Mercurial > cpython-lru_cache-weakref

annotate Tools/stringbench/README @ 84007:dbfbdf2b5c19 3.3

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Fix #17967: For ftp urls CWD to target instead of hopping to each directory towards target. This fixes a bug where target is accessible, but parent directories are restricted.
author Senthil Kumaran <senthil@uthcode.com>
date Sat, 01 Jun 2013 08:27:06 -0700
parents 704630a9c5d5
children
Ignore whitespace changes - Everywhere: Within whitespace: At end of lines:
rev   line source
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704630a9c5d5 Issue #13165: stringbench is now available in the Tools/stringbench folder.
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1 stringbench is a set of performance tests comparing byte string
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2 operations with unicode operations. The two string implementations
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3 are loosely based on each other and sometimes the algorithm for one is
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4 faster than the other.
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5
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6 These test set was started at the Need For Speed sprint in Reykjavik
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7 to identify which string methods could be sped up quickly and to
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8 identify obvious places for improvement.
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9
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10 Here is an example of a benchmark
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704630a9c5d5 Issue #13165: stringbench is now available in the Tools/stringbench folder.
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13 @bench('"Andrew".startswith("A")', 'startswith single character', 1000)
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14 def startswith_single(STR):
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15 s1 = STR("Andrew")
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16 s2 = STR("A")
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17 s1_startswith = s1.startswith
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18 for x in _RANGE_1000:
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19 s1_startswith(s2)
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20
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21 The bench decorator takes three parameters. The first is a short
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22 description of how the code works. In most cases this is Python code
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23 snippet. It is not the code which is actually run because the real
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24 code is hand-optimized to focus on the method being tested.
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25
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26 The second parameter is a group title. All benchmarks with the same
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27 group title are listed together. This lets you compare different
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28 implementations of the same algorithm, such as "t in s"
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29 vs. "s.find(t)".
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31 The last is a count. Each benchmark loops over the algorithm either
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32 100 or 1000 times, depending on the algorithm performance. The output
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33 time is the time per benchmark call so the reader needs a way to know
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34 how to scale the performance.
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35
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36 These parameters become function attributes.
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37
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38
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39 Here is an example of the output
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41
704630a9c5d5 Issue #13165: stringbench is now available in the Tools/stringbench folder.
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42 ========== count newlines
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43 38.54 41.60 92.7 ...text.with.2000.newlines.count("\n") (*100)
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44 ========== early match, single character
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45 1.14 1.18 96.8 ("A"*1000).find("A") (*1000)
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46 0.44 0.41 105.6 "A" in "A"*1000 (*1000)
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47 1.15 1.17 98.1 ("A"*1000).index("A") (*1000)
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49 The first column is the run time in milliseconds for byte strings.
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50 The second is the run time for unicode strings. The third is a
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51 percentage; byte time / unicode time. It's the percentage by which
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52 unicode is faster than byte strings.
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53
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54 The last column contains the code snippet and the repeat count for the
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55 internal benchmark loop.
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56
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57 The times are computed with 'timeit.py' which repeats the test more
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58 and more times until the total time takes over 0.2 seconds, returning
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59 the best time for a single iteration.
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61 The final line of the output is the cumulative time for byte and
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62 unicode strings, and the overall performance of unicode relative to
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63 bytes. For example
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65 4079.83 5432.25 75.1 TOTAL
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66
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67 However, this has no meaning as it evenly weights every test.
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68