Correct imports

ml_garden/core/data_container.py

@@ -13,8 +13,8 @@
 from explainerdashboard.explainers import BaseExplainer
 from sklearn.compose import ColumnTransformer
 
-from pipeline_lib.core.model import Model
-from pipeline_lib.utils.compression_utils import compress_zipfile, decompress_zipfile
+from ml_garden.core.model import Model
+from ml_garden.utils.compression_utils import compress_zipfile, decompress_zipfile
 
 
 class DataContainer:

ml_garden/core/model_registry.py

@@ -2,7 +2,7 @@
 import logging
 import pkgutil
 
-from pipeline_lib.core.model import Model
+from ml_garden.core.model import Model
 
 
 class ModelClassNotFoundError(Exception):

ml_garden/core/pipeline.py

@@ -10,11 +10,11 @@
 import mlflow
 import pandas as pd
 
-from pipeline_lib.core.data_container import DataContainer
-from pipeline_lib.core.model_registry import ModelRegistry
-from pipeline_lib.core.random_state_generator import initialize_random_state
-from pipeline_lib.core.step_registry import StepRegistry
-from pipeline_lib.core.steps import PipelineStep
+from ml_garden.core.data_container import DataContainer
+from ml_garden.core.model_registry import ModelRegistry
+from ml_garden.core.random_state_generator import initialize_random_state
+from ml_garden.core.step_registry import StepRegistry
+from ml_garden.core.steps import PipelineStep
 
 
 class Pipeline:

ml_garden/core/step_registry.py

@@ -3,7 +3,7 @@
 import os
 import pkgutil
 
-from pipeline_lib.core.steps.base import PipelineStep
+from ml_garden.core.steps.base import PipelineStep
 
 
 class StepClassNotFoundError(Exception):

ml_garden/core/steps/base.py

@@ -2,7 +2,7 @@
 from abc import ABC, abstractmethod
 from typing import Optional
 
-from pipeline_lib.core.data_container import DataContainer
+from ml_garden.core.data_container import DataContainer
 
 
 class PipelineStep(ABC):

ml_garden/core/steps/calculate_features.py

@@ -3,8 +3,8 @@
 import pandas as pd
 from pandas.api.types import is_datetime64_any_dtype
 
-from pipeline_lib.core import DataContainer
-from pipeline_lib.core.steps.base import PipelineStep
+from ml_garden.core import DataContainer
+from ml_garden.core.steps.base import PipelineStep
 
 
 class UnsupportedFeatureError(Exception):

ml_garden/core/steps/calculate_metrics.py

@@ -4,8 +4,8 @@
 import pandas as pd
 from sklearn.metrics import mean_absolute_error, mean_squared_error, r2_score
 
-from pipeline_lib.core import DataContainer
-from pipeline_lib.core.steps.base import PipelineStep
+from ml_garden.core import DataContainer
+from ml_garden.core.steps.base import PipelineStep
 
 
 class CalculateMetricsStep(PipelineStep):

ml_garden/core/steps/calculate_reports.py

@@ -5,8 +5,8 @@
 import shap
 from tqdm import tqdm
 
-from pipeline_lib.core import DataContainer
-from pipeline_lib.core.steps.base import PipelineStep
+from ml_garden.core import DataContainer
+from ml_garden.core.steps.base import PipelineStep
 
 
 class CalculateReportsStep(PipelineStep):

ml_garden/core/steps/clean.py

@@ -2,8 +2,8 @@
 
 import pandas as pd
 
-from pipeline_lib.core import DataContainer
-from pipeline_lib.core.steps.base import PipelineStep
+from ml_garden.core import DataContainer
+from ml_garden.core.steps.base import PipelineStep
 
 
 class CleanStep(PipelineStep):

ml_garden/core/steps/encode.py

@@ -7,8 +7,8 @@
 from sklearn.compose import ColumnTransformer
 from sklearn.preprocessing import OrdinalEncoder
 
-from pipeline_lib.core import DataContainer
-from pipeline_lib.core.steps.base import PipelineStep
+from ml_garden.core import DataContainer
+from ml_garden.core.steps.base import PipelineStep
 
 
 class EncodeStep(PipelineStep):

ml_garden/core/steps/explainer_dashboard.py

@@ -2,9 +2,9 @@
 import pandas as pd
 from explainerdashboard import RegressionExplainer
 
-from pipeline_lib.core import DataContainer
-from pipeline_lib.core.random_state_generator import get_random_state
-from pipeline_lib.core.steps.base import PipelineStep
+from ml_garden.core import DataContainer
+from ml_garden.core.random_state_generator import get_random_state
+from ml_garden.core.steps.base import PipelineStep
 
 
 class ExplainerDashboardStep(PipelineStep):

ml_garden/core/steps/fit_model.py

@@ -9,9 +9,9 @@
     root_mean_squared_error,
 )
 
