remove dependencies and move some to optional

Author: SimonBlanke

docs/source/installation.rst

@@ -9,15 +9,15 @@ This page covers various ways to install Surfaces and its dependencies.
 Requirements
 ============
 
-Surfaces requires:
+Surfaces has minimal core requirements:
 
 - Python |min_python| or higher
 - NumPy >= 1.18.1
-- pandas
-- matplotlib
-- plotly
-- scikit-learn
-- search-data-collector >= 0.6.0
+
+Optional dependencies for additional features:
+
+- **Visualization**: matplotlib, plotly
+- **Machine Learning functions**: scikit-learn
 
 Installing from PyPI
 ====================
@@ -26,26 +26,44 @@ The recommended way to install Surfaces is via pip:
 
 .. code-block:: bash
 
+    # Minimal install (algebraic + engineering functions only)
     pip install surfaces
 
-This will install Surfaces and all required dependencies.
+    # With visualization support
+    pip install surfaces[viz]
+
+    # With machine learning functions
+    pip install surfaces[ml]
+
+    # Full installation (all features)
+    pip install surfaces[full]
+
+The minimal installation includes all algebraic (mathematical) and engineering
+test functions. These require only NumPy and are ideal for CI/CD pipelines
+where minimal dependencies are preferred.
 
 Installing with Extras
 ======================
 
-For development or testing, you can install additional dependencies:
+Available optional dependency groups:
 
 .. code-block:: bash
 
+    # Visualization (matplotlib + plotly)
+    pip install surfaces[viz]
+
+    # Machine learning functions (scikit-learn)
+    pip install surfaces[ml]
+
+    # All optional features
+    pip install surfaces[full]
+
     # Development dependencies
     pip install surfaces[dev]
 
     # Test dependencies
     pip install surfaces[test]
 
-    # All extras
-    pip install surfaces[dev,test]
-
 Installing from Source
 ======================
 
@@ -116,11 +134,18 @@ Troubleshooting
 Import Errors
 -------------
 
-If you get import errors, make sure all dependencies are installed:
+If you get import errors for visualization or ML functions:
 
 .. code-block:: bash
 
-    pip install numpy pandas matplotlib plotly scikit-learn
+    # For visualization functions
+    pip install surfaces[viz]
+
+    # For machine learning functions
+    pip install surfaces[ml]
+
+    # For all features
+    pip install surfaces[full]
 
 Version Conflicts
 -----------------

pyproject.toml

@@ -33,28 +33,42 @@ classifiers=[
 ]
 dependencies = [
     "numpy>=1.18.1",
-    "pandas",
+]
+
+[project.optional-dependencies]
+# Visualization (matplotlib + plotly)
+viz = [
     "matplotlib",
     "plotly",
+]
+# Machine learning test functions
+ml = [
     "scikit-learn",
-    "search-data-collector>=0.6.0",
 ]
-
-[project.optional-dependencies]
+# All optional features
+full = [
+    "surfaces[viz,ml]",
+]
+# Development
 dev = [
+    "surfaces[full]",
     "flake8",
     "check-manifest",
 ]
+# Testing
 test = [
+    "surfaces[full]",
     "pytest>=7.0.0",
     "pytest-cov",
     "flake8",
     "tox",
     "gradient-free-optimizers",
 ]
+# Build
 build = [
     "build",
 ]
+# Surrogate models
 surrogate = [
     "onnxruntime>=1.16.0",
 ]

src/surfaces/_visualize.py

@@ -5,26 +5,52 @@
 # Internal module - not part of public API
 # Visualization utilities for test functions (experimental)
 
-import numpy as np
-import plotly.graph_objects as go
-import plotly.express as px
-import matplotlib as mpl
-import matplotlib.pyplot as plt
-from typing import Dict, List, Optional, Union, Any
+from __future__ import annotations
 
