diff --git a/MANIFEST.in b/MANIFEST.in
index d2580a4b..d9087bf1 100644
--- a/MANIFEST.in
+++ b/MANIFEST.in
@@ -16,6 +16,19 @@ include setup.cfg
 include watex/utils/epsg.npy
 include .coveragerc
 
+# Include specific files from the 'watex' package
+include watex/utils/_openmp_helpers.pxd
+include watex/utils/espg.npy
+recursive-include watex/etc *.*
+include watex/wlog.yml
+recursive-include watex/wlogfiles *.txt
+
+# Include .pxd files located in the watex root and subdirectories
+global-include watex/*.pxd
+
+# Include 'examples' directory Python scripts and text files
+recursive-include examples *.py *.txt
+
 # exclude from sdist
 recursive-exclude asv_benchmarks *
 recursive-exclude examples *.png 
diff --git a/docs/conf.py b/docs/conf.py
index 75c45483..a09cb3bf 100644
--- a/docs/conf.py
+++ b/docs/conf.py
@@ -17,7 +17,7 @@
 import re 
 import time 
 
-import sphinx_gallery
+import sphinx_gallery # noqa 
 from sphinx_gallery.sorting import ExampleTitleSortKey
 
 
@@ -46,8 +46,10 @@
 copyright = f"2022-{time.strftime('%Y')}"
 author = 'K. Laurent Kouadio'
 # The full version, including alpha/beta/rc tags
-try : version = release = watex._version.version
-except : version = release = watex.__version__
+try :
+    version = release = watex._version.version
+except :
+    version = release = watex.__version__
 
 # -- General configuration ---------------------------------------------------
 
diff --git a/pyproject.toml b/pyproject.toml
index 6e4c35d9..d9a881cc 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,29 +1,85 @@
 [build-system]
-requires = ["setuptools >= 61.0.0",
-             "wheel", 
-             "setuptools_scm>=6.2", 
-             "Cython>=0.29.33",
-        ]
+requires = ["setuptools>=61.0.0", "wheel", "setuptools_scm>=6.2", "Cython>=0.29.33"]
 build-backend = "setuptools.build_meta"
 
 [project]
 name = "watex"
-version="0.3.0"
+version = "0.3.1"
+description = "Machine learning research in water exploration"
+readme = "README.md"
+authors = [{name = "Laurent Kouadio", email = "etanoyau@gmail.com"}]
+license = {file = "LICENSE"}
+keywords = ["exploration", "groundwater", "machine learning", "water", "hydro-geophysics"]
+classifiers = [
+    "Development Status :: 3 - Alpha",
+    "Intended Audience :: Science/Research",
+    "Intended Audience :: Developers",
+    "Topic :: Software Development",
+    "Topic :: Scientific/Engineering",
+    "Programming Language :: C",
+    "Programming Language :: Python",
+    "Programming Language :: Python :: 3.9",
+    "Programming Language :: Python :: 3.10",
+    "Programming Language :: Python :: 3.11",
+    "Programming Language :: Python :: Implementation :: CPython",
+    "Operating System :: OS Independent",
+    "Operating System :: Microsoft :: Windows",
+    "Operating System :: POSIX",
+    "Operating System :: Unix",
+]
+dependencies = [
+    "seaborn>=0.12.0",
+    "pandas>=1.4.0",
+    "Cython>=0.29.33",
+    "PyYAML>=5.0.0",
+    "openpyxl>=3.0.3",
+    "pyproj>=3.3.0",
+    "pycsamt>=1.1.2",
+    "tqdm>=4.64.1",
+    "tables>=3.6.0",
+    "scikit-learn==1.2.1",
+    "joblib>=1.2.0",
+    "threadpoolctl>=3.1.0",
+    "matplotlib==3.5.3",
+    "statsmodels>=0.13.1",
+    "numpy>=1.23.0",
+    "scipy>=1.9.0",
+    "h5py>=3.2.0",
+    "pytest"
+]
+
+requires-python = ">=3.9"
 
