openpilot/cereal/messaging/tests/validate_sp_cereal_upstream.py
github-actions[bot] 1f7233cb98 sunnypilot v0.10.1
version: sunnypilot v0.10.1 (staging-tici)
date: 2025-10-13T01:35:37
master commit: 737a6c4236e843034680c951005b38d15815363f
2025-10-13 01:35:37 +00:00

223 lines
6.0 KiB
Python
Executable File

#!/usr/bin/env python3
import argparse
import sys
from typing import Any, List, Tuple
DEBUG = False
def print_debug(string: str) -> None:
if DEBUG:
print(string)
def create_schema_instance(struct: Any, prop: Tuple[str, Any]) -> Any:
"""
Create a new instance of a schema type, handling different field types.
Args:
struct: The Cap'n Proto schema structure
prop: A tuple containing the field name and field metadata
Returns:
A new initialized schema instance
"""
struct_instance = struct.new_message()
field_name, field_metadata = prop
try:
field_type = field_metadata.proto.slot.type.which()
# Initialize different types of fields
if field_type in ('list', 'text', 'data'):
struct_instance.init(field_name, 1)
print_debug(f"Initialized list/text/data field: {field_name}")
elif field_type in ('struct', 'object'):
struct_instance.init(field_name)
print_debug(f"Initialized struct/object field: {field_name}")
return struct_instance
except Exception as e:
print(f"Error creating instance for {field_name}: {e}")
return None
def get_schema_fields(schema_struct: Any) -> List[Tuple[str, Any]]:
"""
Retrieve all fields from a given schema structure.
Args:
schema_struct: The Cap'n Proto schema structure
Returns:
A list of field names and their metadata
"""
try:
# Get all fields from the schema
schema_fields = list(schema_struct.schema.fields.items())
print_debug("Discovered schema fields:")
for field_name, field_metadata in schema_fields:
print_debug(f"- {field_name}")
return schema_fields
except Exception as e:
print(f"Error retrieving schema fields: {e}")
return []
def generate_schema_instances(schema_struct: Any) -> List[Any]:
"""
Generate instances for all fields in a given schema.
Args:
schema_struct: The Cap'n Proto schema structure
Returns:
A list of schema instances
"""
schema_fields = get_schema_fields(schema_struct)
instances = []
for field_prop in schema_fields:
try:
instance = create_schema_instance(schema_struct, field_prop)
if instance is not None:
instances.append(instance)
except Exception as e:
print(f"Skipping field due to error: {e}")
print(f"Generated {len(instances)} schema instances")
return instances
def persist_instances(instances: List[Any], filename: str) -> None:
"""
Write schema instances to a binary file.
Args:
instances: List of schema instances
filename: Output file path
"""
try:
with open(filename, 'wb') as f:
for instance in instances:
f.write(instance.to_bytes())
print(f"Successfully wrote {len(instances)} instances to {filename}")
except Exception as e:
print(f"Error persisting instances: {e}")
sys.exit(1)
def read_instances(filename: str, schema_type: Any) -> List[Any]:
"""
Read schema instances from a binary file.
Args:
filename: Input file path
schema_type: The schema type to use for reading
Returns:
A list of read schema instances
"""
try:
with open(filename, 'rb') as f:
data = f.read()
instances = list(schema_type.read_multiple_bytes(data))
print(f"Read {len(instances)} instances from {filename}")
return instances
except Exception as e:
print(f"Error reading instances: {e}")
sys.exit(1)
def compare_schemas(original_instances: List[Any], read_instances: List[Any]) -> bool:
"""
Compare original and read-back instances to detect potential breaking changes.
Args:
original_instances: List of originally generated instances
read_instances: List of instances read back from file
Returns:
Boolean indicating whether schemas appear compatible
"""
if len(original_instances) != len(read_instances):
print("❌ Schema Compatibility Warning: Instance count mismatch")
return False
compatible = True
for struct in read_instances:
try:
getattr(struct, struct.which()) # Attempting to access the field to validate readability
except Exception as e:
print(f"❌ Structural change detected: {struct.which()} is not readable.\nFull error: {e}")
compatible = False
return compatible
def main():
"""
CLI entry point for schema compatibility testing.
"""
# Setup argument parser
parser = argparse.ArgumentParser(
description='Cap\'n Proto Schema Compatibility Testing Tool',
epilog='Test schema compatibility by generating and reading back instances.'
)
# Add mutually exclusive group for generation or reading mode
mode_group = parser.add_mutually_exclusive_group(required=True)
mode_group.add_argument('-g', '--generate', action='store_true',
help='Generate schema instances')
mode_group.add_argument('-r', '--read', action='store_true',
help='Read and validate schema instances')
# Common arguments
parser.add_argument('-f', '--file',
default='schema_instances.bin',
help='Output/input binary file (default: schema_instances.bin)')
# Parse arguments
args = parser.parse_args()
# Import the schema dynamically
try:
from cereal import log
schema_type = log.Event
except ImportError:
print("Error: Unable to import schema. Ensure 'cereal' is installed.")
sys.exit(1)
# Execute based on mode
if args.generate:
print("🔧 Generating Schema Instances")
instances = generate_schema_instances(schema_type)
persist_instances(instances, args.file)
print("✅ Instance generation complete")
elif args.read:
print("🔍 Reading and Validating Schema Instances")
generated_instances = generate_schema_instances(schema_type)
read_back_instances = read_instances(args.file, schema_type)
# Compare schemas
if compare_schemas(generated_instances, read_back_instances):
print("✅ Schema Compatibility: No breaking changes detected")
sys.exit(0)
else:
print("❌ Potential Schema Breaking Changes Detected")
sys.exit(1)
if __name__ == "__main__":
main()