Refactor app initialization

Author: MDUYN

README.md

@@ -38,6 +38,8 @@ The following algorithm connects to binance and buys BTC every 5 seconds. It als
 
 ```python
 import logging
+import logging.config
+
 from investing_algorithm_framework import create_app, PortfolioConfiguration, \
     TimeUnit, CCXTOHLCVMarketDataSource, Algorithm, \
     CCXTTickerMarketDataSource, MarketCredential, DEFAULT_LOGGING_CONFIG
@@ -59,7 +61,6 @@ bitvavo_btc_eur_ticker = CCXTTickerMarketDataSource(
     symbol="BTC/EUR",
 )
 app = create_app()
-algorithm = Algorithm()
 # Bitvavo market credentials are read from .env file
 app.add_market_credential(MarketCredential(market="bitvavo"))
 app.add_portfolio_configuration(
@@ -69,18 +70,16 @@ app.add_portfolio_configuration(
         initial_balance=400
     )
 )
-app.add_algorithm(algorithm)
 
 # Run every two hours and register the data sources
-@algorithm.strategy(
+@app.strategy(
     time_unit=TimeUnit.HOUR,
     interval=2,
     market_data_sources=[bitvavo_btc_eur_ticker, bitvavo_btc_eur_ohlcv_2h]
 )
 def perform_strategy(algorithm: Algorithm, market_data: dict):
     # Access the data sources with the indentifier
     polars_df = market_data["BTC-ohlcv"]
-
     # Convert the polars dataframe to a pandas dataframe
     pandas_df = polars_df.to_pandas()
     ticker_data = market_data["BTC-ticker"]
@@ -91,13 +90,19 @@ def perform_strategy(algorithm: Algorithm, market_data: dict):
     closed_trades = algorithm.get_closed_trades()
 
     # Create a buy oder
-    algorithm.create_limit_order(
+    trade = algorithm.create_limit_order(
         target_symbol="BTC/EUR",
         order_side="buy",
         amount=0.01,
         price=ticker_data["ask"],
     )
 
+    # Add a stop loss percentage of 5%
+    algorithm.add_stop_loss(trade.id, percentage=5)
+
+    # Add a take profit percentage of 10%
+    algorithm.add_take_profit(trade.id, percentage=5)
+
     # Close a trade
     algorithm.close_trade(trades[0].id)
 

investing_algorithm_framework/app/algorithm.py

@@ -164,6 +164,17 @@ def start(self, number_of_iterations: int = None):
             number_of_iterations=number_of_iterations
         )
 
+    def stop(self) -> None:
+        """
+        Function to stop the algorithm. This function will stop the
+        algorithm by stopping all jobs in the strategy orchestrator
+        service.
+
+        Returns:
+            None
+        """
+        self.strategy_orchestrator_service.stop()
+
     @property
     def name(self):
         return self._name
@@ -186,6 +197,14 @@ def config(self):
         """
         return self.configuration_service.get_config()
 
+    def get_config(self):
+        """
+        Function to get a config instance. This allows users when
+        having access to the algorithm instance also to read the
+        configs of the app.
+        """
+        return self.configuration_service.get_config()
+
     @property
     def description(self):
         """
@@ -1222,7 +1241,7 @@ def get_open_trades(self, target_symbol=None, market=None) -> List[Trade]:
         is specified, the open trades with the specified market will be
         returned.
 
-        Parameters:
+        Args:
             target_symbol: The symbol of the asset
             market: The market of the asset
 
@@ -1238,7 +1257,7 @@ def close_trade(self, trade, market=None, precision=None) -> None:
         parameter is specified, the amount of the order will be rounded
         down to the specified precision.
 
-        Parameters:
+        Args:
             trade: Trade - The trade to close
             market: str - The market of the trade
             precision: float - The precision of the amount
@@ -1400,3 +1419,9 @@ def get_unfilled_sell_value(self):
             [order.get_amount() * order.get_price()
              for order in pending_orders]
         )
+
+    def get_trade_service(self):
+        return self.trade_service
+
+    def get_market_data_source_service(self):
+        return self._market_data_source_service