Merge pull request #864 from janga1997/typeHint8

Add type hints to oncebitten, prober, punisher, rand

Author: meatballs

axelrod/strategies/oncebitten.py

@@ -1,5 +1,5 @@
 import random
-from axelrod.actions import Actions
+from axelrod.actions import Actions, Action
 from axelrod.player import Player
 
 C, D = Actions.C, Actions.D
@@ -22,13 +22,13 @@ class OnceBitten(Player):
         'manipulates_state': False
     }
 
-    def __init__(self):
+    def __init__(self) -> None:
         super().__init__()
         self.mem_length = 10
         self.grudged = False
         self.grudge_memory = 0
 
-    def strategy(self, opponent):
+    def strategy(self, opponent: Player) -> Action:
         """
         Begins by playing C, then plays D for mem_length rounds if the opponent
         ever plays D twice in a row.
@@ -72,7 +72,7 @@ class FoolMeOnce(Player):
     }
 
     @staticmethod
-    def strategy(opponent):
+    def strategy(opponent: Player) -> Action:
         if not opponent.history:
             return C
         if opponent.defections > 1:
@@ -98,7 +98,7 @@ class ForgetfulFoolMeOnce(Player):
         'manipulates_state': False
     }
 
-    def __init__(self, forget_probability=0.05):
+    def __init__(self, forget_probability: float=0.05) -> None:
         """
         Parameters
         ----------
@@ -110,7 +110,7 @@ def __init__(self, forget_probability=0.05):
         self._initial = C
         self.forget_probability = forget_probability
 
-    def strategy(self, opponent):
+    def strategy(self, opponent: Player) -> Action:
         r = random.random()
         if not opponent.history:
             return self._initial
@@ -145,7 +145,7 @@ class FoolMeForever(Player):
     }
 
     @staticmethod
-    def strategy(opponent):
+    def strategy(opponent: Player) -> Action:
         if opponent.defections > 0:
             return C
         return D

axelrod/strategies/prober.py

@@ -1,4 +1,4 @@
-from axelrod.actions import Actions
+from axelrod.actions import Actions, Action
 from axelrod.player import Player
 from axelrod.random_ import random_choice
 
@@ -31,7 +31,7 @@ class CollectiveStrategy(Player):
         'manipulates_state': False
     }
 
-    def strategy(self, opponent):
+    def strategy(self, opponent: Player) -> Action:
         turn = len(self.history)
         if turn == 0:
             return C
@@ -61,7 +61,7 @@ class Prober(Player):
         'manipulates_state': False
     }
 
-    def strategy(self, opponent):
+    def strategy(self, opponent: Player) -> Action:
         turn = len(self.history)
         if turn == 0:
             return D
@@ -94,7 +94,7 @@ class Prober2(Player):
         'manipulates_state': False
     }
 
-    def strategy(self, opponent):
+    def strategy(self, opponent: Player) -> Action:
         turn = len(self.history)
         if turn == 0:
             return D
@@ -127,7 +127,7 @@ class Prober3(Player):
         'manipulates_state': False
     }
 
-    def strategy(self, opponent):
+    def strategy(self, opponent: Player) -> Action:
         turn = len(self.history)
         if turn == 0:
             return D
@@ -165,7 +165,7 @@ class Prober4(Player):
         'manipulates_state': False
     }
 
-    def __init__(self):
+    def __init__(self) -> None:
         super().__init__()
         self.init_sequence = [
             C, C, D, C, D, D, D, C, C, D, C, D, C, C, D, C, D, D, C, D
@@ -174,7 +174,7 @@ def __init__(self):
         self.unjust_Ds = 0
         self.turned_defector = False
 
-    def strategy(self, opponent):
+    def strategy(self, opponent: Player) -> Action:
         if not self.history:
             return self.init_sequence[0]
         turn = len(self.history)
@@ -219,7 +219,7 @@ class HardProber(Player):
         'manipulates_state': False
     }
 
-    def strategy(self, opponent):
+    def strategy(self, opponent: Player) -> Action:
         turn = len(self.history)
         if turn == 0:
             return D
@@ -258,7 +258,7 @@ class NaiveProber(Player):
         'manipulates_state': False
     }
 
-    def __init__(self, p=0.1):
+    def __init__(self, p: Player=0.1) -> None:
         """
         Parameters
         ----------
@@ -270,7 +270,7 @@ def __init__(self, p=0.1):
         if (self.p == 0) or (self.p == 1):
             self.classifier['stochastic'] = False
 
-    def strategy(self, opponent):
+    def strategy(self, opponent: Player) -> Action:
         # First move
         if len(self.history) == 0:
             return C
@@ -281,7 +281,7 @@ def strategy(self, opponent):
         choice = random_choice(1 - self.p)
         return choice
 
-    def __repr__(self):
+    def __repr__(self) -> str:
         return "%s: %s" % (self.name, round(self.p, 2))
 
 
@@ -314,11 +314,11 @@ class RemorsefulProber(NaiveProber):
         'manipulates_state': False
     }
 
