mirror of
https://github.com/trustgraph-ai/trustgraph.git
synced 2026-04-25 08:26:21 +02:00
d35473f7f7
Introduces `workspace` as the isolation boundary for config, flows,
library, and knowledge data. Removes `user` as a schema-level field
throughout the code, API specs, and tests; workspace provides the
same separation more cleanly at the trusted flow.workspace layer
rather than through client-supplied message fields.
Design
------
- IAM tech spec (docs/tech-specs/iam.md) documents current state,
proposed auth/access model, and migration direction.
- Data ownership model (docs/tech-specs/data-ownership-model.md)
captures the workspace/collection/flow hierarchy.
Schema + messaging
------------------
- Drop `user` field from AgentRequest/Step, GraphRagQuery,
DocumentRagQuery, Triples/Graph/Document/Row EmbeddingsRequest,
Sparql/Rows/Structured QueryRequest, ToolServiceRequest.
- Keep collection/workspace routing via flow.workspace at the
service layer.
- Translators updated to not serialise/deserialise user.
API specs
---------
- OpenAPI schemas and path examples cleaned of user fields.
- Websocket async-api messages updated.
- Removed the unused parameters/User.yaml.
Services + base
---------------
- Librarian, collection manager, knowledge, config: all operations
scoped by workspace. Config client API takes workspace as first
positional arg.
- `flow.workspace` set at flow start time by the infrastructure;
no longer pass-through from clients.
- Tool service drops user-personalisation passthrough.
CLI + SDK
---------
- tg-init-workspace and workspace-aware import/export.
- All tg-* commands drop user args; accept --workspace.
- Python API/SDK (flow, socket_client, async_*, explainability,
library) drop user kwargs from every method signature.
MCP server
----------
- All tool endpoints drop user parameters; socket_manager no longer
keyed per user.
Flow service
------------
- Closure-based topic cleanup on flow stop: only delete topics
whose blueprint template was parameterised AND no remaining
live flow (across all workspaces) still resolves to that topic.
Three scopes fall out naturally from template analysis:
* {id} -> per-flow, deleted on stop
* {blueprint} -> per-blueprint, kept while any flow of the
same blueprint exists
* {workspace} -> per-workspace, kept while any flow in the
workspace exists
* literal -> global, never deleted (e.g. tg.request.librarian)
Fixes a bug where stopping a flow silently destroyed the global
librarian exchange, wedging all library operations until manual
restart.
RabbitMQ backend
----------------
- heartbeat=60, blocked_connection_timeout=300. Catches silently
dead connections (broker restart, orphaned channels, network
partitions) within ~2 heartbeat windows, so the consumer
reconnects and re-binds its queue rather than sitting forever
on a zombie connection.
Tests
-----
- Full test refresh: unit, integration, contract, provenance.
- Dropped user-field assertions and constructor kwargs across
~100 test files.
- Renamed user-collection isolation tests to workspace-collection.
543 lines
21 KiB
Python
543 lines
21 KiB
Python
"""
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Unit tests for Cassandra Rows GraphQL Query Processor (Unified Table Implementation)
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Tests the business logic of the GraphQL query processor including:
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- Schema configuration handling
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- Query execution using unified rows table
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- Name sanitization
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- GraphQL query execution
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- Message processing logic
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"""
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import pytest
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from unittest.mock import MagicMock, AsyncMock, patch
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import json
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from trustgraph.query.rows.cassandra.service import Processor
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from trustgraph.schema import RowsQueryRequest, RowsQueryResponse, GraphQLError
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from trustgraph.schema import RowSchema, Field
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class TestRowsGraphQLQueryLogic:
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"""Test business logic for unified table query implementation"""
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def test_sanitize_name_cassandra_compatibility(self):
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"""Test name sanitization for Cassandra field names"""
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processor = MagicMock()
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processor.sanitize_name = Processor.sanitize_name.__get__(processor, Processor)
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# Test field name sanitization (uses r_ prefix like storage processor)
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assert processor.sanitize_name("simple_field") == "simple_field"
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assert processor.sanitize_name("Field-With-Dashes") == "field_with_dashes"
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assert processor.sanitize_name("field.with.dots") == "field_with_dots"
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assert processor.sanitize_name("123_field") == "r_123_field"
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assert processor.sanitize_name("field with spaces") == "field_with_spaces"
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assert processor.sanitize_name("special!@#chars") == "special___chars"
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assert processor.sanitize_name("UPPERCASE") == "uppercase"
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assert processor.sanitize_name("CamelCase") == "camelcase"
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def test_get_index_names(self):
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"""Test extraction of index names from schema"""
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processor = MagicMock()
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processor.get_index_names = Processor.get_index_names.__get__(processor, Processor)
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schema = RowSchema(
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name="test_schema",
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fields=[
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Field(name="id", type="string", primary=True),
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Field(name="category", type="string", indexed=True),
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Field(name="name", type="string"), # Not indexed
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Field(name="status", type="string", indexed=True)
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]
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)
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index_names = processor.get_index_names(schema)
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assert "id" in index_names
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assert "category" in index_names
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assert "status" in index_names
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assert "name" not in index_names
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assert len(index_names) == 3
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def test_find_matching_index_exact_match(self):
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"""Test finding matching index for exact match query"""
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processor = MagicMock()
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processor.get_index_names = Processor.get_index_names.__get__(processor, Processor)
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processor.find_matching_index = Processor.find_matching_index.__get__(processor, Processor)
