Source code for runtimedocs.core

import os
import sys
import time
import inspect
from functools import wraps, partial
import logging
import platform

    from collections import ChainMap

    signature_func = inspect.signature
except ImportError:
    from chainmap import ChainMap
    from funcsigs import signature

    signature_func = lambda x: str(signature(x))

from runtimedocs import helpers
from runtimedocs.helpers import get_type

HOSTNAME = platform.node()

[docs]def runtimedocs(force_enable_runtimedocs=False, verbosity=0, timing_info=True, default_type_parser=helpers.default_type_parser, max_stringify=1000, prefix_module_name_to_logger_name=True, custom_logger_name=None, extra_logger_handlers=None, common_types_parsers_dict=helpers.common_types_parsers_dict, custom_types_parsers_dict=None ): ''' runtimedocs decorator helps you understand how your code behaves at runtime. It provides detailed information about: - what was the expected signature of a function/class. - what was the actual signature used when calling that function/class at run time. - where was the function/class declared in and called from. - what's the hostname of the machine running the code. - what are the types, names, values of the input parameters and returned values of that function. - when relevant also add specific information like their : len, signature, inheritance_tree, etc ... - what were the positional/key-word arguments at call time. - has the function exited successfully or ran into an exception. - how long it took to run in case of success. - display what was the exception otherwise and raises it back to not side-effect your program. All these information are saved in a file usually named as follows: module_name.function_name.rundimedocs.log Additionally they can be printed on the terminal if the verbosity level is set to 1. You can easily toggle the runtimedocs decorator off by setting the env variable DISABLE_RUNTIMEDOCS to True. Parameters ---------- force_enable_runtimedocs: bool | DEFAULT = False In case the environment variable DISABLE_RUNTIMEDOCS is set to True, setting this flag to True allows you to activate the decorator for a specific function/class. verbosity: int | DEFAULT = 0 When set to 0, it means the runtimedocs information won't be printed on the terminal This allows you to still see your usual printed messages easily. When set to a value > 0, it means rundimedocs will also print on the terminal what its been saved in the runtimedocs log file of the decorated function. timing_info: bool | DEFAULT = True True, means you want to keep track and log the time at which the decorated function was called default_type_parser: function | DEFAULT = runtimedocs.helpers.default_type_parser default way to parse the input parameters and returned values. This will take as input for instance one the arguments been passed in to the decorated function and return an OrderDict with keys: type, value. But also len and keys when relevant. max_stringify: int | DEFAULT = 1000 this value is used by the default_type_parser function to chunk the length of the string returned by repr of the arg been parsed. ie: value_of_arg_been_parsed = repr(arg_been_parsed)[:max_stringify] prefix_module_name_to_logger_name: bool | DEFAULT = True True, means that runtimedocs decorator will save the information for a specific function/class been decorated in a file called: current_module_name.decorated_function_name.rundimedocs.log if False that file is called: decorated_function_name.rundimedocs.log custom_logger_name: str | DEFAULT = None if a string is specified, this will be the name of the logger and runtimedocs will save information in a file called: custom_logger_name.runtimedocs.log no matter what's the value of prefix_module_name_to_logger_name extra_logger_handlers: list | DEFAULT = None runtimedocs decorator uses the builting logging module to create log information. So this argument allows you to specify additional [file]handlers to where to save the runtime information being extracted. This could be useful for example to centralized all the logged info in a single file or group of files since by default every function in every module has its own log file. Note that, this allows you to add additional handlers, not overrides the default one. Also each handler of the list could be a string or a custom instance of logging.FileHandler() common_types_parsers_dict: dict | DEFAULT = helpers.common_types_parsers_dict this parameter allows you to bypass the default_type_parser for certain specific builtin python types it is a dictionary with keys representing the type as str and the parsing functions as values. If the runtimedocs_types_parsers plugin is installed then additional parsers for third-parties types are available and will bypass the default_type_parser. For instance if the plugin is installed, new parsers are avalaible for numpy, scipy, pandas enabling