-    def __init__(self, p=0.1):
+    def __init__(self, p: float=0.1) -> None:
         super().__init__(p)
         self.probing = False
 
-    def strategy(self, opponent):
+    def strategy(self, opponent: Player) -> Action:
         # First move
         if len(self.history) == 0:
             return C

axelrod/strategies/punisher.py

@@ -1,4 +1,4 @@
-from axelrod.actions import Actions
+from axelrod.actions import Actions, Action
 from axelrod.player import Player
 
 C, D = Actions.C, Actions.D
@@ -27,7 +27,7 @@ class Punisher(Player):
         'manipulates_state': False
     }
 
-    def __init__(self):
+    def __init__(self) -> None:
         """
         Initialised the player
         """
@@ -36,7 +36,7 @@ def __init__(self):
         self.grudged = False
         self.grudge_memory = 1
 
-    def strategy(self, opponent):
+    def strategy(self, opponent: Player) -> Action:
         """
         Begins by playing C, then plays D for an amount of rounds proportional
         to the opponents historical '%' of playing D if the opponent ever
@@ -89,14 +89,14 @@ class InversePunisher(Player):
         'manipulates_state': False
     }
 
-    def __init__(self):
+    def __init__(self) -> None:
         super().__init__()
-        self.history = []
+        self.history = [] # type: List[Action]
         self.mem_length = 1
         self.grudged = False
         self.grudge_memory = 1
 
-    def strategy(self, opponent):
+    def strategy(self, opponent: Player) -> Action:
         """
         Begins by playing C, then plays D for an amount of rounds proportional
         to the opponents historical '%' of playing C if the opponent ever plays
@@ -147,7 +147,7 @@ class LevelPunisher(Player):
         'manipulates_state': False
     }
 
-    def strategy(self, opponent):
+    def strategy(self, opponent: Player) -> Action:
         if len(opponent.history) < 10:
             return C
         elif (len(opponent.history) - opponent.cooperations) / len(opponent.history) > 0.2:

axelrod/strategies/rand.py

@@ -1,4 +1,5 @@
 from axelrod.player import Player
+from axelrod.actions import Action
 from axelrod.random_ import random_choice
 
 
@@ -22,7 +23,7 @@ class Random(Player):
         'manipulates_state': False
     }
 
-    def __init__(self, p=0.5):
+    def __init__(self, p: float=0.5) -> None:
         """
         Parameters
         ----------
@@ -39,8 +40,8 @@ def __init__(self, p=0.5):
         if p in [0, 1]:
             self.classifier['stochastic'] = False
 
-    def strategy(self, opponent):
+    def strategy(self, opponent: Player) -> Action:
         return random_choice(self.p)
 
-    def __repr__(self):
+    def __repr__(self) -> str:
         return "%s: %s" % (self.name, round(self.p, 2))

type_tests.sh

@@ -21,16 +21,20 @@ mypy --ignore-missing-imports --follow-imports skip axelrod/strategies/cycler.py
 mypy --ignore-missing-imports --follow-imports skip axelrod/strategies/darwin.py
 mypy --ignore-missing-imports --follow-imports skip axelrod/strategies/defector.py
 mypy --ignore-missing-imports --follow-imports skip axelrod/strategies/forgiver.py
+mypy --ignore-missing-imports --follow-imports skip axelrod/strategies/geller.py
 mypy --ignore-missing-imports --follow-imports skip axelrod/strategies/gradualkiller.py
 mypy --ignore-missing-imports --follow-imports skip axelrod/strategies/grudger.py
 mypy --ignore-missing-imports --follow-imports skip axelrod/strategies/grumpy.py
 mypy --ignore-missing-imports --follow-imports skip axelrod/strategies/handshake.py
+mypy --ignore-missing-imports --follow-imports skip axelrod/strategies/hunter.py
 mypy --ignore-missing-imports --follow-imports skip axelrod/strategies/inverse.py
 mypy --ignore-missing-imports --follow-imports skip axelrod/strategies/mathematicalconstants.py
+mypy --ignore-missing-imports --follow-imports skip axelrod/strategies/memorytwo.py
 mypy --ignore-missing-imports --follow-imports skip axelrod/strategies/mindcontrol.py
 mypy --ignore-missing-imports --follow-imports skip axelrod/strategies/mindreader.py
 mypy --ignore-missing-imports --follow-imports skip axelrod/strategies/mutual.py
 mypy --ignore-missing-imports --follow-imports skip axelrod/strategies/negation.py
-mypy --ignore-missing-imports --follow-imports skip axelrod/strategies/hunter.py
-mypy --ignore-missing-imports --follow-imports skip axelrod/strategies/geller.py
-mypy --ignore-missing-imports --follow-imports skip axelrod/strategies/memorytwo.py
+mypy --ignore-missing-imports --follow-imports skip axelrod/strategies/oncebitten.py
+mypy --ignore-missing-imports --follow-imports skip axelrod/strategies/prober.py
+mypy --ignore-missing-imports --follow-imports skip axelrod/strategies/punisher.py
+mypy --ignore-missing-imports --follow-imports skip axelrod/strategies/rand.py