 [project.optional-dependencies]
-dev  = ["click", 
-       "missingno>=0.4.2", 
-       "yellowbrick>=1.5.0", 
-       "pyjanitor>=0.1.7", 
-       "mlxtend>=0.21"
- ]
+dev = [
+    "click",
+    "missingno>=0.4.2",
+    "yellowbrick>=1.5.0",
+    "pyjanitor>=0.1.7",
+    "mlxtend>=0.21",
+    "xgboost>=1.7.0",
+]
+
+[project.urls]
+"Home" = "https://watex.readthedocs.io"
+"Documentation" = "https://watex.readthedocs.io/en/latest/api_references.html"
+"Bugs Tracker" = "https://github.com/WEgeophysics/watex/issues"
+"Installation Guide" = "https://watex.readthedocs.io/en/latest/installation.html"
+"User Guide" = "https://watex.readthedocs.io/en/latest/user_guide.html"
+"Source" = "https://github.com/WEgeophysics/watex"
+"Download" = "https://pypi.org/project/watex/#files"
 
-[tool.setuptools.dynamic]
-version = {attr = "watex._version.version"}
 
 [tool.setuptools_scm]
 write_to = "watex/_version.py"
 
+[project.scripts]
+wx = "watex.cli:cli"
+version = "watex.cli:version"
+
+[tool.setuptools.dynamic]
+version = {attr = "watex._version.version"}
+
 [tool.pytest.ini_options]
 minversion = "6.0"
 doctest_optionflags = "NORMALIZE_WHITESPACE IGNORE_EXCEPTION_DETAIL"
@@ -40,4 +96,4 @@ exclude = '''
   | docs/_build
   | docs/glr_examples
 )/
-'''
\ No newline at end of file
+'''
diff --git a/setup.cfg b/setup.cfg
index 5b197895..724ca83a 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -69,3 +69,7 @@ ignore =
 [codespell]
 skip = ./.git,./.mypy_cache,./docs/_build,./docs/glr_examples,./docs/modules/generated
 ignore-words = build_tools/codespell_ignore_words.txt
+
+[options.package_data]
+watex = utils/_openmp_helpers.pxd, utils/espg.npy, etc/*, wlog.yml, wlogfiles/*.txt
+* = *.pxd, data/*, examples/*.py, examples/*.txt
diff --git a/setup.py b/setup.py
index 0033766c..b96e3cf8 100644
--- a/setup.py
+++ b/setup.py
@@ -16,7 +16,7 @@
 # We can actually import watex version from 
 # in editable mode :$ python -m pip install -e .
 try: 
-    import watex  # noqa
+    import watex  
     VERSION = watex.__version__
 except: VERSION ='0.3.1'
 # set global variables 
diff --git a/watex/_version.py b/watex/_version.py
index bc02bc27..747927e0 100644
--- a/watex/_version.py
+++ b/watex/_version.py
@@ -1,4 +1,4 @@
 # file generated by setuptools_scm
 # don't change, don't track in version control
-__version__ = version = '0.3.0.dev1+g10707dc.d20230709'
-__version_tuple__ = version_tuple = (0, 3, 0, 'dev1', 'g10707dc.d20230709')
+__version__ = version = '0.3.1.dev1+g10707dc.d20230709'
+__version_tuple__ = version_tuple = (0, 3, 2, 'dev1', 'g10707dc.d20230709')
diff --git a/watex/cases/modeling.py b/watex/cases/modeling.py
index 559de8bf..d10e1ff2 100644
--- a/watex/cases/modeling.py
+++ b/watex/cases/modeling.py
@@ -46,7 +46,6 @@
 
