253 lines
8.5 KiB
Python
253 lines
8.5 KiB
Python
import re
|
|
import io
|
|
import requests
|
|
import demjson
|
|
import pandas as pd
|
|
from bs4 import BeautifulSoup
|
|
from datetime import datetime
|
|
from urllib.parse import quote, urlencode
|
|
from fake_useragent import UserAgent
|
|
|
|
url = {
|
|
"moneywatch": "https://www.marketwatch.com/investing/"
|
|
}
|
|
|
|
|
|
def forex(instrument="eurusd", startdate="2019-01-01", enddate="2021-01-01"):
|
|
startdate = datetime.strptime(startdate, "%Y-%m-%d").strftime("%m/%d/%y")
|
|
enddate = datetime.strptime(enddate, "%Y-%m-%d").strftime("%m/%d/%y")
|
|
df = pd.DataFrame()
|
|
|
|
def _FX(instrument="eurusd", startdate="01/01/2020", enddate="01/01/2021"):
|
|
"""
|
|
https://www.marketwatch.com/investing/
|
|
"""
|
|
tmp_url = url["moneywatch"] + \
|
|
"currency/{}/downloaddatapartial".format(instrument)
|
|
ua = UserAgent(verify_ssl=False)
|
|
request_header = {"User-Agent": ua.random}
|
|
request_params = urlencode({
|
|
"startdate": r"{}".format(startdate),
|
|
"enddate": r"{}".format(enddate),
|
|
"daterange": "d30",
|
|
"frequency": "p1d",
|
|
"csvdownload": "true",
|
|
"downloadpartial": "false",
|
|
"newdates": "false"}, quote_via=quote)
|
|
r = requests.get(tmp_url, params=request_params.replace(
|
|
"%2F", "/").replace("%20", " ").replace("%3A", ":"), headers=request_header)
|
|
data_text = r.content
|
|
df = pd.read_csv(io.StringIO(data_text.decode('utf-8')))
|
|
Date = []
|
|
for i in range(0, len(df)):
|
|
Date.append(datetime.strptime(df["Date"][i], "%m/%d/%Y"))
|
|
|
|
df["Date"] = Date
|
|
return df
|
|
|
|
for i in range(int(startdate[6:10]), int(enddate[6:10])):
|
|
if i == int(startdate[6:10]):
|
|
tmp_startdate = startdate
|
|
else:
|
|
tmp_startdate = "01/01/" + str(i) + " 00:00:00"
|
|
if (i + 1) == int(enddate[6:10]):
|
|
tmp_enddate = enddate
|
|
else:
|
|
tmp_enddate = "01/01/" + str(i + 1) + " 00:00:00"
|
|
|
|
tmp_df = _FX(
|
|
instrument=instrument,
|
|
startdate=tmp_startdate,
|
|
enddate=tmp_enddate)
|
|
if i == int(startdate[6:10]):
|
|
df = tmp_df
|
|
else:
|
|
df = pd.concat([tmp_df, df], axis=0)
|
|
|
|
df = df.reset_index(drop=True)
|
|
return df
|
|
|
|
|
|
def index(instrument="vix", startdate="2019-01-01", enddate="2021-01-01"):
|
|
startdate = datetime.strptime(startdate, "%Y-%m-%d").strftime("%m/%d/%y")
|
|
enddate = datetime.strptime(enddate, "%Y-%m-%d").strftime("%m/%d/%y")
|
|
df = pd.DataFrame()
|
|
|
|
def _index(instrument="vix", startdate="01/01/2020", enddate="01/01/2021"):
|
|
"""
|
|
https://www.marketwatch.com/investing/
|
|
"""
|
|
tmp_url = url["moneywatch"] + \
|
|
"index/{}/downloaddatapartial".format(instrument)
|
|
ua = UserAgent(verify_ssl=False)
|
|
request_header = {"User-Agent": ua.random}
|
|
request_params = urlencode({
|
|
"startdate": r"{}".format(startdate),
|
|
"enddate": r"{}".format(enddate),
|
|
"daterange": "d30",
|
|
"frequency": "p1d",
|
|
"csvdownload": "true",
|
|
"downloadpartial": "false",
|
|
"newdates": "false"}, quote_via=quote)
|
|
r = requests.get(tmp_url, params=request_params.replace(
|
|
"%2F", "/").replace("%20", " ").replace("%3A", ":"), headers=request_header)
|
|
data_text = r.content
|
|
df = pd.read_csv(io.StringIO(data_text.decode('utf-8')))
|
|
Date = []
|
|
for i in range(0, len(df)):
|
|
Date.append(datetime.strptime(df["Date"][i], "%m/%d/%Y"))
|
|
|
|
df["Date"] = Date
|
|
return df
|
|
|
|
for i in range(int(startdate[6:10]), int(enddate[6:10])):
|
|
if i == int(startdate[6:10]):
|
|
tmp_startdate = startdate
|
|
else:
|
|
tmp_startdate = "01/01/" + str(i) + " 00:00:00"
|
|
if (i + 1) == int(enddate[6:10]):
|
|
tmp_enddate = enddate
|
|
else:
|
|
tmp_enddate = "01/01/" + str(i + 1) + " 00:00:00"
|
|
|
|
tmp_df = _index(
|
|
instrument=instrument,
|
|
startdate=tmp_startdate,
|
|
enddate=tmp_enddate)
|
|
if i == int(startdate[6:10]):
|
|
df = tmp_df
|
|
else:
|
|
df = pd.concat([tmp_df, df], axis=0)
|
|
|
|
