This repository contains a Python module to compute the Weissman Score of a compression algorithm.

The Weissman Score is a fictional performance score for lossless data compression algorithms devised by Tsachy Weissman and Vinith Misra at Stanford University and used in the HBO comedy series Silicon Valley.

The Weissman score W is computed as:

W = alpha * r/r_b * log(T_b)/log(T)

where r and T refer to the compression ratio and time-to-compress of the target algorithm, r_b and T_b refer to same quantities for a standard universal compressor (this implementation uses gzip) and alpha is a scaling constant.

Further information here and here.

You can run the script as follows:

python weissman.py -c <command> -i <input> -o <output> -a <alpha> -r <reps>

Where:

• command is the command to launch the target compression algorithm and compress a specific input file into the output file. This command must keep the original (uncompressed) file
• input is the path to the uncompressed file used in the test
• output is the path to the compressed file generated by command
• alpha is the scaling parameter of the Weissman score
• reps is the number of times the experiment needs to be repeated (mean values are taken to compute the score)

A trivial usage example to compute bzip score is:

python weissman.py -c "bzip2 --keep README.md" -i README.md -o README.md.bz2 -a 1.0 -r 5

This code can also be used within a Python program:

>>> import weissman
>>> weissman.weissman("bzip2 --keep README.md", "README.md", "README.md.bz2", alpha=1.0, reps=5)