client API for on-chain pyth programs
# depends on openssl
apt install libssl-dev
# depends on libz
apt install zlib1g zlib1g-dev
# depends on libzstd
apt install libzstd-dev
# uses cmake to build
apt install cmake
# default is release build
./scripts/build.sh
You may want to build this repository inside a linux docker container for various reasons, e.g., if building on an M1 mac, or to run BPF binaries. You can run the following command to open a shell in a linux docker container with the pyth-client directory mounted:
export PYTH_REPO=/path/to/host/pyth-client
export IMAGE="docker.io/pythfoundation/pyth-client:devnet-v2.8.1"
docker run -it \
--volume "${HOME}:/home/pyth/home" \
--volume "${HOME}/.config:/home/pyth/.config" \
--mount "type=bind,src=${PYTH_REPO},target=/home/pyth/pyth-client" \
--userns=host \
--user="$( id -ur ):$( id -gr )" \
--platform linux/amd64 \
$IMAGE \
/bin/bash -l
This command runs a recent pyth-client docker image that already has the necessary dependencies installed.
Therefore, once the container is running, all you have to do is run cd pyth-client && ./scripts/build.sh.
Note that updates to the pyth-client directory made inside the docker container will be persisted to the host filesystem (which is probably desirable).
Build a docker image for running fuzz tests:
docker build . --platform linux/amd64 -f docker/fuzz/Dockerfile -t pyth-fuzz
Each fuzz test is invoked via an argument to the fuzz command-line program,
and has a corresponding set of test cases in the subdirectory with the same name as the test.
You can run these tests using a command like:
docker run -t \
--platform linux/amd64 \
-v "$(pwd)"/findings:/home/pyth/pyth-client/findings \
pyth-fuzz \
sh -c "./afl/afl-fuzz -i ./pyth-client/pyth/tests/fuzz/add/testcases -o ./pyth-client/findings ./pyth-client/build/fuzz add"
This command will run the add fuzz test on the tests cases in pyth/tests/fuzz/add/testcases, saving any outputs to findings/.
Note that findings/ is shared between the host machine and the docker container, so you can inspect any error cases
by looking in that subdirectory on the host.
If you find an error case that you want to investigate further, you can run the program on the failing input using something like:
docker run -t \
--platform linux/amd64 \
-v "$(pwd)"/findings:/home/pyth/pyth-client/findings \
pyth-fuzz \
sh -c "./pyth-client/build/fuzz add < ./pyth-client/findings/crashes/id\:000000\,sig\:06\,src\:000000\,op\:flip1\,pos\:0"
in this example, id\:000000\,sig\:06\,src\:000000\,op\:flip1\,pos\:0 is the file containing the failing input.