enhanced-logger 0.1.3

An enhanced logging package for Python with additional features and performance metrics.

Enhanced Logger

---

The Enhanced Logger package is an extension of the built-in Python logging module, designed to address additional features and performance metrics. This package includes:

• Trace logging to log all function entry and exit
• JSON and XML formatters
• Performance metrics logging
• HTTP and database logging handlers
• File logging for all logger types (except DB Handler)

Features

• Trace Logging: Log entry and exit points of functions with context.
• Performance Metrics: Log execution time and memory usage of functions.
• Enhanced Formatters: Log entries in JSON and XML formats.
• HTTP Logging: Send log entries to a remote server via HTTP.
• Database Logging: Store log entries in various types of databases (SQLite, PostgreSQL, MongoDB).
• File Logging: Option to store logs in a .log file.

Installation

To install the Enhanced Logger package, use the following command:

pip install enhanced-logger

Usage

Trace Logger

Trace logging allows you to trace the entry and exit points of functions.

from enhanced_logger import EnhancedLogger

trace_logger = EnhancedLogger.configure_trace_logger('trace_logger')

@trace_logger.trace
def sample_function(x, y):
    return x + y

sample_function(5, 10)

Performance Logger

Performance logging provides execution time and memory usage information.

from enhanced_logger import EnhancedLogger

performance_logger = EnhancedLogger.configure_performance_logger('performance_logger')

@performance_logger.log_performance
def example_function(n):
    total = 0
    for i in range(n):
        total += i
    return total

example_function(1000000)

Enhanced Performance Logger

Enhanced performance logging with additional details.

from enhanced_logger import EnhancedLogger

enhanced_performance_logger = EnhancedLogger.configure_enhanced_performance_logger('enhanced_performance_logger')

@enhanced_performance_logger.log_performance
def compute_factorial(n):
    if n == 0:
        return 1
    else:
        return n * compute_factorial(n - 1)

compute_factorial(10)

JSON Formatter

Logs entries in JSON format.

from enhanced_logger import EnhancedLogger

json_logger = EnhancedLogger.configure_json_logger('json_logger')
json_logger.info('This is a test log entry in JSON format.')

You can also log context data.

from enhanced_logger import EnhancedLogger

json_logger = EnhancedLogger.configure_json_logger('json_logger')
context_info = {
    'context': {
        'user_id': 12345,
        'transaction_id': 'abcde12345'
    }
}
json_logger.info('This is a test log entry in JSON format with context.', extra=context_info)

or you can also use decorator.

@EnhancedLogger.json_log('json_logger')
def add(x, y):
    return x + y

@EnhancedLogger.json_log('json_logger')
def multiply(x, y):
    return x * y

print(add(5, 3))
print(multiply(5, 3))

XML Formatter

Logs entries in XML format.

from enhanced_logger import EnhancedLogger

xml_logger = EnhancedLogger.configure_xml_logger('xml_logger')
xml_logger.info('This is a test log entry in XML format.')

HTTP Handler

Sends log entries to a remote server via HTTP. (Assumes a logging endpoint is available)

from enhanced_logger import EnhancedLogger

http_logger = EnhancedLogger.configure_http_logger('http_logger', 'http://example.com/log', method='POST', headers={'Content-Type': 'application/json'})
http_logger.info('This is a test log entry sent via HTTP.')

DB Handler

Stores log entries in various types of databases likes SQLite/Postgres/MongoDB.

SQLite

from enhanced_logger import EnhancedLogger

sqlite_logger = EnhancedLogger.configure_db_logger('sqlite_logger', 'sqlite', {'db_path': 'logs.db'})
sqlite_logger.info('This is a test log entry stored in a SQLite database.')

PostgreSQL

from enhanced_logger import EnhancedLogger
postgres_logger = EnhancedLogger.configure_db_logger('postgres_logger', 'postgres', {
    'dbname': 'testdb',
    'user': 'dbuser',
    'password': 'dbpass',
    'host': 'localhost',
    'port': 5432
})
postgres_logger.info('This is a test log entry stored in a PostgreSQL database.')

MongoDB

from enhanced_logger import EnhancedLogger
mongodb_logger = EnhancedLogger.configure_db_logger('mongodb_logger', 'mongodb', {
    'uri': 'mongodb://localhost:27017/',
    'db_name': 'testdb'
})
mongodb_logger.info('This is a test log entry stored in a MongoDB database.')

More Examples

You can also store logs in a .log file by specifying file name for the log_to_file argument.

from enhanced_logger import EnhancedLogger

# JSON Logger
@EnhancedLogger.json_log('json_logger', log_to_file='json_logs.log')
def add(x, y):
    return x + y

print(add(5, 3))


# Performance Logger
performance_logger = EnhancedLogger.configure_performance_logger('performance_logger', log_to_file='performance_logs.log')

@performance_logger.log_performance
def compute_factorial(n):
    if n == 0:
        return 1
    else:
        return n * compute_factorial(n - 1)

print(compute_factorial(10))

# HTTP Logger
from enhanced_logger import EnhancedLogger

http_logger = EnhancedLogger.configure_http_logger('http_logger', 'http://example.com/log', method='POST', headers={'Content-Type': 'application/json'}, log_to_file='http_logs.log')
http_logger.info('This is a test log entry sent via HTTP.')