Merge branch 'main' into dependabot/pip/tqdm-4.66.3

.flake8

@@ -0,0 +1,4 @@
+[flake8]
+exclude =
+    investing_algorithm_framework/domain/utils/backtesting.py
+    examples

.github/workflows/test.yml

@@ -34,7 +34,7 @@ jobs:
       #----------------------------------------------
       - run: python -m pip install black flake8 isort
       - run: |
-          flake8 ./investing_algorithm_framework --exclude="investing_algorithm_framework/domain/utils/backtesting.py"
+          flake8 ./investing_algorithm_framework
   test:
     needs: linting
     strategy:

__init__.py

@@ -1 +1 @@
-__version__='v3.6.0'
+__version__ = 'v3.6.0'

examples/backtest_example/algorithm/strategy.py

@@ -2,6 +2,8 @@
 
 from investing_algorithm_framework import TimeUnit, TradingStrategy, \
     Algorithm, OrderSide
+from .data_sources import bitvavo_btc_eur_ohlcv_2h, bitvavo_btc_eur_ticker, \
+    bitvavo_dot_eur_ticker, bitvavo_dot_eur_ohlcv_2h
 
 """
 This strategy is based on the golden cross strategy. It will buy when the
@@ -47,10 +49,10 @@ class CrossOverStrategy(TradingStrategy):
     time_unit = TimeUnit.HOUR
     interval = 2
     market_data_sources = [
-        "BTC/EUR-ohlcv",
-        "DOT/EUR-ohlcv",
-        "BTC/EUR-ticker",
-        "DOT/EUR-ticker"
+        bitvavo_dot_eur_ticker,
+        bitvavo_btc_eur_ticker,
+        bitvavo_dot_eur_ohlcv_2h,
+        bitvavo_btc_eur_ohlcv_2h
     ]
     symbols = ["BTC/EUR", "DOT/EUR"]
     fast = 21

examples/backtest_example/run_backtest.py

@@ -5,7 +5,7 @@
     bitvavo_dot_eur_ohlcv_2h, bitvavo_dot_eur_ticker, bitvavo_btc_eur_ticker
 from app import app
 from investing_algorithm_framework import PortfolioConfiguration, \
-    pretty_print_backtest
+    pretty_print_backtest, BacktestDateRange
 
 app.add_algorithm(algorithm)
 app.add_market_data_source(bitvavo_btc_eur_ohlcv_2h)
@@ -26,9 +26,12 @@
 if __name__ == "__main__":
     end_date = datetime(2023, 12, 2)
     start_date = end_date - timedelta(days=100)
+    date_range = BacktestDateRange(
+        start_date=start_date,
+        end_date=end_date
+    )
     backtest_report = app.run_backtest(
         algorithm=algorithm,
-        start_date=start_date,
-        end_date=end_date,
+        backtest_date_range=date_range,
     )
     pretty_print_backtest(backtest_report)

examples/bitvavo_trading_bot/bitvavo.py

@@ -5,15 +5,15 @@
     create_app, PortfolioConfiguration, Algorithm, SYMBOLS, RESOURCE_DIRECTORY
 
 """
-Bitvavo trading bot example with market data sources of bitvavo. 
+Bitvavo trading bot example with market data sources of bitvavo.
 Bitvavo does not requires you to have an API key and secret key to access 
-their market data
-
-If you just want to backtest your strategy, you don't need to 
-add a market credential. If your running your strategy live,
+their market data. If you just want to backtest your strategy, 
+you don't need to add a market credential. If your running your strategy live,
 you need to add a market credential to the app, that accesses your 
 account on bitvavo.
 """
+
+
 # Define your market credential for bitvavo
 bitvavo_market_credential = MarketCredential(
     api_key="<your_api_key>",
@@ -38,10 +38,7 @@
 class BitvavoTradingStrategy(TradingStrategy):
     time_unit = TimeUnit.HOUR
     interval = 2
-    market_data_sources = [
-        "BTC/EUR-ohlcv",
-        "BTC/EUR-ticker"
-    ]
+    market_data_sources = [bitvavo_btc_eur_ohlcv_2h, bitvavo_btc_eur_ticker]
 
     def apply_strategy(self, algorithm, market_data):
         print(market_data["BTC/EUR-ohlcv"])
@@ -75,4 +72,3 @@ def apply_strategy(self, algorithm, market_data):
 
 if __name__ == "__main__":
     app.run()
-

examples/coinbase_trading_bot/coinbase.py

@@ -9,8 +9,9 @@
 and secret key to access their market data. You can create them here:
 https://www.coinbase.com/settings/api
 
