haive.core.utils.debugkit

Unified development utilities for Python debugging, profiling, and analysis.

This package provides a comprehensive suite of development tools including: - Enhanced debugging with multiple debugger integrations - Rich logging with structured output and context management - Advanced code tracing and execution analysis - Performance profiling with multiple profiler backends - Comprehensive static analysis orchestration - Code complexity and type analysis - Benchmarking and load testing utilities

All utilities are designed to work together seamlessly and provide both simple interfaces for quick debugging and advanced features for comprehensive code analysis.

Examples

Quick start with unified interface:

from haive.core.utils.debugkit import debugkit

# Enhanced debugging
debugkit.ice("Debug variable", value=42)

# Rich logging with context
with debugkit.context("operation") as ctx:
    ctx.log("Starting process")
    # ... work ...
    ctx.log("Process complete")

# Complete analysis
@debugkit.instrument(analyze=True, profile=True)
def my_function(data: List[str]) -> Dict[str, int]:
    return process_data(data)

Individual component usage:

from haive.core.utils.debugkit import debug, log, trace, profile

# Use specific components
debug.ice("Variable inspection", data=my_data)
log.info("Process started", context={"user": "alice"})

@trace.calls
@profile.time
def traced_function():
    return complex_operation()

Advanced analysis:

from haive.core.utils.debugkit import debugkit

# Analyze code quality
analysis = debugkit.analyze_code(my_function)
print(f"Type coverage: {analysis.type_analysis.type_coverage:.1%}")
print(f"Complexity grade: {analysis.complexity_analysis.complexity_grade}")

# Run static analysis
results = debugkit.static_analysis.analyze_file(Path("module.py"))
report = debugkit.static_analysis.generate_report(results)

Submodules