feat: implement lazy loading for optional dependencies (#621)

Author: spline2hg

src/optimagic/config.py

@@ -1,3 +1,4 @@
+import importlib.util
 from pathlib import Path
 
 import pandas as pd
@@ -15,105 +16,29 @@
 CRITERION_PENALTY_SLOPE = 0.1
 CRITERION_PENALTY_CONSTANT = 100
 
-# ======================================================================================
-# Check Available Packages
-# ======================================================================================
-
-try:
-    from petsc4py import PETSc  # noqa: F401
-except ImportError:
-    IS_PETSC4PY_INSTALLED = False
-else:
-    IS_PETSC4PY_INSTALLED = True
-
-try:
-    import nlopt  # noqa: F401
-except ImportError:
-    IS_NLOPT_INSTALLED = False
-else:
-    IS_NLOPT_INSTALLED = True
-
-try:
-    import pybobyqa  # noqa: F401
-except ImportError:
-    IS_PYBOBYQA_INSTALLED = False
-else:
-    IS_PYBOBYQA_INSTALLED = True
-
-try:
-    import dfols  # noqa: F401
-except ImportError:
-    IS_DFOLS_INSTALLED = False
-else:
-    IS_DFOLS_INSTALLED = True
-
-try:
-    import pygmo  # noqa: F401
-except ImportError:
-    IS_PYGMO_INSTALLED = False
-else:
-    IS_PYGMO_INSTALLED = True
-
-try:
-    import cyipopt  # noqa: F401
-except ImportError:
-    IS_CYIPOPT_INSTALLED = False
-else:
-    IS_CYIPOPT_INSTALLED = True
-
-try:
-    import fides  # noqa: F401
-except ImportError:
-    IS_FIDES_INSTALLED = False
-else:
-    IS_FIDES_INSTALLED = True
 
-try:
-    import jax  # noqa: F401
-except ImportError:
-    IS_JAX_INSTALLED = False
-else:
-    IS_JAX_INSTALLED = True
+def _is_installed(module_name: str) -> bool:
+    """Return True if the given module is installed, otherwise False."""
+    return importlib.util.find_spec(module_name) is not None
 
 
-try:
-    import tranquilo  # noqa: F401
-except ImportError:
-    IS_TRANQUILO_INSTALLED = False
-else:
-    IS_TRANQUILO_INSTALLED = True
-
-
-try:
-    import numba  # noqa: F401
-except ImportError:
-    IS_NUMBA_INSTALLED = False
-else:
-    IS_NUMBA_INSTALLED = True
-
-
-try:
-    import iminuit  # noqa: F401
-except ImportError:
-    IS_IMINUIT_INSTALLED = False
-else:
-    IS_IMINUIT_INSTALLED = True
-
-
-try:
-    import nevergrad  # noqa: F401
-except ImportError:
-    IS_NEVERGRAD_INSTALLED = False
-else:
-    IS_NEVERGRAD_INSTALLED = True
-
+# ======================================================================================
+# Check Available Packages
+# ======================================================================================
 
-try:
-    from bayes_opt import BayesianOptimization  # noqa: F401
-except ImportError:
-    IS_BAYESOPT_INSTALLED = False
-else:
-    IS_BAYESOPT_INSTALLED = True
+IS_PETSC4PY_INSTALLED = _is_installed("petsc4py")
+IS_NLOPT_INSTALLED = _is_installed("nlopt")
+IS_PYBOBYQA_INSTALLED = _is_installed("pybobyqa")
+IS_DFOLS_INSTALLED = _is_installed("dfols")
+IS_PYGMO_INSTALLED = _is_installed("pygmo")
+IS_CYIPOPT_INSTALLED = _is_installed("cyipopt")
+IS_FIDES_INSTALLED = _is_installed("fides")
+IS_JAX_INSTALLED = _is_installed("jax")
+IS_TRANQUILO_INSTALLED = _is_installed("tranquilo")
+IS_NUMBA_INSTALLED = _is_installed("numba")
+IS_IMINUIT_INSTALLED = _is_installed("iminuit")
+IS_NEVERGRAD_INSTALLED = _is_installed("nevergrad")
+IS_BAYESOPT_INSTALLED = _is_installed("bayes_opt")
 
 
 # ======================================================================================

src/optimagic/optimizers/fides.py

@@ -29,9 +29,6 @@
     PositiveInt,
 )
 
