It's always best to make the common case fast, that's why no arguments are required. The repository contains the pre-processed pcap files for ease-of-use. Providing no arguments will run all available strategies.

python ProcessPCAP.py

Use python ProcessPCACP.py -h to see all the available options.

The repo contains a parsed json version of feed_arbitaage.pcap. If you want to parse your own, the application allows that. Just specify your input file with -i and its output with -o.

It's a way of using parsed frames (from .pcap) to generate an understanding of the lowest-latency -n (default=2) sources.

No problem - the program will run them all.

Please do. Just add to the main.strategies package and adjust the StrategyMap accordingly.

There is a set of strategies, FrequencyFastestKStrategy that use this parameter. -k normally defaults to 1, which means that we are counting the number of times a given source is the fastest.

Adjusting -k to be 2, for example, means we're curious if a given source is one of the first 2 fastest, and so forth. The obvious downside is that increasing k also means giving less relative merit to 1st place, as opposed to kth place, which are judged equally. This makes sense if there are large number of inputs.

To get fine-grained differentiation, there are other strategies like WeightedFastestStrategy that would distinguish between 1st and 3rd place, for example.