The SearchGoat Python library family
DEVELOPER TOOLING · PYTHON · DATA ANALYSIS
| See the root project on github ↗
Turning Cribl Search results into DataFrames
A Python library family that removes the API plumbing between operational telemetry and familiar data-analysis workflows.
SearchGoat lets developers query Cribl Search and receive pandas DataFrames while handling authentication, job submission, polling, pagination, result retrieval, and format conversion.
Separate packages support standalone Python applications, local Jupyter notebooks, and Hex projects without forcing users to rebuild the same integration for each environment.
Why it matters
Operational data is valuable beyond the observability platform, but accessing it programmatically requires redundant API work.
SearchGoat abstracts that workflow into a small Python interface so analysts and developers can spend more time exploring data and less time managing API mechanics.
Core features
Query Cribl Search from Python, Jupyter, or Hex.
Return results as analysis-ready pandas DataFrames.
Handle asynchronous jobs, polling, and pagination automatically.
Export results to CSV or Parquet for later analysis.
Keep credentials out of scripts and notebooks.
What this work demonstrates
A developer-experience approach to integration design: identify repetitive platform friction, create a focused abstraction, and support it with clear onboarding, examples, error handling, and environment-specific documentation.