Added some tests

axelrod/__init__.py

@@ -9,7 +9,8 @@
 from axelrod.plot import Plot
 from axelrod.game import DefaultGame, Game
 from axelrod.history import History, LimitedHistory
-from axelrod.player import is_basic, obey_axelrod, Player
+from axelrod.player import Player
+from axelrod.classifier import Classifiers, is_basic, obey_axelrod
 from axelrod.evolvable_player import EvolvablePlayer
 from axelrod.mock_player import MockPlayer
 from axelrod.match import Match

axelrod/classifier.py

@@ -1,6 +1,7 @@
 from typing import Any, Callable, Generic, List, Optional, Set, Text, Type, \
     TypeVar, Union
 
+import os
 import yaml
 
 from axelrod.player import Player
@@ -11,11 +12,34 @@
 
 
 class Classifier(Generic[T]):
+    """Describes a Player (strategy).
+
+    User sets a name and function, f, at initialization.  Through
+    calc_for_player, looks for the classifier to be set in the passed Player
+    class.  If not set, then passes to f for calculation.
+
+    f must operate on the class, and not an instance.  If necessary, f may
+    initialize an instance, but this shouldn't depend on runtime states, because
+    the result gets stored in a file.  If a strategy's classifier depends on
+    runtime states, such as those created by transformers, then it can set the
+    field in its classifier dict, and that will take precedent over saved
+    values.
+
+    Attributes
+    ----------
+    name: An identifier for the classifier, used as a dict key in storage and in
+        'classifier' dicts of Player classes.
+    f: A function that takes in a Player class (not an instance) and returns a
+        value.
+    """
+
     def __init__(self, name: Text, f: Callable[[Type[Player]], T]):
         self.name = name
         self.f = f
 
     def calc_for_player(self, player: Type[Player]) -> T:
+        """Look for this classifier in the passed player's 'classifier' dict,
+        otherwise pass to the player to f."""
         if self.name in player.classifier:
             return player.classifier[self.name]
 
@@ -33,6 +57,7 @@ def calc_for_player(self, player: Type[Player]) -> T:
 manipulates_state = Classifier[Optional[bool]]("manipulates_state",
                                                lambda _: None)
 
+# Should list all known classifiers.
 all_classifiers = [
     stochastic,
     memory_depth,
@@ -47,37 +72,88 @@ def calc_for_player(self, player: Type[Player]) -> T:
 def rebuild_classifier_table(classifiers: List[Classifier],
                              players: List[Type[Player]],
                              path: Text = ALL_CLASSIFIERS_PATH) -> None:
+    """Builds the classifier table in data.
+
+    Parameters
+    ----------
+    classifiers: A list of classifiers to calculate on the strategies
+    players: A list of strategies (classes, not instances) to compute the
+        classifiers for.
+    path: Where to save the resulting yaml file.
+    """
+    # Get absolute path
+    dirname = os.path.dirname(__file__)
+    filename = os.path.join(dirname, path)
+
     all_player_dicts = dict()
     for p in players:
         new_player_dict = dict()
         for c in classifiers:
             new_player_dict[c.name] = c.calc_for_player(p)
         all_player_dicts[p.name] = new_player_dict
 
-    with open(path, 'w') as f:
+    with open(filename, 'w') as f:
         yaml.dump(all_player_dicts, f)
 
 
 class Classifiers(object):
+    """A singleton used to calculate any known classifier.
+
+    Attributes
+    ----------
+    all_player_dicts: A local copy of the dict saved in the classifier table.
+        The keys are player names, and the values are 'classifier' dicts (keyed
+        by classifier name).
+    """
     _instance = None
     all_player_dicts = dict()
 