 # import  watex.exceptions as Wex 
 # import  watex.decorators as deco
-
 _logger =watexlog().get_watex_logger(__name__)
 
 __all__=["BaseModel"] 
diff --git a/watex/etc/__memory.pkl b/watex/etc/__memory.pkl
index a02b2c0d..24c3c33b 100644
Binary files a/watex/etc/__memory.pkl and b/watex/etc/__memory.pkl differ
diff --git a/watex/exlib/__init__.py b/watex/exlib/__init__.py
index 1b07bce6..5e6631cb 100644
--- a/watex/exlib/__init__.py
+++ b/watex/exlib/__init__.py
@@ -1,162 +1,114 @@
-""" 
-'Exlib' sub-package is composed of best :term:`Machine Learning` libraries called for 
-:mod:`~watex.models` prediction with common datasets. 
-`scikit-learn <https://scikit-learn.org/>`__ and 
-`gradient boosting machine <https://docs.h2o.ai/h2o/latest-stable/h2o-docs/data-science/gbm.html>`__ (GBM)
-especially (XGBoost) are build as top module for general prediction purpose.
-
 """
-from .sklearn import ( 
-        BaseEstimator,
-        TransformerMixin,
-        ClassifierMixin, 
-        clone, 
-        KMeans, 
-        make_column_transformer,
-        make_column_selector , 
-        ColumnTransformer,
-        ShrunkCovariance, 
-        LedoitWolf, 
-        FactorAnalysis,
-        PCA ,
-        IncrementalPCA,
-        KernelPCA, 
-        DummyClassifier, 
-        SelectKBest, 
-        f_classif,
-        SelectFromModel, 
-        SimpleImputer,
-        permutation_importance,
-        LogisticRegression, 
-        SGDClassifier,
-        confusion_matrix,
-        classification_report ,
-        mean_squared_error, 
-        f1_score,
-        accuracy_score,
-        precision_recall_curve, 
-        precision_score,
-        recall_score, 
-        roc_auc_score, 
-        roc_curve,
-        silhouette_samples, 
-        make_scorer,
-        matthews_corrcoef, 
-        train_test_split , 
-        validation_curve, 
-        StratifiedShuffleSplit , 
-        RandomizedSearchCV,
-        GridSearchCV, 
-        learning_curve , 
-        cross_val_score,
-        cross_val_predict,
-        KNeighborsClassifier,
-        Pipeline, 
-        make_pipeline ,
-        FeatureUnion, 
-        _name_estimators,
-        OneHotEncoder,
-        PolynomialFeatures, 
-        RobustScaler ,
-        OrdinalEncoder, 
-        StandardScaler,
-        MinMaxScaler, 
-        LabelBinarizer,
-        Normalizer,
-        LabelEncoder,
-        SVC, 
-        LinearSVC, 
-        LinearSVR, 
-        DecisionTreeClassifier,
-        RandomForestClassifier,
-        AdaBoostClassifier, 
-        VotingClassifier, 
-        BaggingClassifier,
-        StackingClassifier , 
-        ExtraTreesClassifier, 
-        skl_ensemble_, 
-        sklearndoc, 
-        _HAS_ENSEMBLE_
-        )
+The 'Exlib' sub-package aggregates prominent Machine Learning libraries for use in 
+prediction tasks with common datasets within the `watex.models` framework, notably 
+including `scikit-learn <https://scikit-learn.org/>`__.
+"""
+
+import importlib
+
+def __getattr__(name):
+    """
+    Dynamically imports scikit-learn components upon access through the 
+    watex.exlib.sklearn namespace, facilitating seamless integration of scikit-learn 
+    objects into watex workflows.
+
+    Parameters:
+    - name (str): The name of the scikit-learn component (module, class, or function) 
+      being accessed.
+
+    Returns:
+    - The dynamically imported scikit-learn component.
+
+    Raises:
+    - AttributeError: If the specified scikit-learn component cannot be found or 
+      does not exist within the scikit-learn library.
+    
+    This method leverages a predefined mapping (`sklearn_component_mapping`) that 
+    associates simplified attribute names with their corresponding modules in 
+    scikit-learn, enabling both explicit and implicit module path resolution.
+    """
