dt.date
|
|
temp_df["value"] = pd.to_numeric(temp_df["value"], errors="coerce")
|
|
return temp_df
|
|
elif symbol == "仔猪价格":
|
|
url = "https://xt.yangzhu.vip/data/getmapdata"
|
|
params = {
|
|
"ptype": "2",
|
|
"areano": "-1",
|
|
}
|
|
r = requests.post(url, params=params)
|
|
data_json = r.json()
|
|
temp_df = pd.DataFrame(data_json["data"])
|
|
temp_df.columns = ["date", "value"]
|
|
temp_df["date"] = pd.to_datetime(temp_df["date"], errors="coerce").dt.date
|
|
temp_df["value"] = pd.to_numeric(temp_df["value"], errors="coerce")
|
|
return temp_df
|
|
|
|
|
|
def futures_hog_supply(symbol: str = "猪肉批发价") -> pd.DataFrame:
|
|
"""
|
|
玄田数据-供应维度
|
|
https://zhujia.zhuwang.com.cn
|
|
:param symbol: choice of {"猪肉批发价", "储备冻猪肉", "饲料原料数据", "白条肉",
|
|
"生猪产能", "育肥猪", "肉类价格指数", "猪粮比价"}
|
|
:type symbol: str
|
|
:return: 玄田数据-供应维度
|
|
:rtype: pandas.DataFrame
|
|
"""
|
|
if symbol == "猪肉批发价":
|
|
url = "https://xt.yangzhu.vip/data/getmapdata"
|
|
params = {"ptype": "3", "areano": "-1"}
|
|
r = requests.post(url, params=params)
|
|
data_json = r.json()
|
|
temp_df = pd.DataFrame(data_json["data"])
|
|
temp_df.columns = ["date", "item", "value"]
|
|
del temp_df["item"]
|
|
temp_df["date"] = pd.to_datetime(temp_df["date"], errors="coerce").dt.date
|
|
temp_df["value"] = pd.to_numeric(temp_df["value"], errors="coerce")
|
|
return temp_df
|
|
elif symbol == "储备冻猪肉":
|
|
url = "https://xt.yangzhu.vip/data/getmapdata"
|
|
params = {"ptype": "4", "areano": "-1"}
|
|
r = requests.post(url, params=params)
|
|
data_json = r.json()
|
|
temp_df = pd.DataFrame(data_json["data"])
|
|
temp_df.columns = ["date", "value"]
|
|
temp_df["date"] = pd.to_datetime(temp_df["date"], errors="coerce").dt.date
|
|
temp_df["value"] = pd.to_numeric(temp_df["value"], errors="coerce")
|
|
return temp_df
|
|
elif symbol == "饲料原料数据":
|
|
url = "https://xt.yangzhu.vip/data/getmapdata"
|
|
params = {"ptype": "5", "areano": "-1"}
|
|
r = requests.post(url, params=params)
|
|
data_json = r.json()
|
|
temp_df = pd.DataFrame(data_json["data"])
|
|
temp_df.columns = [
|
|
"周期",
|
|
"大豆进口金额",
|
|
"大豆播种面积",
|
|
"玉米进口金额",
|
|
"玉米播种面积",
|
|
]
|
|
temp_df["周期"] = temp_df["周期"].astype(int).astype(str)
|
|
temp_df["大豆进口金额"] = pd.to_numeric(
|
|
temp_df["大豆进口金额"], errors="coerce"
|
|
)
|
|
temp_df["大豆播种面积"] = pd.to_numeric(
|
|
temp_df["大豆播种面积"], errors="coerce"
|
|
)
|
|
temp_df["玉米进口金额"] = pd.to_numeric(
|
|
temp_df["玉米进口金额"], errors="coerce"
|
|
)
|
|
temp_df["玉米播种面积"] = pd.to_numeric(
|
|
temp_df["玉米播种面积"], errors="coerce"
|
|
)
|
|
return temp_df
|
|
elif symbol == "白条肉":
|
|
url = "https://xt.yangzhu.vip/data/getmapdata"
|
|
params = {"ptype": "6", "areano": "-1"}
|
|
r = requests.post(url, params=params)
|
|
data_json = r.json()
|
|
temp_df = pd.DataFrame(data_json["data"])
|
|
temp_df.columns = ["周期", "白条肉平均出厂价格", "环比", "同比"]
|
|
temp_df["白条肉平均出厂价格"] = pd.to_numeric(
|
|
temp_df["白条肉平均出厂价格"], errors="coerce"
|
|
)
|
|
temp_df["环比"] = pd.to_numeric(temp_df["环比"], errors="coerce")
|
|
temp_df["同比"] = pd.to_numeric(temp_df["同比"], errors="coerce")
|
|
return temp_df
|
|
elif symbol == "生猪产能":
|
|
url = "https://xt.yangzhu.vip/data/getmapdata"
|
|
params = {"ptype": "7", "areano": "-1"}
|
|
r = requests.post(url, params=params)
|
|
data_json = r.json()
|
|