     # Make this a singleton
     def __new__(cls):
         if cls._instance is None:
             cls._instance = super(Classifiers, cls).__new__(cls)
-            with open(ALL_CLASSIFIERS_PATH, 'r') as f:
+            # When this is first created, read from the classifier table file.
+            # Get absolute path
+            dirname = os.path.dirname(__file__)
+            filename = os.path.join(dirname, ALL_CLASSIFIERS_PATH)
+            with open(filename, 'r') as f:
                 cls.all_player_dicts = yaml.load(f, Loader=yaml.FullLoader)
 
         return cls._instance
 
+    @classmethod
+    def known_classifier(cls, classifier_name: Text) -> bool:
+        """Returns True if the passed classifier_name is known."""
+        global all_classifiers
+        return classifier_name in (c.name for c in all_classifiers)
+
     @classmethod
     def get(cls, classifier: Union[Classifier, Text],
             player: Player) -> Any:
+        """Looks up the classifier for the player.
+
+        If the classifier is found in the 'classifier' dict on the player, then
+        return that.  Otherwise look for the classifier for the player in the
+        all_player_dicts.  Returns None if the classifier is not found in either
+        of those.
+
+        Parameters
+        ----------
+        classifier: A classifier or classifier name that we want to calculate
+            for the player.
+        player: The player (instance) for which we compute the classifier.
+
+        Returns
+        -------
+        The classifier value for the player, or None if unknown.
+        """
         # Classifier may be the name or an instance.  Convert to name.
         if not isinstance(classifier, str):
             classifier = classifier.name
 
+        if not cls.known_classifier(classifier):
+            raise KeyError("Unknown classifier")
+
         # Factory-generated players won't exist in the table.  As well, some
         # players, like Random, may change classifiers at construction time;
         # this get() function takes a player instance, while the saved-values
@@ -102,3 +178,34 @@ def return_missing() -> None:
         if classifier not in player_classifiers:
             return return_missing()
         return player_classifiers[classifier]
+
+
+# Strategy classifiers
+
+def is_basic(s):
+    """
+    Defines criteria for a strategy to be considered 'basic'
+    """
+    stochastic = Classifiers().get("stochastic", s)
+    depth = Classifiers().get("memory_depth", s)
+    inspects_source = Classifiers().get("inspects_source", s)
+    manipulates_source = Classifiers().get("manipulates_source", s)
+    manipulates_state = Classifiers().get("manipulates_state", s)
+    return (
+        not stochastic
+        and not inspects_source
+        and not manipulates_source
+        and not manipulates_state
+        and depth in (0, 1)
+    )
+
+
+def obey_axelrod(s):
+    """
+    A function to check if a strategy obeys Axelrod's original tournament
+    rules.
+    """
+    for c in ["inspects_source", "manipulates_source", "manipulates_state"]:
+        if Classifiers().get(c, s):
+            return False
+    return True

axelrod/player.py

@@ -7,46 +7,13 @@
 import numpy as np
 
 from axelrod.action import Action
-from axelrod.classifier import Classifiers
 from axelrod.game import DefaultGame
 from axelrod.history import History
 from axelrod.random_ import random_flip
 
 C, D = Action.C, Action.D
 
 
-# Strategy classifiers
-
-
-def is_basic(s):
-    """
-    Defines criteria for a strategy to be considered 'basic'
-    """
-    stochastic = Classifiers().get("stochastic", s)
-    depth = Classifiers().get("depth", s)
-    inspects_source = Classifiers().get("inspects_source", s)
-    manipulates_source = Classifiers().get("manipulates_source", s)
-    manipulates_state = Classifiers().get("manipulates_state", s)
-    return (
-        not stochastic
-        and not inspects_source
-        and not manipulates_source
-        and not manipulates_state
-        and depth in (0, 1)
-    )
-
-
-def obey_axelrod(s):
-    """
-    A function to check if a strategy obeys Axelrod's original tournament
-    rules.
-    """
-    for c in ["inspects_source", "manipulates_source", "manipulates_state"]:
-        if Classifiers().get(c, s):
-            return False
-    return True
-
-
 def simultaneous_play(player, coplayer, noise=0):
     """This pits two players against each other."""
     s1, s2 = player.strategy(coplayer), coplayer.strategy(player)

axelrod/strategies/__init__.py

@@ -1,5 +1,4 @@
-from ..classifier import Classifiers
-from ..player import is_basic, obey_axelrod
+from ..classifier import Classifiers, is_basic, obey_axelrod
 from ._strategies import *
 from ._filters import passes_filterset
 
