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 k
th 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.