temp_df = pd.DataFrame(data_json["data"])
|
|
temp_df.columns = ["周期", "能繁母猪存栏", "猪肉产量", "生猪存栏", "生猪出栏"]
|
|
temp_df["能繁母猪存栏"] = pd.to_numeric(
|
|
temp_df["能繁母猪存栏"], errors="coerce"
|
|
)
|
|
temp_df["猪肉产量"] = pd.to_numeric(temp_df["猪肉产量"], errors="coerce")
|
|
temp_df["生猪存栏"] = pd.to_numeric(temp_df["生猪存栏"], errors="coerce")
|
|
temp_df["生猪出栏"] = pd.to_numeric(temp_df["生猪出栏"], errors="coerce")
|
|
return temp_df
|
|
elif symbol == "育肥猪":
|
|
url = "https://xt.yangzhu.vip/data/getmapdata"
|
|
params = {"ptype": "9", "areano": "-1"}
|
|
r = requests.post(url, params=params)
|
|
data_json = r.json()
|
|
temp_df = pd.DataFrame(data_json["data"])
|
|
temp_df = temp_df[["date", "benzhou"]]
|
|
temp_df["date"] = pd.to_datetime(temp_df["date"], errors="coerce").dt.date
|
|
temp_df["benzhou"] = pd.to_numeric(temp_df["benzhou"], errors="coerce")
|
|
return temp_df
|
|
elif symbol == "肉类价格指数":
|
|
url = "https://xt.yangzhu.vip/data/getmapdata"
|
|
params = {"ptype": "10", "areano": "-1"}
|
|
r = requests.post(url, params=params)
|
|
data_json = r.json()
|
|
temp_df = pd.DataFrame(data_json["data"])
|
|
temp_df.columns = ["date", "item", "value"]
|
|
del temp_df["item"]
|
|
temp_df["date"] = pd.to_datetime(temp_df["date"], errors="coerce").dt.date
|
|
temp_df["value"] = pd.to_numeric(temp_df["value"], errors="coerce")
|
|
return temp_df
|
|
elif symbol == "猪粮比价":
|
|
url = "https://xt.yangzhu.vip/data/getmapdata"
|
|
params = {"ptype": "11", "areano": "-1"}
|
|
r = requests.post(url, params=params)
|
|
data_json = r.json()
|
|
temp_df = pd.DataFrame(data_json["data"])
|
|
temp_df.columns = ["date", "value"]
|
|
temp_df["date"] = pd.to_datetime(temp_df["date"], errors="coerce").dt.date
|
|
temp_df["value"] = pd.to_numeric(temp_df["value"], errors="coerce")
|
|
return temp_df
|
|
|
|
|
|
if __name__ == "__main__":
|
|
futures_hog_core_df = futures_hog_core(symbol="外三元")
|
|
print(futures_hog_core_df)
|
|
|
|
futures_hog_core_df = futures_hog_core(symbol="内三元")
|
|
print(futures_hog_core_df)
|
|
|
|
futures_hog_core_df = futures_hog_core(symbol="土杂猪")
|
|
print(futures_hog_core_df)
|
|
|
|
futures_hog_cost_df = futures_hog_cost(symbol="玉米")
|
|
print(futures_hog_cost_df)
|
|
|
|
futures_hog_cost_df = futures_hog_cost(symbol="豆粕")
|
|
print(futures_hog_cost_df)
|
|
|
|
futures_hog_cost_df = futures_hog_cost(symbol="二元母猪价格")
|
|
print(futures_hog_cost_df)
|
|
|
|
futures_hog_cost_df = futures_hog_cost(symbol="仔猪价格")
|
|
print(futures_hog_cost_df)
|
|
|
|
futures_hog_supply_df = futures_hog_supply(symbol="猪肉批发价")
|
|
print(futures_hog_supply_df)
|
|
|
|
futures_hog_supply_df = futures_hog_supply(symbol="储备冻猪肉")
|
|
print(futures_hog_supply_df)
|
|
|
|
futures_hog_supply_df = futures_hog_supply(symbol="饲料原料数据")
|
|
print(futures_hog_supply_df)
|
|
|
|
futures_hog_supply_df = futures_hog_supply(symbol="白条肉")
|
|
print(futures_hog_supply_df)
|
|
|
|
futures_hog_supply_df = futures_hog_supply(symbol="生猪产能")
|
|
print(futures_hog_supply_df)
|
|
|
|
futures_hog_supply_df = futures_hog_supply(symbol="育肥猪")
|
|
print(futures_hog_supply_df)
|
|
|
|
futures_hog_supply_df = futures_hog_supply(symbol="肉类价格指数")
|
|
print(futures_hog_supply_df)
|
|
|
|
futures_hog_supply_df = futures_hog_supply(symbol="猪粮比价")
|
|
print(futures_hog_supply_df)
|