Housekeeping and documentation

catalyst/examples/buy_low_sell_high_neo_with_interface.py

@@ -154,8 +154,8 @@ def analyze(context, stats):
 #     exchange_name='bittrex,bitfinex',
 #     live=True,
 #     algo_namespace=algo_namespace,
-#     base_currency='eth',
-#     live_graph=True
+#     base_currency='btc',
+#     live_graph=False
 # )
 run_algorithm(
     capital_base=250,

catalyst/exchange/exchange.py

@@ -437,6 +437,7 @@ class Exchange:
             data_frequency=frequency,
             assets=assets,
             bar_count=bar_count,
+            end_dt=end_dt
         )
 
         series = dict()
@@ -495,18 +496,6 @@ class Exchange:
                 portfolio.portfolio_value = \
                     portfolio.positions_value + portfolio.cash
 
-    @abstractmethod
-    def get_balances(self):
-        """
-        Retrieve wallet balances for the exchange
-        :return balances: A dict of currency => available balance
-        """
-        pass
-
-    @abstractmethod
-    def create_order(self, asset, amount, is_buy, style):
-        pass
-
     def order(self, asset, amount, limit_price=None, stop_price=None,
               style=None):
         """Place an order.
@@ -592,6 +581,34 @@ class Exchange:
         else:
             return None
 
+    # The methods below must be implemented for each exchange.
+    @abstractmethod
+    def get_balances(self):
+        """
+        Retrieve wallet balances for the exchange
+        :return balances: A dict of currency => available balance
+        """
+        pass
+
+    @abstractmethod
+    def create_order(self, asset, amount, is_buy, style):
+        """
+        Place an order on the exchange.
+
+        :param asset : Asset
+            The asset that this order is for.
+        :param amount : int
+            The amount of shares to order. If ``amount`` is positive, this is
+            the number of shares to buy or cover. If ``amount`` is negative,
+            this is the number of shares to sell or short.
+        :param style : ExecutionStyle
+            The execution style for the order.
+        :param is_buy: boolean
+            Is it a buy order?
+        :return:
+        """
+        pass
+
     @abstractmethod
     def get_open_orders(self, asset):
         """Retrieve all of the current open orders.
@@ -649,12 +666,28 @@ class Exchange:
         Retrieve OHLCV candles for the given assets
 
         :param data_frequency:
-        :param assets:
-        :param end_dt:
+            The candle frequency: minute, 5-minute or daily
+        :param assets: list[TradingPair]
+            The targeted assets.
         :param bar_count:
-        :param limit:
-        :param start_date:
-        :return:
+            The number of bar desired. (default 1)
+        :param end_dt: datetime, optional
+            The last bar date.
+        :param start_date: datetime, optional
+            The first bar date.
+
+        :return dict[TradingPair, dict[str, Object]]: OHLCV data
+            A dictionary of OHLCV candles. Each TradingPair instance is
+            mapped to a list of dictionaries with this structure:
+                open: float
+                high: float
+                low: float
+                close: float
+                volume: float
+                last_traded: datetime
+
+            See definition here:
+                http://www.investopedia.com/terms/o/ohlcchart.asp
         """
         pass
 

catalyst/exchange/exchange_bundle.py

@@ -32,33 +32,6 @@ def fetch_candles_chunk(exchange, assets, data_frequency, end_dt, bar_count):
     )
     return candles
 
-    # series = dict()
-    #
-    # for asset in assets:
-    #     asset_candles = candles[asset]
-    #
-    #     candle_start_dt = None
-    #     candle_end_dt = None
-    #     for candle in asset_candles:
-    #         last_traded = candle['last_traded']
-    #
-    #         if candle_start_dt is None or candle_start_dt > last_traded:
-    #             candle_start_dt = last_traded
-    #
-    #         if candle_end_dt is None or candle_end_dt < last_traded:
-    #             candle_end_dt = last_traded
-    #
-    #
-    #     asset_df = pd.DataFrame(asset_candles)
-    #     if not asset_df.empty:
-    #         asset_df.set_index('last_traded', inplace=True, drop=True)
-    #         asset_df.sort_index(inplace=True)
-    #         asset_df = asset_df.resample('1T').ffill()
-    #
-    #         series[asset] = asset_df
-    #
-    # return series
-
 
 def process_bar_data(exchange, assets, writer, data_frequency,
                      show_progress, start, end):
@@ -117,9 +90,15 @@ def process_bar_data(exchange, assets, writer, data_frequency,
             chunk_end = chunk['end']
             chunk_start = chunk_end - timedelta(minutes=chunk['bar_count'])
 
+            chunk_assets = []
+            for asset in assets:
+                if asset.start_date <= chunk_end:
+                    chunk_assets.append(asset)
+
+            # TODO: ensure correct behavior for assets starting in the chunk
             candles = fetch_candles_chunk(
                 exchange=exchange,
-                assets=assets,
+                assets=chunk_assets,
                 data_frequency=frequency,
                 end_dt=chunk_end,
                 bar_count=chunk['bar_count']
@@ -133,7 +112,7 @@ def process_bar_data(exchange, assets, writer, data_frequency,
                 if not asset_candles:
                     log.debug(
                         'no data: {symbols} on {exchange}, date {end}'.format(
-                            symbols=assets,
+                            symbols=chunk_assets,
                             exchange=exchange.name,
                             end=chunk_end
                         )

catalyst/utils/run_algo.py

@@ -143,7 +143,6 @@ def _run(handle_data,
     if exchange_name is None:
         raise ValueError('Please specify at least one exchange.')
 
-
     exchange_list = [x.strip().lower() for x in exchange.split(',')]
 
     exchanges = dict()
@@ -170,6 +169,7 @@ def _run(handle_data,
                 base_currency=base_currency,
                 portfolio=portfolio
             )
+
         elif exchange_name == 'bittrex':
             exchanges[exchange_name] = Bittrex(
                 key=exchange_auth['key'],
@@ -177,17 +177,11 @@ def _run(handle_data,
                 base_currency=base_currency,
                 portfolio=portfolio
             )
+
         else:
             raise ExchangeNotFoundError(exchange_name=exchange_name)
 
     open_calendar = get_calendar('OPEN')
-    sim_params = create_simulation_parameters(
-        start=start,
-        end=end,
-        capital_base=capital_base,
-        data_frequency=data_frequency,
-        emission_rate=data_frequency,
-    )
 
     env = TradingEnvironment(
         environ=environ,
@@ -274,9 +268,17 @@ def _run(handle_data,
 
         data = DataPortalExchangeBacktest(
             exchanges=exchanges,
-            asset_finder=env.asset_finder,
+            asset_finder=None,
             trading_calendar=open_calendar,
-            first_trading_day=start,
+            first_trading_day=None,
+        )
+
+        sim_params = create_simulation_parameters(
+            start=start,
+            end=end,
+            capital_base=capital_base,
+            data_frequency=data_frequency,
+            emission_rate=data_frequency,
         )
 
         algorithm_class = partial(