Removed explicit inheritance from "object" (not needed in python > 3) (…

…#790)

src/tests/audition_tests/test_distance_from_best.py

@@ -203,7 +203,7 @@ def test_BestDistancePlotter_plot():
 
 
 def test_BestDistancePlotter_plot_bounds():
-    class FakeDistanceTable(object):
+    class FakeDistanceTable:
         @property
         def observed_bounds(self):
             return {

src/tests/audition_tests/test_selection_rule_performance.py

@@ -15,7 +15,7 @@
 TRAIN_END_TIMES = ["2014-01-01", "2015-01-01"]
 
 
-class MockSelectionRulePicker(object):
+class MockSelectionRulePicker:
     def results_for_rule(*args, **kwargs):
         return [
             {

src/tests/catwalk_tests/test_storage.py

@@ -24,7 +24,7 @@
 from tests.utils import CallSpy
 
 
-class SomeClass(object):
+class SomeClass:
 
     def __init__(self, val):
         self.val = val

src/tests/utils.py

@@ -32,7 +32,7 @@ def fake_labels(length):
     return numpy.array([random.choice([True, False]) for i in range(0, length)])
 
 
-class MockTrainedModel(object):
+class MockTrainedModel:
     def predict_proba(self, dataset):
         return numpy.random.rand(len(dataset), len(dataset))
 

src/triage/component/architect/builders.py

@@ -11,7 +11,7 @@
 from triage.util.pandas import downcast_matrix
 
 
-class BuilderBase(object):
+class BuilderBase:
     def __init__(
         self,
         db_config,

src/triage/component/architect/entity_date_table_generators.py

@@ -7,7 +7,7 @@
 DEFAULT_ACTIVE_STATE = "active"
 
 
-class EntityDateTableGenerator(object):
+class EntityDateTableGenerator:
     """Create a table containing state membership on different dates
 
     The structure of the output table is:

src/triage/component/architect/feature_dictionary_creator.py

@@ -3,7 +3,7 @@
 from triage.util.structs import FeatureNameList
 
 
-class FeatureDictionaryCreator(object):
+class FeatureDictionaryCreator:
     def __init__(self, features_schema_name, db_engine):
         self.features_schema_name = features_schema_name
         self.db_engine = db_engine

src/triage/component/architect/feature_generators.py

@@ -16,7 +16,7 @@
 )
 
 
-class FeatureGenerator(object):
+class FeatureGenerator:
     def __init__(
         self,
         db_engine,

src/triage/component/architect/feature_group_creator.py

@@ -40,7 +40,7 @@ def all_subsetter(config_item, table, features):
     return features
 
 
-class FeatureGroupCreator(object):
+class FeatureGroupCreator:
     """Divides a feature dictionary into groups based on given criteria"""
 
     subsetters = {

src/triage/component/architect/feature_group_mixer.py

@@ -67,7 +67,7 @@ def all_features(feature_groups):
     return [feature_dict]
 
 
-class FeatureGroupMixer(object):
+class FeatureGroupMixer:
     """Generates different combinations of feature groups
     based on a list of strategies"""
 

src/triage/component/architect/label_generators.py

@@ -6,7 +6,7 @@
 DEFAULT_LABEL_NAME = "outcome"
 
 
-class LabelGeneratorNoOp(object):
+class LabelGeneratorNoOp:
     def generate_all_labels(self, labels_table, as_of_dates, label_timespans):
         logging.warning(
             "No label configuration is available, so no labels will be created"
@@ -21,7 +21,7 @@ def clean_up(self, labels_table_name):
         pass
 
 
-class LabelGenerator(object):
+class LabelGenerator:
     def __init__(self, db_engine, query, label_name=None, replace=True):
         self.db_engine = db_engine
         self.replace = replace

src/triage/component/architect/planner.py

@@ -6,7 +6,7 @@
 from . import utils, entity_date_table_generators
 
 
-class Planner(object):
+class Planner:
     def __init__(
         self,
         feature_start_time,

src/triage/component/architect/utils.py

@@ -129,7 +129,7 @@ def fake_labels(length):
     return numpy.array([random.choice([True, False]) for i in range(0, length)])
 
