urbalurba-logging 1.0.5

Professional structured logging library following 'Loggeloven av 2025' requirements

Urbalurba Logging - Python Implementation

Professional Python implementation of Urbalurba structured logging following "Loggeloven av 2025" requirements. Provides consistent API across all programming languages with full OpenTelemetry integration and production-ready OTLP export capabilities.

✅ Current Status: PRODUCTION READY

• 🎉 Complete Feature Parity: Matches TypeScript Winston → OpenTelemetry architecture
• 📡 OTLP Export: Fully functional logs + traces export to observability stack
• 🔄 Multiple Transports: Simultaneous console + file + OTLP logging
• 🧪 Comprehensive Testing: Demo, library tests, and real-world validation complete
• 📊 Live Verification: Successfully integrated with Loki + Grafana observability stack

Repository

This package is part of the multi-language Urbalurba logging system:

• Repository: https://github.com/terchris/urbalurba-logging
• Python Package: https://github.com/terchris/urbalurba-logging/tree/main/python

Installation

From Source (Current Method)

git clone https://github.com/terchris/urbalurba-logging.git
cd urbalurba-logging/python
pip install -e .

From PyPI

pip install urbalurba-logging

From Test PyPI

pip install -i https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple/ urbalurba-logging

Quick Start

1. Initialize Logger (Required)

from urbalurba_logging import urbinitializelogger, urblog, LOGLEVELS

# Initialize once at application startup
urbinitializelogger("your-system-id")

2. Basic Logging

FUNCTIONNAME = "MyFunction"

# Simple logging
urblog(LOGLEVELS.INFO, FUNCTIONNAME, "Processing completed", None)

# With context data
urblog(LOGLEVELS.INFO, FUNCTIONNAME, "User created", None, 
       {"userId": "12345"}, {"status": "success"})

# Error logging with exception
try:
    # some operation
    pass
except Exception as error:
    urblog(LOGLEVELS.ERROR, FUNCTIONNAME, "Operation failed", error)

3. Job Tracking

from urbalurba_logging import urblogjobstatus, urblogjobprogress

FUNCTIONNAME = "ProcessData"

# Job lifecycle tracking
urblogjobstatus(LOGLEVELS.INFO, FUNCTIONNAME, "DataImport", "Started")
urblogjobprogress(LOGLEVELS.INFO, FUNCTIONNAME, "item-1", 1, 100)
urblogjobstatus(LOGLEVELS.INFO, FUNCTIONNAME, "DataImport", "Completed")

4. Graceful Shutdown

from urbalurba_logging import urbflushlog

# Flush all logs before application exit
urbflushlog()

Running the Demo

The demo demonstrates real-world usage with API calls and comprehensive logging patterns.

Step 1: Clone and Navigate

git clone https://github.com/terchris/urbalurba-logging.git
cd urbalurba-logging/python/examples/demo

Step 2: Install Dependencies

# Install demo dependencies
pip install -r requirements.txt

# Install main package in development mode
pip install -e ../../

Step 3: Configure Environment

# Run interactive setup (choose logging destination)
./setup-dev-env.sh

Choose from three options:

1. Console Output - JSON logs to terminal (good for development)
2. File Logging - Logs to ./logs/dev.log (good for analysis)
3. OTLP Collector - Export to observability stack (requires Docker)

Step 4: Run Demo

python demo.py

Project Structure

python/
├── src/
│   └── urbalurba_logging/
│       ├── __init__.py          # Package exports
│       ├── urblogger.py         # Core logging implementation  
│       └── log_levels.py        # Log level constants
├── examples/
│   └── demo/
│       ├── demo.py              # Complete working example
│       ├── requirements.txt     # Demo dependencies
│       ├── setup-dev-env.sh     # Development environment setup
│       └── .env                 # Environment template
├── setup.py                     # PyPI package configuration
├── requirements.txt             # Main dependencies
└── README-python.md            # This documentation

API Reference

Initialization

urbinitializelogger(system_id: str)

• Required: Must be called once at application startup
• Purpose: Initialize logger with unique system identifier
• Example: urbinitializelogger("payment-service")

Core Logging

urblog(level, function_name, message, exception, input_json=None, response_json=None)

• Purpose: General purpose structured logging
• Parameters:
  • level: Use LOGLEVELS constants (INFO, ERROR, etc.)
  • function_name: Name of calling function (use constant)
  • message: Human-readable description
  • exception: Exception object or None
  • input_json: Input parameters/context (optional)
  • response_json: Output/response data (optional)

Job Tracking

urblogjobstatus(level, function_name, job_name, status, input_json=None)

• Purpose: Track job lifecycle (Started, Completed, Failed)
• Example: urblogjobstatus(LOGLEVELS.INFO, "ProcessPayments", "MonthlyBatch", "Started")

urblogjobprogress(level, function_name, item_id, current, total, input_json=None)

• Purpose: Track progress through collections/batches
• Example: urblogjobprogress(LOGLEVELS.INFO, "ProcessPayments", "payment-123", 5, 100)

Log Levels

Level	Purpose	Usage Example
LOGLEVELS.TRACE	Detailed debugging	Successful operations with full context
LOGLEVELS.DEBUG	Development info	Function entry/exit, data flow
LOGLEVELS.INFO	Important events	Business logic, progress tracking
LOGLEVELS.WARN	Potential issues	Missing optional parameters, retries
LOGLEVELS.ERROR	Actual failures	API errors, validation failures
LOGLEVELS.FATAL	Critical failures	System crashes, data corruption

