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Tests
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Cyber MacGeddon
parent
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commit
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1 changed files with 86 additions and 226 deletions
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@ -14,13 +14,7 @@ from io import StringIO
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import asyncio
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# Import the function we're testing
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from trustgraph.cli.load_structured_data import (
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load_structured_data,
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parse_csv_data,
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parse_json_data,
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parse_xml_data,
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apply_transformations
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)
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from trustgraph.cli.load_structured_data import load_structured_data
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class TestLoadStructuredDataUnit:
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@ -68,228 +62,94 @@ Bob Johnson,bob@company.org,42,UK"""
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}
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}
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# CSV Parsing Tests
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def test_csv_parsing_with_header(self):
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"""Test CSV parsing with header row"""
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format_info = {"type": "csv", "encoding": "utf-8", "options": {"header": True, "delimiter": ","}}
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# CLI Dry-Run Tests - Test CLI behavior without actual connections
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def test_csv_dry_run_processing(self):
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"""Test CSV processing in dry-run mode"""
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input_file = self.create_temp_file(self.test_csv_data, '.csv')
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descriptor_file = self.create_temp_file(json.dumps(self.test_descriptor), '.json')
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records = parse_csv_data(self.test_csv_data, format_info)
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assert len(records) == 3
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assert records[0]["name"] == "John Smith"
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assert records[0]["email"] == "john@email.com"
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assert records[1]["country"] == "CA"
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def test_csv_parsing_without_header(self):
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"""Test CSV parsing without header row"""
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csv_data = """John Smith,john@email.com,35,US
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Jane Doe,jane@email.com,28,CA"""
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format_info = {"type": "csv", "encoding": "utf-8", "options": {"header": False, "delimiter": ","}}
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records = parse_csv_data(csv_data, format_info)
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assert len(records) == 2
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# Should use column indices as keys
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assert records[0]["0"] == "John Smith"
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assert records[0]["1"] == "john@email.com"
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def test_csv_parsing_custom_delimiter(self):
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"""Test CSV parsing with custom delimiter"""
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csv_data = """name;email;age
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John Smith;john@email.com;35
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Jane Doe;jane@email.com;28"""
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format_info = {"type": "csv", "encoding": "utf-8", "options": {"header": True, "delimiter": ";"}}
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records = parse_csv_data(csv_data, format_info)
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assert len(records) == 2
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assert records[0]["name"] == "John Smith"
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assert records[1]["email"] == "jane@email.com"
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# JSON Parsing Tests
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def test_json_parsing_array_format(self):
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"""Test JSON parsing with array format"""
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json_data = json.dumps(self.test_json_data)
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format_info = {"type": "json", "encoding": "utf-8"}
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records = parse_json_data(json_data, format_info)
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assert len(records) == 2
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assert records[0]["name"] == "John Smith"
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assert records[1]["country"] == "CA"
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def test_json_parsing_newline_delimited(self):
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"""Test JSON parsing with newline-delimited format"""
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json_data = '{"name": "John", "age": 35}\n{"name": "Jane", "age": 28}'
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format_info = {"type": "json", "encoding": "utf-8", "options": {"newline_delimited": True}}
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records = parse_json_data(json_data, format_info)
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assert len(records) == 2
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assert records[0]["name"] == "John"
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assert records[1]["age"] == 28
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def test_json_parsing_malformed_data(self):
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"""Test JSON parsing with malformed data"""
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json_data = '{"name": "John", "age": 35' # Missing closing brace
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format_info = {"type": "json", "encoding": "utf-8"}
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with pytest.raises(json.JSONDecodeError):
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parse_json_data(json_data, format_info)
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# XML Parsing Tests
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def test_xml_parsing_xpath_expressions(self):
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"""Test XML parsing with XPath expressions"""
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format_info = {
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"type": "xml",
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"encoding": "utf-8",
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"options": {
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"record_path": "/ROOT/data/record",
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"field_attribute": "name"
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}
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}
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records = parse_xml_data(self.test_xml_data, format_info)
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assert len(records) == 2
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assert records[0]["name"] == "John Smith"
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assert records[0]["email"] == "john@email.com"
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assert records[1]["name"] == "Jane Doe"
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def test_xml_parsing_field_attributes(self):
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"""Test XML parsing with field attributes"""
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xml_data = """<?xml version="1.0"?>
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<records>
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<item id="1" name="Product A" price="19.99"/>
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<item id="2" name="Product B" price="29.99"/>
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</records>"""
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format_info = {
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"type": "xml",
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"encoding": "utf-8",
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"options": {"record_path": "//item"}
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}
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records = parse_xml_data(xml_data, format_info)
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assert len(records) == 2
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assert records[0]["id"] == "1"
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assert records[0]["name"] == "Product A"
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assert records[1]["price"] == "29.99"
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# Data Transformation Tests
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def test_field_mappings_application(self):
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"""Test field mapping application"""
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record = {"source_name": "John Smith", "source_email": "JOHN@EMAIL.COM"}
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mappings = [
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{"source_field": "source_name", "target_field": "name", "transforms": []},
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{"source_field": "source_email", "target_field": "email", "transforms": []}
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]
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result = apply_transformations(record, mappings)
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assert result["name"] == "John Smith"
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assert result["email"] == "JOHN@EMAIL.COM"
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def test_data_transforms_trim(self):
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"""Test trim transformation"""
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record = {"name": " John Smith ", "email": "john@email.com"}
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mappings = [
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{"source_field": "name", "target_field": "name", "transforms": [{"type": "trim"}]}
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]
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result = apply_transformations(record, mappings)
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assert result["name"] == "John Smith"
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def test_data_transforms_case_conversion(self):
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"""Test case conversion transformations"""
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record = {"name": "John Smith", "email": "JOHN@EMAIL.COM"}
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mappings = [
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{"source_field": "name", "target_field": "name", "transforms": [{"type": "upper"}]},
