b6b4cd0a4c
### Overview Major restructuring from monolithic `arcade-ai` package to modular library architecture with standardized uv-based dependency management.  ### New Package Structure - **`arcade-tdk`** - Lightweight toolkit development kit (core decorators, auth) - **`arcade-core`** - Core execution engine and catalog functionality - **`arcade-serve`** - FastAPI/MCP server components - **`arcade-ai`** - Meta package that includes CLI functionality. Optionally include evals via the `evals` extra. Optionally include all packages via the `all` extra. ### Key Benefits - **Lighter Dependencies**: Toolkits now depend only on `arcade-tdk` (~2 deps) vs full `arcade-ai` (~30+ deps) - **Faster Builds**: uv provides 10-100x faster dependency resolution and installation - **Better Modularity**: Clear separation of concerns, consumers import only what they need - **Standard Tooling**: Eliminates custom poetry scripts, uses standard Python packaging ### Migration Impact - All 20 toolkits converted from poetry → uv with `arcade-tdk` dependencies plus `arcade-ai[evals]` and `arcade-serve` dev dependencies. When developing locally, devs should install toolkits via `make install-local`. - Modern Python 3.10+ type hints throughout - Standardized build system with hatchling backend - Enhanced Makefile with robust toolkit management commands - Removed `arcade dev` CLI command - Reduce the number of files created by `arcade new` and add an option to not generate a tests and evals folder. This foundation enables faster development cycles and cleaner dependency chains for the growing toolkit ecosystem. ### Todo After this PR is merged - [ ] Post-merge workflow(s) (release & publish containers, etc) - [ ] Release order plan. @EricGustin suggests releasing in the following order: 1. `arcade-core` version 0.1.0 2. `arcade-serve` version 0.1.0 and `arcade-tdk` version 0.1.0 3. `arcade-ai` version 2.0.0 4. Patch release for all toolkits (all changes in toolkits are internal refactors) - [ ] [Update docs](https://github.com/ArcadeAI/docs/pull/318) --------- Co-authored-by: Eric Gustin <eric@arcade.dev> Co-authored-by: Eric Gustin <34000337+EricGustin@users.noreply.github.com>
96 lines
3.4 KiB
Python
96 lines
3.4 KiB
Python
from unittest.mock import AsyncMock, MagicMock, patch
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import pytest
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from arcade_tdk import ToolContext
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from arcade_google.tools import create_contact
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@pytest.fixture
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def mock_context():
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context = AsyncMock(spec=ToolContext)
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context.authorization = MagicMock()
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context.authorization.token = "mock_token" # noqa: S105
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return context
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@pytest.mark.asyncio
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async def test_create_contact_success(mock_context):
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# Test create_contact with all parameters (given, family names and email)
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created_contact_data = {"resourceName": "people/123", "etag": "abc"}
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create_contact_call = MagicMock()
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create_contact_call.execute.return_value = created_contact_data
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people_mock = MagicMock()
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people_mock.createContact.return_value = create_contact_call
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service_mock = MagicMock()
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service_mock.people.return_value = people_mock
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with patch(
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"arcade_google.tools.contacts.build_people_service", return_value=service_mock
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) as mock_build:
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result = await create_contact(
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mock_context,
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given_name="Alice",
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family_name="Smith",
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email="alice@example.com",
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)
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assert "contact" in result
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assert result["contact"] == created_contact_data
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# Verify that the createContact API was called with the correct body contents.
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expected_body = {
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"names": [{"givenName": "Alice", "familyName": "Smith"}],
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"emailAddresses": [{"value": "alice@example.com", "type": "work"}],
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}
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people_mock.createContact.assert_called_once_with(
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body=expected_body, personFields="names,emailAddresses"
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)
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mock_build.assert_called_once()
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@pytest.mark.asyncio
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async def test_create_contact_success_without_optional(mock_context):
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# Test create_contact without optional parameters family_name and email.
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created_contact_data = {"resourceName": "people/456", "etag": "def"}
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create_contact_call = MagicMock()
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create_contact_call.execute.return_value = created_contact_data
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people_mock = MagicMock()
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people_mock.createContact.return_value = create_contact_call
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service_mock = MagicMock()
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service_mock.people.return_value = people_mock
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with patch("arcade_google.tools.contacts.build_people_service", return_value=service_mock):
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result = await create_contact(mock_context, given_name="Bob", family_name=None, email=None)
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assert "contact" in result
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assert result["contact"] == created_contact_data
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# Expected body should only include the givenName when family_name and email are omitted.
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expected_body = {"names": [{"givenName": "Bob"}]}
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people_mock.createContact.assert_called_once_with(
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body=expected_body, personFields="names,emailAddresses"
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)
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@pytest.mark.asyncio
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async def test_create_contact_error(mock_context):
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# Simulate an error thrown by createContact
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error_call = MagicMock()
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error_call.execute.side_effect = Exception("Create error")
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people_mock = MagicMock()
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people_mock.createContact.return_value = error_call
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service_mock = MagicMock()
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service_mock.people.return_value = people_mock
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with (
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patch("arcade_google.tools.contacts.build_people_service", return_value=service_mock),
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pytest.raises(Exception, match="Error in execution of CreateContact"),
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):
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await create_contact(mock_context, given_name="Alice", family_name="Doe", email=None)
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