Liquidity providers deposit funds into Thruster, receive trading fees from traders (supply-side fees).

Thruster is a non-custodial exchange protocol built on Blast. Thruster was launched in 2024.

Thruster team and investors own and govern the protocol. They currently take a cut of the total trading fees paid by traders, and earn native yield (revenue). Thruster's investors include Mirana Ventures, Manifold, OKX Ventures, etc.

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Thruster

# Thruster Trade count Methodology

## 1. Overview

The Thruster trade count metric measures the number of unique trading transactions executed on the Thruster DEX protocols on the Blast network per day. This metric counts distinct transaction hashes that contain swap events, providing insight into trading activity frequency. Thruster operates two types of AMM protocols: Classic AMM (similar to Uniswap V2) and CLAMM (concentrated liquidity AMM similar to Uniswap V3).

## 2. Data sources

- **Thruster factory events**: Parsed `PairCreated` events from ThrusterFactory03 and ThrusterFactory1 contracts, and `PoolCreated` events from ThrusterPoolFactory contract on Blast network
- **Thruster swap events**: Parsed `Swap` events from Thruster Classic AMM pairs (Pair03_Swap_event, Pair1_Swap_event) and CLAMM pools (Pool_Swap_event) on Blast network  
- **Protocol fee events**: Parsed `SetYieldCut` events from Thruster factory contracts tracking fee tier changes over time
- **Blast transaction records**: Complete transaction data including sender addresses and transaction hashes
- **Token metadata**: Token symbols, decimal places, and contract addresses for proper amount normalization
- **End-of-day price feeds**: USD price data for currency conversion in final metric formatting

## 3. Step-by-step calculation

### Component A: Trading pair identification
- **Purpose**: Establish the universe of valid Thruster trading pairs and their metadata
- **Logic**: Extract all pair and pool creation events from Thruster factory contracts. For each trading pair, capture the factory address, pair/pool contract address, token0 and token1 addresses, and fee tier. Join with token metadata to obtain decimal places for each token and create human-readable pair names using token symbols. Apply denylist filtering to exclude problematic pairs (specifically address `0x1d16788b97edb7d9a6ae66d5c5c16469037faa00`).
- **Key fields**: `factory_address`, `account_address` (pair/pool address), `token0_address`, `token1_address`, `fee_tier`, `token0_decimals`, `token1_decimals`, `account_name`

### Component B: Protocol fee tracking
- **Purpose**: Track changes to protocol fee tiers over time from factory events
- **Logic**: Process `SetYieldCut` events from Thruster factory contracts to capture fee tier changes. Calculate protocol fee tier as 1/yieldCut value from the event. Use fill-forward logic to propagate fee tier values across time periods until the next update event occurs.
- **Key fields**: `timestamp`, `account_address`, `protocol_fee_tier`

### Component C: Raw trade extraction
- **Purpose**: Extract and normalize all swap events from Thruster protocols
- **Logic**: Process swap events from both Thruster Classic AMM and CLAMM protocols. For Classic AMM swaps, calculate net token amounts as the difference between `amountIn` and `amountOut` for each token. For CLAMM swaps, use the direct `amount0` and `amount1` values from the swap event. Join each swap event with Blast transaction data to identify the actual user address (transaction sender) rather than just the contract caller. Extract business classification metadata including chain ID, market sector as 'exchanges', business segment as 'dex', and product ID based on protocol type ('thrusterclassic' or 'thrusterclamm').
- **Key fields**: `block_timestamp`, `transaction_hash`, `log_index`, `account_address`, `contract_user_address`, `user_address`, `token0_amount`, `token1_amount`

### Component D: Trade data enrichment
- **Purpose**: Combine raw trade data with pair metadata and normalize amounts
- **Logic**: Join the raw trade events with trading pair metadata to obtain token addresses, decimals, and fee tiers. Add protocol fee tier information using the fee tracking data, with special logic that applies different default fee tiers before and after the fee switch activation timestamp (April 10, 2024 04:58:19 UTC). Normalize token amounts by dividing raw values by 10 raised to the power of each token's decimal places to convert from blockchain integer representation to human-readable amounts. Take absolute values of token amounts to handle directional differences between buy and sell operations.
- **Key fields**: `timestamp`, `transaction_hash`, `token0_address`, `token1_address`, `fee_tier`, `protocol_fee_tier`, `token0_amount`, `token1_amount`

### Final aggregation
- **Combining components**: The enriched trade data serves as the complete dataset containing all necessary trade information with proper normalization and metadata
- **Currency conversion**: USD conversion is handled by the finalize_metric macro using end-of-day price feeds
- **Time aggregation**: Block timestamps are truncated to daily boundaries using timestamp_trunc function to create daily aggregation periods
- **Final calculation**: Group the enriched trade data by timestamp (day), chain ID, market sector ID, business segment ID, and product ID. Count distinct transaction hashes within each group to determine the number of unique trading transactions per day. Apply the finalize_metric_trade_count macro for standardized formatting with fill_zeros strategy to ensure continuous time series. Filter final results based on chain availability configuration to include only supported networks.

*This methodology was automatically generated by Token Terminal's methodology analyzer.*

Number of trades executed on a decentralized exchange.

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