Enable the hybrid solver interface

release-notes/next-release.md

@@ -2,10 +2,17 @@
 
 ## New features
 
+* Added a new "hybrid" solver that exposes an HIGHS/OSQP combinations for large scale
+  LPs, MILPs, and QPs.
+
 ## Fixes
 
 ## Other
 
 ## Deprecated features
 
+* The OSQP solver is deprecated in favor of the hybrid solver which also uses OSQP but
+  will not attempt to solve LPs with OSQP anymore. Setting the `model.solver = "osqp"`
+  will now use the hybrid interface and will raise an error in a future release.
+
 ## Backwards incompatible changes

setup.cfg

@@ -6,7 +6,7 @@ parse = (?P<major>\d+)
 	\.(?P<minor>\d+)
 	\.(?P<patch>\d+)
 	(?P<release>[a]*)(?P<num>\d*)
-serialize = 
+serialize =
 	{major}.{minor}.{patch}{release}{num}
 	{major}.{minor}.{patch}
 tag_name = {new_version}
@@ -15,15 +15,15 @@ tag_name = {new_version}
 name = cobra
 url = https://opencobra.github.io/cobrapy
 download_url = https://pypi.org/project/cobra
-project_urls = 
+project_urls =
 	Source Code = https://github.com/opencobra/cobrapy
 	Documentation = https://cobrapy.readthedocs.io
 	Bug Tracker = https://github.com/opencobra/cobrapy/issues
 author = The cobrapy core development team.
 author_email = [email protected]
 maintainer = Moritz E. Beber
 maintainer_email = [email protected]
-classifiers = 
+classifiers =
 	Development Status :: 5 - Production/Stable
 	Intended Audience :: Science/Research
 	License :: OSI Approved :: GNU General Public License v2 or later (GPLv2+)
@@ -40,7 +40,7 @@ license = LGPL-2.0-or-later OR GPL-2.0-or-later
 description = COBRApy is a package for constraint-based modeling of metabolic networks.
 long_description = file: README.rst, INSTALL.rst
 long_description_content_type = text/x-rst
-keywords = 
+keywords =
 	metabolism
 	biology
 	constraint-based
@@ -52,39 +52,39 @@ keywords =
 
 [options]
 zip_safe = True
-install_requires = 
+install_requires =
 	appdirs ~=1.4
 	depinfo ~=2.2
 	diskcache ~=5.0
 	future
 	httpx ~=0.24
 	importlib_resources
 	numpy >=1.13
-	optlang ~=1.5
+	optlang ~=1.8
 	pandas >=1.0,<3.0
 	pydantic >=1.6
 	python-libsbml ~=5.19
 	rich >=8.0
 	ruamel.yaml ~=0.16
 	swiglpk
-tests_require = 
+tests_require =
 	tox
 packages = find:
-package_dir = 
+package_dir =
 	= src
 
 [options.packages.find]
 where = src
 
 [options.package_data]
-cobra = 
+cobra =
 	data/*
 	io/*.json
 
 [options.extras_require]
-array = 
+array =
 	scipy
-development = 
+development =
 	black
 	bumpversion
 	isort
@@ -96,7 +96,7 @@ universal = 1
 [bumpversion:part:release]
 optional_value = placeholder
 first_value = placeholder
-values = 
+values =
 	placeholder
 	a
 

src/cobra/util/solver.py

@@ -50,11 +50,11 @@
 solvers = {
     match.split("_interface")[0]: getattr(optlang, match)
     for match in dir(optlang)
-    if "_interface" in match
+    if "_interface" in match and match != "matrix_interface"
 }
 
 # Defines all the QP solvers implemented in optlang.
-qp_solvers = ["cplex", "gurobi", "osqp"]
+qp_solvers = ["cplex", "gurobi", "hybrid"]
 
 # optlang solution statuses which still allow retrieving primal values
 has_primals = [NUMERIC, FEASIBLE, INFEASIBLE, SUBOPTIMAL, ITERATION_LIMIT, TIME_LIMIT]
@@ -252,9 +252,9 @@ def get_solver_name(mip: bool = False, qp: bool = False) -> str:
     if len(solvers) == 0:
         raise SolverNotFound("No solvers found.")
     # Those lists need to be updated as optlang implements more solvers
-    mip_order = ["gurobi", "cplex", "glpk"]
-    lp_order = ["glpk", "cplex", "gurobi"]
-    qp_order = ["gurobi", "cplex", "osqp"]
+    mip_order = ["gurobi", "cplex", "hybrid", "glpk"]
+    lp_order = ["glpk", "hybrid", "cplex", "gurobi"]
+    qp_order = ["cplex", "gurobi", "hybrid"]
 
     if mip is False and qp is False:
         for solver_name in lp_order:

tests/test_flux_analysis/conftest.py

@@ -15,7 +15,7 @@
 # solutions.
 @pytest.fixture(
     scope="session",
-    params=[s for s in ["glpk", "cplex", "gurobi"] if s in sutil.solvers],
+    params=[s for s in ["glpk", "cplex", "gurobi", "hybrid"] if s in sutil.solvers],
 )
 def all_solvers(request) -> List[str]:
     """Return the avaialble solvers."""
@@ -24,7 +24,7 @@ def all_solvers(request) -> List[str]:
 
 @pytest.fixture(
     scope="session",
-    params=[s for s in ["cplex", "gurobi", "osqp"] if s in sutil.solvers],
+    params=[s for s in ["cplex", "gurobi", "hybrid"] if s in sutil.solvers],
 )
 def qp_solvers(request) -> List[str]:
     """Return the available QP solvers."""

tests/test_flux_analysis/test_deletion.py

@@ -25,7 +25,7 @@ def test_single_gene_deletion_fba_benchmark(
 ) -> None:
     """Benchmark single gene deletion using FBA."""
     model.solver = all_solvers
-    benchmark(single_gene_deletion, model)
+    benchmark(single_gene_deletion, model, model.genes[1::10])
 
 
 def test_single_gene_deletion_fba(model: Model, all_solvers: List[str]) -> None:
@@ -187,7 +187,9 @@ def test_single_reaction_deletion_benchmark(
 ) -> None:
     """Benchmark single reaction deletion."""
     model.solver = all_solvers
-    benchmark(single_reaction_deletion, model=model, processes=1)
+    benchmark(
+        single_reaction_deletion, model=model, genes=model.genes[1::10], processes=1
+    )
 
 
 def test_single_reaction_deletion(model: Model, all_solvers) -> None:
@@ -410,7 +412,7 @@ def test_double_reaction_deletion_benchmark(
     large_model: Model, benchmark: Callable
 ) -> None:
     """Benchmark double reaction deletion."""
-    reactions = large_model.reactions[1::100]
+    reactions = large_model.reactions[100:105]
     benchmark(double_reaction_deletion, large_model, reaction_list1=reactions)
 
 

tests/test_flux_analysis/test_variability.py

@@ -26,7 +26,7 @@ def test_flux_variability_benchmark(
     benchmark(
         flux_variability_analysis,
         large_model,
-        reaction_list=large_model.reactions[1::3],
+        reaction_list=large_model.reactions[1::100],
         processes=1,
     )
 
@@ -106,7 +106,7 @@ def test_flux_variability_loopless_benchmark(
         flux_variability_analysis,
         model,
         loopless=True,
-        reaction_list=model.reactions[1::3],
+        reaction_list=model.reactions[1::50],
     )