 
-class MockTrainedModel(object):
+class MockTrainedModel:
     def predict_proba(self, dataset):
         return numpy.random.rand(len(dataset), len(dataset))
 

src/triage/component/audition/__init__.py

@@ -12,7 +12,7 @@
 from .pre_audition import PreAudition
 
 
-class Auditioner(object):
+class Auditioner:
     def __init__(
         self,
         db_engine,
@@ -354,7 +354,7 @@ def register_selection_rule_grid(self, rule_grid, plot=True):
             self.plot_selection_rules()
 
 
-class AuditionRunner(object):
+class AuditionRunner:
     def __init__(self, config_dict, db_engine, directory=None):
         self.dir = directory
         self.config = config_dict

src/triage/component/audition/distance_from_best.py

@@ -8,7 +8,7 @@
 from .plotting import plot_cats, plot_bounds
 
 
-class DistanceFromBestTable(object):
+class DistanceFromBestTable:
     def __init__(self, db_engine, models_table, distance_table):
         """A database table that stores the distance from models and the
         best model for that train end time for a variety of chosen metrics
@@ -207,7 +207,7 @@ def dataframe_as_of(self, model_group_ids, train_end_time):
         return base_df[base_df["train_end_time"] == train_end_time]
 
 
-class BestDistancePlotter(object):
+class BestDistancePlotter:
     def __init__(self, distance_from_best_table, directory=None):
         """Generate a plot illustrating the effect of different below-best maximum
         thresholds across the dataset.

src/triage/component/audition/model_group_performance.py

@@ -7,7 +7,7 @@
 from .utils import str_in_sql
 
 
-class ModelGroupPerformancePlotter(object):
+class ModelGroupPerformancePlotter:
     def __init__(self, distance_from_best_table, directory=None):
         """Generate a plot illustrating the performance of a model group over time
 

src/triage/component/audition/pre_audition.py

@@ -1,7 +1,7 @@
 import pandas as pd
 
 
-class PreAudition(object):
+class PreAudition:
     def __init__(self, db_engine):
         """Prepare the model_groups and train_end_times for Auditioner to use
 

src/triage/component/audition/regrets.py

@@ -6,7 +6,7 @@
 from .plotting import plot_cats, plot_bounds
 
 
-class SelectionRulePicker(object):
+class SelectionRulePicker:
     def __init__(self, distance_from_best_table):
         """Runs simulations of different model group selection rules
 
@@ -102,7 +102,7 @@ def model_group_from_rule(
         return bound_selection_rule.pick(localized_df, train_end_time)
 
 
-class SelectionRulePlotter(object):
+class SelectionRulePlotter:
     """Plot selection rules
 
     Args:

src/triage/component/audition/rules_maker.py

@@ -1,4 +1,4 @@
-class BaseRules(object):
+class BaseRules:
     def __init__(self):
         self._metric = None
         self._parameter = None

src/triage/component/audition/selection_rule_performance.py

@@ -3,7 +3,7 @@
 from .plotting import plot_cats
 
 
-class SelectionRulePerformancePlotter(object):
+class SelectionRulePerformancePlotter:
     """Plot regrets over time
 
     Generates a simple line chart with audition.BoundSelectionRule objects as

src/triage/component/audition/selection_rules.py

@@ -447,7 +447,7 @@ def wm(x):
 }
 
 
-class BoundSelectionRule(object):
+class BoundSelectionRule:
     """A selection rule bound with a set of arguments
 
     Args:

src/triage/component/audition/thresholding.py

@@ -91,7 +91,7 @@ def model_groups_filter(
     return model_group_ids
 
 
-class ModelGroupThresholder(object):
+class ModelGroupThresholder:
     def __init__(
         self,
         distance_from_best_table,

src/triage/component/catwalk/__init__.py

@@ -16,7 +16,7 @@
 TaskBatch = namedtuple('TaskBatch', ['parallelizable', 'tasks', 'description'])
 
