Adds 3.12 support

diffcp/__init__.py

@@ -1,4 +1,4 @@
-__version__ = "1.1.0"
+__version__ = "1.1.1"
 
 from diffcp.cone_program import solve_and_derivative, \
     solve_and_derivative_batch, \

diffcp/cone_program.py

@@ -2,12 +2,8 @@
 import warnings
 from multiprocessing.pool import ThreadPool
 
-import ecos
-import clarabel
 import numpy as np
 import scipy.sparse as sparse
-import scs
-from distutils.version import StrictVersion
 from threadpoolctl import threadpool_limits
 
 import _diffcp
@@ -319,25 +315,17 @@ def solve_internal(A, b, c, cone_dict, solve_method=None,
             solve_method = "ECOS"
 
     if solve_method == "SCS":
+        import scs
 
-        # SCS versions SCS 2.*
-        if StrictVersion(scs.__version__) < StrictVersion('3.0.0'):
-            if "eps_abs" in kwargs or "eps_rel" in kwargs:
-                # Take the min of eps_rel and eps_abs to be eps
-                kwargs["eps"] = min(kwargs.get("eps_abs", 1),
-                                    kwargs.get("eps_rel", 1))
-
-        # SCS version 3.*
-        else:
-            if "eps" in kwargs:  # eps replaced by eps_abs, eps_rel
-                kwargs["eps_abs"] = kwargs["eps"]
-                kwargs["eps_rel"] = kwargs["eps"]
-                del kwargs["eps"]
+        if "eps" in kwargs:  # eps replaced by eps_abs, eps_rel
+            kwargs["eps_abs"] = kwargs["eps"]
+            kwargs["eps_rel"] = kwargs["eps"]
+            del kwargs["eps"]
 
         data = {
             "A": A,
             "b": b,
-            "c": c
+            "c": c,
         }
 
         if warm_start is not None:
@@ -367,6 +355,8 @@ def solve_internal(A, b, c, cone_dict, solve_method=None,
                 return result
 
     elif solve_method == "ECOS":
+        import ecos
+
         if warm_start is not None:
             raise ValueError('ECOS does not support warmstart.')
         if ('s' in cone_dict) and (cone_dict['s'] != []):
@@ -448,6 +438,7 @@ def solve_internal(A, b, c, cone_dict, solve_method=None,
                           'iter': solution['info']['iter'],
                           'pobj': solution['info']['pcost']}
     elif solve_method == "Clarabel":
+        import clarabel
         # for now set P to 0
         P = sparse.csc_matrix((c.size, c.size))
 

diffcp/cones.py

@@ -1,15 +1,8 @@
 import numpy as np
 import scipy.sparse as sparse
 from _diffcp import project_exp_cone, Cone, ConeType
-from distutils.version import StrictVersion
-import scs
 
-if StrictVersion(scs.__version__) >= StrictVersion('3.0.0'):
-    EQ_DIM = "z"
-else:
-    EQ_DIM = "f"
-
-ZERO = EQ_DIM
+ZERO = "z"
 POS = "l"
 SOC = "q"
 PSD = "s"
@@ -21,7 +14,7 @@
 
 # Map from Python cones to CPP format
 CONE_MAP = {
-    EQ_DIM: ConeType.ZERO,
+    "z": ConeType.ZERO,
     "l": ConeType.POS,
     "q": ConeType.SOC,
     "s": ConeType.PSD,

pyproject.toml

@@ -1,14 +1,14 @@
 
 [project]
 name = "diffcp"
-version = "1.1.0"
+version = "1.1.1"
 description = "A library to compute gradients for convex optimization problems"
 requires-python = ">= 3.10"
 
 readme = "README.md"
 
-requires = [
-    "threadpoolctl >= 1.1"
+dependencies = [
+    "threadpoolctl >= 1.1",
 ]
 urls = {Homepage = "https://github.com/cvxgrp/diffcp/"}
 license = {text = "Apache License, Version 2.0"}
@@ -30,7 +30,7 @@ build-backend = "scikit_build_core.build"
 test = [
     "clarabel >= 0.5.1",
     "ecos >= 2.0.10",
-    "scs >= 2.0.2",
+    "scs >= 3.0.0",
 ]
 
 [tool.scikit-build]