7bd105007e* add opentelemetry utility functions and unit tests * review comments * add label validation
112 lines
4.8 KiB
Python
112 lines
4.8 KiB
Python
import pytest
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import threading
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from langflow.services.telemetry.opentelemetry import OpenTelemetry
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from concurrent.futures import ThreadPoolExecutor, as_completed
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fixed_labels = {"flow_id": "this_flow_id", "service": "this", "user": "that"}
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@pytest.fixture
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def opentelemetry_instance():
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return OpenTelemetry()
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def test_init(opentelemetry_instance):
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assert isinstance(opentelemetry_instance, OpenTelemetry)
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assert len(opentelemetry_instance._metrics) > 1
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assert len(opentelemetry_instance._metrics) == len(opentelemetry_instance._metrics_registry) == 2
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assert "file_uploads" in opentelemetry_instance._metrics
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def test_gauge(opentelemetry_instance):
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opentelemetry_instance.update_gauge("file_uploads", 1024, fixed_labels)
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def test_gauge_with_counter_method(opentelemetry_instance):
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with pytest.raises(ValueError, match="Metric 'file_uploads' is not a counter"):
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opentelemetry_instance.increment_counter(metric_name="file_uploads", value=1, labels=fixed_labels)
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def test_gauge_with_historgram_method(opentelemetry_instance):
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with pytest.raises(ValueError, match="Metric 'file_uploads' is not a histogram"):
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opentelemetry_instance.observe_histogram("file_uploads", 1, fixed_labels)
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def test_gauge_with_up_down_counter_method(opentelemetry_instance):
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with pytest.raises(ValueError, match="Metric 'file_uploads' is not an up down counter"):
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opentelemetry_instance.up_down_counter("file_uploads", 1, labels=fixed_labels)
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def test_increment_counter(opentelemetry_instance):
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opentelemetry_instance.increment_counter(metric_name="num_files_uploaded", value=5, labels=fixed_labels)
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def test_increment_counter_empty_label(opentelemetry_instance):
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with pytest.raises(ValueError, match="Labels must be provided for the metric"):
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opentelemetry_instance.increment_counter(metric_name="num_files_uploaded", value=5, labels={})
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def test_increment_counter_missing_mandatory_label(opentelemetry_instance):
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with pytest.raises(ValueError, match="Missing required labels: {'flow_id'}"):
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opentelemetry_instance.increment_counter(metric_name="num_files_uploaded", value=5, labels={"service": "one"})
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def test_increment_counter_unregisted_metric(opentelemetry_instance):
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with pytest.raises(ValueError, match="Metric 'num_files_uploaded_1' is not registered"):
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opentelemetry_instance.increment_counter(metric_name="num_files_uploaded_1", value=5, labels=fixed_labels)
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def test_opentelementry_singleton(opentelemetry_instance):
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opentelemetry_instance_2 = OpenTelemetry()
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assert opentelemetry_instance is opentelemetry_instance_2
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opentelemetry_instance_3 = OpenTelemetry(prometheus_enabled=False)
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assert opentelemetry_instance is opentelemetry_instance_3
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assert opentelemetry_instance.prometheus_enabled == opentelemetry_instance_3.prometheus_enabled
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def test_missing_labels(opentelemetry_instance):
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with pytest.raises(ValueError, match="Labels must be provided for the metric"):
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opentelemetry_instance.increment_counter(metric_name="num_files_uploaded", labels=None, value=1.0)
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with pytest.raises(ValueError, match="Labels must be provided for the metric"):
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opentelemetry_instance.up_down_counter("num_files_uploaded", 1, None)
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with pytest.raises(ValueError, match="Labels must be provided for the metric"):
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opentelemetry_instance.update_gauge(metric_name="num_files_uploaded", value=1.0, labels=dict())
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with pytest.raises(ValueError, match="Labels must be provided for the metric"):
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opentelemetry_instance.observe_histogram("num_files_uploaded", 1, dict())
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def test_multithreaded_singleton():
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def create_instance():
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return OpenTelemetry()
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# Create instances in multiple threads
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with ThreadPoolExecutor(max_workers=10) as executor:
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futures = [executor.submit(create_instance) for _ in range(100)]
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instances = [future.result() for future in as_completed(futures)]
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# Check that all instances are the same
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first_instance = instances[0]
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for instance in instances[1:]:
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assert instance is first_instance
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def test_multithreaded_singleton_race_condition():
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# This test simulates a potential race condition
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start_event = threading.Event()
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def create_instance():
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start_event.wait() # Wait for all threads to be ready
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return OpenTelemetry()
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# Create instances in multiple threads, all starting at the same time
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with ThreadPoolExecutor(max_workers=100) as executor:
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futures = [executor.submit(create_instance) for _ in range(100)]
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start_event.set() # Start all threads simultaneously
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instances = [future.result() for future in as_completed(futures)]
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# Check that all instances are the same
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first_instance = instances[0]
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for instance in instances[1:]:
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assert instance is first_instance
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