+    sklearn_component_mapping = {
+        'BaseEstimator': 'sklearn.base',
+        'TransformerMixin': 'sklearn.base',
+        'ClassifierMixin': 'sklearn.base',
+        'clone': 'sklearn.base',
+        'KMeans': 'sklearn.cluster',
+        'make_column_transformer': 'sklearn.compose',
+        'make_column_selector': 'sklearn.compose',
+        'ColumnTransformer': 'sklearn.compose',
+        'ShrunkCovariance': 'sklearn.covariance',
+        'LedoitWolf': 'sklearn.covariance',
+        'FactorAnalysis': 'sklearn.decomposition',
+        'PCA': 'sklearn.decomposition',
+        'IncrementalPCA': 'sklearn.decomposition',
+        'KernelPCA': 'sklearn.decomposition',
+        'DummyClassifier': 'sklearn.dummy',
+        'SelectKBest': 'sklearn.feature_selection',
+        'f_classif': 'sklearn.feature_selection',
+        'SelectFromModel': 'sklearn.feature_selection',
+        'SimpleImputer': 'sklearn.impute',
+        'permutation_importance': 'sklearn.inspection',
+        'LogisticRegression': 'sklearn.linear_model',
+        'SGDClassifier': 'sklearn.linear_model',
+        'confusion_matrix': 'sklearn.metrics',
+        'classification_report': 'sklearn.metrics',
+        'mean_squared_error': 'sklearn.metrics',
+        'f1_score': 'sklearn.metrics',
+        'accuracy_score': 'sklearn.metrics',
+        'precision_recall_curve': 'sklearn.metrics',
+        'precision_score': 'sklearn.metrics',
+        'recall_score': 'sklearn.metrics',
+        'roc_auc_score': 'sklearn.metrics',
+        'roc_curve': 'sklearn.metrics',
+        'silhouette_samples': 'sklearn.metrics',
+        'make_scorer': 'sklearn.metrics',
+        'matthews_corrcoef': 'sklearn.metrics',
+        'train_test_split': 'sklearn.model_selection',
+        'validation_curve': 'sklearn.model_selection',
+        'StratifiedShuffleSplit': 'sklearn.model_selection',
+        'RandomizedSearchCV': 'sklearn.model_selection',
+        'GridSearchCV': 'sklearn.model_selection',
+        'learning_curve': 'sklearn.model_selection',
+        'cross_val_score': 'sklearn.model_selection',
+        'cross_val_predict': 'sklearn.model_selection',
+        'KNeighborsClassifier': 'sklearn.neighbors',
+        'Pipeline': 'sklearn.pipeline',
+        'make_pipeline': 'sklearn.pipeline',
+        'FeatureUnion': 'sklearn.pipeline',
+        '_name_estimators': 'sklearn.utils',
+        'OneHotEncoder': 'sklearn.preprocessing',
+        'PolynomialFeatures': 'sklearn.preprocessing',
+        'RobustScaler': 'sklearn.preprocessing',
+        'OrdinalEncoder': 'sklearn.preprocessing',
+        'StandardScaler': 'sklearn.preprocessing',
+        'MinMaxScaler': 'sklearn.preprocessing',
+        'LabelBinarizer': 'sklearn.preprocessing',
+        'Normalizer': 'sklearn.preprocessing',
+        'LabelEncoder': 'sklearn.preprocessing',
+        'SVC': 'sklearn.svm',
+        'LinearSVC': 'sklearn.svm',
+        'LinearSVR': 'sklearn.svm',
+        'DecisionTreeClassifier': 'sklearn.tree',
+        'RandomForestClassifier': 'sklearn.ensemble',
+        'AdaBoostClassifier': 'sklearn.ensemble',
+        'VotingClassifier': 'sklearn.ensemble',
+        'BaggingClassifier': 'sklearn.ensemble',
+        'StackingClassifier': 'sklearn.ensemble',
+        'ExtraTreesClassifier': 'sklearn.ensemble',
+    }
+    # Check if the component is in the predefined mapping
+    if name in sklearn_component_mapping:
+        full_module_path = sklearn_component_mapping[name]
+        module = importlib.import_module(full_module_path)
+        return getattr(module, name)
+    
+    # Default import behavior for unmapped names
+    try:
+        module = importlib.import_module(f"sklearn.{name.lower()}")
+        return module
+    except ImportError as e:
+        raise AttributeError(f"scikit-learn component '{name}' not found") from e
+
+
 
