forked from IQ.Lvbs/IQ.Pilot
IQ.Pilot Release Commit @ f2a861c
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222
iqpilot/cereal/messaging/tests/validate_sp_cereal_upstream.py
Executable file
222
iqpilot/cereal/messaging/tests/validate_sp_cereal_upstream.py
Executable file
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#!/usr/bin/env python3
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import argparse
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import sys
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from typing import Any, List, Tuple
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DEBUG = False
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def print_debug(string: str) -> None:
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if DEBUG:
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print(string)
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def create_schema_instance(struct: Any, prop: Tuple[str, Any]) -> Any:
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"""
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Create a new instance of a schema type, handling different field types.
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Args:
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struct: The Cap'n Proto schema structure
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prop: A tuple containing the field name and field metadata
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Returns:
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A new initialized schema instance
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"""
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struct_instance = struct.new_message()
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field_name, field_metadata = prop
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try:
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field_type = field_metadata.proto.slot.type.which()
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# Initialize different types of fields
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if field_type in ('list', 'text', 'data'):
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struct_instance.init(field_name, 1)
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print_debug(f"Initialized list/text/data field: {field_name}")
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elif field_type in ('struct', 'object'):
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struct_instance.init(field_name)
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print_debug(f"Initialized struct/object field: {field_name}")
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return struct_instance
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except Exception as e:
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print(f"Error creating instance for {field_name}: {e}")
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return None
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def get_schema_fields(schema_struct: Any) -> List[Tuple[str, Any]]:
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"""
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Retrieve all fields from a given schema structure.
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Args:
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schema_struct: The Cap'n Proto schema structure
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Returns:
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A list of field names and their metadata
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"""
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try:
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# Get all fields from the schema
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schema_fields = list(schema_struct.schema.fields.items())
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print_debug("Discovered schema fields:")
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for field_name, field_metadata in schema_fields:
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print_debug(f"- {field_name}")
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return schema_fields
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except Exception as e:
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print(f"Error retrieving schema fields: {e}")
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return []
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def generate_schema_instances(schema_struct: Any) -> List[Any]:
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"""
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Generate instances for all fields in a given schema.
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Args:
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schema_struct: The Cap'n Proto schema structure
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Returns:
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A list of schema instances
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"""
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schema_fields = get_schema_fields(schema_struct)
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instances = []
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for field_prop in schema_fields:
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try:
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instance = create_schema_instance(schema_struct, field_prop)
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if instance is not None:
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instances.append(instance)
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except Exception as e:
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print(f"Skipping field due to error: {e}")
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print(f"Generated {len(instances)} schema instances")
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return instances
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def persist_instances(instances: List[Any], filename: str) -> None:
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"""
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Write schema instances to a binary file.
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Args:
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instances: List of schema instances
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filename: Output file path
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"""
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try:
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with open(filename, 'wb') as f:
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for instance in instances:
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f.write(instance.to_bytes())
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print(f"Successfully wrote {len(instances)} instances to {filename}")
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except Exception as e:
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print(f"Error persisting instances: {e}")
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sys.exit(1)
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def read_instances(filename: str, schema_type: Any) -> List[Any]:
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"""
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Read schema instances from a binary file.
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Args:
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filename: Input file path
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schema_type: The schema type to use for reading
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Returns:
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A list of read schema instances
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"""
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try:
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with open(filename, 'rb') as f:
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data = f.read()
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instances = list(schema_type.read_multiple_bytes(data))
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print(f"Read {len(instances)} instances from {filename}")
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return instances
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except Exception as e:
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print(f"Error reading instances: {e}")
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sys.exit(1)
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def compare_schemas(original_instances: List[Any], read_instances: List[Any]) -> bool:
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"""
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Compare original and read-back instances to detect potential breaking changes.
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Args:
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original_instances: List of originally generated instances
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read_instances: List of instances read back from file
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Returns:
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Boolean indicating whether schemas appear compatible
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"""
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if len(original_instances) != len(read_instances):
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print("❌ Schema Compatibility Warning: Instance count mismatch")
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return False
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compatible = True
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for struct in read_instances:
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try:
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getattr(struct, struct.which()) # Attempting to access the field to validate readability
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except Exception as e:
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print(f"❌ Structural change detected: {struct.which()} is not readable.\nFull error: {e}")
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compatible = False
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return compatible
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def main():
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"""
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CLI entry point for schema compatibility testing.
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"""
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# Setup argument parser
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parser = argparse.ArgumentParser(
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description='Cap\'n Proto Schema Compatibility Testing Tool',
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epilog='Test schema compatibility by generating and reading back instances.'
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)
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# Add mutually exclusive group for generation or reading mode
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mode_group = parser.add_mutually_exclusive_group(required=True)
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mode_group.add_argument('-g', '--generate', action='store_true',
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help='Generate schema instances')
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mode_group.add_argument('-r', '--read', action='store_true',
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help='Read and validate schema instances')
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# Common arguments
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parser.add_argument('-f', '--file',
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default='schema_instances.bin',
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help='Output/input binary file (default: schema_instances.bin)')
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# Parse arguments
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args = parser.parse_args()
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# Import the schema dynamically
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try:
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from iqpilot.cereal import log
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schema_type = log.Event
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except ImportError:
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print("Error: Unable to import schema. Ensure 'cereal' is installed.")
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sys.exit(1)
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# Execute based on mode
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if args.generate:
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print("🔧 Generating Schema Instances")
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instances = generate_schema_instances(schema_type)
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persist_instances(instances, args.file)
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print("✅ Instance generation complete")
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elif args.read:
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print("🔍 Reading and Validating Schema Instances")
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generated_instances = generate_schema_instances(schema_type)
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read_back_instances = read_instances(args.file, schema_type)
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# Compare schemas
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if compare_schemas(generated_instances, read_back_instances):
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print("✅ Schema Compatibility: No breaking changes detected")
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sys.exit(0)
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else:
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print("❌ Potential Schema Breaking Changes Detected")
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sys.exit(1)
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if __name__ == "__main__":
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main()
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