📝 Professional Logging

High-fidelity audit trails and contextual debugging for global execution.

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The framework features a ContextualLogger designed for clear audit trails and high-fidelity debugging in both local and CI/CD environments.

🚀 Overview

Unlike standard print statements, the ContextualLogger: - Automatically detects context: Extracts Feature and Scenario names from Behave. - Color-coded output: Standardized colors for different severity levels. - Audit-ready: Prepend every log with a high-precision timestamp. - Terminal Friendly: Uses ANSI codes for beautiful terminal formatting.

📊 Log Levels

Level	Color	Usage
info	🔵 Blue	General progress, navigation, request sending.
success	🟢 Green	Key milestones or successful assertions.
warning	🟡 Yellow	Deprecated steps, explicit waits, or unusual states.
error	🔴 Red	Critical failures, environmental issues.
debug	⚪ Gray	Verbose data, variable storage, internal state.

🛠️ Usage in Steps

The logger is readily available inside step definitions. Just import it and pass the context object to enable automatic context detection.

from qa_framework.utils.logger import ContextualLogger

@when('I do something important')
def step_example(context):
    ContextualLogger.info("Starting important action...", context)
    # ... logic ...
    ContextualLogger.success("Action completed successfully!", context)

Automatic Context Extraction

When you pass context to a log method, the logger will automatically prepend the output with: [FeatureName | ScenarioName]

Output Example: 19:29:45 [Billing | Process Invoice] INFO: Starting important action...

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🎨 Aesthetic Headers

For major sections or debugging blocks, use the section method:

ContextualLogger.section("Response JSON")
print(json.dumps(data, indent=2))

CI/CD Integration

In GitHub Actions or Jenkins, these logs will be much easier to scan than white-on-black text, allowing you to quickly identify which scenario was running when an error occurred.