Merge pull request #6559 from freqtrade/short_docs

Futures strategy migration docs

freqtrade/strategy/interface.py

@@ -62,7 +62,8 @@ class IStrategy(ABC, HyperStrategyMixin):
     # Default to version 2
     # Version 1 is the initial interface without metadata dict
     # Version 2 populate_* include metadata dict
-    INTERFACE_VERSION: int = 2
+    # Version 3 - First version with short and leverage support
+    INTERFACE_VERSION: int = 3
 
     _populate_fun_len: int = 0
     _buy_fun_len: int = 0

freqtrade/templates/base_strategy.py.j2

@@ -35,7 +35,7 @@ class {{ strategy }}(IStrategy):
     """
     # Strategy interface version - allow new iterations of the strategy interface.
     # Check the documentation or the Sample strategy to get the latest version.
-    INTERFACE_VERSION = 2
+    INTERFACE_VERSION = 3
 
     # Optimal timeframe for the strategy.
     timeframe = '5m'

freqtrade/templates/sample_short_strategy.py

@@ -36,7 +36,7 @@ class SampleShortStrategy(IStrategy):
     """
     # Strategy interface version - allow new iterations of the strategy interface.
     # Check the documentation or the Sample strategy to get the latest version.
-    INTERFACE_VERSION = 2
+    INTERFACE_VERSION = 3
 
     # Can this strategy go short?
     can_short: bool = True

freqtrade/templates/sample_strategy.py

@@ -35,7 +35,7 @@ class SampleStrategy(IStrategy):
     """
     # Strategy interface version - allow new iterations of the strategy interface.
     # Check the documentation or the Sample strategy to get the latest version.
-    INTERFACE_VERSION = 2
+    INTERFACE_VERSION = 3
 
     # Can this strategy go short?
     can_short: bool = False

freqtrade/templates/strategy_analysis_example.ipynb

@@ -110,7 +110,7 @@
    "outputs": [],
    "source": [
     "# Report results\n",
-    "print(f\"Generated {df['buy'].sum()} buy signals\")\n",
+    "print(f\"Generated {df['enter_long'].sum()} entry signals\")\n",
     "data = df.set_index('date', drop=False)\n",
     "data.tail()"
    ]
@@ -348,7 +348,7 @@
     "hist_data = [trades.profit_ratio]\n",
     "group_labels = ['profit_ratio']  # name of the dataset\n",
     "\n",
-    "fig = ff.create_distplot(hist_data, group_labels,bin_size=0.01)\n",
+    "fig = ff.create_distplot(hist_data, group_labels, bin_size=0.01)\n",
     "fig.show()\n"
    ]
   },