-from .gbm import ( 
-    xgboost, 
-    xgboostdoc, 
-    XGBClassifier 
-    )
 
-__all__=[
-    "BaseEstimator",
-    "TransformerMixin",
-    "ClassifierMixin", 
-    "clone", 
-    "KMeans", 
-    "make_column_transformer",
-    'make_column_selector' , 
-    'ColumnTransformer',
-    'ShrunkCovariance', 
-    'LedoitWolf', 
-    'FactorAnalysis',
-    'PCA' ,
-    'IncrementalPCA',
-    'KernelPCA', 
-    'DummyClassifier', 
-    'SelectKBest', 
-    'f_classif',
-    'SelectFromModel', 
-    'SimpleImputer',
-    'permutation_importance',
-    'LogisticRegression', 
-    'SGDClassifier',
-    'confusion_matrix',
-    'classification_report' ,
-    'mean_squared_error', 
-    'f1_score',
-    'accuracy_score',
-    'precision_recall_curve', 
-    'precision_score',
-    'recall_score', 
-    'roc_auc_score', 
-    'roc_curve',
-    'silhouette_samples', 
-    'make_scorer',
-    'matthews_corrcoef', 
-    'train_test_split' , 
-    'validation_curve', 
-    'StratifiedShuffleSplit' , 
-    'RandomizedSearchCV',
-    'GridSearchCV', 
-    'learning_curve' , 
-    'cross_val_score',
-    'cross_val_predict',
-    'KNeighborsClassifier',
-    'Pipeline', 
-    'make_pipeline' ,
-    'FeatureUnion', 
-    '_name_estimators',
-    'OneHotEncoder',
-    'PolynomialFeatures', 
-    'RobustScaler' ,
-    'OrdinalEncoder', 
-    'StandardScaler',
-    'MinMaxScaler', 
-    'LabelBinarizer',
-    'Normalizer',
-    'LabelEncoder',
-    'SVC', 
-    'LinearSVC', 
-    'LinearSVR', 
-    'DecisionTreeClassifier',
-    'RandomForestClassifier',
-    'AdaBoostClassifier', 
-    'VotingClassifier', 
-    'BaggingClassifier',
-    'StackingClassifier' , 
-    'ExtraTreesClassifier', 
-    'skl_ensemble_', 
-    'sklearndoc', 
-    '_HAS_ENSEMBLE_',
-    'xgboost', 
-    'xgboostdoc', 
-    'XGBClassifier'
-    ]
\ No newline at end of file
diff --git a/watex/exlib/sklearn.py b/watex/exlib/sklearn.py
index 617cf61e..5d0d65b9 100644
--- a/watex/exlib/sklearn.py
+++ b/watex/exlib/sklearn.py
@@ -86,6 +86,79 @@
 else :
     _HAS_ENSEMBLE_=True
     
