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Extension repository on GitHub

Extension descriptor (YAML)

Parse and analyze test results, build outputs, and CI/CD pipeline logs from 45+ development tools with dynamic regexp patterns

Installing and Loading

INSTALL duck_hunt FROM community;
LOAD duck_hunt;

Example

-- Parse build errors from a log file
SELECT file_path, line_number, severity, message
FROM read_duck_hunt_log('build.log', 'auto')
WHERE status = 'ERROR';

-- Parse test results from string content
SELECT test_name, status, execution_time
FROM parse_duck_hunt_log('{"tests": [{"name": "test_auth", "outcome": "passed"}]}', 'pytest_json');

-- Use custom regexp pattern for any log format
SELECT severity, message
FROM parse_duck_hunt_log('ERROR: Connection failed
WARNING: Retrying...', 'regexp:(?P<severity>ERROR|WARNING):\s+(?P<message>.+)');

-- Analyze CI/CD workflow structure
SELECT workflow_name, job_name, step_name, step_status
FROM read_duck_hunt_workflow_log('github_actions.log', 'github_actions')
WHERE step_status = 'failure';

-- Generate status badges from results
SELECT status_badge(status) as badge, tool_name, message
FROM read_duck_hunt_log('build.log', 'auto');

-- Aggregate build health with badge
SELECT status_badge(
    COUNT(CASE WHEN status = 'ERROR' THEN 1 END),
    COUNT(CASE WHEN status = 'WARNING' THEN 1 END)
) as build_status
FROM read_duck_hunt_log('build.log', 'auto');

About duck_hunt

Duck Hunt is a comprehensive DuckDB extension for parsing and analyzing development tool outputs. It provides a unified SQL interface to query test results, build logs, linting output, and CI/CD pipeline data from 45+ tools and formats.

Core Table Functions:

• read_duck_hunt_log(file, format) - Parse tool outputs from files
• parse_duck_hunt_log(content, format) - Parse tool outputs from strings
• read_duck_hunt_workflow_log(file, format) - Parse CI/CD workflow logs from files
• parse_duck_hunt_workflow_log(content, format) - Parse CI/CD workflow logs from strings

Scalar Functions:

• status_badge(status) - Convert status to badge: [ OK ], [FAIL], [WARN], [ .. ], [ ?? ]
• status_badge(errors, warnings) - Compute badge from counts
• status_badge(errors, warnings, is_running) - Badge with running state

Supported Formats (45+):

• Dynamic: regexp:<pattern> - Custom patterns with named capture groups
• Test Frameworks: pytest, Go test, Cargo test, JUnit, RSpec, Mocha/Chai, Google Test, NUnit/xUnit
• Linting Tools: ESLint, RuboCop, Pylint, Flake8, MyPy, Clippy, SwiftLint, PHPStan, and more
• Build Systems: CMake, Make, Maven, Gradle, Cargo, MSBuild, Node.js, Python
• CI/CD Engines: GitHub Actions, GitLab CI, Jenkins, Docker
• Debugging: Valgrind, GDB/LLDB

Schema Fields (38):

• Core: event_id, tool_name, event_type, file_path, line_number, column_number, status, severity, message
• Error Analysis: error_fingerprint, similarity_score, pattern_id, root_cause_category
• Workflow: workflow_name, job_name, step_name, workflow_status, job_status, step_status, duration

Key Features:

• Automatic format detection
• Error pattern clustering and fingerprinting
• Root cause categorization (network, permission, config, syntax, build, resource)
• Multi-file glob processing with Hive-style paths
• Pipeline integration with stdin support
• Hierarchical CI/CD workflow parsing

Perfect for CI/CD analysis, automated debugging, test aggregation, quality gates, and agent-driven development workflows.

Added Functions