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-rw-r--r--Lib/timeit.py14
1 files changed, 14 insertions, 0 deletions
diff --git a/Lib/timeit.py b/Lib/timeit.py
index 4ed24de..2178d52 100644
--- a/Lib/timeit.py
+++ b/Lib/timeit.py
@@ -51,6 +51,9 @@ without arguments.
# python -O for the older versions to avoid timing SET_LINENO
# instructions.
+# XXX Maybe for convenience of comparing with previous Python versions,
+# itertools.repeat() should not be used at all?
+
import sys
import math
import time
@@ -133,6 +136,17 @@ class Timer:
specifies how many times to call timer(), defaulting to 10;
the second argument specifies the timer argument, defaulting
to one million.
+
+ Note: it's tempting to calculate mean and standard deviation
+ from the result vector and report these. However, this is not
+ very useful. In a typical case, the lowest value gives a
+ lower bound for how fast your machine can run the given code
+ snippet; higher values in the result vector are typically not
+ caused by variability in Python's speed, but by other
+ processes interfering with your timing accuracy. So the min()
+ of the result is probably the only number you should be
+ interested in. After that, you should look at the entire
+ vector and apply common sense rather than statistics.
"""
r = []
for i in range(repeat):