+__all__=[
+    "BaseEstimator",
+    "TransformerMixin",
+    "ClassifierMixin", 
+    "clone", 
+    "KMeans", 
+    "make_column_transformer",
+    'make_column_selector' , 
+    'ColumnTransformer',
+    'ShrunkCovariance', 
+    'LedoitWolf', 
+    'FactorAnalysis',
+    'PCA' ,
+    'IncrementalPCA',
+    'KernelPCA', 
+    'DummyClassifier', 
+    'SelectKBest', 
+    'f_classif',
+    'SelectFromModel', 
+    'SimpleImputer',
+    'permutation_importance',
+    'LogisticRegression', 
+    'SGDClassifier',
+    'confusion_matrix',
+    'classification_report' ,
+    'mean_squared_error', 
+    'f1_score',
+    'accuracy_score',
+    'precision_recall_curve', 
+    'precision_score',
+    'recall_score', 
+    'roc_auc_score', 
+    'roc_curve',
+    'silhouette_samples', 
+    'make_scorer',
+    'matthews_corrcoef', 
+    'train_test_split' , 
+    'validation_curve', 
+    'StratifiedShuffleSplit' , 
+    'RandomizedSearchCV',
+    'GridSearchCV', 
+    'learning_curve' , 
+    'cross_val_score',
+    'cross_val_predict',
+    'KNeighborsClassifier',
+    'Pipeline', 
+    'make_pipeline' ,
+    'FeatureUnion', 
+    '_name_estimators',
+    'OneHotEncoder',
+    'PolynomialFeatures', 
+    'RobustScaler' ,
+    'OrdinalEncoder', 
+    'StandardScaler',
+    'MinMaxScaler', 
+    'LabelBinarizer',
+    'Normalizer',
+    'LabelEncoder',
+    'SVC', 
+    'LinearSVC', 
+    'LinearSVR', 
+    'DecisionTreeClassifier',
+    'RandomForestClassifier',
+    'AdaBoostClassifier', 
+    'VotingClassifier', 
+    'BaggingClassifier',
+    'StackingClassifier' , 
+    'ExtraTreesClassifier', 
+    'skl_ensemble_', 
+    'sklearndoc', 
+    '_HAS_ENSEMBLE_'
+    ]
+
 from sklearn.ensemble import  (  
     AdaBoostClassifier, 
     VotingClassifier, 
@@ -109,6 +182,7 @@
     ClassifierMixin, 
     clone 
 )
+
 from sklearn.cluster import KMeans
 from sklearn.compose import ( 
     make_column_transformer, 
@@ -188,77 +262,3 @@
 from sklearn.tree import DecisionTreeClassifier
 
 
-__all__=[
-    "BaseEstimator",
-    "TransformerMixin",
-    "ClassifierMixin", 
-    "clone", 
-    "KMeans", 
-    "make_column_transformer",
-    'make_column_selector' , 
-    'ColumnTransformer',
-    'ShrunkCovariance', 
-    'LedoitWolf', 
-    'FactorAnalysis',
-    'PCA' ,
-    'IncrementalPCA',
-    'KernelPCA', 
-    'DummyClassifier', 
-    'SelectKBest', 
-    'f_classif',
-    'SelectFromModel', 
-    'SimpleImputer',
-    'permutation_importance',
-    'LogisticRegression', 
-    'SGDClassifier',
-    'confusion_matrix',
-    'classification_report' ,
-    'mean_squared_error', 
-    'f1_score',
-    'accuracy_score',
-    'precision_recall_curve', 
-    'precision_score',
-    'recall_score', 
-    'roc_auc_score', 
-    'roc_curve',
-    'silhouette_samples', 
-    'make_scorer',
-    'matthews_corrcoef', 
-    'train_test_split' , 
-    'validation_curve', 
-    'StratifiedShuffleSplit' , 
-    'RandomizedSearchCV',
-    'GridSearchCV', 
-    'learning_curve' , 
-    'cross_val_score',
-    'cross_val_predict',
-    'KNeighborsClassifier',
-    'Pipeline', 
-    'make_pipeline' ,
-    'FeatureUnion', 
-    '_name_estimators',
-    'OneHotEncoder',
-    'PolynomialFeatures', 
-    'RobustScaler' ,
-    'OrdinalEncoder', 
-    'StandardScaler',
-    'MinMaxScaler', 
-    'LabelBinarizer',
-    'Normalizer',
-    'LabelEncoder',
-    'SVC', 
-    'LinearSVC', 
-    'LinearSVR', 
-    'DecisionTreeClassifier',
-    'RandomForestClassifier',
-    'AdaBoostClassifier', 
-    'VotingClassifier', 
-    'BaggingClassifier',
-    'StackingClassifier' , 
-    'ExtraTreesClassifier', 
-    'skl_ensemble_', 
-    'sklearndoc', 
-    '_HAS_ENSEMBLE_'
-    ]
-
-