Sverchok Errors Common

sverchok-errors-common

Quick Reference

Purpose

This skill documents the 17 most frequent Sverchok errors: 7 common error patterns that cause silent data corruption, crashes, or wasted computation, and 10 AI-specific mistakes that LLMs consistently make when generating Sverchok code.

Critical Warnings

NEVER output flat data to sv_set() — ALWAYS wrap in the object-level list: sv_set([[data]]), not sv_set([data]).

NEVER mutate data retrieved with sv_get(deepcopy=False) — this corrupts the upstream node's cached output and all downstream consumers.

NEVER use __init__ for node initialization — ALWAYS use sv_init(self, context).

NEVER create sockets inside process() — sockets are created in sv_init() or sv_update() only.

NEVER use zip() directly on mismatched Sverchok lists — ALWAYS use match_long_repeat() first.

NEVER store IFC entity STEP IDs between IfcSverchok tree runs — SvIfcStore.purge() invalidates all IDs on every re-run.

ALWAYS use update=updateNode on every bpy.props property in a Sverchok node.

ALWAYS check output.is_linked before computing expensive results in process().

Decision Tree

Node produces wrong geometry silently?
├── Vertices treated as separate objects → Missing object wrapper: use [[(v1),(v2)]] not [(v1),(v2)]
├── Data appears truncated → Using zip() instead of match_long_repeat()
├── Upstream data corrupted after run → Mutating sv_get(deepcopy=False) data in-place
└── Numbers wrong but no error → Wrong nesting level for data type

Node property changes have no effect?
├── No update= callback on bpy.props → Add update=updateNode
├── Using custom lambda callback → Replace with updateNode
└── Tree.sv_process is False → Enable processing on the tree

Node errors on initialization?
├── Using __init__ instead of sv_init → Use sv_init(self, context)
├── Creating sockets in process() → Move socket creation to sv_init()
└── Wrong socket type alias in SNLite → Use single-letter aliases (v, s, m)

IfcSverchok-specific issues?
├── Entity IDs change between runs → SvIfcStore.purge() resets everything; query by GUID
├── Crash on undo → Known issue; save frequently, use "Re-run all nodes" instead
├── Data not reaching IFC nodes → Use double-nested lists: [["value"]] not ["value"]
└── Entities lost after re-run → Purge clears all entities; rebuild is by design

Part A: 7 Common Error Patterns

Error 1: Nesting Level Errors (Silent Data Corruption)

Wrong nesting level causes downstream nodes to misinterpret data structure. Each vertex is treated as a separate object instead of part of one object.

# WRONG: Flat vertex list: each vertex becomes a separate "object"
self.outputs['Vertices'].sv_set([(0,0,0), (1,0,0)])

# CORRECT: Object-wrapped vertex list: one object with 2 vertices
self.outputs['Vertices'].sv_set([[(0,0,0), (1,0,0)]])

Rule: ALWAYS wrap output data in the object-level list. Even a single object must be [[...]]. See sverchok-syntax-data for full nesting rules.

Error 2: Missing updateNode Callback

Property changes do not trigger node re-evaluation. The node appears stuck on its initial value.

# WRONG: No update callback: property changes are ignored
my_prop: FloatProperty(name='Scale', default=1.0)

# CORRECT: updateNode dispatches PropertyEvent to the update system
from sverchok.data_structure import updateNode
my_prop: FloatProperty(name='Scale', default=1.0, update=updateNode)

Error 3: Not Checking Output Connections

Unnecessary computation runs when outputs are not connected, wasting CPU time.

# WRONG: Always computes, even when no downstream node reads the output
def process(self):
    data = expensive_computation()
    self.outputs['Result'].sv_set(data)

# CORRECT: Early exit when no output is connected
def process(self):
    if not any(s.is_linked for s in self.outputs):
        return
    data = expensive_computation()
    self.outputs['Result'].sv_set(data)

Error 4: Socket Data Mutation (Upstream Corruption)

Modifying input data in-place corrupts the upstream node's cached output. All other downstream nodes reading from the same source receive corrupted data.

