Lint fixes for incorrectly sorted inputs

evalml/__init__.py

@@ -3,16 +3,18 @@
 # hack to prevent warnings from skopt
 # must import sklearn first
 import sklearn
+
+import evalml.data_checks
 import evalml.demos
 import evalml.model_family
 import evalml.objectives
 import evalml.pipelines
 import evalml.preprocessing
 import evalml.problem_types
 import evalml.utils
-import evalml.data_checks
 from evalml.automl import AutoMLSearch
 from evalml.utils import print_info
+
 with warnings.catch_warnings():
     warnings.simplefilter("ignore", FutureWarning)
     warnings.simplefilter("ignore", DeprecationWarning)

evalml/data_checks/__init__.py

@@ -1,17 +1,20 @@
+from .class_imbalance_data_check import ClassImbalanceDataCheck
 from .data_check import DataCheck
+from .data_check_message import (
+    DataCheckError,
+    DataCheckMessage,
+    DataCheckWarning
+)
 from .data_check_message_code import DataCheckMessageCode
-
-from .data_checks import AutoMLDataChecks, DataChecks
-from .data_check_message import DataCheckMessage, DataCheckWarning, DataCheckError
 from .data_check_message_type import DataCheckMessageType
+from .data_checks import AutoMLDataChecks, DataChecks
 from .default_data_checks import DefaultDataChecks
-from .utils import EmptyDataChecks
-from .invalid_targets_data_check import InvalidTargetDataCheck
+from .high_variance_cv_data_check import HighVarianceCVDataCheck
 from .highly_null_data_check import HighlyNullDataCheck
 from .id_columns_data_check import IDColumnsDataCheck
-from .target_leakage_data_check import TargetLeakageDataCheck
-from .outliers_data_check import OutliersDataCheck
-from .no_variance_data_check import NoVarianceDataCheck
-from .class_imbalance_data_check import ClassImbalanceDataCheck
-from .high_variance_cv_data_check import HighVarianceCVDataCheck
+from .invalid_targets_data_check import InvalidTargetDataCheck
 from .multicollinearity_data_check import MulticollinearityDataCheck
+from .no_variance_data_check import NoVarianceDataCheck
+from .outliers_data_check import OutliersDataCheck
+from .target_leakage_data_check import TargetLeakageDataCheck
+from .utils import EmptyDataChecks

evalml/demos/__init__.py

@@ -1,5 +1,5 @@
 from .breast_cancer import load_breast_cancer
+from .churn import load_churn
 from .diabetes import load_diabetes
 from .fraud import load_fraud
 from .wine import load_wine
-from .churn import load_churn

evalml/exceptions/__init__.py

@@ -1,15 +1,15 @@
 
 from .exceptions import (
-    MethodPropertyNotFoundError,
-    PipelineNotFoundError,
-    ObjectiveNotFoundError,
-    IllFormattedClassNameError,
-    MissingComponentError,
-    ComponentNotYetFittedError,
-    PipelineNotYetFittedError,
     AutoMLSearchException,
-    PipelineScoreError,
+    ComponentNotYetFittedError,
     DataCheckInitError,
     EnsembleMissingPipelinesError,
-    NullsInColumnWarning
+    IllFormattedClassNameError,
+    MethodPropertyNotFoundError,
+    MissingComponentError,
+    NullsInColumnWarning,
+    ObjectiveNotFoundError,
+    PipelineNotFoundError,
+    PipelineNotYetFittedError,
+    PipelineScoreError
 )

evalml/model_understanding/__init__.py

@@ -1,20 +1,24 @@
 from .graphs import (
-    precision_recall_curve,
-    graph_precision_recall_curve,
-    roc_curve,
-    graph_roc_curve,
-    graph_confusion_matrix,
+    binary_objective_vs_threshold,
     calculate_permutation_importance,
-    graph_permutation_importance,
     confusion_matrix,
-    normalize_confusion_matrix,
-    binary_objective_vs_threshold,
+    get_prediction_vs_actual_data,
+    get_prediction_vs_actual_over_time_data,
     graph_binary_objective_vs_threshold,
-    partial_dependence,
+    graph_confusion_matrix,
     graph_partial_dependence,
-    get_prediction_vs_actual_data,
+    graph_permutation_importance,
+    graph_precision_recall_curve,
     graph_prediction_vs_actual,
-    get_prediction_vs_actual_over_time_data,
     graph_prediction_vs_actual_over_time,
+    graph_roc_curve,
+    normalize_confusion_matrix,
+    partial_dependence,
+    precision_recall_curve,
+    roc_curve
+)
+from .prediction_explanations import (
+    explain_prediction,
+    explain_predictions,
+    explain_predictions_best_worst
 )
-from .prediction_explanations import explain_prediction, explain_predictions_best_worst, explain_predictions

