Decorator for logging function arguments by human-readable way
Project description
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
pretty_str
PrettyFormat
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():
passis equal to:
@logwrap.logwrap
def foo():
passGet decorator for use without parameters:
get_logs = logwap.logwrap() # set required parameters via arguments
@get_logs
def foo():
passLimitations: * return value from awaitable objects (async def(…) is not accessible - on call asyncio object is returned.
nested wrapping (@logwrap @deco2 …) is not parsed under python 2.7: funcsigs limitation. Please set logwrap as the first level decorator.
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
indent_step=4, # step between indents
py2_str=False, # use bytes for python 2 __repr__ and __str__
)Limitation: Dict like objects is always marked inside {} for readability, even if it is collections.OrderedDict (standard repr as list of tuples).
pretty_str
This is specified helper for making human-readable repr on complex objects. Signature is self-documenting:
def pretty_str(
src, # object for __str__
indent=0, # start indent
no_indent_start=False, # do not indent the first level
max_indent=20, # maximum allowed indent level
indent_step=4, # step between indents
py2_str=False, # use bytes for python 2 __repr__ and __str__
)- Limitations:
Dict like objects is always marked inside {} for readability, even if it is collections.OrderedDict (standard repr as list of tuples). Iterable types is not declared, only brackets is used. String and bytes looks the same (its __str__, not __repr__).
PrettyFormat
PrettyFormat is the main formatting implementation class. on pretty_repr instance of this class is created and executed. Object signature:
def __init__(
self,
simple_formatters, # Will be used to repr not complex. Keys is data types and 'default'.
complex_formatters, # Currently only legacy pretty_repr formatters is supported, will be extended in the future
keyword='repr', # Currently 'repr' is supported, will be extended in the future
max_indent=20, # maximum allowed indent level
indent_step=4, # step between indents
py2_str=False, # use bytes for python 2 __repr__ and __str__
)Callable object (PrettyFormat instance) signature:
def __call__(
self,
src, # object for repr
indent=0, # start indent
no_indent_start=False # do not indent the first level
)Adopting your code
pretty_repr behavior could be overridden for your classes by implementing specific magic method:
def __pretty_repr__(
self,
parser # PrettyFormat class instance,
indent # start indent,
no_indent_start # do not indent the first level
):
return ...This method will be executed instead of __repr__ on your object.
Testing
The main test mechanism for the package logwrap is using tox. Test environments available:
pep8 py27 py34 py35 pypy pylint docs
CI systems
For code checking several CI systems is used in parallel:
Travis CI: is used for checking: PEP8, pylint, bandit, installation possibility and unit tests. Also it’s publishes coverage on coveralls.
coveralls: is used for coverage display.
CD system
Travis CI: is used for package delivery on PyPI.
