From 86edc6570df54fa986456e8dfdcf8d929e50cbf5 Mon Sep 17 00:00:00 2001 From: Diego Marvid Date: Mon, 18 Mar 2024 12:49:55 -0300 Subject: [PATCH] add generate and clean steps to core --- .gitignore | 4 + pipeline_lib/core/__init__.py | 1 - pipeline_lib/core/step_registry.py | 2 +- pipeline_lib/core/steps/__init__.py | 2 + pipeline_lib/core/steps/augment.py | 3 +- pipeline_lib/core/steps/base.py | 2 +- pipeline_lib/core/steps/calculate_features.py | 3 +- pipeline_lib/core/steps/calculate_metrics.py | 3 +- pipeline_lib/core/steps/calculate_reports.py | 3 +- pipeline_lib/core/steps/clean.py | 69 + pipeline_lib/core/steps/encode.py | 3 +- .../core/steps/explainer_dashboard.py | 2 +- pipeline_lib/core/steps/fit_encoders.py | 3 +- pipeline_lib/core/steps/fit_model.py | 3 +- pipeline_lib/core/steps/generate.py | 65 + pipeline_lib/core/steps/input_scaling.py | 3 +- pipeline_lib/core/steps/predict.py | 3 +- pipeline_lib/core/steps/tabular_split.py | 3 +- pipeline_lib/core/steps/target_scaling.py | 3 +- .../tabular/xgboost/fit_model.py | 17 +- poetry.lock | 2924 ++++++++--------- 21 files changed, 1572 insertions(+), 1549 deletions(-) create mode 100644 pipeline_lib/core/steps/clean.py create mode 100644 pipeline_lib/core/steps/generate.py diff --git a/.gitignore b/.gitignore index 2a7ca1a..912a3d9 100644 --- a/.gitignore +++ b/.gitignore @@ -6,6 +6,10 @@ __pycache__/ # C extensions *.so +*.joblib +*.bin +*.json + # ignore examples folder examples/ diff --git a/pipeline_lib/core/__init__.py b/pipeline_lib/core/__init__.py index 3e73bca..eb20821 100644 --- a/pipeline_lib/core/__init__.py +++ b/pipeline_lib/core/__init__.py @@ -1,3 +1,2 @@ from .data_container import DataContainer # noqa: F401 -from .pipeline import Pipeline # noqa: F401 from .steps import PipelineStep # noqa: F401 diff --git a/pipeline_lib/core/step_registry.py b/pipeline_lib/core/step_registry.py index 9a1b800..e415eba 100644 --- a/pipeline_lib/core/step_registry.py +++ b/pipeline_lib/core/step_registry.py @@ -3,7 +3,7 @@ import os import pkgutil -from pipeline_lib.core.steps import PipelineStep +from pipeline_lib.core.steps.base import PipelineStep class StepClassNotFoundError(Exception): diff --git a/pipeline_lib/core/steps/__init__.py b/pipeline_lib/core/steps/__init__.py index 9c8593c..779f096 100644 --- a/pipeline_lib/core/steps/__init__.py +++ b/pipeline_lib/core/steps/__init__.py @@ -3,10 +3,12 @@ from .calculate_features import CalculateFeaturesStep # noqa: F401 from .calculate_metrics import CalculateMetricsStep # noqa: F401 from .calculate_reports import CalculateReportsStep # noqa: F401 +from .clean import CleanStep # noqa: F401 from .encode import EncodeStep # noqa: F401 from .explainer_dashboard import ExplainerDashboardStep # noqa: F401 from .fit_encoders import FitEncodersStep # noqa: F401 from .fit_model import FitModelStep # noqa: F401 +from .generate import GenerateStep # noqa: F401 from .input_scaling import InputScalingStep # noqa: F401 from .predict import PredictStep # noqa: F401 from .tabular_split import TabularSplitStep # noqa: F401 diff --git a/pipeline_lib/core/steps/augment.py b/pipeline_lib/core/steps/augment.py index 895d5c8..21708d7 100644 --- a/pipeline_lib/core/steps/augment.py +++ b/pipeline_lib/core/steps/augment.py @@ -1,8 +1,7 @@ from typing import Optional from pipeline_lib.core import DataContainer - -from .base import PipelineStep +from pipeline_lib.core.steps.base import PipelineStep class AugmentStep(PipelineStep): diff --git a/pipeline_lib/core/steps/base.py b/pipeline_lib/core/steps/base.py index 9530368..2381422 100644 --- a/pipeline_lib/core/steps/base.py +++ b/pipeline_lib/core/steps/base.py @@ -2,7 +2,7 @@ from abc import ABC, abstractmethod from typing import