EmadHelmi/herodotus

Herodotus

An awesome enhanced python logger
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Table of Contents

About The Project
- The history behind the project
- The naming convention
Getting Started
- Installation
Usage
Contributing
License
Contact

About The Project

The history behind the project

The Python logging package is a powerful tool for logging messages to various streams, ranging from files to third-party services like Elasticsearch.

However, there was a particular instance in a project where I needed to log messages through multiple streams with varying levels of severity. To illustrate, I aimed to create a logger object equipped with three handlers: one for a rotating file, one for standard output (stdout), and one for Elasticsearch.

My objective was to route each severity level to a specific stream. Additionally, I intended to apply colorization to the logs displayed in stdout, while omitting colorization for logs saved in the file.

When I employed code similar to the following:

import logging
import some_colorizer_function

my_logger = logging.getLogger("my_logger")
my_logger.debug(
    some_colorizer_function("some message with %s"),
    "args"
)

It yielded a visually appealing colorized output on stdout. However, when directed to Elasticsearch or written to a file, the output appeared unattractive due to the presence of ANSI color symbols. Consequently, I embarked on refining the logging package and subsequently contemplated making these improvements available for public use. If you're interested, I welcome you to contribute to this endeavor.

The naming convention

Herodotus stands as an ancient Greek historian acclaimed as the "Father of History." Renowned for penning the book "The Histories," he holds a position among the earliest contributors to historical literature. This opus spans an array of topics encompassing history, geography, cultures, civilizations, and conflicts. Notably, he adeptly merged meticulous event accounts with captivating narratives. His opus presents a fusion of historical scrutiny and cultural storytelling, rendering him a pivotal influencer in the evolution of historical writing.

Getting Started

I've also created a pypi package for this library. So you can easily use and install it with pip or clone the project.

Installation

pip install herodotus_logger --upgrade

Usage

Basic usage

To begin, it's essential to instantiate a logger object with a designated severity level. This configuration dictates that the logger will transmit all severities equal to or surpassing the specified level. Further insight into severity numbers can be found here. For instance, if a logger object is established with a WARNING level, it will refrain from dispatching INFO, DEBUG, or NOTSET levels to its associated handlers.
```
import logging
from herodotus import logger
 
lg = logger.Logger(
     name="test_logger",
     level=logging.WARNING
)
```

You also should give it some handlers. You have two main options to do so:

Use some basic provided handlers in the herodotus.handlers which are starting with Enhanced*
- Note that all provided handlers' arguments are as the main one. They just accept some more arguments I'll explain.
Use any custom or other handlers which are of type Handler in python.

import logging
from sys import stdout

from herodotus import logger
from herodotus import handlers

lg = logger.Logger(
    name="test_logger",
    level=logging.WARNING,
    handlers=[
        handlers.EnhancedStreamHandler(
            stream=stdout,
            level=logging.WARNING
        ),
        handlers.EnhancedFileHandler(
            filename="logs/test_logfile.log",
            mode="a",
            encoding="utf-8",
            level=logging.CRITICAL
        )
    ]
)

You're all set! Lean back and simply instruct your logger object to start logging!
1. Create the logs directory:
```
mkdir logs
```
2. Call the logger logs functions (ex debug, info,...)
```
lg.logger.info("Hello")
```
However, at this juncture, no action will transpire. This outcome arises due to the fact that the log level lg is established as logging.WARNING, while we endeavor to initiate logging with the info level. Evidently, the hierarchy dictates that log.INFO holds a lesser value than log.WARNING.

Let's try another one:
```
lg.logger.warning("Hello")
```
and the bash output is:
```
2023-08-09T10:39:05|test_logger|WARNING|Hello
```
However, no logs have been recorded in the log file, and the rationale behind this outcome is evident.

Let's run another example:
```
lg.logger.critical("Hello")
```
and the bash output is:
```
2023-08-09T10:45:45|test_logger|CRITICAL|Hello
```
Consequently, the log file located at logs/test_logfile.log mirrors the identical output.

Use strict levels

What should we do If we want strict logging levels. I mean that I want to log to the stream JUST the warning level and not higher (ex. error.) It's also simple. You can use strict_level parameter and set it True:

import logging
from sys import stdout

from herodotus import logger
from herodotus import handlers

lg = logger.Logger(
    name="test_logger",
    level=logging.WARNING,
    formatter=logging.Formatter(
        datefmt="%Y-%m-%dT%H:%M:%S",
        fmt="%(asctime)s %(levelname)s: %(message)s"
    ),
    handlers=[
        handlers.EnhancedStreamHandler(
            stream=sys.stdout,
            level=logging.ERROR,
            strict_level=True
        ),
        handlers.EnhancedFileHandler(
            filename="logs/test_log.log",
            mode="a",
            encoding="utf-8",
            level=logging.WARNING,
            strict_level=True
        )
    ]
)

lg.logger.error("hello, world")

If you don't set the strict_level parameter, you will see the log message both in the stdout and the file. But with set it to True you don't see the message in the file.

