update moneywatch

CEDA/Market/market.py

@@ -1,14 +1,20 @@
+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 = {
-    "dukascopy": "http://data.uicstat.com/api_1.0"
+    "dukascopy": "http://data.uicstat.com/api_1.0",
+    "moneywatch": "https://www.marketwatch.com/investing/"
 }
 
 
-def market_data(
+def dukascopy(
         instrument: str,
         startdate: str,
         enddate: str,
@@ -44,9 +50,34 @@ def market_data(
     ]
     return df
 
+def currency_list(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()
+    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, 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
+
 
 if __name__ == "__main__":
-    data = market_data(instrument="eurusd",
+    data = dukascopy(instrument="eurusd",
                        startdate="2020-01-01",
                        enddate="2021-01-01",
                        timeframe="d1",

setup.py

@@ -22,6 +22,7 @@ setup(
         "demjson>=2.2.4",
         "html5lib>=1.0.1",
         "xlrd==1.2.0",
+        "bs4"
     ],
     license = "MIT",
     classifiers=[