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fix: fix currency_pair_map
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@albertandking
albertandking committed Jun 26, 2024
1 parent d72529e commit b4a16e6
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304 changes: 19 additions & 285 deletions akshare/fx/currency_investing.py
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Original file line number Diff line number Diff line change
@@ -1,229 +1,29 @@
#!/usr/bin/env python
# -*- coding:utf-8 -*-
"""
Date: 2022/8/8 20:33
Date: 2024/6/26 15:33
Desc: 英为财情-外汇-货币对历史数据
https://cn.investing.com/currencies/
https://cn.investing.com/currencies/eur-usd-historical-data
"""
import json

import pandas as pd
import requests
from bs4 import BeautifulSoup
from tqdm import tqdm
from akshare.utils.tqdm import get_tqdm

from akshare.index.cons import short_headers


def _currency_name_url() -> dict:
"""
货币键值对
:return: 货币键值对
:rtype: dict
"""
url = "https://cn.investing.com/currencies/"
res = requests.post(url, headers=short_headers)
data_table = pd.read_html(res.text)[0].iloc[:, 1:] # 实时货币行情
data_table.columns = ["中文名称", "英文名称", "最新", "最高", "最低", "涨跌额", "涨跌幅", "时间"]
name_code_dict = dict(
zip(
data_table["中文名称"].tolist(),
[
item.lower().replace("/", "-")
for item in data_table["英文名称"].tolist()
],
)
)
return name_code_dict


def currency_hist_area_index_name_code(symbol: str = "usd-jpy") -> dict:
"""
指定 symbol 的所有指数和代码
https://cn.investing.com/indices/
:param symbol: 指定的国家或地区；ak._get_global_country_name_url() 函数返回的国家或地区的名称
:type symbol: str
:return: 指定 area 的所有指数和代码
:rtype: dict
"""
pd.set_option("mode.chained_assignment", None)
url = f"https://cn.investing.com/currencies/{symbol}-historical-data"
r = requests.get(url)
soup = BeautifulSoup(r.text, "lxml")
data_text = soup.find("script", attrs={"id": "__NEXT_DATA__"}).text
data_json = json.loads(data_text)
code = json.loads(data_json["props"]["pageProps"]["state"])["dataStore"][
"pageInfoStore"
]["identifiers"]["instrument_id"]
return code


def currency_hist(
symbol: str = "usd-jpy",
period: str = "每日",
start_date: str = "20030101",
end_date: str = "20220808",
) -> pd.DataFrame:
"""
外汇历史数据, 注意获取数据区间的长短, 输入任意货币对, 具体能否获取, 通过 currency_name_code_dict 查询
https://www.investing.com/
:param symbol: 货币对
:type symbol: str
:param period: choice of {"每日", "每周", "每月"}
:type period: str
:param start_date: 日期
:type start_date: str
:param end_date: 日期
:type end_date: str
:return: 货币对历史数据
:rtype: pandas.DataFrame
"""
start_date = "-".join([start_date[:4], start_date[4:6], start_date[6:]])
end_date = "-".join([end_date[:4], end_date[4:6], end_date[6:]])
code = currency_hist_area_index_name_code(symbol)
url = f"https://api.investing.com/api/financialdata/historical/{code}"
period_map = {"每日": "Daily", "每周": "Weekly", "每月": "Monthly"}
params = {
"start-date": start_date,
"end-date": end_date,
"time-frame": period_map[period],
"add-missing-rows": "false",
}
headers = {
"accept": "application/json, text/plain, */*",
"accept-encoding": "gzip, deflate, br",
"accept-language": "zh-CN,zh;q=0.9,en;q=0.8",
"cache-control": "no-cache",
"domain-id": "cn",
"origin": "https://cn.investing.com",
"pragma": "no-cache",
"referer": "https://cn.investing.com/",
"sec-ch-ua": '"Google Chrome";v="105", "Not)A;Brand";v="8", "Chromium";v="105"',
"sec-ch-ua-mobile": '"?0"',
"sec-ch-ua-platform": '"Windows"',
"sec-fetch-dest": "empty",
"sec-fetch-mode": "cors",
"sec-fetch-site": "same-site",
"user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/105.0.0.0 Safari/537.36",
}
r = requests.get(url, params=params, headers=headers)
data_json = r.json()
df_data = pd.DataFrame(data_json["data"])
df_data.columns = [
"-",
"-",
"-",
"日期",
"-",
"-",
"-",
"-",
"-",
"交易量",
"-",
"收盘",
"开盘",
"高",
"低",
"涨跌幅",
]
df_data = df_data[["日期", "收盘", "开盘", "高", "低", "交易量", "涨跌幅"]]
df_data["日期"] = pd.to_datetime(df_data["日期"]).dt.date
df_data["收盘"] = pd.to_numeric(df_data["收盘"])
df_data["开盘"] = pd.to_numeric(df_data["开盘"])
df_data["高"] = pd.to_numeric(df_data["高"])
df_data["低"] = pd.to_numeric(df_data["低"])
df_data["交易量"] = pd.to_numeric(df_data["交易量"])
df_data["涨跌幅"] = pd.to_numeric(df_data["涨跌幅"])
df_data.sort_values("日期", inplace=True)
df_data.reset_index(inplace=True, drop=True)
return df_data


