Source code for sosw.components.helpers

"""
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Static helper methods which you can use in any Lambdas.
Must be completely independent with no specific requirements.
"""

__all__ = ['validate_account_to_dashed',
           'validate_account_to_int',
           'validate_list_of_numbers_from_csv',
           'camel_case_to_underscore',
           'chunks',
           'validate_uuid4',
           'rstrip_all',
           'get_one_or_none_from_dict',
           'get_one_from_dict',
           'get_list_of_multiple_or_one_or_empty_from_dict',
           'validate_date_list_from_event_or_days_back',
           'validate_date_from_something',
           'validate_datetime_from_something',
           'validate_string_matches_datetime_format',
           'is_valid_date',
           'recursive_matches_soft',
           'recursive_matches_strict',
           'recursive_matches_extract',
           'dunder_to_dict',
           'nested_dict_from_keys',
           'convert_string_to_words',
           'construct_dates_from_event',
           'validate_list_of_words_from_csv_or_list',
           'first_or_none',
           'recursive_update',
           'trim_arn_to_name',
           'trim_arn_to_account',
           'make_hash',
           'to_bool'
           ]

import re
import collections
import uuid
import datetime
from datetime import timezone

from collections import defaultdict, Hashable
from copy import deepcopy
from typing import Iterable, Callable, Dict, Mapping, List, Optional


