mirror of
https://github.com/NVIDIA-NeMo/DataDesigner
synced 2026-05-24 09:48:29 +00:00
1439bbea7e
* perf: defer heavy imports to improve CLI startup time Move expensive imports (engine, models, controllers) out of the module-level import path so that data-designer --help and other non-generation commands no longer pay the full startup cost. Key changes: - Defer controller imports to inside command functions - Remove eager re-export chains from CLI package __init__ files - Move default-settings bootstrap into load_config_builder() and DataDesigner.__init__() instead of running at import time - Add lazy __getattr__ exports in interface/__init__.py - Replace module-level tokenizer init with cached lazy getter - Fix ModelProvider import to use config layer instead of engine - Update test mock paths to match new import locations Reduces CLI import-time from ~1.67s to ~0.46s. * perf: defer pandas/numpy in io_helpers and add config_list benchmark - Replace eager `from lazy_heavy_imports import pd, np` in io_helpers with module-level __getattr__ (for backwards-compatible external access / test mocks) and function-level imports in the 3 functions that actually use them (read_parquet_dataset, smart_load_dataframe, _convert_to_serializable). Importing io_helpers no longer triggers pandas/numpy loading. - Defer heavy imports in list and reset CLI commands into function bodies to avoid loading repositories, Rich, and prompt_toolkit at module import time. - Add `config_list` (data-designer config list) measurement to the CLI startup benchmark with isolated cold measurement in a separate venv and a --skip-config-list-check flag. - Update test mock paths to match new import locations. * Refine lazy import usage and TYPE_CHECKING cleanup * Run license header updater on PR-touched files * fix: update sqlfluff mock target for lazy imports in test_sql * perf: cache globals() in lazy __getattr__ to avoid repeated lookups Add globals() caching and explanatory comment to all three lazy __getattr__ implementations (lazy_heavy_imports, config/__init__, interface/__init__) so subsequent attribute accesses bypass __getattr__. * perf: lazy CLI command loading and deferred heavy import evaluations - Add LazyTyperGroup to defer command module loading until invocation, allowing module-level imports in all CLI command files - Split DataFrameSeedSource into seed_source_dataframe.py to isolate pandas dependency from other seed source classes - Move TypeVar/TypeAlias definitions (DataT, NumpyArray1dT, RadomStateT, EngineT) to TYPE_CHECKING blocks with runtime fallbacks - Wrap module-level constants in lru_cache (phone_number parquet data, jsonschema validator) to defer I/O and heavy imports to first use - Update test mock targets to patch at usage-site for module-level imports * refactor: use direct pandas import in seed_source_dataframe Drop lazy-loading for pandas in DataFrameSeedSource; use direct import for simplicity. * update lazy import pattern * update tests to use lazy import namespace Switch test modules to import data_designer.lazy_heavy_imports as lazy and reference heavy libraries through that namespace. This keeps heavy imports deferred during module import and aligns tests with the new lazy-import usage pattern. * tighten import perf test thresholds Document recent baseline timings and lower the allowed average import time and timeout so regressions are detected sooner. * document pandas import requirement Clarify that Pydantic needs DataFrame resolved at module load and that keeping the direct import preserves IDE typing support. * increase timeout time * use lazy pandas imports in visualization tests - replace direct pandas usage with lazy.pd in visualization tests to avoid eager imports - add TYPE_CHECKING pandas import and keep CLI controller imports sorted * fix lazy pandas runtime usage and preview mocks Switch sample-record handling to lazy pandas types so runtime paths no longer depend on TYPE_CHECKING imports. Align preview controller tests to patch the module-local DataDesigner symbol, preventing real engine invocation in save results scenarios.
64 lines
1.9 KiB
Python
64 lines
1.9 KiB
Python
# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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# SPDX-License-Identifier: Apache-2.0
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from __future__ import annotations
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import json
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from typing import TYPE_CHECKING
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import pytest
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from pytest_httpx import HTTPXMock
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import data_designer.lazy_heavy_imports as lazy
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from data_designer.config.validator_params import RemoteValidatorParams
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from data_designer.engine.validators.remote import (
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RemoteEndpointClient,
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RemoteValidator,
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)
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if TYPE_CHECKING:
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import httpx
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@pytest.fixture()
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def stub_data() -> list[dict]:
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return [{"text": "Sample text", "id": 1}]
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def test_validate_with_remote_endpoint(httpx_mock: HTTPXMock, stub_data: list[dict]):
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# Setup mock response
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httpx_mock.add_response(
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method="POST", url="http://localhost:8080", json={"data": [{"is_valid": True, "confidence": "0.98"}]}
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)
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validator = RemoteValidator(
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RemoteValidatorParams(
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endpoint_url="http://localhost:8080",
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)
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)
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results = validator.run_validation(stub_data)
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# Verify results
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assert len(results) == 1
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assert results[0].is_valid is True
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assert results[0].confidence == "0.98"
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def test_remote_endpoint_client(httpx_mock: HTTPXMock):
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# Add custom callback response that tests auth and parses content
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def custom_response_callback(request: httpx.Request):
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content = request.read().decode("utf-8")
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parsed_content = json.loads(content)
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return lazy.httpx.Response(status_code=200, json={"sample_text": parsed_content["sample_content"]["text"]})
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httpx_mock.add_callback(custom_response_callback)
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client = RemoteEndpointClient(
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config=RemoteValidatorParams(
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endpoint_url="http://localhost:8080",
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),
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)
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response = client.post_to_remote_endpoint({"sample_content": {"text": ["Sample text"]}})
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assert response["sample_text"] == ["Sample text"]
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