def _currency_single() -> pd.DataFrame:
"""
英为财情-外汇-单种货币兑换汇率-单种货币列表
:return: 单种货币列表
:rtype: pandas.DataFrame
"""
url = "https://cn.investing.com/currencies/single-currency-crosses"
res = requests.post(url, headers=short_headers)
soup = BeautifulSoup(res.text, "lxml")
name_url_option_list = soup.find(
"select", attrs={"class": "newInput selectBox"}
).find_all("option")
temp_df = pd.DataFrame(
[item.get_text().split("-", 1) for item in name_url_option_list]
)
temp_df.columns = ["short_name", "name"]
temp_df["short_name"] = temp_df["short_name"].str.strip()
temp_df["name"] = temp_df["name"].str.strip()
temp_df["code"] = [item["value"] for item in name_url_option_list]
return temp_df


def currency_name_code(symbol: str = "usd/jpy") -> pd.DataFrame:
def currency_pair_map(symbol: str = "美元") -> pd.DataFrame:
"""
当前所有可兑换货币对
:param symbol: "usd/jpy"
指定货币的所有可获取货币对的数据
https://cn.investing.com/currencies/cny-jmd
:param symbol: 指定货币
:type symbol: str
:return: 中英文货币对
:return: 指定货币的所有可获取货币对的数据
:rtype: pandas.DataFrame
name code
0 欧元/美元 eur-usd
1 英镑/美元 gbp-usd
2 美元/日元 usd-jpy
3 美元/瑞士法郎 usd-chf
4 澳大利亚元/美元 aud-usd
.. ... ...
268 日元/新加坡元 jpy-sgd
269 科威特第纳尔/日元 kwd-jpy
270 日元/白俄罗斯卢布 jpy-byn
271 日元/乌克兰赫里纳 jpy-uah
272 日元/土耳其里拉 jpy-try
"""
symbol = symbol.upper()
currency_df = _currency_single()
url = "https://cn.investing.com/currencies/Service/ChangeCurrency"
params = {
"session_uniq_id": "53bee677662a2336ec07b40738753fc1",
"currencies": currency_df[
currency_df["short_name"] == symbol.split("/")[0]
]["code"].values[0],
}
headers = {
"Accept": "application/json, text/javascript, */*; q=0.01",
"Accept-Language": "zh-CN,zh;q=0.9,en;q=0.8",
"Cache-Control": "no-cache",
"Connection": "keep-alive",
"Host": "cn.investing.com",
"Pragma": "no-cache",
"Referer": "https://cn.investing.com/currencies/single-currency-crosses",
"Sec-Fetch-Mode": "cors",
"Sec-Fetch-Site": "same-origin",
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/79.0.3945.130 Safari/537.36",
"X-Requested-With": "XMLHttpRequest",
}
r = requests.get(url, params=params, headers=headers)
temp_df = pd.read_html(r.json()["HTML"])[0].iloc[:, 1:]
temp_df.rename(columns={"名称.1": "简称"}, inplace=True)
temp_df["pids"] = [item[:-1] for item in r.json()["pids"]]
name_code_dict_one = dict(
zip(
temp_df["名称"].tolist(),
[
item.lower().replace("/", "-")
for item in temp_df["简称"].tolist()
],
)
)
params = {
"session_uniq_id": "53bee677662a2336ec07b40738753fc1",
"currencies": currency_df[
currency_df["short_name"] == symbol.split("/")[1]
]["code"].values[0],
}
region_code = []
region_name = []
headers = {
"Accept": "application/json, text/javascript, */*; q=0.01",
# "Accept-Encoding": "gzip, deflate, br",
Expand All @@ -235,75 +35,29 @@ def currency_name_code(symbol: str = "usd/jpy") -> pd.DataFrame:
"Referer": "https://cn.investing.com/currencies/single-currency-crosses",
"Sec-Fetch-Mode": "cors",
"Sec-Fetch-Site": "same-origin",
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/79.0.3945.130 Safari/537.36",
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) "
"Chrome/79.0.3945.130 Safari/537.36",
"X-Requested-With": "XMLHttpRequest",
}
r = requests.get(url, params=params, headers=headers)
temp_df = pd.read_html(r.json()["HTML"])[0].iloc[:, 1:]
temp_df.rename(columns={"名称.1": "简称"}, inplace=True)
temp_df["pids"] = [item[:-1] for item in r.json()["pids"]]
name_code_dict_two = dict(
zip(
temp_df["名称"].tolist(),
[
item.lower().replace("/", "-")
for item in temp_df["简称"].tolist()
],
)
)
name_code_dict_one.update(name_code_dict_two)
temp_df = pd.DataFrame.from_dict(
name_code_dict_one, orient="index"
).reset_index()
temp_df.columns = ["name", "code"]
return temp_df