@@ -85,10 +84,10 @@
 strategies = [s for s in all_strategies if obey_axelrod(s())]
 
 long_run_time_strategies = [
-    s for s in all_strategies if Classifiers().get("long_run_time", s)
+    s for s in all_strategies if Classifiers().get("long_run_time", s())
 ]
 short_run_time_strategies = [
-    s for s in strategies if not Classifiers().get("long_run_time", s)
+    s for s in strategies if not Classifiers().get("long_run_time", s())
 ]
 cheating_strategies = [s for s in all_strategies if not obey_axelrod(s())]
 

axelrod/strategies/meta.py

@@ -4,8 +4,8 @@
 from numpy.random import choice
 
 from axelrod.action import Action
-from axelrod.classifier import Classifiers
-from axelrod.player import Player, obey_axelrod
+from axelrod.classifier import Classifiers, obey_axelrod
+from axelrod.player import Player
 from axelrod.strategies import TitForTat
 from axelrod.strategy_transformers import NiceTransformer
 from ._strategies import all_strategies

axelrod/tests/unit/test_classification.py

@@ -1,12 +1,39 @@
 """Tests for the classification."""
 
+import os
 import unittest
+from typing import Text
+
+import yaml
 
 import axelrod as axl
-from axelrod.classifier import Classifiers
+from axelrod.classifier import Classifier, Classifiers, rebuild_classifier_table
 
 
 class TestClassification(unittest.TestCase):
+    def test_classifier_build(self):
+        test_path = "../test_outputs/classifier_test.yaml"
+
+        # Just returns the name of the player.  For testing.
+        name_classifier = Classifier[Text]("name", lambda player: player.name)
+        rebuild_classifier_table(classifiers=[name_classifier],
+                                 players=[axl.Cooperator, axl.Defector],
+                                 path=test_path)
+
+        filename = os.path.join("../..", test_path)
+        with open(filename, 'r') as f:
+            all_player_dicts = yaml.load(f, Loader=yaml.FullLoader)
+
+        self.assertDictEqual(all_player_dicts,
+                             {"Cooperator": {"name": "Cooperator"},
+                              "Defector": {"name": "Defector"}})
+
+    def test_singletonity_of_classifiers_class(self):
+        classifiers_1 = Classifiers()
+        classifiers_2 = Classifiers()
+
+        self.assertIs(classifiers_1, classifiers_2)
+
     def test_known_classifiers(self):
         # A set of dimensions that are known to have been fully applied
         known_keys = [
@@ -223,7 +250,7 @@ def test_long_run_strategies(self):
             str_reps(axl.long_run_time_strategies)
         )
         self.assertTrue(
-            all(Classifiers().get("long_run_time", s) for s in
+            all(Classifiers().get("long_run_time", s()) for s in
                 axl.long_run_time_strategies)
         )
 
@@ -237,7 +264,7 @@ def test_short_run_strategies(self):
             str_reps(axl.short_run_time_strategies)
         )
         self.assertFalse(
-            any(Classifiers().get("long_run_time", s) for s in
+            any(Classifiers().get("long_run_time", s()) for s in
                 axl.short_run_time_strategies)
         )
 

rebuild_classifier_table.py

@@ -1,10 +1,8 @@
 import os
 
 from axelrod import all_strategies
-from axelrod.classifier import ALL_CLASSIFIERS_PATH, all_classifiers, \
-    rebuild_classifier_table
+from axelrod.classifier import all_classifiers, rebuild_classifier_table
 
 if __name__ == "__main__":
     # Change to relative path inside axelrod folder
-    axelrod_path = os.path.join("axelrod", ALL_CLASSIFIERS_PATH)
-    rebuild_classifier_table(all_classifiers, all_strategies, path=axelrod_path)
+    rebuild_classifier_table(all_classifiers, all_strategies)