Optional -from pipeline_lib.core import DataContainer +from pipeline_lib.core.data_container import DataContainer class PipelineStep(ABC): diff --git a/pipeline_lib/core/steps/calculate_features.py b/pipeline_lib/core/steps/calculate_features.py index eb145c1..0316cb1 100644 --- a/pipeline_lib/core/steps/calculate_features.py +++ b/pipeline_lib/core/steps/calculate_features.py @@ -1,8 +1,7 @@ from typing import Optional from pipeline_lib.core import DataContainer - -from .base import PipelineStep +from pipeline_lib.core.steps.base import PipelineStep class CalculateFeaturesStep(PipelineStep): diff --git a/pipeline_lib/core/steps/calculate_metrics.py b/pipeline_lib/core/steps/calculate_metrics.py index 85454d3..8589283 100644 --- a/pipeline_lib/core/steps/calculate_metrics.py +++ b/pipeline_lib/core/steps/calculate_metrics.py @@ -2,8 +2,7 @@ from sklearn.metrics import mean_absolute_error, mean_squared_error from pipeline_lib.core import DataContainer - -from .base import PipelineStep +from pipeline_lib.core.steps.base import PipelineStep class CalculateMetricsStep(PipelineStep): diff --git a/pipeline_lib/core/steps/calculate_reports.py b/pipeline_lib/core/steps/calculate_reports.py index 75129cd..39cab38 100644 --- a/pipeline_lib/core/steps/calculate_reports.py +++ b/pipeline_lib/core/steps/calculate_reports.py @@ -1,8 +1,7 @@ from typing import Optional from pipeline_lib.core import DataContainer - -from .base import PipelineStep +from pipeline_lib.core.steps.base import PipelineStep class CalculateReportsStep(PipelineStep): diff --git a/pipeline_lib/core/steps/clean.py b/pipeline_lib/core/steps/clean.py new file mode 100644 index 0000000..0341f5a --- /dev/null +++ b/pipeline_lib/core/steps/clean.py @@ -0,0 +1,69 @@ +from typing import Optional + +from pipeline_lib.core import DataContainer +from pipeline_lib.core.steps.base import PipelineStep + + +class CleanStep(PipelineStep): + def __init__( + self, + fill_missing: Optional[dict] = None, + remove_outliers: Optional[dict] = None, + convert_dtypes: Optional[dict] = None, + ): + self.init_logger() + self.fill_missing = fill_missing + self.remove_outliers = remove_outliers + self.convert_dtypes = convert_dtypes + + def execute(self, data: DataContainer) -> DataContainer: + self.logger.info("Cleaning tabular data...") + + df = data[DataContainer.RAW] + + if self.fill_missing: + for column, fill_value in self.fill_missing.items(): + if column in df.columns: + df[column].fillna(fill_value, inplace=True) + self.logger.info( + f"Filled missing values in column '{column}' with {fill_value}" + ) + else: + self.logger.warning(f"Column '{column}' not found in the DataFrame") + + if self.remove_outliers: + for column, method in self.remove_outliers.items(): + if column in df.columns: + if method == "clip": + q1 = df[column].quantile(0.25) + q3 = df[column].quantile(0.75) + iqr = q3 - q1 + lower_bound = q1 - (1.5 * iqr) + upper_bound = q3 + (1.5 * iqr) + df[column] = df[column].clip(lower=lower_bound, upper=upper_bound) + self.logger.info(f"Clipped outliers in column '{column}'") + elif method == "drop": + q1 = df[column].quantile(0.25) + q3 = df[column].quantile(0.75) + iqr = q3 - q1 + lower_bound = q1 - (1.5 * iqr) + upper_bound = q3 + (1.5 * iqr) + outliers = (df[column] < lower_bound) | (df[column] > upper_bound) + df = df[~outliers] + self.logger.info(f"Dropped outliers in column '{column}'") + else: + self.logger.warning(f"Unsupported outlier removal method '{method}'") + else: + self.logger.warning(f"Column '{column}' not found in the DataFrame") + + if self.convert_dtypes: + for column, dtype in self.convert_dtypes.items(): + if column in df.columns: + df[column] = df[column].astype(dtype) + self.logger.info(f"Converted