Cross-Network Relationship Mapping

Implementation Details

Class Names

Model Name	Parameters Class	Data Class
CrossNetworkMapping	CrossNetworkMappingQueryParams	CrossNetworkMappingData

Import Statement

pythonCopyEditfrom satoshi_terminal.models.cross_network_mapping import (
    CrossNetworkMapping,
    CrossNetworkMappingQueryParams,
    CrossNetworkMappingData,
)

---

Parameters

Name	Type	Description	Default	Optional
source_chain	str	Source blockchain (e.g., Ethereum, Solana) for asset mapping.	None	True
target_chain	str	Target blockchain for asset flow analysis.	None	True
asset_type	Union[str, List[str]]	Asset type(s) to track (e.g., tokens, NFTs).	None	True
time_range	Tuple[datetime, datetime]	Date range for transaction flow analysis.	None	True

---

Data

Name	Type	Description
transaction_id	str	Unique identifier for cross-chain transactions.
source_chain	str	Blockchain where the transaction originated.
target_chain	str	Blockchain where the transaction was completed.
asset_id	str	Identifier of the asset being transferred.
transfer_amount	float	Amount of the asset transferred.
timestamp	datetime	Date and time of the transfer.

---

Feature Documentation: Smart Contract Behavioral Profiling

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Implementation Details

Class Names

Model Name	Parameters Class	Data Class
SmartContractBehaviorProfiling	SmartContractBehaviorQueryParams	SmartContractBehaviorData

Import Statement

pythonCopyEditfrom satoshi_terminal.models.smart_contract_behavior import (
    SmartContractBehaviorProfiling,
    SmartContractBehaviorQueryParams,
    SmartContractBehaviorData,
)

---

Parameters

Name	Type	Description	Default	Optional
contract_address	Union[str, List[str]]	Smart contract address(es) to analyze.	None	True
event_type	str	Event type (e.g., "Transfer", "Approval") to monitor.	None	True
time_range	Tuple[datetime, datetime]	Date range for behavioral profiling.	None	True

---

Data

Name	Type	Description
contract_address	str	Address of the smart contract analyzed.
anomaly_score	float	Anomaly score indicating unusual behavior.
event_count	int	Number of events triggered during the time range.
function_call_patterns	List[str]	Frequent function calls and their occurrence patterns.
timestamp	datetime	Timestamp of the last analysis.

---

Feature Documentation: Machine-Learning-Driven Wallet Clustering

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Implementation Details

Class Names

Model Name	Parameters Class	Data Class
WalletClustering	WalletClusteringQueryParams	WalletClusteringData

Import Statement

pythonCopyEditfrom satoshi_terminal.models.wallet_clustering import (
    WalletClustering,
    WalletClusteringQueryParams,
    WalletClusteringData,
)

---

Parameters

Name	Type	Description	Default	Optional
wallet_address	Union[str, List[str]]	Wallet address(es) to include in clustering analysis.	None	True
clustering_method	str	Method for clustering (e.g., "Behavioral", "Geographic").	None	True
time_range	Tuple[datetime, datetime]	Date range for activity clustering.	None	True

---

Data

Name	Type	Description
cluster_id	str	Identifier for the wallet cluster.
wallet_addresses	List[str]	List of wallets in the cluster.
common_behaviors	List[str]	Frequently observed patterns among wallets in the cluster.
anomaly_score	float	Anomaly score for unusual activity within the cluster.
timestamp	datetime	Timestamp of the clustering operation.