Merge pull request #349 from robbievanleeuwen/optional-numba

Make `numba` an optional dependency

Author: robbievanleeuwen

.readthedocs.yaml

@@ -23,3 +23,4 @@ python:
       extra_requirements:
         - dxf
         - rhino
+        - numba

docs/installation.rst

@@ -26,6 +26,18 @@ package index:
 
     pip install sectionproperties
 
+Installing ``Numba``
+--------------------
+
+``Numba`` translates a subset of Python and NumPy code into fast machine code, allowing
+algorithms to approach the speeds of C. The speed of several ``sectionproperties``
+analysis functions have been enhanced with `numba <https://github.com/numba/numba>`_.
+To take advantage of this increase in performance you can install ``numba`` alongside
+``sectionproperties`` with:
+
+.. code-block:: shell
+
+    pip install sectionproperties[numba]
 
 Installing ``PARDISO`` Solver
 -----------------------------

noxfile.py

@@ -212,7 +212,13 @@ def docs_build(session: Session) -> None:
         args.insert(0, "--color")
 
     session.run_always(
-        "poetry", "install", "--only", "main", "--extras", "dxf rhino", external=True
+        "poetry",
+        "install",
+        "--only",
+        "main",
+        "--extras",
+        "dxf rhino numba",
+        external=True,
     )
     session.install(
         "furo",
@@ -243,7 +249,13 @@ def docs(session: Session) -> None:
     """
     args = session.posargs or ["--open-browser", "docs", "docs/_build"]
     session.run_always(
-        "poetry", "install", "--only", "main", "--extras", "dxf rhino", external=True
+        "poetry",
+        "install",
+        "--only",
+        "main",
+        "--extras",
+        "dxf rhino numba",
+        external=True,
     )
     session.install(
         "furo",

poetry.lock

@@ -48,15 +48,15 @@ Changelog = "https://github.com/robbievanleeuwen/section-properties/releases"
 
 [tool.poetry.dependencies]
 python = ">=3.9.0,<3.12"
-numpy = "^1.25.2"  # numba requires numpy <1.26
+numpy = "^1.25.2"
 scipy = "^1.11.3"
 matplotlib = "^3.8.0"
 shapely = "^2.0.1"
 triangle = "^20230923"
 rich = "^13.6.0"
 click = "^8.1.7"
 more-itertools = "^10.1.0"
-numba = "^0.58.0"
+numba = { version = "^0.58.0", optional = true }
 cad-to-shapely = { version = "^0.3.1", optional = true }
 rhino-shapley-interop = { version = "^0.0.4", optional = true }
 rhino3dm = { version = "==8.0.0b3", optional = true }
@@ -97,6 +97,7 @@ sphinxext-opengraph = "^0.8.2"
 [tool.poetry.extras]
 dxf = ["cad-to-shapely"]
 rhino = ["rhino-shapley-interop", "rhino3dm"]
+numba = ["numba"]
 pardiso = ["pypardiso"]
 
 [tool.poetry.scripts]

pyproject.toml

@@ -10,19 +10,67 @@
 import warnings
 from dataclasses import dataclass, field
 from functools import lru_cache
-from typing import TYPE_CHECKING
+from typing import TYPE_CHECKING, Any, Callable
 
 import numpy as np
 import numpy.typing as npt
-from numba import njit
-from numba.core.errors import NumbaPerformanceWarning
 
 
 if TYPE_CHECKING:
     from sectionproperties.pre.pre import Material
 
 
-@njit(cache=True, nogil=True)  # type: ignore
+# numba is an optional dependency
+try:
+    from numba import njit
+    from numba.core.errors import NumbaPerformanceWarning
+
+    USE_NUMBA = True
+except ImportError:
+
+    def njit() -> None:
+        """Assigns empty function to njit if numba isn't installed.
+
+        Returns:
+            None
+        """
+        return None
+
+    USE_NUMBA = False
+
+
+def conditional_decorator(
+    dec: Callable[[Any], Any],
+    condition: bool,
+) -> Callable[[Any], Any]:
+    """A decorator that applies a decorator only if a condition is True.
+
+    Args:
+        dec: Decorator to apply
+        condition: Apply decorator if this is true
+
+    Returns:
+        Decorator wrapper
+    """
+
+    def decorator(func: Callable[[Any], Any]) -> Callable[[Any], Any]:
+        """Decorator wrapper.
+
+        Args:
+            func: Function decorator operates on.
+
+        Returns:
+            Original or decorated function.
+        """
+        if not condition:
+            return func
+
+        return dec(func)  # type: ignore
+
+    return decorator
+
+
+@conditional_decorator(njit, USE_NUMBA)
 def _assemble_torsion(
     k_el: npt.NDArray[np.float64],
     f_el: npt.NDArray[np.float64],
@@ -55,7 +103,7 @@ def _assemble_torsion(
     return k_el, f_el, c_el
 
