PIOTEAM-41 yahoo stock import example.
diff --git a/examples/import_yahoo.py b/examples/import_yahoo.py
new file mode 100644
index 0000000..c7ac26f
--- /dev/null
+++ b/examples/import_yahoo.py
@@ -0,0 +1,211 @@
+"""
+Import historical stock data from yahoo finance.
+"""
+
+import argparse
+from datetime import datetime
+import predictionio
+import pytz
+import time
+from pandas.io import data as pdata
+import numpy
+
+EPOCH = datetime(1970, 1, 1, tzinfo=pytz.utc)
+
+SP500_LIST = [
+    "A", "AA", "AAPL", "ABBV", "ABC", "ABT", "ACE", "ACN", "ACT", "ADBE", "ADI",
+    "ADM", "ADP", "ADS", "ADSK", "ADT", "AEE", "AEP", "AES", "AET", "AFL",
+    "AGN", "AIG", "AIV", "AIZ", "AKAM", "ALL", "ALLE", "ALTR", "ALXN", "AMAT",
+    "AME", "AMGN", "AMP", "AMT", "AMZN", "AN", "AON", "APA", "APC", "APD",
+    "APH", "ARG", "ATI", "AVB", "AVP", "AVY", "AXP", "AZO", "BA", "BAC", "BAX",
+    "BBBY", "BBT", "BBY", "BCR", "BDX", "BEAM", "BEN", "BF-B", "BHI", "BIIB",
+    "BK", "BLK", "BLL", "BMS", "BMY", "BRCM", "BRK-B", "BSX", "BTU", "BWA",
+    "BXP", "C", "CA", "CAG", "CAH", "CAM", "CAT", "CB", "CBG", "CBS", "CCE",
+    "CCI", "CCL", "CELG", "CERN", "CF", "CFN", "CHK", "CHRW", "CI", "CINF",
+    "CL", "CLX", "CMA", "CMCSA", "CME", "CMG", "CMI", "CMS", "CNP", "CNX",
+    "COF", "COG", "COH", "COL", "COP", "COST", "COV", "CPB", "CRM", "CSC",
+    "CSCO", "CSX", "CTAS", "CTL", "CTSH", "CTXS", "CVC", "CVS", "CVX", "D",
+    "DAL", "DD", "DE", "DFS", "DG", "DGX", "DHI", "DHR", "DIS", "DISCA", "DLPH",
+    "DLTR", "DNB", "DNR", "DO", "DOV", "DOW", "DPS", "DRI", "DTE", "DTV", "DUK",
+    "DVA", "DVN", "EA", "EBAY", "ECL", "ED", "EFX", "EIX", "EL", "EMC", "EMN",
+    "EMR", "EOG", "EQR", "EQT", "ESRX", "ESS", "ESV", "ETFC", "ETN", "ETR",
+    "EW", "EXC", "EXPD", "EXPE", "F", "FAST", "FB", "FCX", "FDO", "FDX", "FE",
+    "FFIV", "FIS", "FISV", "FITB", "FLIR", "FLR", "FLS", "FMC", "FOSL", "FOXA",
+    "FRX", "FSLR", "FTI", "FTR", "GAS", "GCI", "GD", "GE", "GGP", "GHC", "GILD",
+    "GIS", "GLW", "GM", "GMCR", "GME", "GNW", "GOOG", "GOOGL", "GPC", "GPS",
+    "GRMN", "GS", "GT", "GWW", "HAL", "HAR", "HAS", "HBAN", "HCBK", "HCN",
+    "HCP", "HD", "HES", "HIG", "HOG", "HON", "HOT", "HP", "HPQ", "HRB", "HRL",
+    "HRS", "HSP", "HST", "HSY", "HUM", "IBM", "ICE", "IFF", "IGT", "INTC",
+    "INTU", "IP", "IPG", "IR", "IRM", "ISRG", "ITW", "IVZ", "JBL", "JCI", "JEC",
+    "JNJ", "JNPR", "JOY", "JPM", "JWN", "K", "KEY", "KIM", "KLAC", "KMB", "KMI",
+    "KMX", "KO", "KORS", "KR", "KRFT", "KSS", "KSU", "L", "LB", "LEG", "LEN",
+    "LH", "LLL", "LLTC", "LLY", "LM", "LMT", "LNC", "LO", "LOW", "LRCX", "LSI",
+    "LUK", "LUV", "LYB", "M", "MA", "MAC", "MAR", "MAS", "MAT", "MCD", "MCHP",
+    "MCK", "MCO", "MDLZ", "MDT", "MET", "MHFI", "MHK", "MJN", "MKC", "MMC",
+    "MMM", "MNST", "MO", "MON", "MOS", "MPC", "MRK", "MRO", "MS", "MSFT", "MSI",
