Placate ruff 0.16.5

examples/from-wiki/gpu_scalar_mult.py

@@ -55,18 +55,15 @@ def get_lin_comb_kernel_no_tex(summand_descriptors,
     for i, (is_gpu_scalar, scalar_dtype, vector_dtype) in \
             enumerate(summand_descriptors):
         if is_gpu_scalar:
-            args.append(VectorArg(vector_dtype, "global_a%d" % i))
-            args.append(VectorArg(vector_dtype, "x%d" % i))
+            args.extend((VectorArg(vector_dtype, "global_a%d" % i), VectorArg(vector_dtype, "x%d" % i)))
             loop_prep.append("%s a%d = *global_a%d"
                     % (dtype_to_ctype(scalar_dtype), i, i))
         else:
-            args.append(ScalarArg(scalar_dtype, "a%d" % i))
-            args.append(VectorArg(vector_dtype, "x%d" % i))
+            args.extend((ScalarArg(scalar_dtype, "a%d" % i), VectorArg(vector_dtype, "x%d" % i)))
 
         summands.append("a%d*x%d[i]" % (i, i))
 
-    args.append(VectorArg(dtype_z, "z"))
-    args.append(ScalarArg(numpy.uintp, "n"))
+    args.extend((VectorArg(dtype_z, "z"), ScalarArg(numpy.uintp, "n")))
 
     mod = get_elwise_module(args,
             "z[i] = " + " + ".join(summands),

pycuda/debug.py

@@ -27,4 +27,4 @@
 sys.argv = args
 
 with open(mainpyfile) as mainpy:
-    exec(compile(mainpy.read(), mainpyfile, "exec"))  # ruff:ignore[exec-builtin]
+    exec(compile(mainpy.read(), mainpyfile, "exec"))

pycuda/driver.py

@@ -340,7 +340,7 @@ def function_prepare_pre_v4(func, arg_types, block=None, shared=None, texrefs=No
 
         func.arg_format = ""
 
-        for _i, arg_type in enumerate(arg_types):
+        for arg_type in arg_types:
             if (
                 isinstance(arg_type, type)
                 and np is not None
@@ -541,7 +541,7 @@ def function_prepare(func, arg_types, texrefs=None):
 
         func.arg_format = ""
 
-        for _i, arg_type in enumerate(arg_types):
+        for arg_type in arg_types:
             if isinstance(arg_type, type) and np.number in arg_type.__mro__:
                 func.arg_format += np.dtype(arg_type).char
             elif isinstance(arg_type, np.dtype):

pycuda/elementwise.py

@@ -269,8 +269,7 @@ def __call__(self, *args, **kwargs):
             range_ = slice(*slice_.indices(repr_vec.size))
 
         if range_ is not None:
-            invocation_args.append(range_.start)
-            invocation_args.append(range_.stop)
+            invocation_args.extend((range_.start, range_.stop))
             if range_.step is None:
                 invocation_args.append(1)
             else:
@@ -439,13 +438,11 @@ def get_linear_combination_kernel(summand_descriptors, dtype_z):
                 % (dtype_to_ctype(scalar_dtype), i, i)
             )
         else:
-            args.append(ScalarArg(scalar_dtype, "a%d" % i))
-            args.append(VectorArg(vector_dtype, "x%d" % i))
+            args.extend((ScalarArg(scalar_dtype, "a%d" % i), VectorArg(vector_dtype, "x%d" % i)))
 
         summands.append("a%d*x%d[i]" % (i, i))
 
-    args.append(VectorArg(dtype_z, "z"))
-    args.append(ScalarArg(np.uintp, "n"))
+    args.extend((VectorArg(dtype_z, "z"), ScalarArg(np.uintp, "n")))
 
     mod = get_elwise_module(
         args,

pycuda/gl/autoinit.py

@@ -12,7 +12,7 @@
 from pycuda.tools import make_default_context
 
 
-context = make_default_context(lambda dev: cudagl.make_context(dev))
+context = make_default_context(cudagl.make_context)
 device = context.get_device()
 
 atexit.register(context.pop)

pycuda/gpuarray.py

@@ -419,7 +419,7 @@ def __bool__(self):
 
     @property
     def ptr(self):
-        return self.gpudata.__int__()
+        return int(self.gpudata)
 
     # kernel invocation wrappers ----------------------------------------------
     def _axpbyz(self, selffac, other, otherfac, out, add_timer=None, stream=None):

pycuda/sparse/cg.py

@@ -62,9 +62,7 @@ def lc2(self, a, x, b, y, out=None):
             b.bind_to_texref_ext(texrefs.pop(0), allow_double_hack=True)
         else:
             args.append(b)
-        args.append(y.gpudata)
-        args.append(out.gpudata)
-        args.append(x.mem_size)
+        args.extend((y.gpudata, out.gpudata, x.mem_size))
 
         kernel.prepared_call(x._grid, x._block, *args)
 

test/test_gpuarray.py

@@ -26,7 +26,7 @@ def get_random_array(rng, shape, dtype):
         return rng.random(shape, dtype)
     elif dtype.kind in "il":
         return rng.integers(-42, 42, shape, dtype)
-    elif dtype.kind in "u":
+    elif dtype.kind == "u":
         return rng.integers(0, 42, shape, dtype)
     elif dtype.kind == "c":
         real_dtype = np.empty(0, dtype).real.dtype