regex-dna benchmark N=10,000

Each chart bar shows how many times more Memory, one ↓ regex-dna program used, compared to the program that used least Memory.

These are not the only programs that could be written. These are not the only compilers and interpreters. These are not the only programming languages.

Column × shows how many times more each program used compared to the benchmark program that used least.

    sortsort sort
  ×   Program Source Code CPU secs Elapsed secs Memory KB Code B ≈ CPU Load
 Python 3 0.140.19?573  16% 11% 50% 16%
 Python 3 0.140.19?573  28% 53% 11% 15%
 Nuitka 0.140.19?573  11% 30% 22% 40%
 Nuitka 0.140.20?573  16% 19% 11% 42%
 Pyston #5 0.080.08?501  13% 0% 0% 100%
 Cython #5 0.050.05?524  0% 0% 0% 100%
 Pyston #5 0.080.08?501  0% 0% 0% 100%
 Python 2 #5 0.030.03?501  0% 100% 0% 0%
 Python 3 0.110.17?573  25% 13% 6% 19%
 Python 2 #5 0.030.04?501  0% 0% 25% 100%
 Python 2 0.100.16?612  13% 6% 31% 18%
 Pyston #5 0.080.08?501  11% 13% 0% 89%
 Python 2 0.110.17?612  29% 12% 17% 39%
 Cython #5 0.050.06?524  50% 40% 100% 33%
 Python 2 0.090.16?612  31% 13% 7% 13%
 PyPy 2 #5 0.130.13?501  0% 0% 0% 93%
 Python development version 0.120.18?573  17% 6% 6% 41%
 Python development version #5 0.050.05?524  0% 0% 100% 0%
 Python development version 0.130.19?573  11% 40% 11% 16%
 Nuitka 0.140.19?573  5% 11% 55% 15%
 Python 3 #5 0.050.05?524  17% 83% 0% 0%
 Python 2 #5 0.030.03?501  0% 0% 100% 0%
 Python 3 #5 0.050.05?524  0% 100% 0% 0%
 Python development version 0.120.18?573  12% 17% 35% 6%
 Python 3 #5 0.050.05?524  0% 100% 0% 0%
 Cython #5 0.050.05?524  0% 17% 100% 0%
 Python development version #5 0.060.07?524  17% 86% 25% 0%
 PyPy 2 #5 0.130.15?501  7% 6% 7% 85%
 Python development version #5 0.050.05?524  20% 0% 0% 100%
 PyPy 2 #5 0.140.14?501  14% 0% 100% 7%
 PyPy 3 #5 0.250.261,104524  12% 7% 11% 93%
 PyPy 3 #5 0.230.231,116524  5% 0% 0% 100%
 PyPy 3 #5 0.230.231,116524  9% 4% 100% 4%
 IronPython #5 0.730.7344,844501  8% 3% 100% 5%
 IronPython #5 0.730.7345,660501  5% 100% 3% 6%
 IronPython #5 0.700.7046,832501  3% 29% 44% 32%
 PyPy 3 0.570.5471,820573  15% 11% 24% 79%
 PyPy 3 0.590.5671,852573  13% 16% 88% 11%
 PyPy 3 0.570.5571,944573  14% 11% 84% 7%
 Pyston 0.220.2694,520612  15% 62% 11% 12%
 Pyston 0.200.2594,660612  71% 21% 35% 27%
 Pyston 0.210.2594,996612  12% 23% 16% 60%
 Jython #5 3.401.41173,756501  50% 56% 52% 96%
 Jython #5 3.351.42176,284501  46% 92% 52% 57%
 Jython #5 3.701.57190,872501  69% 52% 72% 64%
 PyPy 2 0.330.28209,616612  23% 71% 19% 20%
 PyPy 2 0.320.27210,072612  28% 15% 25% 76%
 PyPy 2 0.370.33223,560612  25% 25% 22% 71%
missing benchmark programs
Shedskin No program
Numba No program
MicroPython No program
Grumpy No program
Graal No program

 regex-dna benchmark : Match DNA 8-mers and substitute nucleotides for IUB codes

diff program output for this 100KB input file (generated with the fasta program N = 10000) with this output file to check your program is correct before contributing.

We are trying to show the performance of various programming language implementations - so we ask that contributed programs not only give the correct result, but also use the same algorithm to calculate that result.

We use FASTA files generated by the fasta benchmark as input for this benchmark. Note: the file may include both lowercase and uppercase codes.

Each program should

Revised BSD license

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