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schema = RowSchema(
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name="test_schema",
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fields=[
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Field(name="id", type="string", primary=True),
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Field(name="category", type="string", indexed=True),
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Field(name="name", type="string") # Not indexed
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]
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)
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# Filter on indexed field should return match
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filters = {"category": "electronics"}
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result = processor.find_matching_index(schema, filters)
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assert result is not None
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assert result[0] == "category"
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assert result[1] == ["electronics"]
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# Filter on non-indexed field should return None
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filters = {"name": "test"}
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result = processor.find_matching_index(schema, filters)
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assert result is None
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@pytest.mark.asyncio
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async def test_schema_config_parsing(self):
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"""Test parsing of schema configuration"""
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processor = MagicMock()
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processor.schemas = {}
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processor.schema_builders = {}
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processor.graphql_schemas = {}
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processor.config_key = "schema"
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processor.query_cassandra = MagicMock()
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processor.on_schema_config = Processor.on_schema_config.__get__(processor, Processor)
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# Create test config
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schema_config = {
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"schema": {
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"customer": json.dumps({
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"name": "customer",
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"description": "Customer table",
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"fields": [
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{
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"name": "id",
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"type": "string",
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"primary_key": True,
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"required": True,
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"description": "Customer ID"
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},
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{
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"name": "email",
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"type": "string",
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"indexed": True,
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"required": True
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},
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{
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"name": "status",
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"type": "string",
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"enum": ["active", "inactive"]
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}
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]
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})
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}
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}
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# Process config
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await processor.on_schema_config("default", schema_config, version=1)
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# Verify schema was loaded
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assert "customer" in processor.schemas["default"]
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schema = processor.schemas["default"]["customer"]
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assert schema.name == "customer"
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assert len(schema.fields) == 3
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# Verify fields
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id_field = next(f for f in schema.fields if f.name == "id")
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assert id_field.primary is True
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email_field = next(f for f in schema.fields if f.name == "email")
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assert email_field.indexed is True
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status_field = next(f for f in schema.fields if f.name == "status")
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assert status_field.enum_values == ["active", "inactive"]
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# Verify per-workspace schema builder was created and graphql schema built
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assert "default" in processor.schema_builders
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assert "default" in processor.graphql_schemas
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@pytest.mark.asyncio
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async def test_graphql_context_handling(self):
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"""Test GraphQL execution context setup"""
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processor = MagicMock()
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graphql_schema = AsyncMock()
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processor.graphql_schemas = {"default": graphql_schema}
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processor.execute_graphql_query = Processor.execute_graphql_query.__get__(processor, Processor)
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# Mock schema execution
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mock_result = MagicMock()
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mock_result.data = {"customers": [{"id": "1", "name": "Test"}]}
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mock_result.errors = None
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graphql_schema.execute.return_value = mock_result
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result = await processor.execute_graphql_query(
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workspace="default",
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query='{ customers { id name } }',
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variables={},
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operation_name=None,
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collection="test_collection"
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)
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# Verify schema.execute was called with correct context
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graphql_schema.execute.assert_called_once()
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call_args = graphql_schema.execute.call_args
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# Verify context was passed
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context = call_args[1]['context_value']
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assert context["processor"] == processor
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assert context["workspace"] == "default"
