logwrap 1.0.0

Decorator for logging function arguments by human-readable way

logwrap

logwrap is a helper for logging in human-readable format function arguments and call result on function call.

Pros:

• Free software: Apache license

• Open Source: https://github.com/penguinolog/logwrap

• PyPI packaged: https://pypi.python.org/pypi/logwrap

• Self-documented code: docstrings with types in comments

• Tested: see bages on top

• Support miltiple Python versions:

Python 2.7
Python 3.4
Python 3.5
Python 3.6
PyPy

This package also includes helpers:

• pretty_repr

Usage

logwrap

The main decorator. Could be used as not argumented (@logwrap.logwrap) and argumented (@logwrap.logwrap()). Not argumented usage simple calls with default values for all positions. Argumented usage with arguments from signature:

@logwrap.logwrap(
    log=logging.getLogger(__name__),  # __name__ = 'logwrap'
    log_level=logging.DEBUG,
    exc_level=logging.ERROR,
    max_indent=20,  # forwarded to the pretty_repr
    spec=None,  # use target callable function for spec
)

Usage examples:

@logwrap.logwrap()
def foo():
    pass

is equal to:

@logwrap.logwrap
def foo():
    pass

Get decorator for use without parameters:

get_logs = logwap.logwrap()  # set required parameters via arguments

@get_logs
def foo():
    pass

pretty_repr

This is specified helper for making human-readable repr on complex objects. Signature is self-documenting:

def pretty_repr(
    src,  # object for repr
    indent=0,  # start indent
    no_indent_start=False,  # do not indent the first level
    max_indent=20,  # maximum allowed indent level
)

Limitation: Dict like objects is always marked inside {} for readability, even if it is collections.OrderedDict (standard repr as list of tuples).

Testing

The main test mechanism for the package logwrap is using tox. Test environments available:

pep8
py27
py34
py35
pypy
pylint
docs

Also possible to run python setup.py test for unit tests and python setup.py flake8 for code style tests, but it requires all package dependencies to be installed.

CI systems

For code checking several CI systems is used in parallel:

1. Travis CI: is used for checking: PEP8, installation possibility and unit tests

2. Circle CI: is used for checking: pylint, docs. In addition this CI publishes coverage results.

3. Codacy: is used for statical analysis and coverage display.

CD system

Travis CI: is used for package delivery on PyPI.