plogchain 0.0.2

Python Logging based on blockchain

Plogchain

Python Logging based on blockchain.

Messages get chained

The current log line contains the signature of the previous line with your secret.

• detect lines deletion
• detect logs tampering

Philosophy

The package is intended to be a lightweight util for generating incorruptible logs.

For this pupose we rely as much as possible on standard packages.

Usage

Install

pip install plogchain

Init once in main

import ChainedLogger

# Obtained after the -vvv option of the program
verbosity = 3
theSecret = ChainedLogger.generateSecret()
ChainedLogger.init(verbosity, theSecret)

Use everywhere with python logging module

import logging

logging.debug("My message")
logging.info("Some information")

Check your logs integrity afterwards

import ChainedLogger

aLogChain = [
	"2020-03-30 13:38:00.782|0ec90b9839fdd964|TestChaining.py:20 test_logging_happy_case hello gg",
	"2020-03-30 13:38:00.782|2e3f1b4a7b946fb1|TestChaining.py:21 test_logging_happy_case voila1",
	"2020-03-30 13:38:00.782|10d1ab606618492a|TestChaining.py:22 test_logging_happy_case voila2",
	"2020-03-30 13:38:00.782|805757e144f4e385|TestChaining.py:23 test_logging_happy_case voila5",
	"2020-03-30 13:38:00.782|3bda90b5af77d3fe|TestChaining.py:24 test_logging_happy_case voila4"
]
isValid = ChainedLogger.verify(aLogChain, theSecret)

Apply you own logging format (WIP)

The package is suitable for server logging which context changes from one transaction to another. Here is an example of setting contextual information throughout the lifecycle of a server:

# Static formatting at program startup...
ChainedLogger.setFormat(
	# Standard python logging fields
	timestamp = "%(asctime)s.%(msecs)03d",
	fileLine  = "%(filename)s:%(lineno)d",
	message   = "%(message)s",

	# Custom fields
	processId = <current PID>
)

# ... then dynamic formatting with runtime context.
ChainedLogger.updateFormat(transactionId = <current transactionId>

Contributing

Install

Simply clone and submit pull requests.

Testing

The unit tests are located in the test folder which contains the __main__.py entrypoint.

# Run all
python test

# Get additional options
python test --help

Delivery

Use to the awesome Poetry tool for this purpose:

poetry publish