pylint fixes

agents/agent_consider_equity.py

@@ -2,13 +2,11 @@
 
 from gym_env.env import Action
 
-autoplay = True  # play automatically if played against keras-rl
-
 
 class Player:
     """Mandatory class with the player methods"""
 
-    def __init__(self, name='Random', min_call_equity=None, min_bet_equity=None):
+    def __init__(self, name="Random", min_call_equity=None, min_bet_equity=None):
         """Initiaization of an agent"""
         self.equity_alive = 0
         self.name = name
@@ -21,21 +19,30 @@ def __init__(self, name='Random', min_call_equity=None, min_bet_equity=None):
     def action(self, action_space, observation, info):  # pylint: disable=no-self-use
         """Mandatory method that calculates the move based on the observation array and the action space."""
         _ = observation
-        equity_alive = info['player_data']['equity_to_river_alive']
+        equity_alive = info["player_data"]["equity_to_river_alive"]
 
-        incremen1 = .1
-        increment2 = .2
+        incremen1 = 0.1
+        increment2 = 0.2
 
-        if equity_alive > self.min_bet_equity + increment2 and Action.ALL_IN in action_space:
+        if (
+            equity_alive > self.min_bet_equity + increment2
+            and Action.ALL_IN in action_space
+        ):
             action = Action.ALL_IN
 
-        elif equity_alive > self.min_bet_equity + incremen1 and Action.RAISE_2POT in action_space:
+        elif (
+            equity_alive > self.min_bet_equity + incremen1
+            and Action.RAISE_2POT in action_space
+        ):
             action = Action.RAISE_2POT
 
         elif equity_alive > self.min_bet_equity and Action.RAISE_POT in action_space:
             action = Action.RAISE_POT
 
-        elif equity_alive > self.min_bet_equity - incremen1 and Action.RAISE_HALF_POT in action_space:
+        elif (
+            equity_alive > self.min_bet_equity - incremen1
+            and Action.RAISE_HALF_POT in action_space
+        ):
             action = Action.RAISE_HALF_POT
 
         elif equity_alive > self.min_call_equity and Action.CALL in action_space:

agents/agent_custom_q1.py

@@ -6,6 +6,7 @@
 from agents.agent_keras_rl_dqn import TrumpPolicy, memory_limit, window_length
 from gym_env import env
 
+# pylint: disable=import-error
 
 class Player:
     """Mandatory class with the player methods"""

agents/agent_keras_rl_dqn.py

@@ -1,5 +1,5 @@
 """Player based on a trained neural network"""
-# pylint: disable=wrong-import-order,invalid-name
+# pylint: disable=wrong-import-order,invalid-name,import-error,missing-function-docstring
 import logging
 import time
 

gym_env/env.py

@@ -914,6 +914,7 @@ def __init__(self, stack_size, name):
         self.temp_stack = []
         self.name = name
         self.agent_obj = None
+        self.cards = None
         self.num_raises_in_street = {Stage.PREFLOP: 0,
                                      Stage.FLOP: 0,
                                      Stage.TURN: 0,

tests/test_gym_env.py

@@ -122,8 +122,7 @@ def test_raise_to_3_times_big_blind_is_possible_with_enough_remaining_stack():
     assert env.players[0].stack == 0
 
 
-@pytest.mark.skip("Test-scenario is not like title of the test and player_cycle.alive has by several executions a "
-                  "changed behaviour")
+
 def test_heads_up_after_flop():
     """All in at pre-flop leads to heads up after flop.
     For more info about skipping of this test see https://github.com/dickreuter/neuron_poker/issues/39.