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{"source_field": "email", "target_field": "email", "transforms": [{"type": "lower"}]}
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]
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result = apply_transformations(record, mappings)
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assert result["name"] == "JOHN SMITH"
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assert result["email"] == "john@email.com"
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def test_data_transforms_type_conversion(self):
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"""Test type conversion transformations"""
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record = {"age": "35", "price": "19.99", "active": "true"}
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mappings = [
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{"source_field": "age", "target_field": "age", "transforms": [{"type": "to_int"}]},
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{"source_field": "price", "target_field": "price", "transforms": [{"type": "to_float"}]},
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{"source_field": "active", "target_field": "active", "transforms": [{"type": "to_bool"}]}
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]
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result = apply_transformations(record, mappings)
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# All values should be converted to strings for ExtractedObject compatibility
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assert result["age"] == "35"
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assert result["price"] == "19.99"
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assert result["active"] == "True"
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# Batching Functionality Tests
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def test_batch_processing_single_object(self):
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"""Test batch processing with single object"""
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records = [{"name": "John", "age": "35"}]
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batch_size = 10
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schema_name = "customer"
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# Simulate batching logic
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batches = []
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for i in range(0, len(records), batch_size):
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batch_records = records[i:i + batch_size]
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batch_values = [record for record in batch_records]
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batches.append({
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"schema_name": schema_name,
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"values": batch_values
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})
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assert len(batches) == 1
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assert len(batches[0]["values"]) == 1
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assert batches[0]["values"][0]["name"] == "John"
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def test_batch_processing_multiple_objects(self):
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"""Test batch processing with multiple objects"""
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records = [{"name": f"User{i}", "age": str(20+i)} for i in range(5)]
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batch_size = 2
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schema_name = "customer"
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# Simulate batching logic
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batches = []
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for i in range(0, len(records), batch_size):
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batch_records = records[i:i + batch_size]
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batch_values = [record for record in batch_records]
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batches.append({
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"schema_name": schema_name,
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"values": batch_values
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})
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assert len(batches) == 3 # 5 records with batch_size=2 -> 3 batches
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assert len(batches[0]["values"]) == 2
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assert len(batches[1]["values"]) == 2
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assert len(batches[2]["values"]) == 1
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assert batches[2]["values"][0]["name"] == "User4"
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def test_batch_size_configuration(self):
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"""Test batch size configuration"""
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records = [{"id": str(i)} for i in range(10)]
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for batch_size in [1, 3, 5, 10, 15]:
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batches = []
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for i in range(0, len(records), batch_size):
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batch_records = records[i:i + batch_size]
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batches.append(batch_records)
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try:
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# Dry run should complete without errors
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result = load_structured_data(
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api_url="http://localhost:8088",
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input_file=input_file,
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descriptor_file=descriptor_file,
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dry_run=True,
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batch_size=2
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)
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expected_batches = (len(records) + batch_size - 1) // batch_size
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assert len(batches) == expected_batches
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# Dry run returns None
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assert result is None
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# Check all records are included
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total_records = sum(len(batch) for batch in batches)
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assert total_records == len(records)
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finally:
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self.cleanup_temp_file(input_file)
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self.cleanup_temp_file(descriptor_file)
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def test_parse_only_mode(self):
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"""Test parse-only mode functionality"""
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input_file = self.create_temp_file(self.test_csv_data, '.csv')
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descriptor_file = self.create_temp_file(json.dumps(self.test_descriptor), '.json')
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output_file = tempfile.NamedTemporaryFile(mode='w', suffix='.json', delete=False)
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output_file.close()
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try:
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result = load_structured_data(
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api_url="http://localhost:8088",
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input_file=input_file,
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descriptor_file=descriptor_file,
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parse_only=True,
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output_file=output_file.name
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)
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# Check output file was created
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assert os.path.exists(output_file.name)
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# Check it contains parsed data
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with open(output_file.name, 'r') as f:
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parsed_data = json.load(f)
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assert isinstance(parsed_data, list)
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assert len(parsed_data) > 0
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finally:
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self.cleanup_temp_file(input_file)
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self.cleanup_temp_file(descriptor_file)
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self.cleanup_temp_file(output_file.name)
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def test_batch_size_parameter(self):
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"""Test batch size parameter is accepted"""
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input_file = self.create_temp_file(self.test_csv_data, '.csv')
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descriptor_file = self.create_temp_file(json.dumps(self.test_descriptor), '.json')
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try:
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# Should accept batch_size parameter without error
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result = load_structured_data(
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api_url="http://localhost:8088",
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input_file=input_file,
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descriptor_file=descriptor_file,
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batch_size=5,
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dry_run=True
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)
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assert result is None
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finally:
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self.cleanup_temp_file(input_file)
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self.cleanup_temp_file(descriptor_file)
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def create_temp_file(self, content, suffix='.txt'):
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"""Create a temporary file with given content"""
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temp_file = tempfile.NamedTemporaryFile(mode='w', suffix=suffix, delete=False)
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temp_file.write(content)
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temp_file.flush()
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temp_file.close()
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return temp_file.name
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def cleanup_temp_file(self, file_path):
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"""Clean up temporary file"""
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try:
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os.unlink(file_path)
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except:
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pass
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# Schema Suggestion Tests
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@patch('trustgraph.cli.load_structured_data.TrustGraphAPI')
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