runtimedocs to print even more relevant information like: shape, dim, mean, std, etc ... custom_types_parsers_dict: dict | DEFAULT = None similarly to common_types_parsers_dict but for your own custom types. For instance if your program makes uses of a objects from a class you want to parse in a given way then do: custom_types_parsers_dict = {"<class 'MyClassName'>" : my_class_parser_func } where my_class_parser_func returns an OrderDict with keys like: type, value, my_size, etc... Another use of it, is if you want to parse nested lists, the default_type_parser can do that but by overriding the parsing function for the type: "<class'list'>" you have more control on how \ you want to parse the nested lists. Returns ------- wrapper: function the decorated function/class. ''' extra_logger_handlers = extra_logger_handlers if extra_logger_handlers else [] custom_types_parsers_dict = custom_types_parsers_dict if custom_types_parsers_dict else {} # when looking for a parser to parse a value first look at the custom parsers provided by the user of the package # if not found then search in the common types parsers provided natively by the package # or the runtimedocs-typesparsers plugin # if the type is not found there too then we use the default parser. types_parsers = ChainMap(custom_types_parsers_dict, common_types_parsers_dict) def parse_arg(arg): parse_func = types_parsers.get(get_type(arg), partial(default_type_parser, max_stringify=max_stringify)) return parse_func(arg) def print_arg(arg, logger): for key, val in parse_arg(arg).items():'\t {key} = {val}'.format(key=key, val=val))'-' * 5) def decorate(func): # if the DISABLE_RUNTIMEDOCS env var is True AND the force_enable_runtimedocs flag is False then return the # original non-decorated function. if bool(os.environ.get('DISABLE_RUNTIMEDOCS', False)) and not force_enable_runtimedocs: return func if not custom_logger_name or not isinstance(custom_logger_name, str): if prefix_module_name_to_logger_name: logger_name = '{module_name}.{func_name}'.format(module_name=__name__, func_name=func.__name__) else: logger_name = '{func_name}'.format(func_name=func.__name__) else: logger_name = custom_logger_name logger = logging.getLogger(logger_name) logger.setLevel(logging.INFO) if timing_info: formatter = logging.Formatter('%(asctime)s: #%(message)s') else: formatter = logging.Formatter('#%(message)s') if verbosity > 0: stream_handler = logging.StreamHandler(sys.stdout) stream_handler.setFormatter(formatter) logger.addHandler(stream_handler) file_handler = logging.FileHandler('{}.runtimedocs.log'.format(logger_name)) file_handler.setLevel(logging.INFO) file_handler.setFormatter(formatter) logger.addHandler(file_handler) for handler in extra_logger_handlers: if isinstance(handler, str): file_handler = logging.FileHandler(handler) file_handler.setLevel(logging.INFO) file_handler.setFormatter(formatter) logger.addHandler(file_handler) else: logger.addHandler(handler) @wraps(func) def wrapper(*args, **kwargs):'#' * 100)'calling [{}] declared inside module [{}]'.format(func.__name__, func.__module__))'caller name: [{}]'.format(helpers.caller_name()))'ran inside: hostname=[{}]'.format(HOSTNAME))'-' * 100) # getting the signature information args_types = [get_type(el) for el in args] kwargs_types = [(str(k), get_type(v)) for k, v in kwargs.items()] all_args_str = ', '.join(args_types + ['{}={}'.format(k, v) for k, v in kwargs_types])'declared signature = {func_name}{signature}'.format( func_name=func.__name__, signature=signature_func(func) ))'called signature = {func_name}({all_args_str})'.format( func_name=func.__name__, all_args_str=all_args_str ))'-' * 100) # get details info about the function paramters n_args = len(args) n_kwargs = len(kwargs)'Number of positional paramters: {}'.format(n_args)) for i, arg in enumerate(args):'\t#{}:'.format(i)) print_arg(arg, logger)'Number of key word paramters: {}'.format(n_kwargs)) for i, (arg_name, arg) in enumerate(kwargs.items()):'\t{}:'.format(arg_name)) print_arg(arg, logger)'-' * 100) # get details about the return values or the eventual exception raised try: tic = time.time() res = func(*args, **kwargs) tac = time.time() except Exception as e: logger.error('!!!EXCEPTION!!! [{}] ran into an exception before exiting:'.format(func.__name__)) logger.error('\n') logger.error(e, exc_info=True) raise e else:'[{}] ran successfully in [{}]seconds and its returned value has these specs:'.format( func.__name__, str(round(tac - tic, 4)) ) ) if isinstance(res, tuple):'returned value is a tuple and could be a multi output return statement:') for i, el in enumerate(res):'\t#{}:'.format(i)) print_arg(el, logger) else:'single output return statement:') print_arg(res, logger) return res return wrapper return decorate
# if __name__ == '__main__': # @runtimedocs(verbosity=1, timing_info=False) # def myadd(a, b, f=sum, not_used=None): # return f([a, b]) # # # myadd(1, 2, f=sum)