# WRONG: Mutating sv_get() data modifies the shared cache
data = self.inputs['Data'].sv_get(deepcopy=False)
data[0].append(999)  # CORRUPTS upstream node's cached output

# CORRECT: Use deepcopy=True (default) when mutating
data = self.inputs['Data'].sv_get(deepcopy=True)
data[0].append(999)  # Safe — working on an independent copy

# CORRECT: Or create new data without mutating (deepcopy=False for performance)
data = self.inputs['Data'].sv_get(deepcopy=False)
result = [sublist + [999] for sublist in data]  # New list, original untouched

Error 5: List Matching Misunderstandings

Using Python's zip() silently truncates data to the shortest input. Sverchok's convention is to repeat the last element of shorter lists.

# WRONG: zip() truncates to shortest: data is silently lost
for v, s in zip(verts, scale):
    ...

# CORRECT: match_long_repeat extends shorter lists by repeating last element
from sverchok.data_structure import match_long_repeat
verts, scale = match_long_repeat([verts, scale])
for v, s in zip(verts, scale):
    ...

Error 6: IfcSverchok Undo Crashes

Blender crashes when undoing operations in IfcSverchok node trees. This is a known limitation of the IfcSverchok integration.

Workaround: Save frequently. Avoid undo in IfcSverchok trees. Use the "Re-run all nodes" button to restore state instead. See sverchok-impl-ifcsverchok for details.

Error 7: IfcSverchok Purge on Re-run

SvIfcStore.purge() is called before every full tree update, clearing all entity data. IFC entities are recreated from scratch on every update — STEP IDs change between runs.

Consequence: Code that stores IFC entity IDs will break on re-run. Query entities by GUID or type instead of by STEP ID. See sverchok-impl-ifcsverchok for entity management patterns.

Part B: 10 AI Common Mistakes

AI Mistake 1: Flat Vertex Data

AI generates flat number lists instead of the required nested structure.

# AI MISTAKE: Returning flat list: downstream nodes fail or misinterpret
result = [1, 2, 3]
self.outputs['Numbers'].sv_set(result)  # WRONG

# CORRECT: Always wrap in object level
self.outputs['Numbers'].sv_set([[1, 2, 3]])

AI Mistake 2: Missing Object Wrapper for Vertices

AI omits the outer list that represents the object level, causing each vertex to be treated as a separate object.

# AI MISTAKE: Vertices at wrong nesting level
verts = [(0,0,0), (1,0,0), (1,1,0)]
self.outputs['Vertices'].sv_set(verts)  # WRONG — each vertex = separate object

# CORRECT: Vertices at level 3 (object list > vertex list > coordinate tuple)
self.outputs['Vertices'].sv_set([[(0,0,0), (1,0,0), (1,1,0)]])

AI Mistake 3: __init__ Instead of sv_init

AI uses Python's standard __init__ instead of Sverchok's sv_init lifecycle method. Blender node classes do not support __init__ for socket creation.

# AI MISTAKE: __init__ is NOT how Sverchok nodes initialize
def __init__(self):
    self.inputs.new(...)  # WRONG — will fail or be ignored

# CORRECT: Use sv_init: called once when node is created
def sv_init(self, context):
    self.inputs.new('SvStringsSocket', 'Data')
    self.outputs.new('SvStringsSocket', 'Result')

AI Mistake 4: Wrong SNLite Socket Type Aliases

AI invents socket type names instead of using Sverchok's single-letter aliases.

# AI MISTAKE: Invalid type aliases in SNLite header
"""
in  verts  vertices  # WRONG — "vertices" is not a valid alias
out result string    # WRONG — "string" is not a valid alias
"""

# CORRECT: Use single-letter aliases
"""
in  verts  v    # v = SvVerticesSocket
out result s    # s = SvStringsSocket
"""
# Valid aliases: s=Strings, v=Vertices, m=Matrix, c=Color

AI Mistake 5: Forgetting updateNode on Properties

AI defines bpy.props properties without the update=updateNode callback, causing property changes to have no visible effect.

