Metadata-Version: 1.1
Name: log-calls
Version: 0.2.1
Summary: Debugging and profiling decorator that logs caller name(s), args+values, execution time, and more. Eliminates reams of boilerplate code.
Home-page: http://github.com/Twangist/log_calls
Author: Brian O'Neill
Author-email: twangist@gmail.com
License: MIT
Description: 
        `log_calls` is a Python 3 decorator that can print much useful information
        about calls to a decorated function. It can write to `stdout`, to another
        stream, or to a logger. It can save you from writing, rewriting, copying,
        pasting and tweaking a lot of ad hoc, boilerplate code - and it can keep
        your codebase free of that clutter.
        
        For each call of a decorated function, `log_calls` can show you:
        
        * the caller,
        * the arguments passed to the function, and any default values used,
        * the time the function took to execute,
        * the complete call chain back to another `log_calls`-decorated caller,
        * the number of the call,
        * indentation by call level,
        * the function's return value,
        * and more!
        
        These and other features are optional and configurable settings, which
        can be specified for each decorated function via keyword parameters.
        You can also dynamically get and set these settings using attributes
        with the same names as the keywords, or using a dict-like interface
        whose keys are the keywords.
        
        `log_calls`` can also collect profiling data and statistics, accessible dynamically:
        
        * number of calls to a function,
        * total time taken by the function,
        * the function's entire call history (arguments, time elapsed, return values,
          callers, and more), optionally as text in CSV format.
        
        These features and others are optional and configurable settings,
        which can be specified for each decorated function via keyword parameters of
        the decorator. You can also dynamically get and set these settings using attributes
        with the same names as the keywords, or using a dict-like interface whose keys
        are the keywords. In fact, through a mechanism of "indirect parameter values",
        with just a modest amount of cooperation between decorated functions a calling
        function can ensure uniform settings for all log_calls-decorated functions in
        call chains beneath it.
        
        The package contains another decorator, `record_history`, a stripped-down version
        of `log_calls` which only collects call history and statistics, and outputs no messages.
        
        NOTE: This package requires the CPython implementation, as it makes assumptions
        about stack frame internals which may not be valid in other interpreters.
        
        See docs/log_calls.md for details, usage info and examples.
        
Keywords: decorator debugging profiling logging function call caller stack recursion teaching
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Intended Audience :: Developers
Classifier: Operating System :: OS Independent
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Code Generators
Classifier: Topic :: Utilities
Classifier: Topic :: System :: Logging