-color_scale = px.colors.sequential.Jet
+import numpy as np
+from typing import Dict, List, Optional, Union, Any, TYPE_CHECKING
+
+if TYPE_CHECKING:
+    import plotly.graph_objects as go
+    import matplotlib.pyplot as plt
+
+try:
+    import plotly.graph_objects as go
+    import plotly.express as px
+    import matplotlib as mpl
+    import matplotlib.pyplot as plt
+    _HAS_VIZ_DEPS = True
+    color_scale = px.colors.sequential.Jet
+except ImportError:
+    _HAS_VIZ_DEPS = False
+    go = None  # type: ignore[assignment]
+    px = None
+    mpl = None
+    plt = None  # type: ignore[assignment]
+    color_scale = None
+
+
+def _check_viz_deps():
+    """Check if visualization dependencies are available."""
+    if not _HAS_VIZ_DEPS:
+        raise ImportError(
+            "Visualization features require matplotlib and plotly. "
+            "Install with: pip install surfaces[viz]"
+        )
 
 
 def _create_grid(objective_function, search_space: Dict[str, np.ndarray]):
     """Create a 2D grid for visualization from a search space and objective function.
-    
+
     Args:
         objective_function: Function that takes a dict of parameters and returns a scalar
         search_space: Dictionary with exactly 2 keys, each mapping to numpy arrays
-        
+
     Returns:
         tuple: (xi, yi, zi) meshgrid arrays for plotting
     """
+    _check_viz_deps()
+
     def objective_function_np(*args):
         para = {}
         for arg, key in zip(args, search_space.keys()):

src/surfaces/test_functions/__init__.py

@@ -2,22 +2,18 @@
 # Email: simon.blanke@yahoo.com
 # License: MIT License
 
+# Algebraic functions (always available - numpy only)
 from .algebraic import algebraic_functions
 from .algebraic import *  # noqa: F401,F403
 
+# Machine learning functions (require sklearn)
 from .machine_learning import machine_learning_functions
-from .machine_learning import *  # noqa: F401,F403
+if machine_learning_functions:  # Only import if sklearn available
+    from .machine_learning import *  # noqa: F401,F403
 
+# Engineering functions (always available - numpy only)
 from .engineering import *  # noqa: F401,F403
-
-# Engineering function list
-engineering_functions = [
-    "ThreeBarTrussFunction",
-    "WeldedBeamFunction",
-    "PressureVesselFunction",
-    "TensionCompressionSpringFunction",
-    "CantileverBeamFunction",
-]
+from .engineering import engineering_functions
 
 # Backwards compatibility alias
 mathematical_functions = algebraic_functions

src/surfaces/test_functions/engineering/__init__.py

@@ -71,4 +71,13 @@
     "PressureVesselFunction",
     "TensionCompressionSpringFunction",
     "CantileverBeamFunction",
+    "engineering_functions",
+]
+
+engineering_functions = [
+    ThreeBarTrussFunction,
+    WeldedBeamFunction,
+    PressureVesselFunction,
+    TensionCompressionSpringFunction,
+    CantileverBeamFunction,
 ]

src/surfaces/test_functions/machine_learning/__init__.py

@@ -2,23 +2,40 @@
 # Email: simon.blanke@yahoo.com
 # License: MIT License
 
+try:
+    from sklearn.neighbors import KNeighborsClassifier  # noqa: F401
+    _HAS_SKLEARN = True
+except ImportError:
+    _HAS_SKLEARN = False
 
-from .tabular import (
-    KNeighborsClassifierFunction,
-    KNeighborsRegressorFunction,
-    GradientBoostingRegressorFunction,
-)
 
+def _check_sklearn():
+    """Check if scikit-learn is available."""
+    if not _HAS_SKLEARN:
+        raise ImportError(
+            "Machine learning functions require scikit-learn. "
+            "Install with: pip install surfaces[ml]"
+        )
 
-__all__ = [
-    "KNeighborsClassifierFunction",
-    "KNeighborsRegressorFunction",
-    "GradientBoostingRegressorFunction",
-]
 
+if _HAS_SKLEARN:
+    from .tabular import (
+        KNeighborsClassifierFunction,
+        KNeighborsRegressorFunction,
+        GradientBoostingRegressorFunction,
+    )
 
-machine_learning_functions = [
-    KNeighborsClassifierFunction,
-    GradientBoostingRegressorFunction,
-    KNeighborsRegressorFunction,
-]
+    __all__ = [
+        "KNeighborsClassifierFunction",
+        "KNeighborsRegressorFunction",
+        "GradientBoostingRegressorFunction",
+    ]
+
+    machine_learning_functions = [
+        KNeighborsClassifierFunction,
+        GradientBoostingRegressorFunction,
+        KNeighborsRegressorFunction,
+    ]
+else:
+    __all__ = []
+    machine_learning_functions = []