Use with a Formatter

I define a default formatter for the logger as follow:

self.formatter = formatter or logging.Formatter(
    datefmt="%Y-%m-%dT%H:%M:%S",
    fmt="%(asctime)s|%(name)s|%(levelname)s|%(message)s"
)

But you can change it when you create the logger:

import logging
from sys import stdout

from herodotus import logger
from herodotus import handlers

lg = logger.Logger(
    name="test_logger",
    level=logging.WARNING,
    formatter=logging.Formatter(
        datefmt="%Y-%m-%dT%H:%M:%S",
        fmt="%(asctime)s %(levelname)s: %(message)s"
    ),
    handlers=[
        handlers.EnhancedStreamHandler(
            stream=stdout,
            level=logging.WARNING
        ),
        handlers.EnhancedFileHandler(
            filename="logs/test_logfile.log",
            mode="a",
            encoding="utf-8",
            level=logging.CRITICAL
        )
    ]
)

The most important thing to note is that you can also set a different formatter for each handler. However, if you don't specify a formatter for your handler, the logger will fall back to using its own default formatter.

import logging
from sys import stdout

from herodotus import logger
from herodotus import handlers

lg = logger.Logger(
    name="test_logger",
    level=logging.WARNING,
    formatter=logging.Formatter(
        datefmt="%Y-%m-%dT%H:%M:%S",
        fmt="%(asctime)s %(levelname)s: %(message)s"
    ),
    handlers=[
        handlers.EnhancedStreamHandler(
            stream=stdout,
            level=logging.WARNING
        ),
        handlers.EnhancedFileHandler(
            filename="logs/test_logfile.log",
            mode="a",
            encoding="utf-8",
            level=logging.CRITICAL,
            formatter=logging.Formatter(
                datefmt="%H:%M:%S",
                fmt="%(asctime)s: %(message)s"
            )
        )
    ]
)

Using the colorizer

Incorporating colors throughout undoubtedly provides a distinctive perspective, and this holds true in the context of logging as well. One approach is to leverage the colored. Additionally, I've included user-friendly functions that facilitate the inclusion of colors within your logs.

Let's see some examples:

import logging
from sys import stdout

from herodotus import logger
from herodotus import handlers
from herodotus.utils import colorizer

lg = logger.Logger(
    name="test_logger",
    level=logging.WARNING,
    formatter=logging.Formatter(
        datefmt="%Y-%m-%dT%H:%M:%S",
        fmt="%(asctime)s %(levelname)s: %(message)s"
    ),
    handlers=[
        handlers.EnhancedStreamHandler(
            stream=stdout,
            level=logging.WARNING
        )
    ]
)

lg.logger.critical(colorizer.colorize("Hello", foreground="green"))

and the output will be something like this:

You can also add styles (as noted in the colored). To do so, just pass your desired styles as a list to the colorize function:

lg.logger.critical(colorizer.colorize("Hello", foreground="green", styles=['bold', 'underline']))

And the output will be something like this:

But what happens if we add a file handler to a logger which uses the colorize function? Let's see:

import logging
from sys import stdout

from herodotus import logger
from herodotus import handlers
from herodotus.utils import colorizer

lg = logger.Logger(
    name="test_logger",
    level=logging.WARNING,
    formatter=logging.Formatter(
        datefmt="%Y-%m-%dT%H:%M:%S",
        fmt="%(asctime)s %(levelname)s: %(message)s"
    ),
    handlers=[
        handlers.EnhancedStreamHandler(
            stream=stdout,
            level=logging.WARNING
        ),
        handlers.EnhancedFileHandler(
            filename="logs/test_logfile.log",
            mode="a",
            encoding="utf-8",
            level=logging.CRITICAL,
            formatter=logging.Formatter(
                datefmt="%H:%M:%S",
                fmt="%(asctime)s: %(message)s"
            )
        )
    ]
)

lg.logger.critical(colorizer.colorize("Hello", foreground="green"))

In the log file, you will probably see something like this (If you don't have any plugin or extension to convert ansii chars to the colors):

Finding the appearance unappealing? Wondering what steps to take next? No need to fret. I've got a solution for you.

You can make use of the msg_func argument within each of the Enhanced* handlers. This argument expects a function as its type, so you should provide it with a suitable function. As an illustration, I've authored a decolorize function in the herodotus.utils.colorize package. This function takes a string containing ANSI color codes and effectively eliminates them:

handlers.EnhancedFileHandler(
    filename="logs/test_logfile.log",
    mode="a",
    encoding="utf-8",
    level=logging.CRITICAL,
    msg_func=colorizer.decolorize,
    formatter=logging.Formatter(
        datefmt="%H:%M:%S",
        fmt="%(asctime)s: %(message)s"
    )

lg.logger.critical(colorizer.colorize("Hello", foreground="green"))

Finally, in the log file you will see something like this:

See the open issues for a full list of proposed features( and known issues).

Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement." Don't forget to give the project a star! Thanks again!

Fork the Project
Create your Feature Branch (git checkout -b feature/AmazingFeature)
Commit your Changes (git commit -m 'Add some AmazingFeature')
Push to the Branch (git push origin feature/AmazingFeature)
Open a Pull Request

License

Distributed under the MIT License. See LICENSE.txt for more information.

Contact

Emad Helmi | Find me on Twitter @EmadHelmi

Or send me Email s.emad.helmi@gmail.com

EmadHelmi / herodotus