Uniswap Labs collects fees from trades conducted through its interfaces.

Uniswap Labs, established by Hayden Adams in 2018, is a software development company that specializes in creating products for the Uniswap Protocol. This includes the development and maintenance of various applications like the Uniswap web app, a mobile wallet, and an NFT aggregator.

Uniswap Labs acts as a developer and maintainer of the Uniswap Protocol. The company functions independently from the decentralized governance of the protocol.

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Uniswap Labs

# Uniswap Labs Active users (weekly) Methodology

## 1. Overview

Weekly Active Users (WAU) measures the number of unique users who generated fee-paying transactions with Uniswap Labs products within a rolling 7-day window. The metric uses HyperLogLog probabilistic data structures to efficiently count unique users across multiple dimensions including chain, user type, and product. This metric captures trading activity across Uniswap's universal router and UniswapX protocol on seven blockchain networks.

## 2. Data sources

- **Token transfer events**: Parsed `Transfer` events from Ethereum, Arbitrum, Base, BSC, Polygon, Optimism, and Avalanche showing token movements between addresses
- **Transaction records**: Blockchain transaction data from all seven supported chains containing originating user addresses (`from_address`)  
- **UniswapX events**: Parsed `Fill` events from the `UniswapXDutchOrderReactor` contract on Ethereum identifying Dutch auction order executions
- **Router addresses**: Hardcoded list of universal router contract addresses across chains that facilitate swaps
- **Collector addresses**: Hardcoded list of fee collection addresses where Uniswap Labs captures interface fees
- **Contract metadata**: Version identifiers and business classification data for different Uniswap products

## 3. Step-by-step calculation

### Component A: Swap fee identification
- **Purpose**: Identifies fee-paying transactions from universal router swaps across multiple chains
- **Logic**: Filters token transfer events where the `from_address` matches known universal router contracts and the `to_address` matches Uniswap collector addresses. Only includes transfers between July 1, 2023 and December 25, 2025 (when interface fees were set to zero). Joins with transaction records to obtain the originating user address (`from_address`) who initiated the transaction. Excludes transfers involving a specific denylisted token address
- **Key fields**: `block_timestamp` for timing, `transaction_hash` for grouping, `token_address` for fee token identification, `value` for transfer amounts, `from_address` from transactions as user identifier

### Component B: Dutch auction fee identification  
- **Purpose**: Identifies fee-paying transactions from UniswapX Dutch auction orders
- **Logic**: Uses `Fill` events from the UniswapX Dutch order reactor to identify auction transactions, then filters token transfers within those transactions going to collector addresses. Joins with transaction data to get user addresses. Currently only operates on Ethereum network
- **Key fields**: `swapper` from Fill events as user identifier, `block_timestamp` for timing, token transfer `value` amounts

### Component C: Daily active user extraction
- **Purpose**: Converts fee transactions into daily unique user counts  
- **Logic**: Takes the union of swap fees and Dutch auction fees, then groups by daily timestamp boundaries (`timestamp_trunc` to day level). Extracts unique `user_address` values per day and classifies all users as `Trader` type. Maintains dimensional breakdowns by `chain`, `product_id`, and other business metadata
- **Key fields**: `timestamp` truncated to day, `user_address` as the unique identifier, `chain` for network identification

### Component D: HyperLogLog conversion
- **Purpose**: Converts daily user lists into probabilistic sketches for efficient aggregation
- **Logic**: Applies `hll_count.init` function to convert the daily unique user addresses into HyperLogLog sketches with precision parameter 15. Groups data by timestamp, chain, user type, and product dimensions to create separate sketches for each combination
- **Key fields**: `hll` sketch containing compressed user data, dimensional grouping fields

### Component E: Rolling window construction  
- **Purpose**: Creates 7-day rolling windows for each date to calculate weekly active users
- **Logic**: Builds a datespine covering all dates from the earliest data to yesterday. For each date in the spine, creates joins with the 6 preceding days using `generate_timestamp_array` with 6-day lookback. Joins this expanded date range with the daily HLL sketches to capture all user activity within each 7-day window
- **Key fields**: `timestamp` as the window end date, `joinday` representing each day within the window, `hll` sketches from daily data

### Final aggregation
- **Combining components**: Merges HLL sketches across the 7-day window using `hll_count.merge_partial` to combine probabilistic user counts, then extracts the final unique count with `hll_count.extract`
- **Dimensional breakdowns**: Creates separate aggregations for project-level (all dimensions nulled), chain-level, user-type-level, and product-level views, then unions all breakdowns together
- **Time boundaries**: Uses daily timestamp truncation with rolling 7-day windows, applying incremental processing with partition-based filtering and safety margins
- **Final calculation**: The WAU metric represents the estimated count of unique user addresses who generated fee-paying transactions within any 7-day period ending on the given date, calculated using HyperLogLog probabilistic counting across multiple dimensional breakdowns

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

Unique revenue-generating users over a rolling 7-day window.

Uniswap Labs

Active users (weekly)

Active users (weekly)

Competitive landscape

Chain breakdown