def currency_pair_map(symbol: str = "美元") -> pd.DataFrame:
"""
指定货币的所有可获取货币对的数据
https://cn.investing.com/currencies/cny-jmd
:param symbol: 指定货币
:type symbol: str
:return: 指定货币的所有可获取货币对的数据
:rtype: pandas.DataFrame
"""
region_code = []
region_name = []

def has_data_sml_id_but_no_id(tag):
return tag.has_attr("data-sml-id") and not tag.has_attr("title")

tqdm = get_tqdm()
for region_id in tqdm(["4", "1", "8", "7", "6"], leave=False):
url = "https://cn.investing.com/currencies/Service/region"
params = {"region_ID": region_id, "currency_ID": "false"}
headers = {
"Accept": "application/json, text/javascript, */*; q=0.01",
# "Accept-Encoding": "gzip, deflate, br",
"Accept-Language": "zh-CN,zh;q=0.9,en;q=0.8",
"Cache-Control": "no-cache",
"Connection": "keep-alive",
"Host": "cn.investing.com",
"Pragma": "no-cache",
"Referer": "https://cn.investing.com/currencies/single-currency-crosses",
"Sec-Fetch-Mode": "cors",
"Sec-Fetch-Site": "same-origin",
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/79.0.3945.130 Safari/537.36",
"X-Requested-With": "XMLHttpRequest",
}

r = requests.get(url, params=params, headers=headers)
soup = BeautifulSoup(r.text, "lxml")
soup = BeautifulSoup(r.text, features="lxml")
region_code.extend(
[
item["continentid"] + "-" + region_id
for item in soup.find_all(has_data_sml_id_but_no_id)
]
)
region_name.extend(
[
item.find("i").text
for item in soup.find_all(has_data_sml_id_but_no_id)
]
[item.find("i").text for item in soup.find_all(has_data_sml_id_but_no_id)]
)

name_id_map = dict(zip(region_name, region_code))
Expand All @@ -313,34 +67,14 @@ def has_data_sml_id_but_no_id(tag):
"currency_ID": name_id_map[symbol].split("-")[0],
}
r = requests.get(url, params=params, headers=headers)
soup = BeautifulSoup(r.text, "lxml")
soup = BeautifulSoup(r.text, features="lxml")

temp_code = [
item["href"].split("/")[-1] for item in soup.find_all("a")
] # need
temp_name = [
item["title"].replace(" ", "-") for item in soup.find_all("a")
]
temp_df = pd.DataFrame([temp_name, temp_code], index=["name", "code"]).T
temp_code = [item["href"].split("/")[-1] for item in soup.find_all("a")] # need
temp_name = [item["title"].replace(" ", "-") for item in soup.find_all("a")]
temp_df = pd.DataFrame(data=[temp_name, temp_code], index=["name", "code"]).T
return temp_df


if __name__ == "__main__":
currency_hist_area_index_name_code_df = currency_hist_area_index_name_code(
symbol="usd-jpy"
)
print(currency_hist_area_index_name_code_df)

currency_pair_map_df = currency_pair_map(symbol="人民币")
print(currency_pair_map_df)

currency_name_code_df = currency_name_code(symbol="cny/dkk")
print(currency_name_code_df)

currency_hist_df = currency_hist(
symbol="usd-jpy",
period="每日",
start_date="20050101",
end_date="20220808",
)
print(currency_hist_df)
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