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assert context["collection"] == "test_collection"
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# Verify result structure
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assert "data" in result
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assert result["data"] == {"customers": [{"id": "1", "name": "Test"}]}
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@pytest.mark.asyncio
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async def test_error_handling_graphql_errors(self):
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"""Test GraphQL error handling and conversion"""
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processor = MagicMock()
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graphql_schema = AsyncMock()
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processor.graphql_schemas = {"default": graphql_schema}
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processor.execute_graphql_query = Processor.execute_graphql_query.__get__(processor, Processor)
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# Create a simple object to simulate GraphQL error
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class MockError:
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def __init__(self, message, path, extensions):
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self.message = message
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self.path = path
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self.extensions = extensions
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def __str__(self):
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return self.message
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mock_error = MockError(
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message="Field 'invalid_field' doesn't exist",
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path=["customers", "0", "invalid_field"],
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extensions={"code": "FIELD_NOT_FOUND"}
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)
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mock_result = MagicMock()
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mock_result.data = None
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mock_result.errors = [mock_error]
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graphql_schema.execute.return_value = mock_result
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result = await processor.execute_graphql_query(
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workspace="default",
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query='{ customers { invalid_field } }',
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variables={},
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operation_name=None,
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collection="test_collection"
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)
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# Verify error handling
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assert "errors" in result
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assert len(result["errors"]) == 1
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error = result["errors"][0]
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assert error["message"] == "Field 'invalid_field' doesn't exist"
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assert error["path"] == ["customers", "0", "invalid_field"]
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assert error["extensions"] == {"code": "FIELD_NOT_FOUND"}
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@pytest.mark.asyncio
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async def test_message_processing_success(self):
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"""Test successful message processing flow"""
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processor = MagicMock()
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processor.execute_graphql_query = AsyncMock()
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processor.on_message = Processor.on_message.__get__(processor, Processor)
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# Mock successful query result
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processor.execute_graphql_query.return_value = {
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"data": {"customers": [{"id": "1", "name": "John"}]},
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"errors": [],
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"extensions": {}
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}
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# Create mock message
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mock_msg = MagicMock()
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mock_request = RowsQueryRequest(
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collection="test_collection",
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query='{ customers { id name } }',
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variables={},
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operation_name=None
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)
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mock_msg.value.return_value = mock_request
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mock_msg.properties.return_value = {"id": "test-123"}
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# Mock flow
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mock_flow = MagicMock()
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mock_flow.workspace = "default"
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mock_response_flow = AsyncMock()
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mock_flow.return_value = mock_response_flow
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# Process message
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await processor.on_message(mock_msg, None, mock_flow)
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# Verify query was executed
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processor.execute_graphql_query.assert_called_once_with(
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workspace="default",
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query='{ customers { id name } }',
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variables={},
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operation_name=None,
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collection="test_collection"
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)
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# Verify response was sent
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mock_response_flow.send.assert_called_once()
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response_call = mock_response_flow.send.call_args[0][0]
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# Verify response structure
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assert isinstance(response_call, RowsQueryResponse)
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assert response_call.error is None
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assert '"customers"' in response_call.data # JSON encoded
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assert len(response_call.errors) == 0
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@pytest.mark.asyncio
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async def test_message_processing_error(self):
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"""Test error handling during message processing"""
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processor = MagicMock()
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processor.execute_graphql_query = AsyncMock()
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processor.on_message = Processor.on_message.__get__(processor, Processor)
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# Mock query execution error
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processor.execute_graphql_query.side_effect = RuntimeError("No schema available")
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# Create mock message
