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Blockchains (L2)

Settlus

# Settlus Active addresses (weekly) Methodology

## 1. Overview

Active addresses weekly measures the number of unique addresses that have initiated at least one transaction on the Settlus blockchain within a 7-day rolling window. This metric provides insight into user engagement and network activity by tracking distinct transaction senders over time. For blockchain networks like Settlus, active addresses and active users are equivalent concepts since each unique address represents a potential user interacting with the network.

## 2. Data sources

- **Settlus transaction records**: Complete transaction history from the Settlus blockchain including transaction hashes, timestamps, sender addresses (`from_address`), and other transaction metadata
- **Blockchain event data**: Transaction-level data capturing all network activity and user interactions on Settlus

## 3. Step-by-step calculation

### Component A: User transaction extraction
- **Purpose**: Identifies all transaction senders (active users) from Settlus blockchain transactions
- **Logic**: Extract all transactions from Settlus blockchain records and identify the sender address (`from_address`) for each transaction. Each transaction sender is classified as a "Transaction sender" user type. The component includes timestamp information (`block_timestamp`) and transaction identifiers (`transaction_hash`) to enable temporal analysis. All users are categorized under the "blockchains_l2" market sector and "blockchain" business segment since Settlus is a Layer 2 blockchain
- **Key fields**: Transaction timestamp (`block_timestamp`), sender address (`user_address`), transaction hash, and classification metadata

### Component B: Daily active user calculation  
- **Purpose**: Calculates daily distinct active users (DAU) by counting unique addresses per day
- **Logic**: Group transactions by day using timestamp truncation and count distinct sender addresses for each day. This eliminates duplicate counting when the same address initiates multiple transactions on the same day. The result is a daily time series of unique active addresses with day-level granularity
- **Key fields**: Daily timestamp (`timestamp`), unique user address (`user_dau`), and associated metadata including chain, user type, and business classifications

### Component C: Weekly active user aggregation using HyperLogLog
- **Purpose**: Calculates weekly active users (WAU) using a 7-day rolling window with efficient distinct counting
- **Logic**: Create a continuous datespine covering all days in the analysis period, then for each day, establish a 7-day rolling window (current day plus 6 preceding days). Use HyperLogLog (HLL) probabilistic data structure to efficiently count distinct addresses across these overlapping windows without double-counting the same address multiple times within a window. The HLL approach allows for memory-efficient processing of large address sets while maintaining accuracy. Generate multiple dimensional breakdowns including project-level, chain-level, user-type-level, and product-level aggregations
- **Key fields**: Weekly timestamp, dimension type (`dimensions`), chain identifier (`chain_id`), and weekly active user count (`user_wau`)

### Final aggregation
- **Combining components**: The weekly active user calculation flows through the HyperLogLog aggregation process, which merges daily HLL sketches across the 7-day windows and extracts the final distinct count
- **Currency conversion**: Not applicable for this metric as it measures address counts rather than monetary values  
- **Time aggregation**: Uses 7-day rolling windows with daily granularity, where each day represents the count of unique addresses active in that day plus the 6 preceding days
- **Final calculation**: Rename `user_wau` to `active_addresses_weekly` to reflect blockchain terminology where active users and active addresses are equivalent concepts. Apply dimensional filtering to include only 'chain' and 'project_dbt_tag' breakdowns for the final metric. The result represents the number of unique Settlus addresses that initiated at least one transaction within each 7-day rolling window

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

Unique active addresses over a rolling 7-day window.

Settlus

Active addresses (weekly)

Active addresses (weekly)

Competitive landscape