Merge dc24793 into 033f948

AUTHORS.rst

@@ -3,3 +3,4 @@ Authors
 =======
 
 * Junhao Wang - https://the-hao.com/
+* Dongxu Li - https://leodongxu.wixsite.com/quant

src/bittrade/database/googleclient.py

@@ -0,0 +1,83 @@
+from datetime import datetime
+import pandas as pd
+import requests
+
+def get_price_data(query):
+    '''
+        Connected to google finance, get the price data, return to panda
+        Dataframe.
+    '''
+    r = requests.get(
+        "https://finance.google.com/finance/getprices", params=query,
+    )
+    lines = r.text.splitlines()
+    data = []
+    index = []
+    basetime = 0
+    for price in lines:
+        cols = price.split(",")
+        if cols[0][0] == 'a':
+            basetime = int(cols[0][1:])
+            index.append(datetime.fromtimestamp(basetime))
+            data.append([
+                float(cols[4]), float(cols[2]), float(
+                    cols[3],
+                ), float(cols[1]), int(cols[5]),
+            ])
+        elif cols[0][0].isdigit():
+            date = basetime + (int(cols[0])*int(query['i']))
+            index.append(datetime.fromtimestamp(date))
+            data.append([
+                float(cols[4]), float(cols[2]), float(
+                    cols[3],
+                ), float(cols[1]), int(cols[5]),
+            ])
+    return pd.DataFrame(data, index=index, columns=['Open', 'High', 'Low', 'Close', 'Volume'])
+
+def getClosePrice(target, period='1Y'):
+    '''
+        Get the close price, for every target ticker.
+    '''
+    market, ticker = target.split(':')
+    param = {
+        'q': ticker,  # Bitcoin price in USD
+        'i': "86400",  # Interval size in seconds ("86400" = 1 day intervals)
+        'x': market,
+        'p': period,  # Period (Ex: "4Y" = 4 year)
+    }
+    df = get_price_data(param)
+    price = df[['Close']]
+    price = price.reset_index()
+    price['index'] = price['index'].apply(lambda x: x.date())
+    price.columns = ['Date', ticker]
+    return price
+
+
+def getClosePriceTable(targetList, interpolation=True, period='1Y'):
+    '''
+        Function built on getClosePrice, this function take a list of tickers
+        and return to a panda dataframe, where every column is the closed price
+        for the ticker in the tickerList.
+        The interpolation option: if it is true, NAN value in the table with be
+        fitted using interpolation method.
+        period is the time window we want to trace back.
+    '''
+    df_table = pd.DataFrame()
+    for target in targetList:
+        price = getClosePrice(target, period)
+        if (df_table.shape == (0, 0)):
+            df_table = price
+        else:
+            df_table = pd.merge(df_table, price, how='outer', on='Date')
+    if (interpolation == False):
+        return df_table
+    else:
+        priceTable = df_table
+        # The interpolation method I use here is linear interpolation.
+        priceTable['Date'] = pd.to_datetime(priceTable.Date)
+        priceTable = priceTable.sort_values(by='Date')
+        priceTable = priceTable.interpolate(
+            method='linear', axis=0,
+        ).ffill().bfill()
+        priceTable = priceTable.set_index('Date')
+        return priceTable

src/bittrade/database/googleclient_test.py

@@ -0,0 +1,42 @@
+from googleclient import getClosePriceTable
+# Getting the date we need from google finance API
+# currencyTicker represents the bitcoin price, and the most tradable currency include Japanese Yen, Swiss Franc,
+# Australian Dollar, Canadian Dollar, Indian Rupee, Euro. The price data for these currency are all quoted in dollar.
+currencyTickers = [
+    "CURRENCY:BTCUSD", "CURRENCY:GBPUSD", "CURRENCY:JPYUSD", "CURRENCY:CHFUSD",
+    "CURRENCY:AUDUSD", "CURRENCY:CADUSD", "CURRENCY:INRUSD", "CURRENCY:EURUSD",
+]
+# 24 Most Liquid ETFs:
+# SPDR S&P 500 (SPY)
+# Financial Select Sector SPDR (XLF)
+# Russell 2000 Index Fund Profile (IWM)
+# MSCI Emerging Markets Index Fund (EEM)
+# PowerShares QQQ (QQQ)
+# Vanguard MSCI Emerging Markets ETF (VWO)
+# MSCI EAFE Index Fund (EFA)
+# FTSE China 25 Index Fund (FXI)
+# Industrial Select Sector SPDR Fund (XLI)
+# Daily Small Cap Bear 3X Shares Fundamentals (TZA)
+# Energy Select Sector SPDR Fund (XLE)
+# UltraShort S&P500 (SDS)
+# Silver Trust ETF (SLV)
+# Direxion Daily Financial Bear 3x Shares (FAZ)
+# Market Vectors TR Gold Miners ETF (GDX)
+# MSCI Japan Index Fund (EWJ)
+# UltraPro Short S&P500 (SPXU)
+# MSCI Brazil Index Fund (EWZ)
+# Daily Financial Bull 3X Shares (FAS)
+# VelocityShares Daily 2x VIX Short-Term ETN (TVIX)
+# United States Oil Fund (USO)
+# SPDR Gold Shares (GLD)
+# UltraShort Barclays 20+ Year Treasury (TBT)
+# United States Natural Gas Fund (UNG)
+etfTickers = [
+    "NYSEARCA:XLF", "NYSEARCA:IWM", "NYSEARCA:EEM", "NASDAQ:QQQ", "NYSEARCA:VWO", "NYSEARCA:EFA",
+    "NYSEARCA:FXI", "NYSEARCA:XLI", "NYSEARCA:TZA", "NYSEARCA:XLE", "NYSEARCA:SDS", "NYSEARCA:SLV",
+    "NYSEARCA:FAZ", "NYSEARCA:GDX", "NYSEARCA:EWJ", "NYSEARCA:SPXU", "NYSEARCA:EWZ", "NYSEARCA:FAS",
+    "NASDAQ:TVIX", "NYSEARCA:USO", "NYSEARCA:GLD", "NYSEARCA:TBT", "NYSEARCA:UNG",
+]
+
+table = getClosePriceTable(currencyTickers + etfTickers, interpolation=True, period='1Y')
+print(table.head())