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mock_msg = MagicMock()
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mock_request = RowsQueryRequest(
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collection="test_collection",
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query='{ invalid_query }',
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variables={},
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operation_name=None
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)
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mock_msg.value.return_value = mock_request
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mock_msg.properties.return_value = {"id": "test-456"}
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# Mock flow
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mock_flow = MagicMock()
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mock_response_flow = AsyncMock()
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mock_flow.return_value = mock_response_flow
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# Process message
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await processor.on_message(mock_msg, None, mock_flow)
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# Verify error response was sent
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mock_response_flow.send.assert_called_once()
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response_call = mock_response_flow.send.call_args[0][0]
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# Verify error response structure
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assert isinstance(response_call, RowsQueryResponse)
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assert response_call.error is not None
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assert response_call.error.type == "rows-query-error"
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assert "No schema available" in response_call.error.message
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assert response_call.data is None
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class TestUnifiedTableQueries:
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"""Test queries against the unified rows table"""
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@pytest.mark.asyncio
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@patch('trustgraph.query.rows.cassandra.service.async_execute', new_callable=AsyncMock)
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async def test_query_with_index_match(self, mock_async_execute):
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"""Test query execution with matching index"""
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processor = MagicMock()
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processor.session = MagicMock()
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processor.connect_cassandra = MagicMock()
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processor.sanitize_name = Processor.sanitize_name.__get__(processor, Processor)
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processor.get_index_names = Processor.get_index_names.__get__(processor, Processor)
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processor.find_matching_index = Processor.find_matching_index.__get__(processor, Processor)
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processor.query_cassandra = Processor.query_cassandra.__get__(processor, Processor)
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# Mock async_execute to return test data
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mock_row = MagicMock()
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mock_row.data = {"id": "123", "name": "Test Product", "category": "electronics"}
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mock_async_execute.return_value = [mock_row]
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schema = RowSchema(
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name="products",
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fields=[
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Field(name="id", type="string", primary=True),
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Field(name="category", type="string", indexed=True),
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Field(name="name", type="string")
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]
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)
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# Query with filter on indexed field
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results = await processor.query_cassandra(
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workspace="test_workspace",
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collection="test_collection",
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schema_name="products",
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row_schema=schema,
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filters={"category": "electronics"},
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limit=10
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)
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# Verify Cassandra was connected and queried
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processor.connect_cassandra.assert_called_once()
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mock_async_execute.assert_called_once()
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# Verify query structure - should query unified rows table
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call_args = mock_async_execute.call_args
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query = call_args[0][1]
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params = call_args[0][2]
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assert "SELECT data, source FROM test_workspace.rows" in query
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assert "collection = %s" in query
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assert "schema_name = %s" in query
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assert "index_name = %s" in query
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assert "index_value = %s" in query
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assert params[0] == "test_collection"
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assert params[1] == "products"
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assert params[2] == "category"
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assert params[3] == ["electronics"]
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# Verify results
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assert len(results) == 1
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assert results[0]["id"] == "123"
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assert results[0]["category"] == "electronics"
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@pytest.mark.asyncio
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@patch('trustgraph.query.rows.cassandra.service.async_execute', new_callable=AsyncMock)
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async def test_query_without_index_match(self, mock_async_execute):
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"""Test query execution without matching index (scan mode)"""
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processor = MagicMock()
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processor.session = MagicMock()
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processor.connect_cassandra = MagicMock()
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processor.sanitize_name = Processor.sanitize_name.__get__(processor, Processor)
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processor.get_index_names = Processor.get_index_names.__get__(processor, Processor)
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processor.find_matching_index = Processor.find_matching_index.__get__(processor, Processor)
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processor._matches_filters = Processor._matches_filters.__get__(processor, Processor)
