Don't call __Pyx_ImportNumPyArrayTypeIfAvailable() for every fused def function (GH-4935)

Cython.Utils.OrderedSet did not have a `__bool__` function and so
was always treated as "true". The mean that Cython always generated
buffer-handling utility code (`if all_buffer_types:` in FusedNode.py)
even when just handling scalar types.

3 files changed, 34 insertions, 0 deletions

diff --git a/Cython/Utils.py b/Cython/Utils.py
index 0c86ca044..fa4801731 100644
--- a/Cython/Utils.py
+++ b/Cython/Utils.py
@@ -579,6 +579,11 @@ class OrderedSet(object):
             self._list.append(e)
             self._set.add(e)
 
+    def __bool__(self):
+        return bool(self._set)
+
+    __nonzero__ = __bool__
+
 
 # Class decorator that adds a metaclass and recreates the class with it.
 # Copied from 'six'.
diff --git a/tests/compile/fused_buffers.pyx b/tests/compile/fused_buffers.pyx
new file mode 100644
index 000000000..73b0315ed
--- /dev/null
+++ b/tests/compile/fused_buffers.pyx
@@ -0,0 +1,16 @@
+# mode: compile
+
+# cython: test_assert_c_code_has = __Pyx_ImportNumPyArrayTypeIfAvailable
+# cython: test_assert_c_code_has = ndarray
+
+# counterpart test to fused_no_numpy - buffer types are compared against Numpy
+# dtypes as a quick test. fused_no_numpy tests that the mechanism isn't
+# accidentally generated, while this just confirms that the same mechanism is
+# still in use
+
+ctypedef fused IntOrFloat:
+    int
+    float
+
+def f(IntOrFloat[:] x):
+    return x
diff --git a/tests/compile/fused_no_numpy.pyx b/tests/compile/fused_no_numpy.pyx
new file mode 100644
index 000000000..efb49c322
--- /dev/null
+++ b/tests/compile/fused_no_numpy.pyx
@@ -0,0 +1,13 @@
+# mode: compile
+
+# cython: test_fail_if_c_code_has = __Pyx_ImportNumPyArrayTypeIfAvailable
+
+ctypedef fused IntOrFloat:
+    int
+    float
+
+# This function does not use buffers so has no reason to import numpy to
+# look up dtypes. fused_buffers.pyx is the corresponding test for the case
+# where numpy is imported
+def f(IntOrFloat x):
+    return x