evalml/model_understanding/prediction_explanations/__init__.py

@@ -1 +1,5 @@
-from .explainers import explain_prediction, explain_predictions_best_worst, explain_predictions
+from .explainers import (
+    explain_prediction,
+    explain_predictions,
+    explain_predictions_best_worst
+)

evalml/objectives/__init__.py

@@ -13,10 +13,7 @@
     MAE,
     MAPE,
     MSE,
-    MeanSquaredLogError,
     R2,
-    RootMeanSquaredError,
-    RootMeanSquaredLogError,
     AccuracyBinary,
     AccuracyMulticlass,
     AUCMacro,
@@ -33,6 +30,7 @@
     MaxError,
     MCCBinary,
     MCCMulticlass,
+    MeanSquaredLogError,
     MedianAE,
     Precision,
     PrecisionMacro,
@@ -41,7 +39,14 @@
     Recall,
     RecallMacro,
     RecallMicro,
-    RecallWeighted
+    RecallWeighted,
+    RootMeanSquaredError,
+    RootMeanSquaredLogError
+)
+from .utils import (
+    get_all_objective_names,
+    get_core_objective_names,
+    get_core_objectives,
+    get_non_core_objectives,
+    get_objective
 )
-from .utils import get_objective, get_core_objectives, get_all_objective_names, get_non_core_objectives,\
-    get_core_objective_names

evalml/pipelines/__init__.py

@@ -1,57 +1,62 @@
+from .binary_classification_pipeline import BinaryClassificationPipeline
+from .classification import (
+    BaselineBinaryPipeline,
+    BaselineMulticlassPipeline,
+    ModeBaselineBinaryPipeline,
+    ModeBaselineMulticlassPipeline
+)
+from .classification_pipeline import ClassificationPipeline
+from .component_graph import ComponentGraph
 from .components import (
+    CatBoostClassifier,
+    CatBoostRegressor,
+    DecisionTreeClassifier,
+    DecisionTreeRegressor,
+    DelayedFeatureTransformer,
+    DFSTransformer,
+    ElasticNetClassifier,
+    ElasticNetRegressor,
     Estimator,
-    OneHotEncoder,
-    TargetEncoder,
-    SimpleImputer,
-    PerColumnImputer,
-    StandardScaler,
-    Transformer,
+    ExtraTreesClassifier,
+    ExtraTreesRegressor,
+    FeatureSelector,
+    KNeighborsClassifier,
     LightGBMClassifier,
     LightGBMRegressor,
     LinearRegressor,
     LogisticRegressionClassifier,
+    OneHotEncoder,
+    PerColumnImputer,
     RandomForestClassifier,
     RandomForestRegressor,
-    XGBoostClassifier,
-    XGBoostRegressor,
-    FeatureSelector,
     RFClassifierSelectFromModel,
     RFRegressorSelectFromModel,
-    CatBoostClassifier,
-    CatBoostRegressor,
-    ElasticNetClassifier,
-    ElasticNetRegressor,
-    ExtraTreesClassifier,
-    ExtraTreesRegressor,
-    DecisionTreeClassifier,
-    DecisionTreeRegressor,
+    SimpleImputer,
     StackedEnsembleClassifier,
     StackedEnsembleRegressor,
-    DelayedFeatureTransformer,
-    DFSTransformer,
-    KNeighborsClassifier
+    StandardScaler,
+    TargetEncoder,
+    Transformer,
+    XGBoostClassifier,
+    XGBoostRegressor
+)
+from .multiclass_classification_pipeline import (
+    MulticlassClassificationPipeline
 )
-
-from .component_graph import ComponentGraph
 from .pipeline_base import PipelineBase
-from .classification_pipeline import ClassificationPipeline
-from .binary_classification_pipeline import BinaryClassificationPipeline
-from .multiclass_classification_pipeline import MulticlassClassificationPipeline
+from .regression import (
+    BaselineRegressionPipeline,
+    MeanBaselineRegressionPipeline
+)
 from .regression_pipeline import RegressionPipeline
+from .time_series_baselines import (
+    TimeSeriesBaselineBinaryPipeline,
+    TimeSeriesBaselineMulticlassPipeline,
+    TimeSeriesBaselineRegressionPipeline
+)
 from .time_series_classification_pipelines import (
-    TimeSeriesClassificationPipeline,
     TimeSeriesBinaryClassificationPipeline,
+    TimeSeriesClassificationPipeline,
     TimeSeriesMulticlassClassificationPipeline
 )
-from .classification import (
-    BaselineBinaryPipeline,
-    BaselineMulticlassPipeline,
-    ModeBaselineBinaryPipeline,
-    ModeBaselineMulticlassPipeline
-)
 from .time_series_regression_pipeline import TimeSeriesRegressionPipeline
-from .regression import (
-    BaselineRegressionPipeline,
-    MeanBaselineRegressionPipeline,
-)
-from .time_series_baselines import TimeSeriesBaselineRegressionPipeline, TimeSeriesBaselineBinaryPipeline, TimeSeriesBaselineMulticlassPipeline