 
-class ModelTrainTester(object):
+class ModelTrainTester:
     def __init__(
         self,
         matrix_storage_engine,

src/triage/component/catwalk/baselines/rankers.py

@@ -3,7 +3,7 @@
 from triage.component.catwalk.exceptions import BaselineFeatureNotInMatrix
 
 
-class PercentileRankOneFeature(object):
+class PercentileRankOneFeature:
     def __init__(self, feature, descend=False):
         self.feature = feature  # which feature to rank on
         self.descend = (

src/triage/component/catwalk/baselines/thresholders.py

@@ -28,7 +28,7 @@ def get_operator_method(operator_string):
     return operator_method
 
 
-class SimpleThresholder(object):
+class SimpleThresholder:
     """ The simple thresholder applies a set of predetermined logical rules to a
     test matrix to classify entities. By default, it will classify entities as 1
     if they satisfy any of the rules. When 'and' is set as the logical_operator,

src/triage/component/catwalk/evaluation.py

@@ -149,7 +149,7 @@ class MetricEvaluationResult(typing.NamedTuple):
     num_positive_labels: int
 
 
-class ModelEvaluator(object):
+class ModelEvaluator:
     """An object that can score models based on its known metrics"""
 
     """Available metric calculation functions

src/triage/component/catwalk/individual_importance/__init__.py

@@ -28,7 +28,7 @@ def save(self, importance_records, model_id, as_of_date, method_name):
 
 
 
-class IndividualImportanceCalculator(object):
+class IndividualImportanceCalculator:
     """Calculates and saves individual importance scores and rankings using different methods
 
     Args:

src/triage/component/catwalk/metrics.py

@@ -22,7 +22,7 @@
 import numpy
 
 
-class Metric(object):
+class Metric:
     """decorator for metrics: result will be a callable metric with an
     `greater_is_better` parameter defined as either True or False
     depending on whether larger or smaller metric values indicate
@@ -35,7 +35,7 @@ def __init__(self, greater_is_better):
         self.greater_is_better = greater_is_better
 
     def __call__(self, function, *params, **kwparams):
-        class DecoratedMetric(object):
+        class DecoratedMetric:
             def __init__(self, greater_is_better, function):
                 self.greater_is_better = greater_is_better
                 self.function = function

src/triage/component/catwalk/model_grouping.py

@@ -12,7 +12,7 @@
 ]
 
 
-class ModelGrouper(object):
+class ModelGrouper:
     """Assign a model group id to given model input based on default or custom configuration
 
     This class is a wrapper around the `get_model_group_id` stored procedure,

src/triage/component/catwalk/model_trainers.py

@@ -41,7 +41,7 @@ def flatten_grid_config(grid_config):
             yield class_path, parameters
 
 
-class ModelTrainer(object):
+class ModelTrainer:
     """Trains a series of classifiers using the same training set
     Args:
         project_path (string) path to project folder,

src/triage/component/catwalk/predictors.py

@@ -17,7 +17,7 @@ class ModelNotFoundError(ValueError):
     pass
 
 
-class Predictor(object):
+class Predictor:
     expected_matrix_ts_format = "%Y-%m-%d %H:%M:%S"
     available_tiebreakers = AVAILABLE_TIEBREAKERS
 

src/triage/component/catwalk/protected_groups_generators.py

@@ -8,7 +8,7 @@
 from triage.component.catwalk.storage import MatrixStore
 
 
-class ProtectedGroupsGeneratorNoOp(object):
+class ProtectedGroupsGeneratorNoOp:
     def generate_all_dates(self, *args, **kwargs):
         logging.warning(
             "No bias audit configuration is available, so protected groups will not be created"
@@ -23,7 +23,7 @@ def as_dataframe(self, *args, **kwargs):
         return pandas.DataFrame()
 
 
-class ProtectedGroupsGenerator(object):
+class ProtectedGroupsGenerator:
     def __init__(self, db_engine, from_obj, attribute_columns, entity_id_column, knowledge_date_column, protected_groups_table_name, replace=True):
         self.db_engine = db_engine
         self.replace = replace