BLD: saving the cumulative_performance only which seems sufficient to keep the algo state. more testing required.

catalyst/exchange/exchange_algorithm.py

@@ -44,9 +44,9 @@ from catalyst.exchange.stats_utils import get_pretty_stats, stats_to_s3, \
     stats_to_algo_folder
 from catalyst.exchange.utils.serialization import portfolio_to_dict
 from catalyst.finance.execution import MarketOrder
-from catalyst.finance.performance import PerformanceTracker
+from catalyst.finance.performance import PerformanceTracker, Position
 from catalyst.finance.performance.period import calc_period_stats
-from catalyst.protocol import Positions, Position
+from catalyst.finance.performance.position import positiondict
 from catalyst.gens.tradesimulation import AlgorithmSimulator
 from catalyst.utils.api_support import api_method
 from catalyst.utils.input_validation import error_keywords, ensure_upper_case
@@ -353,7 +353,7 @@ class ExchangeTradingAlgorithmLive(ExchangeTradingAlgorithmBase):
         self.retry_order = 2
         self.retry_delay = 5
 
-        self.stats_minutes = 10
+        self.stats_minutes = 1
 
         super(ExchangeTradingAlgorithmLive, self).__init__(*args, **kwargs)
 
@@ -446,39 +446,10 @@ class ExchangeTradingAlgorithmLive(ExchangeTradingAlgorithmBase):
             # Unpacking the perf_tracker and positions if available
             perf = get_algo_object(
                 algo_name=self.algo_namespace,
-                key='perf_tracker',
+                key='cumulative_performance',
             )
             if perf is not None:
-                # Unpack the position and converting dict or object
-                p = get_algo_object(
-                    algo_name=self.algo_namespace,
-                    key='portfolio',
-                    how='json',
-                )
-                portfolio = Portfolio()
-                portfolio.capital_used = p['capital_used']
-                portfolio.starting_cash = p['starting_cash']
-                portfolio.portfolio_value = p['portfolio_value']
-                portfolio.pnl = p['pnl']
-                portfolio.returns = p['returns']
-                portfolio.cash = p['cash']
-                portfolio.start_date = p['start_date']
-                portfolio.positions_value = p['positions_value']
-
-                portfolio.positions = positions = Positions()
-                for p in p['positions']:
-                    exchange = self.exchanges[p['exchange']]
-                    asset = exchange.get_asset(p['symbol'])
-                    positions[asset] = Position(
-                        asset=asset,
-                        amount=p['amount'],
-                        cost_basis=p['cost_basis'],
-                        last_sale_price=p['last_sale_price'],
-                        last_sale_date=None,
-                    )
-
-                tracker.period_start = perf['period_start']
-                tracker.position_tracker.positions = portfolio.positions
+                tracker.cumulative_performance = perf
 
         # Call the simulation trading algorithm for side-effects:
         # it creates the perf tracker
@@ -703,15 +674,8 @@ class ExchangeTradingAlgorithmLive(ExchangeTradingAlgorithmBase):
 
         save_algo_object(
             algo_name=self.algo_namespace,
-            key='perf_tracker',
-            obj=self.perf_tracker.to_dict(emission_type=self.data_frequency),
-        )
-        portfolio = portfolio_to_dict(self.portfolio)
-        save_algo_object(
-            algo_name=self.algo_namespace,
-            key='portfolio',
-            obj=portfolio,
-            how='json',
+            key='cumulative_performance',
+            obj=self.perf_tracker.cumulative_performance,
         )
 
         self.current_day = data.current_dt.floor('1D')
@@ -747,7 +711,7 @@ class ExchangeTradingAlgorithmLive(ExchangeTradingAlgorithmBase):
                 stats=get_pretty_stats(
                     stats=self.frame_stats,
                     recorded_cols=recorded_cols,
-                    num_rows=self.stats_minutes
+                    num_rows=self.stats_minutes,
                 )
             ))
 

catalyst/exchange/stats_utils.py

@@ -10,7 +10,7 @@ import pandas as pd
 from catalyst.assets._assets import TradingPair
 
 from catalyst.exchange.exchange_utils import get_algo_folder
-from catalyst.utils.paths import data_root
+from catalyst.utils.paths import data_root, ensure_directory
 
 s3_conn = []
 mailgun = []
@@ -403,7 +403,10 @@ def stats_to_algo_folder(stats, algo_namespace, recorded_cols=None):
     timestr = time.strftime('%Y%m%d')
     folder = get_algo_folder(algo_namespace)
 
-    filename = os.path.join(folder, '{}-{}.csv'.format(timestr, 'frames'))
+    stats_folder = os.path.join(folder, 'stats')
+    ensure_directory(stats_folder)
+
+    filename = os.path.join(stats_folder, '{}.csv'.format(timestr))
 
     with open(filename, 'wb') as handle:
         handle.write(bytes_to_write)

catalyst/exchange/utils/serialization.py

@@ -46,20 +46,23 @@ class ExchangeJSONDecoder(json.JSONDecoder):
 
 
 def portfolio_to_dict(portfolio):
-    positions = portfolio.positions
+    positions = []
     for asset in portfolio.positions:
-        position = portfolio.positions[asset].to_dict()
-
-        position['symbol'] = asset.symbol
-        position['exchange'] = asset.exchange
-        del position['sid']
+        p = portfolio.positions[asset]  # Type: Position
 
+        position = dict(
+            symbol=asset.symbol,
+            exchange=asset.exchange,
+            amount=p.amount,
+            cost_basis=p.cost_basis,
+            last_sale_price=p.last_sale_price,
+            last_sale_date=p.last_sale_date,
+        )
         positions.append(position)
 
     portfolio_dict = vars(portfolio)
-    del portfolio_dict['positions']
-
     portfolio_dict['positions'] = positions
+
     return portfolio_dict