evalml/pipelines/classification/__init__.py

@@ -1,2 +1,5 @@
 from .baseline_binary import BaselineBinaryPipeline, ModeBaselineBinaryPipeline
-from .baseline_multiclass import BaselineMulticlassPipeline, ModeBaselineMulticlassPipeline
+from .baseline_multiclass import (
+    BaselineMulticlassPipeline,
+    ModeBaselineMulticlassPipeline
+)

evalml/pipelines/components/__init__.py

@@ -1,50 +1,47 @@
 from .component_base import ComponentBase, ComponentBaseMeta
+from .ensemble import StackedEnsembleClassifier, StackedEnsembleRegressor
 from .estimators import (
+    BaselineClassifier,
+    BaselineRegressor,
+    CatBoostClassifier,
+    CatBoostRegressor,
+    DecisionTreeClassifier,
+    DecisionTreeRegressor,
+    ElasticNetClassifier,
+    ElasticNetRegressor,
     Estimator,
-    LinearRegressor,
+    ExtraTreesClassifier,
+    ExtraTreesRegressor,
+    KNeighborsClassifier,
     LightGBMClassifier,
     LightGBMRegressor,
+    LinearRegressor,
     LogisticRegressionClassifier,
     RandomForestClassifier,
     RandomForestRegressor,
-    XGBoostClassifier,
-    CatBoostClassifier,
-    ExtraTreesClassifier,
-    ExtraTreesRegressor,
-    CatBoostRegressor,
-    XGBoostRegressor,
-    ElasticNetClassifier,
-    ElasticNetRegressor,
-    BaselineClassifier,
-    BaselineRegressor,
-    DecisionTreeClassifier,
-    DecisionTreeRegressor,
     TimeSeriesBaselineEstimator,
-    KNeighborsClassifier
+    XGBoostClassifier,
+    XGBoostRegressor
 )
 from .transformers import (
-    Transformer,
+    LSA,
+    PCA,
+    DateTimeFeaturizer,
+    DelayedFeatureTransformer,
+    DFSTransformer,
+    DropColumns,
+    DropNullColumns,
+    FeatureSelector,
+    Imputer,
+    LinearDiscriminantAnalysis,
     OneHotEncoder,
-    TargetEncoder,
+    PerColumnImputer,
     RFClassifierSelectFromModel,
     RFRegressorSelectFromModel,
-    PerColumnImputer,
-    DelayedFeatureTransformer,
+    SelectColumns,
     SimpleImputer,
-    Imputer,
     StandardScaler,
-    FeatureSelector,
-    DropColumns,
-    DropNullColumns,
-    DateTimeFeaturizer,
-    SelectColumns,
+    TargetEncoder,
     TextFeaturizer,
-    LinearDiscriminantAnalysis,
-    LSA,
-    PCA,
-    DFSTransformer
-)
-from .ensemble import (
-    StackedEnsembleClassifier,
-    StackedEnsembleRegressor
+    Transformer
 )

evalml/pipelines/components/estimators/__init__.py

@@ -1,21 +1,25 @@
+from .classifiers import (
+    BaselineClassifier,
+    CatBoostClassifier,
+    DecisionTreeClassifier,
+    ElasticNetClassifier,
+    ExtraTreesClassifier,
+    KNeighborsClassifier,
+    LightGBMClassifier,
+    LogisticRegressionClassifier,
+    RandomForestClassifier,
+    XGBoostClassifier
+)
 from .estimator import Estimator
-from .classifiers import (LogisticRegressionClassifier,
-                          RandomForestClassifier,
-                          XGBoostClassifier,
-                          LightGBMClassifier,
-                          CatBoostClassifier,
-                          ElasticNetClassifier,
-                          ExtraTreesClassifier,
-                          BaselineClassifier,
-                          DecisionTreeClassifier,
-                          KNeighborsClassifier)
-from .regressors import (LinearRegressor,
-                         LightGBMRegressor,
-                         RandomForestRegressor,
-                         CatBoostRegressor,
-                         XGBoostRegressor,
-                         ElasticNetRegressor,
-                         ExtraTreesRegressor,
-                         BaselineRegressor,
-                         TimeSeriesBaselineEstimator,
-                         DecisionTreeRegressor)
+from .regressors import (
+    BaselineRegressor,
+    CatBoostRegressor,
+    DecisionTreeRegressor,
+    ElasticNetRegressor,
+    ExtraTreesRegressor,
+    LightGBMRegressor,
+    LinearRegressor,
+    RandomForestRegressor,
+    TimeSeriesBaselineEstimator,
+    XGBoostRegressor
+)