-if IS_FIDES_INSTALLED:
-    from fides import Optimizer, hessian_approximation
-
 
 @mark.minimizer(
     name="fides",
@@ -163,6 +160,8 @@ def fides_internal(
             "You can install it with `pip install fides>=0.7.4`."
         )
 
+    from fides import Optimizer
+
     fides_options = {
         "delta_init": trustregion_initial_radius,
         "eta": trustregion_increase_threshold,
@@ -251,6 +250,8 @@ def _process_exitflag(exitflag):
 
 
 def _create_hessian_updater_from_user_input(hessian_update_strategy):
+    from fides import hessian_approximation
+
     hessians_needing_residuals = (
         hessian_approximation.FX,
         hessian_approximation.SSM,

src/optimagic/optimizers/ipopt.py

@@ -30,9 +30,6 @@
     YesNoBool,
 )
 
-if IS_CYIPOPT_INSTALLED:
-    import cyipopt
-
 
 @mark.minimizer(
     name="ipopt",
@@ -349,11 +346,14 @@ class Ipopt(Algorithm):
     def _solve_internal_problem(
         self, problem: InternalOptimizationProblem, x0: NDArray[np.float64]
     ) -> InternalOptimizeResult:
-        if not self.algo_info.is_available:
+        if not IS_CYIPOPT_INSTALLED:
             raise NotInstalledError(
-                "The 'ipopt' algorithm requires the cyipopt package to be installed. "
-                "You can it with: `conda install -c conda-forge cyipopt`."
+                "The 'ipopt' algorithm requires the cyipopt package to be installed.\n"
+                "You can install it with: `conda install -c conda-forge cyipopt`."
             )
+
+        import cyipopt
+
         if self.acceptable_tol <= self.convergence_ftol_rel:
             raise ValueError(
                 "The acceptable tolerance must be larger than the desired tolerance."

src/optimagic/optimizers/nag_optimizers.py

@@ -31,13 +31,6 @@
 )
 from optimagic.utilities import calculate_trustregion_initial_radius
 
-if IS_PYBOBYQA_INSTALLED:
-    import pybobyqa
-
-if IS_DFOLS_INSTALLED:
-    import dfols
-
-
 CONVERGENCE_MINIMAL_TRUSTREGION_RADIUS_TOLERANCE = 1e-8
 """float: Stop when the lower trust region radius falls below this value."""
 
@@ -486,6 +479,8 @@ def nag_dfols_internal(
             "For additional installation instructions visit: ",
             r"https://numericalalgorithmsgroup.github.io/dfols/build/html/install.html",
         )
+    import dfols
+
     if trustregion_method_to_replace_extra_points == "momentum":
         trustregion_use_momentum = True
     elif trustregion_method_to_replace_extra_points in ["geometry_improving", None]:
@@ -788,6 +783,7 @@ def nag_pybobyqa_internal(
             r"https://numericalalgorithmsgroup.github.io/pybobyqa/build/html/"
             "install.html",
         )
+    import pybobyqa
 
     if convergence_criterion_value is None:
         convergence_criterion_value = -np.inf

src/optimagic/optimizers/nevergrad_optimizers.py

@@ -2,7 +2,7 @@
 
 import math
 from dataclasses import dataclass
-from typing import Any, Literal
+from typing import TYPE_CHECKING, Any, Literal
 
 import numpy as np
 from numpy.typing import NDArray
@@ -29,7 +29,7 @@
     PositiveInt,
 )
 
-if IS_NEVERGRAD_INSTALLED:
+if TYPE_CHECKING:
     import nevergrad as ng
 
 
@@ -77,6 +77,8 @@ def _solve_internal_problem(
         if not IS_NEVERGRAD_INSTALLED:
             raise NotInstalledError(NEVERGRAD_NOT_INSTALLED_ERROR)
 
+        import nevergrad as ng
+
         configured_optimizer = ng.optimizers.ConfPSO(
             transform=self.transform,
             popsize=self.population_size,
@@ -160,6 +162,8 @@ def _solve_internal_problem(
         if not IS_NEVERGRAD_INSTALLED:
             raise NotInstalledError(NEVERGRAD_NOT_INSTALLED_ERROR)
 
+        import nevergrad as ng
+
         cma_options = {
             "AdaptSigma": self.step_size_adaptive,
             "CSA_dampfac": self.CSA_dampfac,
@@ -285,6 +289,8 @@ def _solve_internal_problem(
         if not IS_NEVERGRAD_INSTALLED:
             raise NotInstalledError(NEVERGRAD_NOT_INSTALLED_ERROR)
 
