CEDApy/CEDA/Market/market.py

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import re
import io
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import requests
import demjson
import pandas as pd
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from bs4 import BeautifulSoup
from datetime import datetime
from urllib.parse import quote, urlencode
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from fake_useragent import UserAgent
url = {
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"dukascopy": "http://data.uicstat.com/api_1.0",
"moneywatch": "https://www.marketwatch.com/investing/"
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}
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def dukascopy(
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instrument: str,
startdate: str,
enddate: str,
timeframe: str,
pricetype: str,
volume: bool,
flat: bool):
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tmp_url = url["dukascopy"]
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ua = UserAgent(verify_ssl=False)
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request_header = {"User-Agent": ua.random}
request_params = {
"instrument": "{}".format(instrument),
"startdate": "{}".format(startdate),
"enddate": "{}".format(enddate),
"timeframe": "{}".format(timeframe),
"pricetype": "{}".format(pricetype),
"volume": "{}".format(volume),
"flat": "{}".format(flat)
}
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r = requests.get(tmp_url, params=request_params, headers=request_header)
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data_text = r.text
data_json = demjson.decode(data_text)
df = pd.DataFrame(data_json['result'])
df['timestamp'] = pd.to_datetime(df['timestamp'], unit='ms')
df.columns = [
"Date",
"Open",
"High",
"Low",
"Close",
"Volume"
]
return df
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def FX(instrument = "eurusd", startdate="01/01/2020", enddate = "01/01/2021", long=False):
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"""
https://www.marketwatch.com/investing/
"""
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if long == False:
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
else:
tmp_url = url["moneywatch"] + "currency/{}/downloaddatapartial".format(instrument)
ua = UserAgent(verify_ssl=False)
request_header = {"User-Agent": ua.random}
df = pd.DataFrame()
for i in range(int(startdate[6:10]), int(enddate[6:10])):
tmp_startdate = "01/01/" + str(i) + " 00:00:00"
if i+1 == int(enddate[6:10]):
tmp_enddate = enddate[0:6] + str((i+1)) + " 00:00:00"
else:
tmp_enddate = "01/01" + str((i+1)) + " 00:00:00"
request_params = urlencode({
"startdate": r"{}".format(tmp_startdate),
"enddate": r"{}".format(tmp_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
tmp_df = pd.read_csv(io.StringIO(data_text.decode('utf-8')))
Date = []
for i in range(0, len(tmp_df)):
Date.append(datetime.strptime(tmp_df["Date"][i], "%m/%d/%Y"))
tmp_df["Date"] = Date
if i == int(startdate[6:10]):
df = tmp_df
else:
df = pd.concat([tmp_df, df], axis=0)
df.reset_index(drop=True, inplace = True)
return df
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if __name__ == "__main__":
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data = dukascopy(instrument="eurusd",
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startdate="2020-01-01",
enddate="2021-01-01",
timeframe="d1",
pricetype="bid",
volume=True,
flat=True)
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#https://www.marketwatch.com/investing/currency/eurusd/downloaddatapartial?startdate=01/04/1971 00:00:00&enddate=06/04/2021 00:00:00&daterange=d30&frequency=p1d&csvdownload=true&downloadpartial=false&newdates=false