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212 lines
6.6 KiB
Python
212 lines
6.6 KiB
Python
import pytest
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import opik
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import opik.hooks
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from opik import opik_context
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from opik.anonymizer import factory, anonymizer
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from . import verifiers
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from ..testlib import generate_project_name
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PROJECT_NAME = generate_project_name("e2e", __name__)
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# Email pattern
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EMAIL_RULE = (
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r"\b[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Z|a-z]{2,}\b",
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"[EMAIL_REDACTED]",
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)
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# Credit card pattern (simplified)
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CC_RULE = (r"\b\d{4}[- ]?\d{4}[- ]?\d{4}[- ]?\d{4}\b", "[CARD_REDACTED]")
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# SSN pattern
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SSN_RULE = {"regex": r"\b\d{3}-\d{2}-\d{4}\b", "replace": "[SSN_REDACTED]"}
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@pytest.mark.parametrize("override_project_name", [True, False])
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def test_tracked_function__regexp_rules_anonymization__happy_flow(
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opik_client, override_project_name
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):
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"""Test that sensitive fields are masked in input, output and metadata."""
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project_name = (
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generate_project_name("e2e", "anonymization", "override")
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if override_project_name
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else None
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)
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# create and register anonymizer
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opik.hooks.clear_anonymizers()
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rules_anonymizer = factory.create_anonymizer([EMAIL_RULE, CC_RULE, SSN_RULE])
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opik.hooks.add_anonymizer(rules_anonymizer)
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# Setup
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ID_STORAGE = {}
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# Example PII values used in this test:
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# Email: john.doe@example.com
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# Credit Card: 1234 5678 9012 3456
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# SSN: 123-45-6789
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@opik.track(
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tags=["outer-tag1", "outer-tag2"],
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metadata={
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"outer-metadata-key": "outer-metadata-value",
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"card-number": "1234 5678 9012 3456",
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},
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project_name=project_name,
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)
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def f_outer(x: str, email: str):
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ID_STORAGE["f_outer-trace-id"] = opik_context.get_current_trace_data().id
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ID_STORAGE["f_outer-span-id"] = opik_context.get_current_span_data().id
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f_inner("inner-input")
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return email
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@opik.track(
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tags=["inner-tag1", "inner-tag2"],
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metadata={"inner-metadata-key": "inner-metadata-value", "ssn": "123-45-6789"},
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project_name=project_name,
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)
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def f_inner(y):
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ID_STORAGE["f_inner-span-id"] = opik_context.get_current_span_data().id
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return "inner-output"
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# Call
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f_outer("outer-input", email="john.doe@example.com")
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opik.flush_tracker()
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anonymized_outer_metadata = {
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"outer-metadata-key": "outer-metadata-value",
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"card-number": "[CARD_REDACTED]",
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}
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# Verify trace
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verifiers.verify_trace(
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opik_client=opik_client,
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trace_id=ID_STORAGE["f_outer-trace-id"],
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name="f_outer",
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input={"x": "outer-input", "email": "[EMAIL_REDACTED]"},
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output={"output": "[EMAIL_REDACTED]"},
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metadata=anonymized_outer_metadata,
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tags=["outer-tag1", "outer-tag2"],
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project_name=project_name or PROJECT_NAME,
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)
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# Verify the top level span
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verifiers.verify_span(
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opik_client=opik_client,
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span_id=ID_STORAGE["f_outer-span-id"],
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parent_span_id=None,
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trace_id=ID_STORAGE["f_outer-trace-id"],
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name="f_outer",
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input={"x": "outer-input", "email": "[EMAIL_REDACTED]"},
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output={"output": "[EMAIL_REDACTED]"},
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metadata=anonymized_outer_metadata,
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tags=["outer-tag1", "outer-tag2"],
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project_name=project_name or PROJECT_NAME,
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)
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anonymized_inner_metadata = {
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"inner-metadata-key": "inner-metadata-value",
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"ssn": "[SSN_REDACTED]",
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}
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# Verify nested span
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verifiers.verify_span(
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opik_client=opik_client,
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span_id=ID_STORAGE["f_inner-span-id"],
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parent_span_id=ID_STORAGE["f_outer-span-id"],
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trace_id=ID_STORAGE["f_outer-trace-id"],
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name="f_inner",
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input={"y": "inner-input"},
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output={"output": "inner-output"},
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metadata=anonymized_inner_metadata,
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tags=["inner-tag1", "inner-tag2"],
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project_name=project_name or PROJECT_NAME,
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)
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@pytest.mark.parametrize("override_project_name", [True, False])
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def test_tracked_function__rules_anonymization_remove_sensitive_key__happy_flow(
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opik_client, override_project_name
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):
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"""Test that sensitive keys are removed from metadata and other sensitive fields are masked in input and output."""
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project_name = (
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generate_project_name("e2e", "anonymization", "override")
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if override_project_name
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else None
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)
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class ApiKeyAnonymizer(anonymizer.Anonymizer):
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def anonymize(self, data, **kwargs):
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field_name = kwargs.get("field_name")
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object_type = kwargs.get("object_type")
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if (
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field_name == "metadata"
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and object_type in ["span", "trace"]
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and "api_key" in data
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):
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del data["api_key"]
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return data
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# create and register anonymizer
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opik.hooks.clear_anonymizers()
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api_key_anonymizer = ApiKeyAnonymizer()
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opik.hooks.add_anonymizer(api_key_anonymizer)
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rules_anonymizer = factory.create_anonymizer([EMAIL_RULE, CC_RULE, SSN_RULE])
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opik.hooks.add_anonymizer(rules_anonymizer)
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# Setup
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ID_STORAGE = {}
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@opik.track(
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tags=["outer-tag1", "outer-tag2"],
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metadata={
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"outer-metadata-key": "outer-metadata-value",
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"card-number": "1234 5678 9012 3456",
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"api_key": "secret-api-key",
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},
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project_name=project_name,
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)
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def f_outer(x: str, email: str):
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ID_STORAGE["f_outer-trace-id"] = opik_context.get_current_trace_data().id
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ID_STORAGE["f_outer-span-id"] = opik_context.get_current_span_data().id
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return email
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# Call
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f_outer("outer-input", email="john.doe@example.com")
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opik.flush_tracker()
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anonymized_metadata = {
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"outer-metadata-key": "outer-metadata-value",
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"card-number": "[CARD_REDACTED]",
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}
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# Verify trace
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verifiers.verify_trace(
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opik_client=opik_client,
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trace_id=ID_STORAGE["f_outer-trace-id"],
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name="f_outer",
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input={"x": "outer-input", "email": "[EMAIL_REDACTED]"},
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output={"output": "[EMAIL_REDACTED]"},
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metadata=anonymized_metadata,
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tags=["outer-tag1", "outer-tag2"],
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project_name=project_name or PROJECT_NAME,
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)
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# Verify the top level span
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verifiers.verify_span(
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opik_client=opik_client,
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span_id=ID_STORAGE["f_outer-span-id"],
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parent_span_id=None,
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trace_id=ID_STORAGE["f_outer-trace-id"],
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name="f_outer",
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input={"x": "outer-input", "email": "[EMAIL_REDACTED]"},
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output={"output": "[EMAIL_REDACTED]"},
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metadata=anonymized_metadata,
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tags=["outer-tag1", "outer-tag2"],
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project_name=project_name or PROJECT_NAME,
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)
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