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2.7 KiB
2.7 KiB
name, description
| name | description |
|---|---|
| python-sdk | Python SDK patterns for Opik. Use when working in sdks/python, on SDK APIs, integrations, or message processing. |
Python SDK
Three-Layer Architecture
Layer 1: Public API (opik.Opik, @opik.track)
↓
Layer 2: Message Processing (queue, batching, retry)
↓
Layer 3: REST Client (OpikApi, HTTP)
Critical Gotchas
Flush Before Exit
# ✅ REQUIRED for async operations
client = opik.Opik()
# ... tracing operations ...
client.flush() # Must call before exit!
Async vs Sync Operations
Async (via message queue) - fire-and-forget:
trace(),span()log_traces_feedback_scores()experiment.insert()
Sync (blocking, returns data):
create_dataset(),get_dataset()create_prompt(),get_prompt()search_traces(),search_spans()
Lazy Imports for Integrations
# ✅ GOOD - integration files assume dependency exists
import anthropic # Only imported when user uses integration
# ❌ BAD - importing at package level
from opik.integrations import anthropic # Would fail if not installed
Integration Patterns
Pattern Selection
Library has callbacks? → Pure Callback (LangChain, LlamaIndex)
No callbacks? → Method Patching (OpenAI, Anthropic)
Callbacks unreliable? → Hybrid (ADK)
Method Patching (OpenAI, Anthropic)
from opik.integrations.anthropic import track_anthropic
client = anthropic.Anthropic()
tracked_client = track_anthropic(client) # Wraps methods
Callback-Based (LangChain)
from opik.integrations.langchain import OpikTracer
tracer = OpikTracer()
chain.invoke(input, config={"callbacks": [tracer]})
Decorator-Based
@opik.track
def my_function(input: str) -> str:
# Auto-creates span, captures input/output
return process(input)
Dependency Policy
- Avoid adding new dependencies
- Use conditional imports for integrations
- Keep version bounds flexible:
>=2.0.0,<3.0.0
Batching System
Messages batch together for efficiency:
- Flush triggers: time (1s), size (100), memory (50MB), manual
- Reduces HTTP overhead significantly
API Method Naming
# CRUD: create/get/list/update/delete
client.create_experiment(name="exp")
client.get_dataset(name="ds")
# Search for complex queries
client.search_spans(project_name="proj")
client.search_traces(project_name="proj")
# Batch for bulk operations
client.batch_create_items(...)
Reference Files
- testing.md - fake_backend, verifiers, test naming
- error-handling.md - Exception hierarchy, MetricComputationError
- good-code.md - Access control, imports, factories, DI