-You need to add a market credential to the app, and then add market data sources
-to the app. You can then use the market data sources in your trading strategy.
+You need to add a market credential to the app, and then add market 
+data sources to the app. You can then use the market data 
+sources in your trading strategy.
 """
 # Define your market credential for coinbase
 coinbase_market_credential = MarketCredential(
@@ -36,22 +37,18 @@
 class CoinBaseTradingStrategy(TradingStrategy):
     time_unit = TimeUnit.SECOND
     interval = 5
-    market_data_sources = [
-        "BTC/EUR-ohlcv",
-        "BTC/EUR-ticker"
-    ]
+    market_data_sources = [coinbase_btc_eur_ticker, coinbase_btc_eur_ohlcv_2h]
 
     def apply_strategy(self, algorithm, market_data):
         pass
 
+
 config = {
     SYMBOLS: ["BTC/EUR"],
     RESOURCE_DIRECTORY: os.path.join(os.path.dirname(__file__), "resources")
 }
-
 algorithm = Algorithm()
 algorithm.add_strategy(CoinBaseTradingStrategy)
-
 app = create_app(config=config)
 app.add_algorithm(algorithm)
 app.add_market_credential(coinbase_market_credential)
@@ -65,4 +62,3 @@ def apply_strategy(self, algorithm, market_data):
 
 if __name__ == "__main__":
     app.run()
-

examples/crossover_moving_average_trading_bot/algorithm/strategy.py

@@ -2,6 +2,9 @@
 
 from investing_algorithm_framework import TimeUnit, TradingStrategy, \
     Algorithm, OrderSide
+from .data_sources import bitvavo_btc_eur_ohlcv_2h, bitvavo_btc_eur_ticker, \
+    bitvavo_dot_eur_ticker, bitvavo_dot_eur_ohlcv_2h
+
 
 """
 This strategy is based on the golden cross strategy. It will buy when the
@@ -49,10 +52,10 @@ class CrossOverStrategy(TradingStrategy):
     time_unit = TimeUnit.HOUR
     interval = 2
     market_data_sources = [
-        "BTC/EUR-ohlcv",
-        "DOT/EUR-ohlcv",
-        "BTC/EUR-ticker",
-        "DOT/EUR-ticker"
+        bitvavo_dot_eur_ticker,
+        bitvavo_dot_eur_ohlcv_2h,
+        bitvavo_btc_eur_ticker,
+        bitvavo_btc_eur_ohlcv_2h
     ]
     symbols = ["BTC/EUR", "DOT/EUR"]
 

examples/crossover_moving_average_trading_bot/backtesting.py

@@ -5,7 +5,7 @@
     bitvavo_dot_eur_ohlcv_2h, bitvavo_dot_eur_ticker, bitvavo_btc_eur_ticker
 from app import app
 from investing_algorithm_framework import PortfolioConfiguration, \
-    pretty_print_backtest
+    pretty_print_backtest, BacktestDateRange
 
 app.add_algorithm(algorithm)
 app.add_market_data_source(bitvavo_btc_eur_ohlcv_2h)
@@ -26,10 +26,13 @@
 if __name__ == "__main__":
     end_date = datetime(2023, 12, 2)
     start_date = end_date - timedelta(days=100)
+    date_range = BacktestDateRange(
+        start_date=start_date,
+        end_date=end_date
+    )
     backtest_report = app.run_backtest(
         algorithm=algorithm,
-        start_date=start_date,
-        end_date=end_date,
+        backtest_date_range=date_range,
         pending_order_check_interval="2h",
     )
     pretty_print_backtest(backtest_report)

investing_algorithm_framework/__init__.py

@@ -10,7 +10,8 @@
     TickerMarketDataSource, MarketService, BacktestReportsEvaluation, \
     pretty_print_backtest_reports_evaluation, load_backtest_reports, \
     RESERVED_BALANCES, APP_MODE, AppMode, DATETIME_FORMAT, \
-    load_backtest_report, BacktestDateRange
+    load_backtest_report, BacktestDateRange, create_ema_graph, \
+    create_prices_graph, create_rsi_graph, get_price_efficiency_ratio
 from investing_algorithm_framework.infrastructure import \
     CCXTOrderBookMarketDataSource, CCXTOHLCVMarketDataSource, \
     CCXTTickerMarketDataSource, CSVOHLCVMarketDataSource, \
@@ -67,5 +68,9 @@
     "load_backtest_report",
     "BacktestDateRange",
     "create_trade_exit_markers_chart",
-    "create_trade_entry_markers_chart"
+    "create_trade_entry_markers_chart",
+    "create_ema_graph",
+    "create_prices_graph",
+    "create_rsi_graph",
+    "get_price_efficiency_ratio"
 ]

investing_algorithm_framework/app/algorithm.py

@@ -24,7 +24,8 @@ class is responsible for managing the strategies and executing
 
     :param (optional) name: The name of the algorithm
     :param (optional) description: The description of the algorithm
-    :param (optional) context: The context of the algorithm, for backtest references
+    :param (optional) context: The context of the algorithm,
+    for backtest references
     :param (optional) strategy: A single strategy to add to the algorithm
     :param (optional) data_sources: The list of data sources to
     add to the algorithm