RuntimeError: Maximum recursion depth exceeded while constructing DAG from /api/v2/flows/{flowId}/nodes
Analyzing Genesys Cloud flow dependency graphs with Python works fine until the pagination loop grabs 1000 nodes per batch. The caching layer misses a few async transitions anyway. Topological sort keeps choking on circular references that shouldn’t exist. Script crashes before generating the impact report.
import sys
from collections import defaultdict, deque
sys.setrecursionlimit(1500)
def build_dag_iterative(nodes):
adj = defaultdict(list)
in_degree = defaultdict(int)
for node in nodes:
in_degree.setdefault(node['id'], 0)
for target in node.get('nextNodeIds', []):
adj[node['id']].append(target)
in_degree[target] = in_degree.get(target, 0) + 1
queue = deque([n for n in in_degree if in_degree[n] == 0])
topo_order = []
while queue:
u = queue.popleft()
topo_order.append(u)
for v in adj[u]:
in_degree[v] -= 1
if in_degree[v] == 0:
queue.append(v)
return topo_order
purecloudsdk doesn’t auto-resolve circular transitions in flow graphs. Studio loops intentionally create back-edges, which breaks standard DFS recursion. Switching to Kahn’s algorithm keeps memory flat and skips the recursion trap entirely. Pagination on /api/v2/flows/{flowId}/nodes returns nextPageToken, not a flat array. You’ll need to loop until the token vanishes before feeding the list into the graph builder. The SDK handles the chunking, but the local cache still misses async handoffs if you don’t wait for the full dataset. Set a hard timeout on the fetch loop. Studio scripts handle this natively via the SNIPPET action when pulling flow metadata, so offloading the heavy lifting to the platform usually saves the local runtime from choking. Check the nextNodeIds array for self-references or fallback loops. Those are usually the real culprits. Leaves the rest to the parser anyway.
The recursion crash usually happens because flow designers drop fallback conditions that loop back to the same queue or IVR node. When the API grabs a thousand nodes per batch, the dependency graph picks up those hidden circular paths and blows past the stack limit. Same pattern that wrecks SIP registration storms on a BYOC failover pool. The system tries to resolve every transition at once instead of pacing the handshake. the earlier post’s iterative queue approach handles the bulk, but the sort still won’t finish without a cycle breaker to skip those recursive fallback edges. Flow v2024.3.1 packs async wait nodes that reference their own parent container, which throws off the in-degree count.
Add a visited set to the queue loop and drop any edges pointing back to an already processed node. That keeps the sort from hanging on circular fallbacks and matches the retry logic used on carrier trunk failovers. Genesys Cloud routes traffic differently when a primary SIP trunk drops, so the graph needs that same graceful degradation.
visited = set()
while queue:
current = queue.popleft()
visited.add(current)
topo_order.append(current)
for neighbor in adj[current]:
in_degree[neighbor] -= 1
if in_degree[neighbor] == 0 and neighbor not in visited:
queue.append(neighbor)
The impact report generates clean after filtering those self-referencing transitions. Run it against the staging org first.