+        import nevergrad as ng
+
         configured_optimizer = ng.optimizers.ParametrizedOnePlusOne(
             noise_handling=self.noise_handling,
             mutation=self.mutation,
@@ -363,6 +369,8 @@ def _solve_internal_problem(
         if not IS_NEVERGRAD_INSTALLED:
             raise NotInstalledError(NEVERGRAD_NOT_INSTALLED_ERROR)
 
+        import nevergrad as ng
+
         configured_optimizer = ng.optimizers.DifferentialEvolution(
             scale=self.scale,
             recommendation=self.recommendation,
@@ -418,6 +426,8 @@ def _solve_internal_problem(
         if not IS_NEVERGRAD_INSTALLED:
             raise NotInstalledError(NEVERGRAD_NOT_INSTALLED_ERROR)
 
+        import nevergrad as ng
+
         configured_optimizer = ng.optimizers.BayesOptim(
             init_budget=self.init_budget,
             pca=self.pca,
@@ -470,6 +480,8 @@ def _solve_internal_problem(
         if not IS_NEVERGRAD_INSTALLED:
             raise NotInstalledError(NEVERGRAD_NOT_INSTALLED_ERROR)
 
+        import nevergrad as ng
+
         configured_optimizer = ng.optimizers.EMNA(
             isotropic=self.isotropic,
             naive=self.noise_handling,
@@ -518,6 +530,8 @@ def _solve_internal_problem(
         if not IS_NEVERGRAD_INSTALLED:
             raise NotInstalledError(NEVERGRAD_NOT_INSTALLED_ERROR)
 
+        import nevergrad as ng
+
         configured_optimizer = ng.optimizers.cGA
 
         res = _nevergrad_internal(
@@ -561,6 +575,8 @@ def _solve_internal_problem(
         if not IS_NEVERGRAD_INSTALLED:
             raise NotInstalledError(NEVERGRAD_NOT_INSTALLED_ERROR)
 
+        import nevergrad as ng
+
         configured_optimizer = ng.optimizers.EDA
 
         res = _nevergrad_internal(
@@ -606,6 +622,8 @@ def _solve_internal_problem(
         if not IS_NEVERGRAD_INSTALLED:
             raise NotInstalledError(NEVERGRAD_NOT_INSTALLED_ERROR)
 
+        import nevergrad as ng
+
         configured_optimizer = ng.optimizers.ParametrizedTBPSA(
             naive=self.noise_handling,
             initial_popsize=self.initial_popsize,
@@ -658,6 +676,8 @@ def _solve_internal_problem(
         if not IS_NEVERGRAD_INSTALLED:
             raise NotInstalledError(NEVERGRAD_NOT_INSTALLED_ERROR)
 
+        import nevergrad as ng
+
         configured_optimizer = ng.optimizers.RandomSearchMaker(
             stupid=False,
             middle_point=self.middle_point,
@@ -715,6 +735,8 @@ def _solve_internal_problem(
         if not IS_NEVERGRAD_INSTALLED:
             raise NotInstalledError(NEVERGRAD_NOT_INSTALLED_ERROR)
 
+        import nevergrad as ng
+
         configured_optimizer = ng.optimizers.SamplingSearch(
             sampler=self.sampler,
             scrambled=self.scrambled,
@@ -820,6 +842,8 @@ def _solve_internal_problem(
         if not IS_NEVERGRAD_INSTALLED:
             raise NotInstalledError(NEVERGRAD_NOT_INSTALLED_ERROR)
 
+        import nevergrad as ng
+
         configured_optimizer = getattr(ng.optimizers, self.optimizer)
 
         res = _nevergrad_internal(
@@ -903,6 +927,8 @@ def _solve_internal_problem(
         if not IS_NEVERGRAD_INSTALLED:
             raise NotInstalledError(NEVERGRAD_NOT_INSTALLED_ERROR)
 
+        import nevergrad as ng
+
         configured_optimizer = getattr(ng.optimizers, self.optimizer)
 
         res = _nevergrad_internal(
@@ -948,6 +974,8 @@ def _nevergrad_internal(
 
     """
 
+    import nevergrad as ng
+
     param = ng.p.Array(
         init=x0,
     )