Continue removing Numba

PlasmaPy · namurphy · Sep 9, 2024 · Aug 28, 2024 · Aug 28, 2024 · Aug 28, 2024
commit 7fe2a10656e0e015d9438bbddd64cd6042b7fda5
@@ -97,7 +97,7 @@ Deprecations and Removals
   <https://github.com/plasmapy/plasmapy/pull/1465>`__)
 - The ``[all]`` option when using |pip| to install `plasmapy` is now
   deprecated and may be removed in a future release. Packages that
-  were previously optional (|h5py|, |lmfit|, |mpmath|, and |Numba|)
+  were previously optional (|h5py|, |lmfit|, |mpmath|, and Numba)
   are now installed by default when running ``pip install
   plasmapy``. To install all packages required for code development of
   PlasmaPy, instead run ``pip install plasmapy[developer]``. (`#1482
@@ -137,7 +137,7 @@ Features
   <https://github.com/plasmapy/plasmapy/pull/1145>`__)
 - Introduced the concept of :term:`lite-functions`, by creating the
   lite-function ``plasmapy.formulary.parameters.thermal_speed_lite``,
-  which is a simplified and |Numba| jitted version of
+  which is a simplified and Numba jitted version of
   ``plasmapy.formulary.parameters.thermal_speed``.  These functions
   are intended for computational use and as such have no validation of
   input or output values.
@@ -603,7 +603,7 @@ Trivial/Internal Changes
   ``1.19.0``, `pandas` to ``1.0.0``, `pytest` to ``5.4.0``, `scipy` to
   ``1.5.0``, and |xarray| to ``0.15.0``. (`#1482
   <https://github.com/plasmapy/plasmapy/pull/1482>`__)
-- Moved |h5py|, |lmfit|, |mpmath|, and |Numba| out of the
+- Moved |h5py|, |lmfit|, |mpmath|, and Numba out of the
   ``extras`` requirements category and into the ``install``
   requirements category.  These packages are now installed when
   running ``pip install plasmapy``. (`#1482

@@ -188,7 +188,6 @@
     (python_role, "lmfit"),
     (python_role, "mpmath"),
     (python_role, "nbsphinx"),
-    (python_role, "numba"),
     (python_role, "xarray"),
     # plasmapy_sphinx
     (python_role, "automod.*"),
@@ -253,7 +252,6 @@
     "astropy": ("https://docs.astropy.org/en/stable/", None),
     "lmfit": ("https://lmfit.github.io/lmfit-py/", None),
     "matplotlib": ("https://matplotlib.org/stable/", None),
-    "numba": ("https://numba.readthedocs.io/en/stable/", None),
     "numpy": ("https://numpy.org/doc/stable/", None),
     "pandas": ("https://pandas.pydata.org/pandas-docs/stable/", None),
     "pytest": ("https://docs.pytest.org/en/stable/", None),

@@ -687,7 +687,7 @@ Dependencies and requirements
      become compatible with the latest versions of its dependencies than
      to set a maximum requirement.
 
-* It sometimes takes a few months for packages like |Numba| to become
+* It sometimes takes a few months for packages like Numba to become
   compatible with the newest minor version of |Python|.
 
 * The ``tests`` and ``docs`` dependency sets are required for running

@@ -77,10 +77,9 @@ functions for situations when performance matters. For example,
 lite-function for `~plasmapy.formulary.frequencies.plasma_frequency`.
 
 Lite-functions accept and return NumPy arrays (assumed to be in SI
-units) instead of |Quantity| objects. Lite-functions make use of
-just-in-time (JIT) compilation via |Numba| to achieve high performance.
-Because lite-functions do not include any validation of inputs, they
-should only be used for performance-critical applications.
+units) instead of |Quantity| objects. Lite-functions have improved
+performance because they do not perform any checks on the inputs, and
+thus should be used cautiously.
 
 If you need a lite-function version of a `plasmapy.formulary` function
 that has not already been implemented, please `raise an issue`_.

@@ -14,7 +14,6 @@
 import astropy.units as u
 import numpy as np
 from astropy.constants.si import e, eps0
-from numba import njit
 
 from plasmapy import particles
 from plasmapy.particles.decorators import particle_input
@@ -156,7 +155,6 @@ def gyrofrequency(
 
 
 @preserve_signature
-@njit
 def plasma_frequency_lite(
     n: float,
     mass: float,

@@ -18,7 +18,6 @@
 import astropy.units as u
 import numpy as np
 from astropy.constants.si import k_B, mu0
-from numba import njit
 
 from plasmapy.formulary import lengths
 from plasmapy.particles import electron
@@ -475,7 +474,6 @@ def thermal_speed_coefficients(method: str, ndim: int) -> float:
 
 
 @preserve_signature
-@njit
 def thermal_speed_lite(T: float, mass: float, coeff: float) -> float:
     r"""
     The :term:`lite-function` for

@@ -11,7 +11,6 @@
 import numpy as np
 import pytest
 from astropy.constants.si import m_p
-from numba.extending import is_jitted
 
 from plasmapy.formulary.frequencies import plasma_frequency, plasma_frequency_lite, wp_
 from plasmapy.particles._factory import _physical_particle_factory
@@ -149,10 +148,6 @@ def test_can_handle_numpy_arrays(self) -> None:
 class TestPlasmaFrequencyLite:
     """Test class for `plasma_frequency_lite`."""
 
-    def test_is_jitted(self) -> None:
-        """Ensure `plasmapy_frequency_lite` was jitted by `numba`."""
-        assert is_jitted(plasma_frequency_lite)
-
     @pytest.mark.parametrize(
         "inputs",
         [

@@ -14,7 +14,6 @@
 import numpy as np
 import pytest
 from astropy.constants.si import k_B
-from numba.extending import is_jitted
 
 from plasmapy.formulary.speeds import (
     kappa_thermal_speed,
@@ -293,10 +292,6 @@ def test_can_handle_numpy_arrays(self) -> None:
 class TestThermalSpeedLite:
     """Test class for `thermal_speed_lite`."""
 
-    def test_is_jitted(self) -> None:
-        """Ensure `thermal_speed_lite` was jitted by `numba`."""
-        assert is_jitted(thermal_speed_lite)
-
     @pytest.mark.parametrize(
         "inputs",
         [

@@ -3,7 +3,6 @@
 """
 
 import pytest
-from numba import jit, njit
 
 from plasmapy.utils.decorators.lite_func import bind_lite_func
 
@@ -47,12 +46,15 @@ def test_raises(lite_func, attrs, _error) -> None:
         bind_lite_func(lite_func, attrs=attrs)(foo)
 
 
+# If we add back Numba as a dependency, we will need to add back two
+# lines in this parametrization that tested lite functions with Numba
+# decorators. See git history.
+
+
 @pytest.mark.parametrize(
     ("lite_func", "attrs"),
     [
         (foo_lite, None),
-        (jit(foo_lite, nopython=True), None),
-        (njit(foo_lite), None),
         (foo_lite, {"bar": bar}),
     ],
 )