22 docs tagged with "contracts"

Learn about macros available in Aztec.nr for code generation and abstraction.

Understand the different types of contract calls in Aztec, including private and public execution modes, and how they compare to Ethereum's call types.

Call functions in other contracts from your Aztec smart contracts to enable composability.

Send messages and data between L1 and L2 contracts using portal contracts and cross-chain messaging.

Compile your Aztec smart contracts into deployable artifacts using aztec-nargo.

Understand the structure and contents of Aztec smart contract artifacts.

Learn how contract classes and instances are created and deployed on the Aztec network.

Learn the fundamental structure of Aztec smart contracts including the contract keyword, directory layout, and how contracts manage state and functions.

Understand contract upgrade patterns in Aztec and how to implement upgradeable contracts.

Define and manage storage state in your Aztec smart contracts using various storage types.

Deploy smart contracts to Aztec using generated TypeScript classes.

Learn how to emit events from your Aztec smart contracts for offchain applications to consume.

Learn how to manage dependencies in your Aztec smart contract projects.

Learn about the inbox mechanism in Aztec portals for receiving messages from L1.

Learn about the outbox mechanism in Aztec portals for sending messages to L1.

Step-by-step guide to profiling Aztec transactions and optimizing contract performance for efficient proof generation.

Prove historical state and note inclusion in your Aztec smart contracts using the Archive tree.

Learn about the portal registry and how it manages L1-L2 contract mappings.

Send transactions to Aztec contracts using Aztec.js with various options and error handling

Learn how to write and run tests for your Aztec.js applications.

Write and run tests for your Aztec smart contracts using Noir's TestEnvironment.

Best practices and techniques for writing gas-efficient contracts on Aztec, optimizing for both proving and execution costs.