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omni:us python logging package

Project description

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reconplogger - omni:us python logger

This repository contains the code of reconplogger, a python package to ease the standardization of logging within omni:us. The main design decision of reconplogger is to allow total freedom to reconfigure loggers without hard coding anything.

The package contains essentially three things:

  • A default logging configuration.
  • A function for loading logging configuration for regular python code.
  • A function for loading logging configuration for flask-based microservices.
  • Lower level functions for:
    • Loading logging configuration from any of: config file, environment variable, or default.
    • Replacing the handlers of an existing Logger object.

How to use

There are two main use cases reconplogger targets. One is for logging in regular generic python code and the second one is logging in microservices. See the two standardizing sections below for a detailed explanation of the two use cases.

Add as requirement

The first step to use reconplogger is adding it as a requirement in the respective package where it will be used. This means adding it in the file setup.cfg as an item in install_requires or in an extras_require depending on whether reconplogger is intended to be a core or an optional requirement.

Note: It is highly discouraged to develop packages in which requirements are added directly to setup.py or to have an ambiguous requirements.txt file. See the setup.cfg file in the reconplogger source code for reference.

Default logging configuration

An feature that reconplogger provides is the possibility of externally setting the logging configuration without having to change code or implement any parsing of configuration. However, if a logging configuration is not given externally, reconplogger provide a default configuration.

The default configuration defines three handlers, two of which are stream handlers and are set to DEBUG log level. The first handler called plain_handler uses a simple plain text formatter, and the second handler called json_handler as the name suggests outputs in json format, using the logmatic JsonFormatter class. The third handler called null_handler is useful to disable all logging.

For each handler the default configuration defines a corresponding logger: plain_logger, json_logger and null_logger.

Standardizing logging in regular python

One objective of reconplogger is to ease the use of logging and standardize the way it is done across all omni:us python code. The use of reconplogger comes down to calling one function to get the logger object. For regular python code (i.e. not a microservice) the function to use is reconplogger.logger_setup. To this function you give as argument two strings, which are names of environment variables, one for the logging configuration and the other for the name of the logger to use. The following code snippet illustrates the use:

import reconplogger

...

logger = reconplogger.logger_setup('LOGGER_CFG', 'LOGGER_NAME')

...

logger.info('My log message')

If the environment variables are not set, this function returns the plain_logger logger from the default configuration. Note that the environment variable names are not required to be LOGGER_CFG, LOGGER_NAME. These can be chosen by the user for each particular application.

For functions or classes that receive logger object as an argument, it might be desired to set a default logger so that it can be called without specifying one. To have as default a null logger, the reconplogger module could be used as follows:

from reconplogger import null_logger

...

def my_func(arg1, arg2, logger=null_logger):

...

Standardizing logging in flask-based microservices

The most important objective of reconplogger is to allow standardization of a structured logging format for all microservices developed. Thus, the logging from all microservices should be configured like explained here. The use is analogous to the previous case, but using the function reconplogger.flask_app_logger_setup instead, and giving as a third argument the flask app object. Additional to the previous case, this function replaces the flask app and werkzeug loggers to use a reconplogger configured one. The usage would be as follows:

import reconplogger
from flask import Flask

...

app = Flask(__name__)

...

logger = reconplogger.flask_app_logger_setup('LOGGER_CFG', 'LOGGER_NAME', app)

## NOTE: do not change logger beyond this point!

...

## Use logger in code
myclass = MyClass(..., logger=logger)

...

An important note is that after configuring the logger, the code should not modify the logger configuration. For example, the logging level should not be modified, or only modified by providing a non-default option. Adding an additional handler to the logger is not a problem. This could be desired for example to also log to a file.

In the helm values.yaml file of the microservice, the default values for the environment variables should be set as:

LOGGER_CFG: reconplogger_default
LOGGER_NAME: json_logger

With the json_logger logger, the format of the logs should look something like the following:

{"asctime": "2018-09-05 17:38:38,137", "levelname": "INFO", "filename": "test_formatter.py", "lineno": 5, "message": "Hello world"}
{"asctime": "2018-09-05 17:38:38,137", "levelname": "DEBUG", "filename": "test_formatter.py", "lineno": 9, "message": "Hello world"}
{"asctime": "2018-09-05 17:38:38,137", "levelname": "ERROR", "filename": "test_formatter.py", "lineno": 13, "message": "Hello world"}
{"asctime": "2018-09-05 17:38:38,137", "levelname": "CRITICAL", "filename": "test_formatter.py", "lineno": 17, "message": "Hello world"}
{"asctime": "2018-09-05 17:38:38,137", "levelname": "ERROR", "filename": "test_formatter.py", "lineno": 25, "message": "division by zero"}
{"asctime": "2018-09-05 17:38:38,138", "levelname": "ERROR", "filename": "test_formatter.py", "lineno": 33, "message": "Exception has occured", "exc_info": "Traceback (most recent call last):\n  File \"reconplogger/tests/test_formatter.py\", line 31, in test_exception_with_trace\n    b = 100 / 0\nZeroDivisionError: division by zero"}
{"asctime": "2018-09-05 17:38:38,138", "levelname": "INFO", "filename": "test_formatter.py", "lineno": 37, "message": "Hello world", "context check": "check"}

Use of the logger object

The logger objects returned by the setup functions are normal python logging.Logger objects, so all the standard logging functionalities should be used. Please refer to the logging package documentation for details.

