Merge pull request #10403 from Carreau/timeit-message

Improve timeit message to fix ambuiguity.

IPython/core/magics/execution.py

@@ -85,10 +85,24 b' class TimeitResult(object):'
         return (math.fsum([(x - mean) ** 2 for x in self.timings]) / len(self.timings)) ** 0.5
 
     def __str__(self):
-        return (u"%s loop%s, average of %d: %s +- %s per loop (using standard deviation)"
-                   % (self.loops,"" if self.loops == 1 else "s", self.repeat,
-                      _format_time(self.average, self._precision),
-                      _format_time(self.stdev, self._precision)))
+        pm = '+-'
+        if hasattr(sys.stdout, 'encoding') and sys.stdout.encoding:
+            try:
+                u'\xb1'.encode(sys.stdout.encoding)
+                pm = u'\xb1'
+            except:
+                pass
+        return (
+            u"{mean} {pm} {std} per loop (mean {pm} std. dev. of {runs} run{run_plural}, {loops} loop{loop_plural} each)"
+                .format(
+                    pm = pm,
+                    runs = self.repeat,
+                    loops = self.loops,
+                    loop_plural = "" if self.loops == 1 else "s",
+                    run_plural = "" if self.repeat == 1 else "s",
+                    mean = _format_time(self.average, self._precision),
+                    std = _format_time(self.stdev, self._precision))
+                )
 
     def _repr_pretty_(self, p , cycle):
        unic = self.__str__()
@@ -959,20 +973,18 b' python-profiler package from non-free.""")'
         ::
 
           In [1]: %timeit pass
-          100000000 loops, average of 7: 5.48 ns +- 0.354 ns per loop (using standard deviation)
+          8.26 ns ± 0.12 ns per loop (mean ± std. dev. of 7 runs, 100000000 loops each)
 
           In [2]: u = None
 
           In [3]: %timeit u is None
-          10000000 loops, average of 7: 22.7 ns +- 2.33 ns per loop (using standard deviation)
+          29.9 ns ± 0.643 ns per loop (mean ± std. dev. of 7 runs, 10000000 loops each)
 
           In [4]: %timeit -r 4 u == None
-          10000000 loops, average of 4: 27.5 ns +- 2.91 ns per loop (using standard deviation)
 
           In [5]: import time
 
           In [6]: %timeit -n1 time.sleep(2)
-          1 loop, average of 7: 2 s +- 4.71 µs per loop (using standard deviation)
 
 
         The times reported by %timeit will be slightly higher than those

IPython/core/tests/test_interactiveshell.py

@@ -598,12 +598,12 b' class TestAstTransform(unittest.TestCase):'
             called.add(x)
         ip.push({'f':f})
         
-        with tt.AssertPrints("average of "):
+        with tt.AssertPrints("std. dev. of"):
             ip.run_line_magic("timeit", "-n1 f(1)")
         self.assertEqual(called, {-1})
         called.clear()
 
-        with tt.AssertPrints("average of "):
+        with tt.AssertPrints("std. dev. of"):
             ip.run_cell_magic("timeit", "-n1 f(2)", "f(3)")
         self.assertEqual(called, {-2, -3})
     
@@ -671,12 +671,12 b' class TestAstTransform2(unittest.TestCase):'
             called.add(x)
         ip.push({'f':f})
 
-        with tt.AssertPrints("average of "):
+        with tt.AssertPrints("std. dev. of"):
             ip.run_line_magic("timeit", "-n1 f(1)")
         self.assertEqual(called, {(1,)})
         called.clear()
 
-        with tt.AssertPrints("average of "):
+        with tt.AssertPrints("std. dev. of"):
             ip.run_cell_magic("timeit", "-n1 f(2)", "f(3)")
         self.assertEqual(called, {(2,), (3,)})