Improve error message for NumPy alias type used as dtype in ArrayNdCtors

Reporting a bug

• I have tried using the latest released version of Numba (most recent is visible in the change log (https://github.com/numba/numba/blob/master/CHANGE_LOG).
• I have included below a minimal working reproducer (if you are unsure how to write one see http://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports).

As per #3993 This

from numba import njit
import numpy as np

@njit
def foo():
    return np.zeros((2, 2), dtype=np.float)

foo()

produces:

numba.core.errors.TypingError: Failed in nopython mode pipeline (step: nopython frontend)
No implementation of function Function(<built-in function zeros>) found for signature:
 
 >>> zeros(UniTuple(Literal[int](2) x 2), dtype=Function(<class 'float'>))
 
There are 2 candidate implementations:
  - Of which 2 did not match due to:
  Overload of function 'zeros': File: numba/core/typing/npydecl.py: Line 504.
    With argument(s): '(UniTuple(int64 x 2), dtype=Function(<class 'float'>))':
   No match.

During: resolving callee type: Function(<built-in function zeros>)
During: typing of call at issue3993.py (25)


File "issue3993.py", line 25:
def foo():
    return np.zeros((2, 2), dtype=np.float)
    ^

which provides correct information given what Numba can infer generically, but this is a common issue and so it’d probably be a good idea to provide a specific message.

Here’s starter patch to provide a better error message:

diff --git a/numba/core/typing/npydecl.py b/numba/core/typing/npydecl.py
index 2dbbed39b..3483fced2 100644
--- a/numba/core/typing/npydecl.py
+++ b/numba/core/typing/npydecl.py
@@ -508,6 +508,25 @@ class NdConstructor(CallableTemplate):
             else:
                 nb_dtype = parse_dtype(dtype)
 
+            if nb_dtype is None:
+                if isinstance(dtype, types.Function):
+                    # user is probably doing `np.float` or `np.int` or similar.
+                    try:
+                        nm = dtype.key[0].__name__
+                        if hasattr(np, nm):
+                            # user probably ought to use a specific type or the
+                            # one with an underscore
+                            if hasattr(np, '%s_' % nm):
+                                msg = ("dtype 'np.%s' is not supported, "
+                                       "perhaps use 'np.%s_' or a more "
+                                       "specific dtype?" % (nm, nm))
+                            else:
+                                msg = "dtype 'np.%s' is not supported" % nm
+                            raise TypingError(msg)
+                    except AttributeError:
+                        pass
+                raise TypingError("dtype '%s' is unsupported." % dtype)
+

with such a patch, this appears:

No implementation of function Function(<built-in function zeros>) found for signature:
 
 >>> zeros(UniTuple(Literal[int](2) x 2), dtype=Function(<class 'float'>))
 
There are 2 candidate implementations:
  - Of which 2 did not match due to:
  Overload in function 'zeros': File: numba/core/typing/npydecl.py: Line 504.
    With argument(s): '(UniTuple(int64 x 2), dtype=Function(<class 'float'>))':
   Rejected as the implementation raised a specific error:
     TypeError: dtype 'np.float' is not supported, perhaps use 'np.float_' or a more specific dtype?

[stuartarchibald]

@abhinavjonnada82 thanks for asking, I think @Luiz6ustav0 has opened a PR for this already in https://github.com/numba/numba/pull/6243. If you’d like to contribute to Numba there’s a good first issue label which contains other issues which might be good to try?

[generic-github-user]

Thank you, I’ve since realized this mistake. The error messages were somewhat difficult to parse at first but it’s more clear now.