[docs]def validate_account_to_dashed(account): """ Validates the the provided string is in valid AdWords account format and converts it to dashed format. :param str account: AdWords Account :rtype: str :return: Dashed format """ account = str(account).strip() if re.match("[0-9]{3}-[0-9]{3}-[0-9]{4}", account): return account elif re.match("^[0-9]{10}$", account): return '-'.join([str(account)[0:3], str(account)[3:6], str(account)[6:]]) else: raise ValueError("Invalid account format provided: {}".format(account))
[docs]def validate_account_to_int(account): """ Validates the the provided string is in valid AdWords account format and converts it to integer format. :param (str, int) account: AdWords Account :return: Account ID as integer """ account = str(account).strip().replace('-', '') if re.match("^[0-9]{10}$", account): return int(account) else: raise ValueError("Invalid account format provided: {}".format(account))
[docs]def validate_list_of_numbers_from_csv(data): """ Converts a comma separated string of numeric values to a list of sorted unique integers. The values that do not match are skipped. :param (str, iterable) data: - str | iterable :return: - list(int) """ if isinstance(data, str): return [int(x.strip()) for x in data.split(',') if x.strip().isnumeric()] else: if isinstance(data, (int, float)): return [data] result = [] try: for x in data: if isinstance(x, (int, float)): result.append(int(x)) elif isinstance(x, str) and x.strip().isnumeric(): result.append(int(x.strip())) except TypeError: pass return result
[docs]def validate_uuid4(uuid_string): """ Validate that a UUID string is in fact a valid uuid4. Happily, the uuid module does the actual checking for us. It is vital that the 'version' kwarg be passed to the UUID() call, otherwise any 32-character hex string is considered valid. """ try: val = uuid.UUID(uuid_string, version=4) except ValueError: # If it's a value error, then the string # is not a valid hex code for a UUID. return False
# If the uuid_string is a valid hex code, # but an invalid uuid4, # the UUID.__init__ will convert it to a # valid uuid4. This is bad for validation purposes.
[docs]def camel_case_to_underscore(name): """ Converts attribute to string and formats it as underscored. :param name: - str - CamelCase string (or something convertable to CamelCase with __str__() method. :return: - str - underscore_formatted_value """ s1 = re.sub('(.)([A-Z][a-z]+)', r'\1_\2', str(name)) return re.sub('([a-z0-9])([A-Z])', r'\1_\2', s1).lower()
[docs]def chunks(l, n): """Yield successive n-sized chunks from l.""" for i in range(0, len(l), n): yield l[i:i + n]
[docs]def rstrip_all(input, patterns): """ Strips all of the patterns from the right of the input. Order and spaces do not matter. :param input: - str - String to modify :param patterns: - list|set|tuple|str - Pattern[-s] to remove. :return: - str """ if isinstance(patterns, str): regex = re.compile("({}$)".format(re.escape(patterns))) else: regex = re.compile("({}$)".format("$|".join(map(re.escape, patterns)))) if isinstance(patterns, str): patterns = [patterns] if not isinstance(patterns, (list, set, tuple)) or not all(isinstance(x, str) for x in patterns): raise ValueError("Patterns for rstrip_all() are supposed to be string or iterable of strings") rabbit = input.strip() r = regex.sub('', rabbit) if not r == rabbit: # Go recursive in case we stripped smth in this iteration. return rstrip_all(r, patterns) else: # If nothing left to change, return the rabbit. return rabbit
[docs]def get_one_or_none_from_dict(input, name, vtype=None): """ Extracts object by 'name' from the 'input'. Tries also plural name in case not found by single 'name'. In case found an iterable by plural name, validates that it has one or zero values in it. If vtype is specified, tries to convert result to it. :param dict input: Input dictionary. Event of Lambda for example. :param str name: Name of attribute (in singular form). :param type vtype: Type to be converted to. Must be callable. Tested types: str, int, float :return: - instance of vtype | something else | None :raises ValueError: In all cases something is wrong. """ if not isinstance(input, dict): raise ValueError("'input' attribute must be a dict. Received: {}".format(type(input))) if not isinstance(name, str): raise ValueError("'name' attribute must be a str. Received: {}".format(type(name))) def convert(obj, t): return obj if not t else t(obj) # Best case scenario. :) result = input.get(name) if result: return convert(result, vtype) # if not result, try to search for plural results = input.get(name + 's') if not results: return None # If we found some results with plural name, we make sure it is iterable and has one or zero value. if isinstance(results, (list, tuple, set)): if len(results) > 1: raise ValueError("More than one {}s found in input.".format(name)) else: return convert(results[0], vtype) elif results: raise ValueError("Some not-iterable '{}s' found in input: {}".format(name, str(type(result))))
[docs]def get_one_from_dict(input, name, vtype=None): """ Extracts object by 'name' from the 'input'. Tries also plural name in case not found by single 'name'. In case found an iterable by plural name, validates that it has exactly one value in it. If vtype is specified, tries to convert result to it. :param input: - dict - Input dictionary. Event of Lambda for example. :param name: - str - Name of attribute (in singular form). :param vtype: - type - Type to be converted to. Must be callable. Tested types: str, int, float :return: - instance of vtype | something else | None :raises ValueError: - In all cases something is wrong. """ result = get_one_or_none_from_dict(input, name, vtype) if result: return result else: raise ValueError("Did not find any value {} in the input {}".format(name, input))
[docs]def get_list_of_multiple_or_one_or_empty_from_dict(input, name, vtype=None): """ Extracts objects by 'name' from the 'input' and returns as a list. Tries both plural and singular names from the input. If vtype is specified, tries to convert each of the elements in the result to this type. :param input: - dict - Input dictionary. Event of Lambda for example. :param name: - str - Name of attribute (in plural form). :param vtype: - type - Type to be converted to. Must be callable. Tested types: str, int, float :return: - list - List of vtypes, or list of whatever was in input, or empty list. :raises ValueError: In all cases something is wrong. """ if not isinstance(input, dict): raise ValueError("'input' attribute must be a dict. Received: {}".format(type(input))) if not isinstance(name, str): raise ValueError("'name' attribute must be a str. Received: {}".format(type(name))) def convert(obj, t): return obj if not t else t(obj) results = input.get(name) or input.get(name.rstrip('s')) if not results: return [] # Wrap to list if not there yet. if not isinstance(results, (list, tuple, set)): results = [results] else: results = list(results) # Apply vtype convertion if required. return [convert(x, vtype) for x in results]