-from pipeline_lib.core import DataContainer
-from pipeline_lib.core.model import Model
-from pipeline_lib.core.steps.base import PipelineStep
+from ml_garden.core import DataContainer
+from ml_garden.core.model import Model
+from ml_garden.core.steps.base import PipelineStep
 
 
 class OptunaOptimizer:

ml_garden/core/steps/generate.py

@@ -5,9 +5,9 @@
 
 import pandas as pd
 
-from pipeline_lib.core import DataContainer
-from pipeline_lib.core.steps.base import PipelineStep
-from pipeline_lib.utils.df_type_conversions import apply_all_dtype_conversions
+from ml_garden.core import DataContainer
+from ml_garden.core.steps.base import PipelineStep
+from ml_garden.utils.df_type_conversions import apply_all_dtype_conversions
 
 
 class FileType(Enum):

ml_garden/core/steps/tabular_split.py

@@ -4,10 +4,10 @@
 import pandas as pd
 from sklearn.model_selection import train_test_split
 
-from pipeline_lib.core import DataContainer
-from pipeline_lib.core.random_state_generator import get_random_state
-from pipeline_lib.core.steps.base import PipelineStep
-from pipeline_lib.utils.string_utils import concatenate_columns
+from ml_garden.core import DataContainer
+from ml_garden.core.random_state_generator import get_random_state
+from ml_garden.core.steps.base import PipelineStep
+from ml_garden.utils.string_utils import concatenate_columns
 
 
 class TabularSplitStep(PipelineStep):

ml_garden/implementation/tabular/xgboost/model.py

@@ -7,8 +7,8 @@
 import pandas as pd
 import xgboost as xgb
 
-from pipeline_lib.core.model import Model
-from pipeline_lib.utils import compression_utils
+from ml_garden.core.model import Model
+from ml_garden.utils import compression_utils
 
 logger = logging.getLogger(__file__)
 

tests/core/steps/test_calculate_features.py

@@ -2,8 +2,8 @@
 import pandas as pd
 import pytest
 
-from pipeline_lib.core import DataContainer
-from pipeline_lib.core.steps.calculate_features import (
+from ml_garden.core import DataContainer
+from ml_garden.core.steps.calculate_features import (
     CalculateFeaturesStep,
     UnsupportedFeatureError,
 )

tests/core/steps/test_calculate_metrics.py

@@ -1,8 +1,8 @@
 import pandas as pd
 import pytest
 
-from pipeline_lib.core import DataContainer
-from pipeline_lib.core.steps import CalculateMetricsStep
+from ml_garden.core import DataContainer
+from ml_garden.core.steps import CalculateMetricsStep
 
 
 @pytest.fixture

tests/core/steps/test_clean.py

@@ -1,8 +1,8 @@
 import pandas as pd
 import pytest
 
-from pipeline_lib.core import DataContainer
-from pipeline_lib.core.steps.clean import CleanStep
+from ml_garden.core import DataContainer
+from ml_garden.core.steps.clean import CleanStep
 
 
 @pytest.fixture

tests/core/steps/test_encoding.py

@@ -3,8 +3,8 @@
 import pandas.testing as pdt
 import pytest
 
-from pipeline_lib.core import DataContainer
-from pipeline_lib.core.steps import EncodeStep
+from ml_garden.core import DataContainer
+from ml_garden.core.steps import EncodeStep
 
 
 @pytest.fixture

tests/core/steps/test_fit_model.py

@@ -3,9 +3,9 @@
 import pandas as pd
 import pytest
 
-from pipeline_lib.core import DataContainer
-from pipeline_lib.core.model import Model
-from pipeline_lib.core.steps.fit_model import ModelStep, OptunaOptimizer
+from ml_garden.core import DataContainer
+from ml_garden.core.model import Model
+from ml_garden.core.steps.fit_model import ModelStep, OptunaOptimizer
 
 
 @pytest.fixture

tests/core/steps/test_generate.py

@@ -1,8 +1,8 @@
 import numpy as np
 import pytest
 
-from pipeline_lib.core import DataContainer
-from pipeline_lib.core.steps import GenerateStep
+from ml_garden.core import DataContainer
+from ml_garden.core.steps import GenerateStep
 
 
 # Fixture to create a sample CSV file for testing

tests/core/steps/test_tabular_split.py

@@ -2,8 +2,8 @@
 import pandas as pd
 import pytest
 
-from pipeline_lib.core import DataContainer
-from pipeline_lib.core.steps import TabularSplitStep
+from ml_garden.core import DataContainer
+from ml_garden.core.steps import TabularSplitStep
 
 
 @pytest.fixture

tests/core/test_model_registry.py

@@ -2,8 +2,8 @@
 
 import pytest
 
-from pipeline_lib.core.model import Model
-from pipeline_lib.core.model_registry import ModelClassNotFoundError, ModelRegistry
+from ml_garden.core.model import Model
+from ml_garden.core.model_registry import ModelClassNotFoundError, ModelRegistry
 
 
 class DummyModel(Model):

tests/core/test_pipeline.py

@@ -5,7 +5,7 @@
 import pandas as pd
 import pytest
 
-from pipeline_lib import Pipeline
+from ml_garden import Pipeline
 
 
 def test_simple_train_pipeline():

tests/core/test_step_registry.py

@@ -2,8 +2,8 @@
 
 import pytest
 
-from pipeline_lib.core.step_registry import StepClassNotFoundError, StepRegistry
-from pipeline_lib.core.steps.base import PipelineStep
+from ml_garden.core.step_registry import StepClassNotFoundError, StepRegistry
+from ml_garden.core.steps.base import PipelineStep
 
 
 class DummyStep(PipelineStep):