This repository contains Jito's fork of the Solana validator.
We recommend checking out our Gitbook for more detailed instructions on building and running Jito-Solana.
$ curl https://sh.rustup.rs -sSf | sh
$ source $HOME/.cargo/env
$ rustup component add rustfmtWhen building the master branch, please make sure you are using the latest stable rust version by running:
$ rustup updateWhen building a specific release branch, you should check the rust version in ci/rust-version.sh and if necessary,
install that version by running:
$ rustup install VERSIONNote that if this is not the latest rust version on your machine, cargo commands may require an override in order to use the correct version.
On Linux systems you may need to install libssl-dev, pkg-config, zlib1g-dev, protobuf etc.
On Ubuntu:
$ sudo apt-get update
$ sudo apt-get install libssl-dev libudev-dev pkg-config zlib1g-dev llvm clang cmake make libprotobuf-dev protobuf-compiler libclang-devOn Fedora:
$ sudo dnf install openssl-devel systemd-devel pkg-config zlib-devel llvm clang cmake make protobuf-devel protobuf-compiler perl-core libclang-dev$ git clone https://github.com/jito-foundation/jito-solana.git
$ cd jito-solana$ ./cargo buildNote
Note that this builds a debug version that is not suitable for running a testnet or mainnet validator. Please read docs/src/cli/install.md for instructions to build a release version for test and production uses.
Run the test suite:
$ ./cargo testStart your own testnet locally, instructions are in the online docs.
devnet- stable public cluster for development accessible via devnet.solana.com. Runs 24/7. Learn more about the public clusters
First, install the nightly build of rustc. cargo bench requires the use of the
unstable features only available in the nightly build.
$ rustup install nightlyRun the benchmarks:
$ cargo +nightly benchThe release process for this project is described here.
To generate code coverage statistics:
$ scripts/coverage.sh
$ open target/cov/lcov-local/index.htmlWhy coverage? While most see coverage as a code quality metric, we see it primarily as a developer productivity metric. When a developer makes a change to the codebase, presumably it's a solution to some problem. Our unit-test suite is how we encode the set of problems the codebase solves. Running the test suite should indicate that your change didn't infringe on anyone else's solutions. Adding a test protects your solution from future changes. Say you don't understand why a line of code exists, try deleting it and running the unit-tests. The nearest test failure should tell you what problem was solved by that code. If no test fails, go ahead and submit a Pull Request that asks, "what problem is solved by this code?" On the other hand, if a test does fail and you can think of a better way to solve the same problem, a Pull Request with your solution would most certainly be welcome! Likewise, if rewriting a test can better communicate what code it's protecting, please send us that patch!