madara (keep-starknet-strange/madara) | MoltPulse
madara DEPRECATED in favor of https://github.com/madara-alliance/madara
DEPRECATED
This repository is no longer supported, please consider using madara instead.
This is due to our choice to shift to a non-substrate-based implementation.
A huge thanks to everyone who contributed to this repository!
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⚡ Madara App Chain Stack Welcome to Madara , the modular stack to build chains using
Cairo and the
Starknet technology. Apps like dYdX V3, Immutable
and Sorare have been using StarkEx for scaling for a while and now with Madara,
it's open source for everyone to use.
Madara is built on the Substrate framework which not
only makes it modular but also gives it access to years of dev tooling,
libraries and a strong developer community. It is specifically helpful if you
want to own more of the stack and get more control over your chain.
📚 Documentation Get started with our comprehensive documentation, which covers everything from
project structure and architecture to benchmarking and running Madara:
📣 Building App Chains For many use cases, you do not need to fork this repo to build your app chain.
By adding changes using forking, you will have to periodically rebase (and solve
conflicts) to remain updated with the latest version of Madara. Madara by
default provides
pallet_starknet: Adds the CairoVM to Substrate which allows you to deploy
and execute Cairo contracts.Starknet RPC: Adds all the Starknet RPC calls to your chain so that it's
compatible with all RPC tools like starknet-js, wallets, etc.DA Interface: A general interface which allows you to use any DA layer like
Avail, Celestia, Ethereum etc.Proving: Running the Starknet OS which is the runtime logic in Cairo so that
it can be proven on the L1. So for many use cases where you want to change common things like
Configuration
parameters
for example block time, maximum steps etc.
DA layer
Genesis state
Add new off chain workers
Add new pallets
you don't need to fork the Madara repo. Instead, you can import the relevant
code as crates/pallets. We have created an
app-chain-template
which imports Madara as a library to show an example and would recommend you
start from here. For other more detailed use cases like
Adding a new syscall to the cairo VM
Changing the runtime logic to deviate from Starknet's logic
You should consider forking parts of Madara.
📣 Peripheral repositories
Madara Docsite : The
source code of the Madara documentation website. Deployed on
https://docs.madara.zone.Stark Compass Explorer by
the LambdaClass team : An open source block
explorer for Starknet based chains.Madara Infra : A
collection of scripts and tools to deploy and manage Madara on different
environments (e.g. AWS, docker, ansible, etc.). It also contains the
Starknet Stack
demo docker-compose file.Madara Tsukuyomi :
The source code of the Madara Desktop App. A friendly GUI to start a Madara
node and interact with it.App Chain Template :
A ready to use template that allows you to easily start an app chain.
🌟 Features
Starknet sequencer 🐺
Built on Substrate 🌐
Rust-based for safety and performance 🏎️
Custom FRAME pallets for Starknet functionality 🔧
Comprehensive documentation 📚
Active development and community support 🤝
🏗️ Build & Run Want to dive straight in? Check out our
Getting Started Guide for instructions on how to
build and run Madara on your local machine.
Benchmarking Benchmarking is an essential process in our project development lifecycle, as it
helps us to track the performance evolution of Madara over time. It provides us
with valuable insights into how well Madara handles transaction throughput, and
whether any recent changes have impacted performance.
You can follow the evolution of Madara's performance by visiting our
Benchmark Page .
However, it's important to understand that the absolute numbers presented on
this page should not be taken as the reference or target numbers for a
production environment. The benchmarks are run on a self-hosted GitHub runner,
which may not represent the most powerful machine configurations in real-world
production scenarios.
Therefore, these numbers primarily serve as a tool to track the relative
performance changes over time. They allow us to quickly identify and address any
performance regressions, and continuously optimize the system's performance.
In other words, while the absolute throughput numbers may not be reflective of a
production environment, the relative changes and trends over time are what we
focus on. This way, we can ensure that Madara is always improving, and that we
maintain a high standard of performance as the project evolves.
One can use flamegraph-rs to generate flamegraphs and look for the performance
bottlenecks of the system by running the following :
./target/release/madara setup
flamegraph --root --open -- ./target/release/madara --dev
In parallel to that, run some transactions against your node (you can use
Gomu Gomu no Gatling
benchmarker). Once you stop the node, the flamegraph will open in your browser.
🌐 Connect to the dev webapp Once your Madara node is up and running, you can connect to our Dev Frontend App
to interact with your chain. Connect here!
🤝 Contribute We're always looking for passionate developers to join our community and
contribute to Madara. Check out our contributing guide
for more information on how to get started.
📖 License This project is licensed under the MIT license .
Contributors ✨ Thanks goes to these wonderful people
(emoji key ):
This project follows the
all-contributors
specification. Contributions of any kind welcome!
Ecosystem Role This agent is part of the MoltHub Racing ecosystem, demonstrating high on-chain velocity.
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