 
-@njit(cache=True, nogil=True)  # type: ignore
+@conditional_decorator(njit, USE_NUMBA)
 def _shear_parameter(
     nx: float, ny: float, ixx: float, iyy: float, ixy: float
 ) -> tuple[float, float, float, float, float, float]:
@@ -81,7 +129,7 @@ def _shear_parameter(
     return r, q, d1, d2, h1, h2
 
 
-@njit(cache=True, nogil=True)  # type: ignore
+@conditional_decorator(njit, USE_NUMBA)
 def _assemble_shear_load(
     f_psi: npt.NDArray[np.float64],
     f_phi: npt.NDArray[np.float64],
@@ -126,7 +174,7 @@ def _assemble_shear_load(
     return f_psi, f_phi
 
 
-@njit(cache=True, nogil=True)  # type: ignore
+@conditional_decorator(njit, USE_NUMBA)
 def _assemble_shear_coefficients(
     kappa_x: float,
     kappa_y: float,
@@ -648,7 +696,9 @@ def element_stress(
 
         # extrapolate results to nodes, ignore numba warnings about performance
         with warnings.catch_warnings():
-            warnings.simplefilter("ignore", category=NumbaPerformanceWarning)
+            if USE_NUMBA:
+                warnings.simplefilter("ignore", category=NumbaPerformanceWarning)
+
             sig_zz_mxx = extrapolate_to_nodes(w=sig_zz_mxx_gp)
             sig_zz_myy = extrapolate_to_nodes(w=sig_zz_myy_gp)
             sig_zz_m11 = extrapolate_to_nodes(w=sig_zz_m11_gp)
@@ -951,7 +1001,7 @@ def gauss_points(*, n: int) -> npt.NDArray[np.float64]:
 
 
 @lru_cache(maxsize=None)
-@njit(cache=True, nogil=True)  # type: ignore
+@conditional_decorator(njit, USE_NUMBA)
 def __shape_function_cached(
     coords: tuple[float, ...],
     gauss_point: tuple[float, float, float],
@@ -1039,7 +1089,7 @@ def shape_function(
 
 
 @lru_cache(maxsize=None)
-@njit(cache=True, nogil=True)  # type: ignore
+@conditional_decorator(njit, USE_NUMBA)
 def shape_function_only(p: tuple[float, float, float]) -> npt.NDArray[np.float64]:
     """The values of the ``Tri6`` shape function at a point ``p``.
 
@@ -1117,7 +1167,7 @@ def shape_function_only(p: tuple[float, float, float]) -> npt.NDArray[np.float64
 )
 
 
-@njit(cache=True, nogil=True)  # type: ignore
+@conditional_decorator(njit, USE_NUMBA)
 def extrapolate_to_nodes(w: npt.NDArray[np.float64]) -> npt.NDArray[np.float64]:
     """Extrapolates results at six Gauss points to the six nodes of a ``Tri6`` element.
 
@@ -1130,7 +1180,7 @@ def extrapolate_to_nodes(w: npt.NDArray[np.float64]) -> npt.NDArray[np.float64]:
     return h_inv @ w
 
 
-@njit(cache=True, nogil=True)  # type: ignore
+@conditional_decorator(njit, USE_NUMBA)
 def principal_coordinate(
     phi: float,
     x: float,
@@ -1153,7 +1203,7 @@ def principal_coordinate(
     return x * cos_phi + y * sin_phi, y * cos_phi - x * sin_phi
 
 
-@njit(cache=True, nogil=True)  # type: ignore
+@conditional_decorator(njit, USE_NUMBA)
 def global_coordinate(
     phi: float,
     x11: float,
@@ -1176,7 +1226,7 @@ def global_coordinate(
     return x11 * cos_phi - y22 * sin_phi, x11 * sin_phi + y22 * cos_phi
 
 
-@njit(cache=True, nogil=True)  # type: ignore
+@conditional_decorator(njit, USE_NUMBA)
 def point_above_line(
     u: npt.NDArray[np.float64],
     px: float,