diff --git a/doc/examples/Multiple Time Frames.py b/doc/examples/Multiple Time Frames.py
index 8a93348..59fb4ea 100644
--- a/doc/examples/Multiple Time Frames.py	
+++ b/doc/examples/Multiple Time Frames.py	
@@ -5,7 +5,7 @@
 #       extension: .py
 #       format_name: light
 #       format_version: '1.3'
-#       jupytext_version: 0.8.6
+#       jupytext_version: 1.0.2
 #   kernelspec:
 #     display_name: Python 3
 #     language: python
@@ -51,6 +51,8 @@ def RSI(array, n):
     loss[loss > 0] = 0
     rs = gain.ewm(n).mean() / loss.abs().ewm(n).mean()
     return 100 - 100 / (1 + rs)
+
+
 # -
 
 # The strategy roughly goes like this:
diff --git a/doc/examples/Parameter Heatmap.py b/doc/examples/Parameter Heatmap.py
index 494da05..b505955 100644
--- a/doc/examples/Parameter Heatmap.py	
+++ b/doc/examples/Parameter Heatmap.py	
@@ -6,7 +6,7 @@
 #       extension: .py
 #       format_name: light
 #       format_version: '1.3'
-#       jupytext_version: 0.8.6
+#       jupytext_version: 1.0.2
 #   kernelspec:
 #     display_name: Python 3
 #     language: python
@@ -83,6 +83,8 @@ class Sma4Cross(Strategy):
                 crossover(self.data.Close, self.sma_exit)):
                 
                 self.position.close()
+
+
 # -
 
 # It's not a robust strategy, but we can optimize it. Let's optimize our strategy on Google stock data.
diff --git a/doc/examples/Quick Start User Guide.py b/doc/examples/Quick Start User Guide.py
index b6c689e..8d29c3b 100644
--- a/doc/examples/Quick Start User Guide.py	
+++ b/doc/examples/Quick Start User Guide.py	
@@ -6,7 +6,7 @@
 #       extension: .py
 #       format_name: light
 #       format_version: '1.3'
-#       jupytext_version: 0.8.6
+#       jupytext_version: 1.0.2
 #   kernelspec:
 #     display_name: Python 3
 #     language: python
@@ -58,6 +58,8 @@ def SMA(values, n):
     each step taking into account `n` previous values.
     """
     return pd.Series(values).rolling(n).mean()
+
+
 # -
 
 # Note, this is the exact same helper function as the one used in the project unit tests, so we could just import that instead.
@@ -99,6 +101,8 @@ class SmaCross(Strategy):
         # Else, if sma1 crosses below sma2, sell it
         elif crossover(self.sma2, self.sma1):
             self.sell()
+
+
 # -
 
 # In `init()` as well as in `next()`, the data the strategy is simulated on is available as an instance variable
diff --git a/doc/examples/Strategies Library.py b/doc/examples/Strategies Library.py
index 04c7965..2914622 100644
--- a/doc/examples/Strategies Library.py	
+++ b/doc/examples/Strategies Library.py	
@@ -5,7 +5,7 @@
 #       extension: .py
 #       format_name: light
 #       format_version: '1.3'
-#       jupytext_version: 0.8.6
+#       jupytext_version: 1.0.2
 #   kernelspec:
 #     display_name: Python 3
 #     language: python
@@ -79,6 +79,8 @@ class SmaCross(SignalStrategy,
         # Set trailing stop-loss to 4x ATR
         # using the method provided by TrailingStrategy
         self.set_trailing_sl(4)
+
+
 # -
 
 # Note, since the strategies in _lib_ may require their own intialization and next-tick logic, be sure to **always call `super().init()` and `super().next()` in your overridden methods**.
diff --git a/setup.py b/setup.py
index a48f4af..7bfa54c 100644
--- a/setup.py
+++ b/setup.py
@@ -38,7 +38,7 @@ if __name__ == '__main__':
         extras_require={
             'doc': [
                 'pdoc3',
-                'jupytext >= 0.7.0',
+                'jupytext >= 1.0.2',
                 'nbconvert',
                 'ipykernel',       # for nbconvert
                 'jupyter_client',  # for nbconvert