Output Format

All logs are structured JSON with consistent fields:

{
  "timestamp": "2025-07-04T12:54:34.447Z",
  "level": "info",
  "systemId": "payment-service", 
  "functionName": "ProcessPayment",
  "correlationId": "e804d7c4-4592-42e6-9923-ab4dad45f41f",
  "message": "Payment processed successfully",
  "inputJSON": {"userId": "12345", "amount": 100.00},
  "responseJSON": {"transactionId": "tx-789", "status": "completed"}
}

Environment Configuration

Create .env.development (or use setup script):

# Logging configuration
LOG_TO_FILE=true
LOG_FILE_PATH=./logs/dev.log
LOG_LEVEL=INFO

# OpenTelemetry OTLP Export (production-ready)
OTEL_EXPORTER_OTLP_TRACES_ENDPOINT=http://localhost:4318/v1/traces
OTEL_EXPORTER_OTLP_LOGS_ENDPOINT=http://localhost:4318/v1/logs
OTEL_ENVIRONMENT=development

# Environment
PYTHON_ENV=development

Dependencies

Core dependencies installed automatically:

• structlog ≥23.1.0 - Structured logging framework
• opentelemetry-api ≥1.21.0 - OpenTelemetry API for tracing
• opentelemetry-sdk ≥1.21.0 - OpenTelemetry SDK
• opentelemetry-exporter-otlp-proto-http ≥1.21.0 - OTLP HTTP exporter
• opentelemetry-sdk-logs ≥1.21.0 - OpenTelemetry logs SDK
• opentelemetry-api-logs ≥1.21.0 - OpenTelemetry logs API
• opentelemetry-instrumentation-auto ≥1.21.0 - Auto-instrumentation
• requests ≥2.31.0 - HTTP client library

Production Usage

OTLP Export (Recommended)

import os
# Configure OTLP endpoints for production observability stack
os.environ['OTEL_EXPORTER_OTLP_TRACES_ENDPOINT'] = 'https://your-otel-collector.com/v1/traces'
os.environ['OTEL_EXPORTER_OTLP_LOGS_ENDPOINT'] = 'https://your-otel-collector.com/v1/logs'
os.environ['OTEL_ENVIRONMENT'] = 'production'

from urbalurba_logging import urbinitializelogger, urbflushlog
urbinitializelogger("production-service")

# Your application code here...

# Graceful shutdown
urbflushlog()

Multiple Transports (Console + File + OTLP)

import os
# Enable all transports simultaneously
os.environ['LOG_TO_FILE'] = 'true'
os.environ['LOG_FILE_PATH'] = '/var/log/myapp/app.log'
os.environ['OTEL_EXPORTER_OTLP_TRACES_ENDPOINT'] = 'https://your-otel-collector.com/v1/traces'
os.environ['OTEL_EXPORTER_OTLP_LOGS_ENDPOINT'] = 'https://your-otel-collector.com/v1/logs'

from urbalurba_logging import urbinitializelogger, urbflushlog
urbinitializelogger("production-service")

File Logging Only

import os
os.environ['LOG_TO_FILE'] = 'true'
os.environ['LOG_FILE_PATH'] = '/var/log/myapp/app.log'

from urbalurba_logging import urbinitializelogger, urbflushlog
urbinitializelogger("production-service")

Best Practices

1. Function Names: Use constants for consistent identification

   FUNCTIONNAME = "ProcessPayment"  # Use PascalCase
   

2. Context Data: Include relevant input/output for debugging

   urblog(LOGLEVELS.INFO, FUNCTIONNAME, "User authenticated", None,
          {"userId": user_id}, {"sessionId": session.id})
   

3. Error Handling: Always include exception objects

   except Exception as error:
       urblog(LOGLEVELS.ERROR, FUNCTIONNAME, "Authentication failed", error)
   

4. Job Processing: Track lifecycle and progress

   urblogjobstatus(LOGLEVELS.INFO, FUNCTIONNAME, "DataExport", "Started")
   for item in items:
       urblogjobprogress(LOGLEVELS.INFO, FUNCTIONNAME, item.id, current, total)
   urblogjobstatus(LOGLEVELS.INFO, FUNCTIONNAME, "DataExport", "Completed")
   

5. Graceful Shutdown: Always flush logs before exit

   from urbalurba_logging import urbflushlog
   
   try:
       # Application code here
       pass
   finally:
       urbflushlog()  # Ensures all logs are sent to OTLP collector
   

Architecture

The Python implementation uses the same architecture as TypeScript:

structlog → OpenTelemetry → OTLP (logs + traces)

Key Components:

• structlog: Primary logging framework (like Winston in TypeScript)
• OpenTelemetry Processor: Custom processor for OpenTelemetry integration
• Multiple Transports: Console, file, and OTLP export simultaneous operation
• Full SDK Configuration: Traces, logs, and auto-instrumentation
• Graceful Shutdown: urbflushlog() ensures data delivery

Testing

The implementation includes comprehensive testing:

1. Demo Application: Real-world Norwegian Brreg API integration
2. Library Tests: All logging scenarios and error handling
3. Setup Scripts: Interactive environment configuration
4. Integration Tests: OTLP export verified with live observability stack

License

MIT