df = df.reset_index(drop=True)
|
|
return df
|
|
|
|
|
|
def crypto(instrument="btcusd", startdate="2019-01-01", enddate="2021-01-01"):
|
|
startdate = datetime.strptime(startdate, "%Y-%m-%d").strftime("%m/%d/%y")
|
|
enddate = datetime.strptime(enddate, "%Y-%m-%d").strftime("%m/%d/%y")
|
|
df = pd.DataFrame()
|
|
|
|
def _crypto(
|
|
instrument="btcusd",
|
|
startdate="01/01/2020",
|
|
enddate="01/01/2021"):
|
|
"""
|
|
https://www.marketwatch.com/investing/
|
|
"""
|
|
tmp_url = url["moneywatch"] + \
|
|
"cryptocurrency/{}/downloaddatapartial".format(instrument)
|
|
ua = UserAgent(verify_ssl=False)
|
|
request_header = {"User-Agent": ua.random}
|
|
request_params = urlencode({
|
|
"startdate": r"{}".format(startdate),
|
|
"enddate": r"{}".format(enddate),
|
|
"daterange": "d30",
|
|
"frequency": "p1d",
|
|
"csvdownload": "true",
|
|
"downloadpartial": "false",
|
|
"newdates": "false"}, quote_via=quote)
|
|
r = requests.get(tmp_url, params=request_params.replace(
|
|
"%2F", "/").replace("%20", " ").replace("%3A", ":"), headers=request_header)
|
|
data_text = r.content
|
|
df = pd.read_csv(io.StringIO(data_text.decode('utf-8')))
|
|
Date = []
|
|
for i in range(0, len(df)):
|
|
Date.append(datetime.strptime(df["Date"][i], "%m/%d/%Y"))
|
|
|
|
df["Date"] = Date
|
|
return df
|
|
|
|
for i in range(int(startdate[6:10]), int(enddate[6:10])):
|
|
if i == int(startdate[6:10]):
|
|
tmp_startdate = startdate
|
|
else:
|
|
tmp_startdate = "01/01/" + str(i) + " 00:00:00"
|
|
if (i + 1) == int(enddate[6:10]):
|
|
tmp_enddate = enddate
|
|
else:
|
|
tmp_enddate = "01/01/" + str(i + 1) + " 00:00:00"
|
|
|
|
tmp_df = _crypto(
|
|
instrument=instrument,
|
|
startdate=tmp_startdate,
|
|
enddate=tmp_enddate)
|
|
if i == int(startdate[6:10]):
|
|
df = tmp_df
|
|
else:
|
|
df = pd.concat([tmp_df, df], axis=0)
|
|
|
|
df = df.reset_index(drop=True)
|
|
return df
|
|
|
|
|
|
def stock(
|
|
countrycode="cn",
|
|
instrument="601988",
|
|
startdate="2019-01-01",
|
|
enddate="2021-01-01"):
|
|
startdate = datetime.strptime(startdate, "%Y-%m-%d").strftime("%m/%d/%y")
|
|
enddate = datetime.strptime(enddate, "%Y-%m-%d").strftime("%m/%d/%y")
|
|
df = pd.DataFrame()
|
|
|
|
def _stock(
|
|
countrycode="cn",
|
|
instrument="601988",
|
|
startdate="01/01/2020",
|
|
enddate="01/01/2021"):
|
|
"""
|
|
https://www.marketwatch.com/investing/
|
|
"""
|
|
tmp_url = url["moneywatch"] + \
|
|
"stock/{}/downloaddatapartial".format(instrument)
|
|
ua = UserAgent(verify_ssl=False)
|
|
request_header = {"User-Agent": ua.random}
|
|
request_params = urlencode({
|
|
"startdate": r"{}".format(startdate),
|
|
"enddate": r"{}".format(enddate),
|
|
"daterange": "d30",
|
|
"frequency": "p1d",
|
|
"csvdownload": "true",
|
|
"downloadpartial": "false",
|
|
"newdates": "false",
|
|
"countrycode": "{}".format(countrycode)}, quote_via=quote)
|
|
r = requests.get(tmp_url, params=request_params.replace(
|
|
"%2F", "/").replace("%20", " ").replace("%3A", ":"), headers=request_header)
|
|
data_text = r.content
|
|
df = pd.read_csv(io.StringIO(data_text.decode('utf-8')))
|
|
Date = []
|
|
for i in range(0, len(df)):
|
|
Date.append(datetime.strptime(df["Date"][i], "%m/%d/%Y"))
|
|
|
|
df["Date"] = Date
|
|
return df
|
|
|
|
for i in range(int(startdate[6:10]), int(enddate[6:10])):
|
|
if i == int(startdate[6:10]):
|
|
tmp_startdate = startdate
|
|
else:
|
|
tmp_startdate = "01/01/" + str(i) + " 00:00:00"
|
|
if (i + 1) == int(enddate[6:10]):
|
|
tmp_enddate = enddate
|
|
else:
|
|
tmp_enddate = "01/01/" + str(i + 1) + " 00:00:00"
|
|
|
|
if countrycode == "us":
|
|
countrycode = ""
|
|
tmp_df = _stock(
|
|
countrycode=countrycode,
|
|
instrument=instrument,
|
|
startdate=tmp_startdate,
|
|
enddate=tmp_enddate)
|
|
if i == int(startdate[6:10]):
|
|
df = tmp_df
|
|
else:
|
|
df = pd.concat([tmp_df, df], axis=0)
|
|
|
|
df = df.reset_index(drop=True)
|
|
return df
|
|
|
|
|
|
if __name__ == "__main__":
|
|
data = FX()
|