regex-dna benchmark N=10,000

Each chart bar shows how many times slower, one ↓ regex-dna program was, compared to the fastest program.

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.

    sort sortsort
  ×   Program Source Code CPU secs Elapsed secs Memory KB Code B ≈ CPU Load
1.0Python 2 #5 0.030.03?501  0% 100% 0% 0%
1.0Python 2 #5 0.030.03?501  0% 0% 100% 0%
1.1Python 2 #5 0.030.04?501  0% 0% 25% 100%
1.4Python development version #5 0.050.05?524  0% 0% 0% 75%
1.4Python development version #5 0.050.05?524  0% 0% 100% 0%
1.4Python development version #5 0.050.05?524  20% 100% 0% 0%
1.6Cython #5 0.050.05?524  0% 0% 0% 100%
1.6Cython #5 0.050.05?524  17% 100% 17% 0%
1.6Cython #5 0.050.05?524  0% 0% 14% 100%
1.7Python 3 #5 0.050.06?524  17% 100% 0% 0%
1.8Python 3 #5 0.050.06?524  100% 0% 0% 0%
1.8Nuitka #5 0.060.06?524  14% 0% 0% 100%
1.8Nuitka #5 0.060.06?524  17% 100% 0% 0%
1.8Nuitka #5 0.060.06?524  0% 100% 0% 0%
2.0Python development version 0.100.07?573  17% 100% 29% 29%
2.1Python 3 #5 0.060.07?524  50% 0% 0% 56%
2.1Python development version 0.110.07?573  88% 38% 29% 25%
2.1Python development version 0.110.07?573  29% 29% 86% 38%
2.2Python 3 0.110.07?573  14% 86% 38% 25%
2.3Python 3 0.120.08?573  29% 14% 86% 25%
2.3Pyston #5 0.080.08?501  0% 0% 0% 100%
2.4Pyston #5 0.080.08?501  13% 0% 0% 100%
2.4Nuitka 0.110.08?573  44% 33% 22% 75%
2.4Nuitka 0.110.08?573  78% 25% 13% 25%
2.4Pyston #5 0.080.08?501  11% 13% 0% 89%
2.5Nuitka 0.120.08?573  29% 22% 86% 25%
3.4Python 3 0.130.11?573  20% 18% 89% 9%
4.2PyPy 2 #5 0.140.14?501  7% 100% 0% 0%
4.2PyPy 2 #5 0.140.14?501  0% 0% 0% 100%
4.4PyPy 2 #5 0.140.14?501  7% 0% 100% 7%
4.8Python 2 0.090.16?612  31% 13% 7% 13%
4.8Python 2 0.100.16?612  13% 6% 31% 18%
5.1Python 2 0.110.17?612  29% 12% 17% 39%
6.8PyPy 3 #5 0.220.23992524  5% 100% 0% 4%
6.9PyPy 3 #5 0.230.231,000524  4% 0% 100% 0%
7.3PyPy 3 #5 0.220.241,068524  8% 0% 4% 92%
7.5Pyston 0.200.2594,660612  71% 21% 35% 27%
7.6Pyston 0.210.2594,996612  12% 23% 16% 60%
8.0Pyston 0.220.2694,520612  15% 62% 11% 12%
10PyPy 2 0.420.341,088612  18% 77% 15% 18%
10PyPy 2 0.430.34996612  23% 20% 79% 18%
11PyPy 2 0.400.35964612  31% 14% 66% 17%
17PyPy 3 0.580.5569,988573  13% 9% 85% 7%
17PyPy 3 0.590.5570,588573  13% 85% 9% 9%
17PyPy 3 0.580.5670,156573  9% 9% 84% 7%
21IronPython #5 0.700.7046,832501  3% 29% 44% 32%
22IronPython #5 0.730.7344,844501  8% 3% 100% 5%
22IronPython #5 0.730.7345,660501  5% 100% 3% 6%
43Jython #5 3.401.41173,756501  50% 56% 52% 96%
43Jython #5 3.351.42176,284501  46% 92% 52% 57%
47Jython #5 3.701.57190,872501  69% 52% 72% 64%
missing benchmark programs
Shedskin No program
Numba No program
MicroPython No program
Grumpy No program
Graal No program
RustPython 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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