column '{column}' to {dtype}") + else: + self.logger.warning(f"Column '{column}' not found in the DataFrame") + + data[DataContainer.CLEAN] = df + + return data diff --git a/pipeline_lib/core/steps/encode.py b/pipeline_lib/core/steps/encode.py index 5e07ceb..c81951b 100644 --- a/pipeline_lib/core/steps/encode.py +++ b/pipeline_lib/core/steps/encode.py @@ -1,8 +1,7 @@ from typing import Optional from pipeline_lib.core import DataContainer - -from .base import PipelineStep +from pipeline_lib.core.steps.base import PipelineStep class EncodeStep(PipelineStep): diff --git a/pipeline_lib/core/steps/explainer_dashboard.py b/pipeline_lib/core/steps/explainer_dashboard.py index 41d3802..5a652c5 100644 --- a/pipeline_lib/core/steps/explainer_dashboard.py +++ b/pipeline_lib/core/steps/explainer_dashboard.py @@ -1,7 +1,7 @@ from explainerdashboard import RegressionExplainer from pipeline_lib.core import DataContainer -from pipeline_lib.core.steps import PipelineStep +from pipeline_lib.core.steps.base import PipelineStep class ExplainerDashboardStep(PipelineStep): diff --git a/pipeline_lib/core/steps/fit_encoders.py b/pipeline_lib/core/steps/fit_encoders.py index 87f352e..177949e 100644 --- a/pipeline_lib/core/steps/fit_encoders.py +++ b/pipeline_lib/core/steps/fit_encoders.py @@ -1,8 +1,7 @@ from typing import Optional from pipeline_lib.core import DataContainer - -from .base import PipelineStep +from pipeline_lib.core.steps.base import PipelineStep class FitEncodersStep(PipelineStep): diff --git a/pipeline_lib/core/steps/fit_model.py b/pipeline_lib/core/steps/fit_model.py index 6103a8d..4eaeef2 100644 --- a/pipeline_lib/core/steps/fit_model.py +++ b/pipeline_lib/core/steps/fit_model.py @@ -1,8 +1,7 @@ from typing import Optional from pipeline_lib.core import DataContainer - -from .base import PipelineStep +from pipeline_lib.core.steps.base import PipelineStep class FitModelStep(PipelineStep): diff --git a/pipeline_lib/core/steps/generate.py b/pipeline_lib/core/steps/generate.py new file mode 100644 index 0000000..6c5173b --- /dev/null +++ b/pipeline_lib/core/steps/generate.py @@ -0,0 +1,65 @@ +import os +from enum import Enum + +import pandas as pd + +from pipeline_lib.core import DataContainer +from pipeline_lib.core.steps.base import PipelineStep + + +class FileType(Enum): + CSV = ".csv" + PARQUET = ".parquet" + + +class GenerateStep(PipelineStep): + def __init__(self, path: str, **kwargs): + self.init_logger() + self.file_path = path + self.kwargs = kwargs + + def execute(self, data: DataContainer) -> DataContainer: + self.logger.info(f"Generating data from file: {self.file_path}") + + if not os.path.exists(self.file_path): + raise FileNotFoundError(f"File not found: {self.file_path}") + + file_type = self._infer_file_type() + + if file_type == FileType.CSV: + df = self._read_csv() + elif file_type == FileType.PARQUET: + df = self._read_parquet() + else: + raise ValueError(f"Unsupported file type: {file_type}") + + data[DataContainer.RAW] = df + + self.logger.info(f"Generated DataFrame with shape: {df.shape}") + + return data + + def _infer_file_type(self) -> FileType: + _, file_extension = os.path.splitext(self.file_path) + file_extension = file_extension.lower() + + try: + return FileType(file_extension) + except ValueError: + raise ValueError(f"Unsupported file extension: {file_extension}") + + def _read_csv(self) -> pd.DataFrame: + kwargs = self.kwargs.copy() + index_col = kwargs.pop("index", None) + df = pd.read_csv(self.file_path, **kwargs) + if index_col is not None: + df.set_index(index_col, inplace=True) + return df + + def _read_parquet(self) -> pd.DataFrame: + kwargs = self.kwargs.copy() + index_col = kwargs.pop("index", None) + df = pd.read_parquet(self.file_path, **kwargs) + if