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Fixtures Reference

The Intel® ESQ framework provides a set of pytest fixtures that are automatically available to all test functions. These fixtures handle caching, validation, reporting, and configuration loading.

Core Fixtures

request

  • Type: pytest.FixtureRequest
  • Scope: function
  • Description: Standard pytest request object for accessing test metadata.
  • Usage: 
    test_name = request.node.name.split("[")[0]

configs

  • Type: Dict[str, Any]
  • Scope: function
  • Description: This function tests configuration parameters merged from the active profile and config.yml.
  • Usage: 
    test_id = configs.get("test_id", "T0000")
devices = configs.get("devices", ["cpu"])
timeout = configs.get("timeout", 300)

Cache Fixtures

cached_result

  • Type: Callable[[Optional[Dict]], Optional[Union[Result, Dict]]]
  • Scope: function
  • Description: This function retrieves cached test results if available and returns None on a cache miss.
  • Usage: 
    cached_data = cached_result(cache_configs={"key": "value"})
if cached_data:
    return cached_data

cache_result

  • Type: Callable[[Union[Result, Dict], Optional[Dict]], None]
  • Scope: function
  • Description: This function stores test results in the cache for future runs.
  • Usage: 
    cache_result(results, cache_configs={"key": "value"})

Validation Fixtures

validate_system_requirements_from_configs

  • Type: Callable[[Dict[str, Any]], None]
  • Scope: function
  • Description: This function validates that the system meets all requirements defined in configs and calls pytest.skip if any requirement is not met.
  • Usage: 
    validate_system_requirements_from_configs(configs)

See System Requirements for all available flags.

validate_test_results

  • Type: Callable[..., Dict[str, Any]]
  • Scope: function
  • Description: This function validates test results against KPI thresholds.
  • Parameters:
Parameter Description
results Result object or dict
configs Test configuration dict
get_kpi_config KPI config retrieval fixture
test_name Test identifier string
mode "all" (default) or "any" — whether all or any KPIs must pass
  • Usage: 
    validation_results = validate_test_results(
    results=results,
    configs=configs,
    get_kpi_config=get_kpi_config,
    test_name=test_name
)
# Returns: {"passed": bool, "validations": {...}, "skipped": bool}

Execution Fixtures

execute_test_with_cache

  • Type: Callable[..., Union[Result, Dict]]
  • Scope: function
  • Description: This function executes test logic with automatic caching support and returns cached results on a cache hit. It also executes run_test_func on a cache miss and caches the result.
  • Parameters:
Parameter Description
cached_result Cached result fixture
cache_result Cache result fixture
run_test_func Callable that runs the test and returns a Result
test_name Test identifier string
configs Test configuration dict
cache_configs Optional dict of cache-specific configuration
name Step name shown in Allure (default: "Analysis")
  • Usage: 
    results = execute_test_with_cache(
    cached_result=cached_result,
    cache_result=cache_result,
    run_test_func=lambda: execute_my_test(),
    test_name=test_name,
    configs=configs
)

prepare_test

  • Type: Callable[..., Any]
  • Scope: function
  • Description: This function runs an asset preparation function with Allure progress tracking. Use this to download models, videos, or set up other dependencies before the main test.
  • Parameters:
Parameter Description
test_name Test identifier string
prepare_func Callable that performs the preparation work
configs Test configuration dict
name Step name shown in Allure (default: "Preparation")
  • Usage: 
    prepare_test(
    test_name=test_name,
    prepare_func=lambda: download_models(),
    configs=configs,
    name="Assets"
)

Reporting Fixtures

summarize_test_results

  • Type: Callable[..., None]
  • Scope: function
  • Description: This function generates a test result summary and attaches it to the Allure report.
  • Parameters:
Parameter Description
results Result object
test_name Test identifier string
configs Test configuration dict (optional)
get_kpi_config KPI config function (optional)
iteration_data Per-iteration metric data (optional)
enable_visualizations Generate charts (default: False)
  • Usage: 
    summarize_test_results(
    results=results,
    test_name=test_name,
    configs=configs,
    get_kpi_config=get_kpi_config
)

Suite Fixtures

suite_configs

  • Type: Dict[str, Any]
  • Scope: function
  • Description: This function loads the suite-level configuration from config.yml in the test directory.
  • Usage: 
    kpis = suite_configs.get("kpi", {})

get_kpi_config

  • Type: Callable[[str], Optional[Dict[str, Any]]]
  • Scope: function
  • Description: This function retrieves a KPI configuration dict by name from config.yml.
  • Usage: 
    kpi_config = get_kpi_config("inference_time")
if kpi_config:
    reference = kpi_config["validation"]["reference"]