+    "MTB", "MU", "MUR", "MWV", "MYL", "NBL", "NBR", "NDAQ", "NE", "NEE", "NEM",
+    "NFLX", "NFX", "NI", "NKE", "NLSN", "NOC", "NOV", "NRG", "NSC", "NTAP",
+    "NTRS", "NU", "NUE", "NVDA", "NWL", "NWSA", "OI", "OKE", "OMC", "ORCL",
+    "ORLY", "OXY", "PAYX", "PBCT", "PBI", "PCAR", "PCG", "PCL", "PCLN", "PCP",
+    "PDCO", "PEG", "PEP", "PETM", "PFE", "PFG", "PG", "PGR", "PH", "PHM", "PKI",
+    "PLD", "PLL", "PM", "PNC", "PNR", "PNW", "POM", "PPG", "PPL", "PRGO", "PRU",
+    "PSA", "PSX", "PVH", "PWR", "PX", "PXD", "QCOM", "QEP", "R", "RAI", "RDC",
+    "REGN", "RF", "RHI", "RHT", "RIG", "RL", "ROK", "ROP", "ROST", "RRC", "RSG",
+    "RTN", "SBUX", "SCG", "SCHW", "SE", "SEE", "SHW", "SIAL", "SJM", "SLB",
+    "SLM", "SNA", "SNDK", "SNI", "SO", "SPG", "SPLS", "SRCL", "SRE", "STI",
+    "STJ", "STT", "STX", "STZ", "SWK", "SWN", "SWY", "SYK", "SYMC", "SYY", "T",
+    "TAP", "TDC", "TE", "TEG", "TEL", "TGT", "THC", "TIF", "TJX", "TMK", "TMO",
+    "TRIP", "TROW", "TRV", "TSCO", "TSN", "TSO", "TSS", "TWC", "TWX", "TXN",
+    "TXT", "TYC", "UNH", "UNM", "UNP", "UPS", "URBN", "USB", "UTX", "V", "VAR",
+    "VFC", "VIAB", "VLO", "VMC", "VNO", "VRSN", "VRTX", "VTR", "VZ", "WAG",
+    "WAT", "WDC", "WEC", "WFC", "WFM", "WHR", "WIN", "WLP", "WM", "WMB", "WMT",
+    "WU", "WY", "WYN", "WYNN", "X", "XEL", "XL", "XLNX", "XOM", "XRAY", "XRX",
+    "XYL", "YHOO", "YUM", "ZION", "ZMH", "ZTS"]
+
+ETF_LIST = ["QQQ", "SPY", "XLY", "XLP", "XLE", "XLF", "XLV", 
+    "XLI", "XLB", "XLK", "XLU"]
+
+
+def since_epoch(dt):
+  return (dt - EPOCH).total_seconds()
+
+
+def import_data(client, app_id, ticker, start_time, end_time, event_time):
+  print "Importing:", ticker, start_time, end_time
+
+  try:
+    df = pdata.DataReader(ticker, 'yahoo', start_time, end_time)
+    print "Extracted:", df.index[0], df.index[-1]
+  except IOError, ex:
+    print ex
+    print "Data not exist. Returning"
+    return
+
+  # assume we only extract US data
+  eastern = pytz.timezone('US/Eastern')
+
+  columns = [
+      ('Open', 'open'),
+      ('High', 'high'),
+      ('Low', 'low'),
+      ('Close', 'close'),
+      ('Volume', 'volume'),
+      ('Adj Close', 'adjclose')]
+
+  yahoo_data = dict()
+  yahoo_data['ticker'] = ticker
+  yahoo_data['t'] = [
+      # hour=16 to indicate market close time
+      since_epoch(eastern.localize(date_.to_pydatetime().replace(hour=16)))
+      for date_ in df.index]
+
+  for column in columns:
+    yahoo_data[column[1]] = map(numpy.asscalar, df[column[0]].values)
+
+  properties = {'yahoo': yahoo_data}
+
+  data = {
+      'event': '$set',
+      'entityType': 'yahoo',
+      'entityId': ticker,
+      'properties': properties,
+      'appId': app_id,
+      'eventTime': event_time.replace(tzinfo=pytz.utc).isoformat(),
+      }
+
+  response = client.create_event(data)
+  print(response)
+
+
+def import_all(app_id):
+  """This method import all SP500 stocks and some SPDR ETFs."""