index_col is not None: + df.set_index(index_col, inplace=True) + return df diff --git a/pipeline_lib/core/steps/input_scaling.py b/pipeline_lib/core/steps/input_scaling.py index 128b0cd..18b826b 100644 --- a/pipeline_lib/core/steps/input_scaling.py +++ b/pipeline_lib/core/steps/input_scaling.py @@ -1,8 +1,7 @@ from typing import Optional from pipeline_lib.core import DataContainer - -from .base import PipelineStep +from pipeline_lib.core.steps.base import PipelineStep class InputScalingStep(PipelineStep): diff --git a/pipeline_lib/core/steps/predict.py b/pipeline_lib/core/steps/predict.py index a8b5a79..6da0a99 100644 --- a/pipeline_lib/core/steps/predict.py +++ b/pipeline_lib/core/steps/predict.py @@ -1,8 +1,7 @@ from typing import Optional from pipeline_lib.core import DataContainer - -from .base import PipelineStep +from pipeline_lib.core.steps.base import PipelineStep class PredictStep(PipelineStep): diff --git a/pipeline_lib/core/steps/tabular_split.py b/pipeline_lib/core/steps/tabular_split.py index c6333cf..ae5673b 100644 --- a/pipeline_lib/core/steps/tabular_split.py +++ b/pipeline_lib/core/steps/tabular_split.py @@ -1,8 +1,7 @@ from sklearn.model_selection import train_test_split from pipeline_lib.core import DataContainer - -from .base import PipelineStep +from pipeline_lib.core.steps.base import PipelineStep class TabularSplitStep(PipelineStep): diff --git a/pipeline_lib/core/steps/target_scaling.py b/pipeline_lib/core/steps/target_scaling.py index 3dad235..cb2f83a 100644 --- a/pipeline_lib/core/steps/target_scaling.py +++ b/pipeline_lib/core/steps/target_scaling.py @@ -1,8 +1,7 @@ from typing import Optional from pipeline_lib.core import DataContainer - -from .base import PipelineStep +from pipeline_lib.core.steps.base import PipelineStep class TargetScalingStep(PipelineStep): diff --git a/pipeline_lib/implementation/tabular/xgboost/fit_model.py b/pipeline_lib/implementation/tabular/xgboost/fit_model.py index 3b43823..6200ee0 100644 --- a/pipeline_lib/implementation/tabular/xgboost/fit_model.py +++ b/pipeline_lib/implementation/tabular/xgboost/fit_model.py @@ -40,6 +40,11 @@ def __init__( self.xgb_params = xgb_params self.optuna_params = optuna_params + + if save_path: + if not save_path.endswith(".joblib"): + raise ValueError("Only joblib format is supported for saving the model.") + self.save_path = save_path def execute(self, data: DataContainer) -> DataContainer: @@ -90,15 +95,9 @@ def execute(self, data: DataContainer) -> DataContainer: # Save the model to the data container data[DataContainer.MODEL] = model - # save model to disk - save_path = self.save_path - - if save_path: - if not save_path.endswith(".joblib"): - raise ValueError("Only joblib format is supported for saving the model.") - self.logger.info(f"Saving the model to {save_path}") - dump(model, save_path) - + if self.save_path: + self.logger.info(f"Saving the model to {self.save_path}") + dump(model, self.save_path) return data def optimize_with_optuna(self, X_train, y_train, X_valid, y_valid, optuna_params): diff --git a/poetry.lock b/poetry.lock index 2be3ece..b64460b 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,10 +1,15 @@ +# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. + [[package]] name = "alembic" version = "1.13.1" description = "A database migration tool for SQLAlchemy." -category = "main" optional = false python-versions = ">=3.8" +files = [ + {file = "alembic-1.13.1-py3-none-any.whl", hash = "sha256:2edcc97bed0bd3272611ce3a98d98279e9c209e7186e43e75bbb1b2bdfdbcc43"}, + {file = "alembic-1.13.1.tar.gz", hash = "sha256:4932c8558bf68f2ee92b9bbcb8218671c627064d5b08939437af6d77dc05e595"}, +] 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