first commit

backend/pricing.py

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+# price history or stream functions
+
+from .config import token, accountID, env
+from oandapyV20 import API
+from oandapyV20.endpoints.instruments import InstrumentsCandles
+from oandapyV20.endpoints.pricing import PricingStream
+import pandas as pd
+import time
+
+api = API(token)
+
+# returns the last 500 OHLCV candles for an instrument
+# maximum count is 500
+# window: M1, M5, M15, H, H4, D, etc.
+def history(instrument, window, collection=False):
+    instrument = instrument
+    data = list()
+    client = API(token)
+    params = {"count": 500, "granularity": window}
+    r = InstrumentsCandles(instrument, params)
+    client.request(r)
+    resp = r.response
+    for candle in resp.get('candles'):
+        dt     = candle['time']
+        Open   = candle['mid']['o']
+        High   = candle['mid']['h']
+        Low    = candle['mid']['l']
+        Close  = candle['mid']['c']
+        Volume = candle['volume']
+        update = [dt, Open, High, Low, Close, Volume]
+        data.append(update)
+    df = pd.DataFrame(data, columns=['dt','Open','High','Low','Close','Volume'])
+    # collect data, useful for research and weekends/holidays when the market isn't open
+    if collection == True:
+        title = 'data/%s_%s_history.csv' % (instrument, window)
+        df.to_csv(title)
+
+    return df
+
+# creates a pricing stream,
+def stream(instrument, window):
+    request_params = {"timeout":100}
+    params = {"instruments":instrument, "granularity":window}
+    api = API(access_token=token,environment=env, request_params=request_params)
+    r = PricingStream(accountID=accountID, params=params)
+
+    while True:
+        try:
+            api.request(r)
+            for R in r.response:
+                time = R['time']
+                ask = R['asks'][0]['price']
+                bid = R['bids'][0]['price']
+                return time, ask, bid
+        except Exception as e:
+            print(e)
+            continue