A couple of logging features that should be very commonly used are the following. To add additional structured information to a log, the extra argument should be used. A simple example could be:

logger.info('Successfully processed document', extra={'uuid': uuid})

When an exception occurs the exc_info=True argument should be used, for example:

try:
    ...
except:
    logger.critical('Failed to run task', exc_info=True)

Adding a file handler

In some circumstances it is desired to add to a logger a file handler so that the logging messages are also saved to a file. This normally requires at least three lines of code, thus to simplify things reconplogger provides the reconplogger.add_file_handler function to do the same with a single line of code. The use is quite straightforward as:

reconplogger.add_file_handler(logger, '/path/to/log/file.log')

Overriding logging configuration

An important feature of reconplogger is that the logging configuration of apps that use it can be easily changed via the environment variables given to the logger setup functions. Using the same environment variables as the previous examples, the following could be done. First set the environment variables with the desired logging configuration and logger name:

export LOGGER_NAME="example_logger"

export LOGGER_CFG="{
    'version': 1,
    'formatters': {
        'verbose': {
            'format': '%(levelname)s %(asctime)s %(module)s %(process)d %(thread)d %(message)s'
        },
    },
    'handlers': {
        'console':{
            'level':'DEBUG',
            'class':'logging.StreamHandler',
            'formatter': 'verbose'
        },
    },
    'loggers': {
        'example_logger': {
            'handlers': ['console'],
            'level': 'ERROR',
        },
    }
}"

Then, in the python code the logger would be used as follows:

>>> import reconplogger
>>> logger = reconplogger.logger_setup('LOGGER_CFG', 'LOGGER_NAME')
>>> logger.error('My error message')
ERROR 2019-10-18 14:45:22,629 <stdin> 16876 139918773925696 My error message

Low level functions

Loading configuration

The reconplogger.load_config function allows loading of a python logging configuration. The loading of configuration can be from a file (giving its path), from an environment variable (giving the variable name), or loading the default configuration that comes with reconplogger. The loading from file and from environment variable expects the format to be yaml or json. See below examples of loading for each of the cases:

import reconplogger

## Load from config file
reconplogger.load_config('/path/to/config.yaml')

## Load from environment variable
reconplogger.load_config('LOGGER_CFG')

## Load default config
reconplogger.load_config('reconplogger_default')

Replacing logger handlers

In some cases it might be needed to replace the handlers of some already existing logger. For this reconplogger provides the reconplogger.replace_logger_handlers function. To use it, simply provide the logger in which to replace the handlers and the logger from where to get the handlers. Using the same environment variables as above, the procedure would be as follows:

import reconplogger

reconplogger.load_config('LOGGER_CFG')
reconplogger.replace_logger_handlers('some_logger_name', os.environ['LOGGER_NAME'])

Contributing

Contributions to this package are very welcome. When you intend to work with the source code, note that this project does not include a requirements.txt file. This is by intention. To make it very clear what are the requirements for different use cases, all the requirements of the project are stored in the file setup.cfg. The basic runtime requirements are defined in section [options] in the install_requires entry. All optional requirements are stored in section [options.extras_require]. There is a dev extras require to be used by developers (e.g. requirements to run the unit tests) and a bump extras require for the maintainer of the package.

The recommended way to work with the source code is the following. First clone the repository, then create a virtual environment, activate it and finally install the development requirements. More precisely the steps would be:

git clone https://github.com/omni-us/reconplogger.git
cd reconplogger
virtualenv -p python3 venv
. venv/bin/activate

The crucial step is installing the requirements which would be done by running:

pip3 install --editable .[dev,doc,test,all]

After changing the code, always run unit tests as follows:

./setup.py test

Pull requests

  • The master branch in bitbucket is blocked for pushing. Thus to contribute it is required to create and push to a new branch and issue a pull request.

  • On every push to any branch, the jenkins server will build the wheel package and run unit tests. The contributor should check the corresponding status to make sure everything runs successfully. The status of the jenkins jobs can also be seen in the bitbucket repo.

  • A pull request will only be accepted if:

    • All python files pass pylint checks.
    • All unit tests run successfully.
    • New code has docstrings and gets included in the html documentation.
    • Jenkins job is successful.
  • When developing, after cloning be sure to run the githook-pre-commit to setup the pre-commit hook. This will help you by automatically running pylint before every commit.

Using bump version

Only the maintainer of this repo should bump versions and this should be done only on the master branch. To bump the version it is required to use the bumpversion that should already be installed if pip3 install --editable .[dev,doc,test,all] was run as previously instructed.

bumpversion major/minor/path

Push the tags to the repository as well

git push; git push --tags

When the version tags are pushed, jenkins will automatically build the wheel file, test it and if successful, push the package to the pypi server.

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