OpenMetadata/ingestion/tests/unit/test_protobuf_parser.py
2025-04-03 10:39:47 +05:30

123 lines
4.2 KiB
Python

# Copyright 2025 Collate
# Licensed under the Collate Community License, Version 1.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# https://github.com/open-metadata/OpenMetadata/blob/main/ingestion/LICENSE
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
Protobuf parser tests
"""
import os
from unittest import TestCase
from metadata.generated.schema.entity.data.table import Column
from metadata.parsers.protobuf_parser import ProtobufParser, ProtobufParserConfig
from metadata.utils.messaging_utils import merge_and_clean_protobuf_schema
class ProtobufParserTests(TestCase):
"""
Check methods from protobuf_parser.py
"""
schema_name = "person_info"
sample_protobuf_schema = """
syntax = "proto3";
package persons;
enum Gender {
M = 0; // male
F = 1; // female
O = 2; // other
}
message Result {
string url = 1;
string title = 2;
repeated string snippets = 3;
}
message PersonInfo {
int32 age = 1; // age in years
Gender gender = 2;
Result gender_new = 3;
int32 height = 4; // height in cm
fixed32 height_new = 5; // height in cm
bool my_bool = 6;
repeated string repeated_string = 7;
}
"""
protobuf_parser = ProtobufParser(
config=ProtobufParserConfig(
schema_name=schema_name, schema_text=sample_protobuf_schema
)
)
parsed_schema = protobuf_parser.parse_protobuf_schema()
def test_schema_name(self):
self.assertEqual(self.parsed_schema[0].name.root, "PersonInfo")
def test_schema_type(self):
self.assertEqual(self.parsed_schema[0].dataType.name, "RECORD")
def test_field_names(self):
field_names = {str(field.name.root) for field in self.parsed_schema[0].children}
self.assertEqual(
field_names,
{
"height",
"gender",
"age",
"gender_new",
"height_new",
"my_bool",
"repeated_string",
},
)
def test_field_types(self):
field_types = {
str(field.dataType.name) for field in self.parsed_schema[0].children
}
self.assertEqual(
field_types, {"INT", "ENUM", "RECORD", "FIXED", "STRING", "BOOLEAN"}
)
def test_column_types(self):
parsed_schema = self.protobuf_parser.parse_protobuf_schema(cls=Column)
field_types = {str(field.dataType.name) for field in parsed_schema[0].children}
self.assertEqual(field_types, {"INT", "ENUM", "RECORD", "STRING", "BOOLEAN"})
def test_complex_protobuf_schema_files(self):
"""
We'll read the files under ./ingestion/tests/unit/resources/protobuf_parser and parse them
This will be similar in way to how we get the data from kafka source
"""
resource_path = f"{os.path.dirname(__file__)}/resources/protobuf_parser/"
schema_name = "employee"
file_list = os.listdir(resource_path)
schema_text = ""
for file_name in file_list:
file_path = os.path.join(resource_path, file_name)
with open(file_path, "r") as file:
schema_text = schema_text + file.read()
schema_text = merge_and_clean_protobuf_schema(schema_text)
protobuf_parser = ProtobufParser(
config=ProtobufParserConfig(
schema_name=schema_name, schema_text=schema_text
)
)
parsed_schema = protobuf_parser.parse_protobuf_schema()
self.assertEqual(parsed_schema[0].name.root, "Employee")
self.assertEqual(len(parsed_schema[0].children), 4)
self.assertEqual(parsed_schema[0].children[3].name.root, "contact")
self.assertEqual(parsed_schema[0].children[3].children[0].name.root, "email")
self.assertEqual(parsed_schema[0].children[3].children[1].name.root, "phone")