108 lines
3.8 KiB
Python
108 lines
3.8 KiB
Python
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"""Fund flow analysis: build directed graph and summary from transactions."""
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from collections import defaultdict
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from decimal import Decimal
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import networkx as nx
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from app.schemas.analysis import (
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AnalysisSummaryResponse,
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AppSummary,
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FlowGraphResponse,
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FlowNode,
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FlowEdge,
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)
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from app.schemas.transaction import TransactionResponse
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# Transaction types that mean money leaving victim's app (outflow)
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OUT_TYPES = {"转出", "消费", "付款", "提现"}
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# Transaction types that mean money entering victim's app (inflow)
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IN_TYPES = {"转入", "收款", "充值"}
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def _is_out(t: TransactionResponse) -> bool:
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return t.transaction_type in OUT_TYPES or "转出" in (t.transaction_type or "") or "消费" in (t.transaction_type or "")
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def _is_in(t: TransactionResponse) -> bool:
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return t.transaction_type in IN_TYPES or "转入" in (t.transaction_type or "") or "收款" in (t.transaction_type or "")
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def _node_id(app_or_counterparty: str, kind: str) -> str:
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"""Generate stable node id; kind in ('victim_app', 'counterparty')."""
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import hashlib
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safe = (app_or_counterparty or "").strip() or "unknown"
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h = hashlib.sha256(f"{kind}:{safe}".encode()).hexdigest()[:12]
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return f"{kind}_{h}"
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def build_flow_graph(transactions: list[TransactionResponse]) -> tuple[FlowGraphResponse, AnalysisSummaryResponse]:
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"""
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Build directed graph and summary from transaction list.
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Node: victim's app (app_source when outflow) or counterparty (counterparty_name or counterparty_account).
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Edge: source -> target with total amount and count.
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"""
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out_by_app: dict[str, Decimal] = defaultdict(Decimal)
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in_by_app: dict[str, Decimal] = defaultdict(Decimal)
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total_out = Decimal(0)
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total_in = Decimal(0)
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counterparties: set[str] = set()
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# (source_id, target_id) -> (amount, count)
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edges_agg: dict[tuple[str, str], tuple[Decimal, int]] = defaultdict(lambda: (Decimal(0), 0))
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node_labels: dict[str, str] = {}
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node_types: dict[str, str] = {}
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for t in transactions:
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amount = t.amount if isinstance(t.amount, Decimal) else Decimal(str(t.amount))
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app = (t.app_source or "").strip() or "未知APP"
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counterparty = (t.counterparty_name or t.counterparty_account or "未知对方").strip() or "未知对方"
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counterparties.add(counterparty)
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victim_node_id = _node_id(app, "victim_app")
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node_labels[victim_node_id] = app
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node_types[victim_node_id] = "victim_app"
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cp_node_id = _node_id(counterparty, "counterparty")
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node_labels[cp_node_id] = counterparty
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node_types[cp_node_id] = "counterparty"
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if _is_out(t):
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out_by_app[app] += amount
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total_out += amount
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key = (victim_node_id, cp_node_id)
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am, cnt = edges_agg[key]
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edges_agg[key] = (am + amount, cnt + 1)
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elif _is_in(t):
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in_by_app[app] += amount
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total_in += amount
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key = (cp_node_id, victim_node_id)
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am, cnt = edges_agg[key]
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edges_agg[key] = (am + amount, cnt + 1)
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all_apps = set(out_by_app.keys()) | set(in_by_app.keys())
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by_app = {
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app: AppSummary(
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in_amount=in_by_app.get(app, Decimal(0)),
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out_amount=out_by_app.get(app, Decimal(0)),
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)
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for app in all_apps
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}
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summary = AnalysisSummaryResponse(
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total_out=total_out,
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total_in=total_in,
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net_loss=total_out - total_in,
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by_app=by_app,
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counterparty_count=len(counterparties),
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)
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nodes = [
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FlowNode(id=nid, label=node_labels[nid], type=node_types.get(nid))
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for nid in node_labels
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]
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edges = [
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FlowEdge(source=src, target=tgt, amount=am, count=cnt)
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for (src, tgt), (am, cnt) in edges_agg.items()
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]
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graph = FlowGraphResponse(nodes=nodes, edges=edges)
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return graph, summary
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