Added new IGNORE_OUTPUT flags for doctests. This is useful in cases w…

…here we want the doctest to *run* (maybe later doctests on the same page depend on this code running), but we don't care *exactly* what the output is (maybe the output differs slightly between platforms, but in ways we aren't concerned about testing)

astropy/tests/output_checker.py

@@ -18,6 +18,7 @@
 
 FIX = doctest.register_optionflag('FIX')
 FLOAT_CMP = doctest.register_optionflag('FLOAT_CMP')
+IGNORE_OUTPUT = doctest.register_optionflag('IGNORE_OUTPUT')
 
 
 class AstropyOutputChecker(doctest.OutputChecker):
@@ -149,6 +150,9 @@ def normalize_floats(self, want, got, flags):
         return False
 
     def check_output(self, want, got, flags):
+        if flags & IGNORE_OUTPUT:
+            return True
+
         if flags & FIX:
             want, got = self.do_fixes(want, got)
 

docs/development/testguide.rst

@@ -870,6 +870,19 @@ traceback is skipped in the example output--only the first and last lines
 of the output are checked.  See the :mod:`doctest` documentation for
 more examples of skipping output.
 
+Ignoring all output
+^^^^^^^^^^^^^^^^^^^
+
+Another possibility for ignoring output is to use the
+``# doctest: +IGNORE_OUTPUT`` flag.  This allows a doctest to execute (and
+check that the code executes without errors), but allows the entire output
+to be ignored in cases where we don't care what the output is.  This differs
+from using ellipses in that we can still provide complete example output, just
+without the test checking that it is exactly right.  For example::
+
+    >>> print('Hello world')  # doctest: +IGNORE_OUTPUT
+    We don't really care what the output is as long as there were no errors...
+
 
 Handling float output
 ---------------------

docs/units/quantity.rst

@@ -90,7 +90,7 @@ feature needs to be explicitly turned on:
 .. doctest-requires:: matplotlib
 
     >>> from astropy.visualization import quantity_support
-    >>> quantity_support()
+    >>> quantity_support()  # doctest: +IGNORE_OUTPUT
     <astropy.visualization.units.MplQuantityConverter ...>
 
 Then |quantity| objects can be passed to matplotlib plotting