+  time_slices = [
+      (datetime(1999, 1, 1), datetime(2004, 1, 1), datetime(2004, 1, 2)),
+      (datetime(2003, 12, 1), datetime(2009, 1, 1), datetime(2009, 1, 2)),
+      (datetime(2008, 12, 1), datetime(2014, 9, 1), datetime(2014, 9, 2)),
+      ]
+
+  url = 'http://localhost:7070'
+  client = predictionio.EventClient(app_id=app_id, threads=1, url=url)
+
+  tickers = SP500_LIST + ETF_LIST 
+
+  for ticker in tickers:
+    for time_slice in time_slices:
+      import_data(client, app_id, ticker, 
+          time_slice[0], time_slice[1], time_slice[2])
+
+
+def import_data_with_gaps(app_id):
+  """This method import data with time gaps. 
+  
+  Data imported by this method is used by stock engine, it demonsrates how it
+  can handle time series data with gaps.
+  """ 
+
+  # time_slices is discontinuted
+  # startTime, endTime, eventDate
+  time_slices = [
+      (datetime(2013, 12, 1), datetime(2014, 2, 1), datetime(2014, 2, 2)),
+      (datetime(2014, 1, 1), datetime(2014, 1, 20), datetime(2014, 2, 10)),
+      (datetime(2014, 1, 10), datetime(2014, 2, 20), datetime(2014, 2, 28)),
+      (datetime(2014, 2, 10), datetime(2014, 3, 31), datetime(2014, 4, 2)),
+      (datetime(2014, 5, 1), datetime(2014, 6, 15), datetime(2014, 6, 20)),
+      (datetime(2014, 6, 1), datetime(2014, 7, 1), datetime(2014, 7, 15)),
+      ]
+
+  tickers = ['SPY', 'AAPL', 'IBM', 'MSFT']
+ 
+  url = 'http://localhost:7070'
+  client = predictionio.EventClient(app_id=app_id, threads=1, url=url)
+
+  for ticker in tickers:
+    for time_slice in time_slices:
+      import_data(client, app_id, ticker, 
+          time_slice[0], time_slice[1], time_slice[2])
+
+  # below are data with holes
+  time_slices = [
+      (datetime(2014, 1, 1), datetime(2014, 1, 20), datetime(2014, 2, 10)),
+      (datetime(2014, 2, 10), datetime(2014, 3, 31), datetime(2014, 4, 2)),
+      (datetime(2014, 6, 1), datetime(2014, 7, 1), datetime(2014, 7, 15)),
+      ]
+
+  tickers = ['AMZN']
+  for ticker in tickers:
+    for time_slice in time_slices:
+      import_data(client, app_id, ticker, 
+          time_slice[0], time_slice[1], time_slice[2])
+
+  time_slices = [
+      (datetime(2014, 1, 10), datetime(2014, 2, 20), datetime(2014, 2, 28)),
+      (datetime(2014, 2, 10), datetime(2014, 3, 31), datetime(2014, 4, 2)),
+      ]
+  tickers = ['FB']
+  for ticker in tickers:
+    for time_slice in time_slices:
+      import_data(client, app_id, ticker, 
+          time_slice[0], time_slice[1], time_slice[2])
+
+
+def import_one(app_id):
+  """Import TSLA.
+  
+  Import data with from 2014-01-01 until 2014-03-01. event_time specifies when
+  this data is extracted. 
+  """
+  start_time = datetime(2014, 1, 1)
+  end_time = datetime(2014, 3, 1)
+  event_time = datetime(2014, 9, 1)
+  ticker = 'TSLA'
+ 
+  url = 'http://localhost:7070'
+  client = predictionio.EventClient(app_id=app_id, threads=1, url=url)
+
+  import_data(client, app_id, ticker, start_time, end_time, event_time)
+
+
+if __name__ == '__main__':
+  #import_all(app_id=2)
+  #import_data_with_gaps(app_id=1)
+  import_one(app_id=1)
diff --git a/predictionio/__init__.py b/predictionio/__init__.py
index 3d8eca1..a148b43 100644
--- a/predictionio/__init__.py
+++ b/predictionio/__init__.py
@@ -147,7 +147,6 @@
     self.app_id = app_id
 
   def acreate_event(self, data):
-    print data
     path = "/events.json"
     request = AsyncRequest("POST", path, **data)
     request.set_rfunc(self._acreate_resp)