# AI MISTAKE: Property changes are silently ignored
count: IntProperty(name='Count', default=5)  # WRONG

# CORRECT: Always include updateNode
from sverchok.data_structure import updateNode
count: IntProperty(name='Count', default=5, update=updateNode)

AI Mistake 6: zip() Instead of match_long_repeat

AI uses Python's zip() which silently truncates mismatched lists. Sverchok's design expects the last element to be repeated.

# AI MISTAKE: zip() silently drops data from longer list
for v, s in zip(verts, scale):  # WRONG — truncates to shortest

# CORRECT: match_long_repeat extends shorter lists
from sverchok.data_structure import match_long_repeat
verts, scale = match_long_repeat([verts, scale])
for v, s in zip(verts, scale):
    ...

AI Mistake 7: Creating Sockets in process()

AI creates sockets inside process(), which runs on every update. This adds duplicate sockets on each evaluation.

# AI MISTAKE: Creates new socket on EVERY update cycle
def process(self):
    self.inputs.new('SvStringsSocket', 'Extra')  # WRONG — duplicates accumulate

# CORRECT: Create sockets in sv_init() (once) or sv_update() (on topology change)
def sv_init(self, context):
    self.inputs.new('SvStringsSocket', 'Extra')

AI Mistake 8: Assuming Matrix Data Is Nested Like Vertices

AI wraps matrices in double-nested lists like vertices. Matrices use a different nesting convention — they are at the object level directly.

# AI MISTAKE: Treating matrices like vertices (extra nesting level)
matrices = [[Matrix(), Matrix()]]  # WRONG — over-nested

# CORRECT: Matrices are at object level (level 1), not nested further
matrices = [Matrix(), Matrix()]
self.outputs['Matrix'].sv_set(matrices)

AI Mistake 9: IfcSverchok Entity ID Persistence

AI stores IFC entity STEP IDs and assumes they persist across tree re-runs. SvIfcStore.purge() resets all data before each full update.

# AI MISTAKE: Caching STEP IDs between runs
saved_id = 42  # WRONG — this ID is invalid after next tree update

# CORRECT: Query by GlobalId (GUID) or by type, never by STEP ID
# GUIDs are stable across re-runs; STEP IDs are not
wall = ifc_file.by_guid("2O2Fr$t4X7Z8jBCV$0Oo9a")

See sverchok-impl-ifcsverchok for stable entity reference patterns.

AI Mistake 10: IfcSverchok Single vs Double Nesting

AI sends single-nested data to IfcSverchok nodes, which expect standard Sverchok double-nested lists.

# AI MISTAKE: Single-nested data to IFC nodes
self.outputs['Names'].sv_set(["Wall_001"])  # WRONG — flat list

# CORRECT: IfcSverchok nodes expect standard Sverchok nesting
self.outputs['Names'].sv_set([["Wall_001"]])

Error Detection Checklist

Use this checklist when debugging Sverchok node issues:

Cross-References

• sverchok-syntax-data — Full data nesting rules, socket types, and nesting level specifications per data type
• sverchok-impl-ifcsverchok — IfcSverchok node patterns, SvIfcStore lifecycle, entity management
• sverchok-impl-custom-nodes — Custom node lifecycle (sv_init, process, sv_update), registration, socket management
• sverchok-core-concepts — Node tree architecture, update system, event types

Reference Links

• references/methods.md — Error detection methods, diagnostic functions, debugging utilities
• references/examples.md — Complete working code examples demonstrating correct patterns for each error
• references/anti-patterns.md — Detailed anti-patterns with WHY explanations and fix strategies

Official Sources

• https://github.com/nortikin/sverchok
• https://github.com/IfcOpenShell/IfcOpenShell/tree/v0.8.0/src/ifcsverchok