Metadata-Version: 2.1
Name: loggerpy
Version: 1.0
Summary: The simplest Python logger for everyday tasks.
Home-page: https://github.com/mett96/loggerpy
Author: Mattia Sanchioni
Author-email: mattia.sanchioni.dev@gmail.com
License: GPLv3
Description: # loggerpy
        
        The simplest Python logger for everyday tasks.
        
        ![](https://img.shields.io/github/manifest-json/v/mett96/loggerpy?color=9cf)
        ![](https://img.shields.io/pypi/v/loggerpy?color=green)
        ![](https://img.shields.io/pypi/pyversions/loggerpy)
        ![](https://img.shields.io/github/license/mett96/loggerpy)
        <!-- ![](https://img.shields.io/github/stars/mett96/loggerpy?style=social) -->
        
        <!-- aumenta questo paragrafo -->
        
        ## Table of Contents
        
        * [Installation](#Installation)
        * [Instructions](#Instructions)
            * [Configuration](#Configuration)
            * [Logger](#Logger)
            * [Customization](#Customization)
            * [Logger Recovery](#LoggerRecovery)
        * [Version](#Version)
        * [Next release](#NextRelease)
        * [License](#License)
        <!-- * [Authors](#Authors) -->
        
        
        ## Installation
        
        The easiest way to install is throw pip.
        
        ```bash
        pip install loggerpy
        ```
        
        Or you can install directly from Github
        ```bash
        pip install git+https://github.com/mett96/loggerpy.git
        ```
        
        ## Instructions
        
        
        In order to use this simple logger, many examples are provided inside [examples directory](https://github.com/mett96/loggerpy/tree/master/examples)
        
        ![](imgs/logger_example.png)
        
        
        
        ### Configuration
        The first thing to do is to configure the global settings of logger package.
        
        ```python
        import loggerpy
        
        loggerpy.configure()
        ```
        
        The possible customization of configurations are:
        - domain: the main name of all loggers
        - path: the path of saving log if you want to save them
        - print_level: the minimum level of printing 
        - save_level: the minimum level of saving, they can be different
        - info: boolean value if you want to print the default string _"Logger configured..."_
        
        In order to simplify the customization of printing and saving level it is provided a class that contained the 6 possible levels of logging. 
        Importing _Level_ from loggerpy, they can be used eg Level.DEBUG or Level.WARNING
        - Level.NO_LOGGER
        - Level.DEBUG
        - Level.INFO
        - Level.WARNING
        - Level.ERROR
        - Level.CRITICAL
        
        Configuration [example](https://github.com/mett96/loggerpy/tree/master/examples/configuration.py)
        
        
        ### Logger
        Now, it's time to create your first logger.
        ```python
        from loggerpy import configure, get_logger
        
        configure()
        
        logger = get_logger('custom_name')
        
        ```
        
        First logger [example](https://github.com/mett96/loggerpy/tree/master/examples/first_logger.py)
        
        ### Customization
        When we use _get_logger_ we can set custom parameters for this specific logger.
        They are independent from the parameters set during configuration.
        The customizable parameters are:
        - print_level
        - save_level
        - path
        
        ```python
        logger = get_logger('first', print_level=Level.WARNING, save_level=Level.INFO, path='custom_logger')
        ```
        
        ### LoggerRecovery
        Each logger has a unique name. So, when you ask to _get_logger_ to create a logger with an already existing name, it returns an instance of the unique logger with input name.    
        Only in this case, if it is given also a custom path it is ignored in order to not split the logs into different files
        
        ```python
        logger = get_logger('unique_name')
        logger1 = get_logger('unique_name')
        
        print(logger1 == logger)
        print(hash(logger))
        print(hash(logger1))
        ```
        
        The equality of the two loggers can be verified by printing the result of the equality of the two objects, or printing the hash of each object.
        
        The complete the in the linkes [example](https://github.com/mett96/loggerpy/tree/master/examples/logger_recovery.py)
        
        
        ## Versions
        - 1.0 : first release
        
        ## NextRelease
        - [ ] custom _format_ for timestamp
        - [ ] custom _format_ for all log
        - [ ] custom _color_ for each level
        - [ ] inherit the _domain_ from another logger
        
        <!-- ## Authors -->
        
        ## License
        This project is under the GPL-3.0 license - see the [LICENSE.md](LICENSE.md) file for more details
        
Keywords: logger log logging simple pylogger py-logger loggerpy logger-py simplelogger
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Operating System :: OS Independent
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Information Technology
Classifier: Topic :: Software Development :: Bug Tracking
Classifier: Topic :: Software Development :: Build Tools
Description-Content-Type: text/markdown