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processor.query_cassandra = Processor.query_cassandra.__get__(processor, Processor)
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# Mock async_execute to return test data
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mock_row1 = MagicMock()
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mock_row1.data = {"id": "1", "name": "Product A", "price": "100"}
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mock_row2 = MagicMock()
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mock_row2.data = {"id": "2", "name": "Product B", "price": "200"}
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mock_async_execute.return_value = [mock_row1, mock_row2]
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schema = RowSchema(
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name="products",
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fields=[
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Field(name="id", type="string", primary=True),
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Field(name="name", type="string"), # Not indexed
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Field(name="price", type="string") # Not indexed
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]
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)
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# Query with filter on non-indexed field
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results = await processor.query_cassandra(
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workspace="test_workspace",
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collection="test_collection",
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schema_name="products",
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row_schema=schema,
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filters={"name": "Product A"},
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limit=10
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)
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# Query should use ALLOW FILTERING for scan
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call_args = mock_async_execute.call_args
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query = call_args[0][1]
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assert "ALLOW FILTERING" in query
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# Should post-filter results
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assert len(results) == 1
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assert results[0]["name"] == "Product A"
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class TestFilterMatching:
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"""Test filter matching logic"""
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def test_matches_filters_exact_match(self):
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"""Test exact match filter"""
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processor = MagicMock()
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processor._matches_filters = Processor._matches_filters.__get__(processor, Processor)
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schema = RowSchema(name="test", fields=[Field(name="status", type="string")])
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row = {"status": "active", "name": "test"}
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assert processor._matches_filters(row, {"status": "active"}, schema) is True
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assert processor._matches_filters(row, {"status": "inactive"}, schema) is False
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def test_matches_filters_comparison_operators(self):
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"""Test comparison operators in filters"""
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processor = MagicMock()
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processor._matches_filters = Processor._matches_filters.__get__(processor, Processor)
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schema = RowSchema(name="test", fields=[Field(name="price", type="float")])
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row = {"price": "100.0"}
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# Greater than
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assert processor._matches_filters(row, {"price_gt": 50}, schema) is True
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assert processor._matches_filters(row, {"price_gt": 150}, schema) is False
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|
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# Less than
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assert processor._matches_filters(row, {"price_lt": 150}, schema) is True
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assert processor._matches_filters(row, {"price_lt": 50}, schema) is False
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|
|
|
# Greater than or equal
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assert processor._matches_filters(row, {"price_gte": 100}, schema) is True
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assert processor._matches_filters(row, {"price_gte": 101}, schema) is False
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|
|
|
# Less than or equal
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assert processor._matches_filters(row, {"price_lte": 100}, schema) is True
|
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assert processor._matches_filters(row, {"price_lte": 99}, schema) is False
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|
|
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def test_matches_filters_contains(self):
|
|
"""Test contains filter"""
|
|
processor = MagicMock()
|
|
processor._matches_filters = Processor._matches_filters.__get__(processor, Processor)
|
|
|
|
schema = RowSchema(name="test", fields=[Field(name="description", type="string")])
|
|
|
|
row = {"description": "A great product for everyone"}
|
|
|
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assert processor._matches_filters(row, {"description_contains": "great"}, schema) is True
|
|
assert processor._matches_filters(row, {"description_contains": "terrible"}, schema) is False
|
|
|
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def test_matches_filters_in_list(self):
|
|
"""Test in-list filter"""
|
|
processor = MagicMock()
|
|
processor._matches_filters = Processor._matches_filters.__get__(processor, Processor)
|
|
|
|
schema = RowSchema(name="test", fields=[Field(name="status", type="string")])
|
|
|
|
row = {"status": "active"}
|
|
|
|
assert processor._matches_filters(row, {"status_in": ["active", "pending"]}, schema) is True
|
|
assert processor._matches_filters(row, {"status_in": ["inactive", "deleted"]}, schema) is False
|
|
|
|
|
|
class TestIndexedFieldFiltering:
|
|
"""Test that only indexed or primary key fields can be directly filtered"""
|
|
|
|
def test_indexed_field_filtering(self):
|
|
"""Test that only indexed or primary key fields can be filtered"""
|
|
schema = RowSchema(
|
|
name="test",
|
|
fields=[
|
|
Field(name="id", type="string", primary=True),
|
|
Field(name="indexed_field", type="string", indexed=True),
|
|
Field(name="normal_field", type="string", indexed=False),
|
|
Field(name="another_field", type="string")
|
|
]
|
|
)
|
|
|
|
filters = {
|
|
"id": "test123", # Primary key - should be included
|
|
"indexed_field": "value", # Indexed - should be included
|
|
"normal_field": "ignored", # Not indexed - should be ignored
|
|
"another_field": "also_ignored" # Not indexed - should be ignored
|
|
}
|
|
|
|
# Simulate the filtering logic from the processor
|
|
valid_filters = []
|
|
for field_name, value in filters.items():
|
|
if value is not None:
|
|
schema_field = next((f for f in schema.fields if f.name == field_name), None)
|
|
if schema_field and (schema_field.indexed or schema_field.primary):
|
|
valid_filters.append((field_name, value))
|
|
|
|
# Only id and indexed_field should be included
|
|
assert len(valid_filters) == 2
|
|
field_names = [f[0] for f in valid_filters]
|
|
assert "id" in field_names
|
|
assert "indexed_field" in field_names
|
|
assert "normal_field" not in field_names
|
|
assert "another_field" not in field_names
|