[docs]def validate_date_list_from_event_or_days_back(input, days_back=0, key_name='date_list'): """ Takes from input the date_list and extracts date_list. Validates and converts to datetime.date. Input should have date_list as list of strings or comma-separated string. * Format: ``YYYY-MM-DD`` * Examples: .. code-block:: python ['2018-01-01', '2018-02-01'] '2018-01-01, 2018-02-01' :param dict input: This is supposed to be your whole Lambda event. :param int days_back: Optional Number of days to take back from today. Ex: days_back=1 is yesterday. Default: today. :param str key_name: Optional custom name of key to extract from 'input'. :return: list(datetime.date) """ date_list = input.get(key_name, '') if not date_list: return [datetime.date.today() - datetime.timedelta(days=days_back)] if not isinstance(date_list, (list, set, tuple)): date_list = str(date_list).split(',') return [datetime.datetime.strptime(x.strip(), '%Y-%m-%d').date() for x in date_list]
[docs]def validate_datetime_from_something(d): """ Converts the input `d` to datetime.datetime. :param d: Some input. Supported types: * datetime.datetime * datetime.date * int - Epoch or Epoch milliseconds * float - Epoch or Epoch milliseconds * str (YYYY-MM-DD) * str (YYYY-MM-DD HH:MM:SS) :return: Transformed `d` :rtype: datetime.datetime :raises: ValueError """ mutators = [ (datetime.datetime, lambda x: x), (datetime.date, lambda x: datetime.datetime.combine(x, datetime.datetime.min.time())), ((int, float), lambda x: datetime.datetime.fromtimestamp(x) if x < datetime.datetime(datetime.MAXYEAR, 12, 31).timestamp() else datetime.datetime.fromtimestamp(x / 1000, tz=timezone.utc)), (str, lambda x: datetime.datetime.strptime(d, '%Y-%m-%d') if len(d) == 10 else datetime.datetime.strptime(d[:19], '%Y-%m-%d %H:%M:%S')) ] for mutator in mutators: if isinstance(d, mutator[0]): return mutator[1](d) raise ValueError("Some unconvertable type for datetime validation: {}".format(d))
[docs]def validate_date_from_something(d): """ Convert valid input to datetime.date() or raise either AttributeError or ValueError. :param d: Some input. Supported types: * datetime.datetime * datetime.date * int - Epoch or Epoch milliseconds * float - Epoch or Epoch milliseconds * str (YYYY-MM-DD) * str (YYYY-MM-DD HH:MM:SS) :return: Transformed `d` :rtype: datetime.date :raises: ValueError """ return validate_datetime_from_something(d).date()
[docs]def validate_string_matches_datetime_format(date_str, date_format, field_name='date'): """ Validate string, make sure it's of the given datetime format :param str date_str: a date or time or both, Example: '2018/09/16' :param str date_format: datetime format, that is acceptable for datetime.strptime. Example: '%Y/%m/%d' (https://docs.python.org/3.6/library/datetime.html#strftime-and-strptime-behavior) :param str field_name: name of the field (for the error) :raises: ValueError """ if not (date_str and isinstance(date_str, str)): raise ValueError(f"Bad input for {field_name} ({date_str}), must be a string") if not (date_format and isinstance(date_format, str)): raise ValueError(f"Bad input for format ({date_format}), must be a string") try: datetime.datetime.strptime(date_str, date_format) except ValueError: raise ValueError(f"Incorrect format of {field_name} ({date_str}), should be {date_format}")
[docs]def is_valid_date(date_str, date_formats): """ Validate string to be at least one of the given datetime formats. :param str date_str: a date or time or both, Example: '2018/09/16' :param list date_formats: List of datetime format, that is acceptable for datetime.strptime. Example: '%Y/%m/%d' :rtype: bool :return: True if the date string is valid for any of the datetime formats, False otherwise. """ for date_format in date_formats: try: validate_string_matches_datetime_format(date_str, date_format) return True except ValueError as err: continue return False
[docs]def recursive_matches_soft(src, key, val, **kwargs): """ Searches the 'src' recursively for nested elements provided in 'key' with dot notation. In case some levels are iterable (list, tuple) it checks every element. In case the full path is inaccessible returns False. If any of the elements addressed by 'key' matches the 'val' - Bingo! Return True. You might also be interested in recursive_exists_strict() helper. :param dict src: Input dictionary. Can contain nested dictionaries and lists. :param str key: Path to search with dot notation. :param any val: Value to match in some elements specified by path. In order to check not just that some element exists, but to check for duplicates, you might want to use optional 'exclude' attributes. If attributes are specified and the last level element following the path (dot notation) will have a key-value, the check for the main key-value will be skipped. See unittests to understand the bahaviour better. :param str exclude_key: Key to check in last level element to exclude. :param srt exclude_val: Value to match in last level element to exclude. :rtype: bool """ if any([x in kwargs for x in ['exclude_key', 'exclude_val']]) \ and not all([x in kwargs for x in ['exclude_key', 'exclude_val']]): raise AttributeError("If you use 'exclude' attributes you must specify both 'exclude_key' and 'exclude_val'") path_elements = key.split('.') # logging.debug("Invoked func: ", src, key, path_elements) # if src is iterable: iterate recursively if isinstance(src, (list, tuple)): return any(recursive_matches_soft(element, key, val, **kwargs) for element in src) # We should try to dig deeper. elif len(path_elements) > 1: try: if recursive_matches_soft(src[path_elements[0]], '.'.join(path_elements[1:]), val, **kwargs): return True except KeyError: pass # Last level of digging elif len(path_elements) == 1: try: if kwargs.get('exclude_key') and src[kwargs['exclude_key']] == kwargs['exclude_val']: # logging.debug("Skipping element because it matches exclude parameters.") return False except KeyError: pass # There is a chance that the exclude key is simply missing. We ignore it then. try: return src[key] == val except (KeyError, TypeError): pass else: raise RuntimeError("Your function is stupid") # If nothing found we return False return False
[docs]def recursive_matches_strict(src, key, val, **kwargs): """ Searches the 'input' recursively for nested elements provided in 'key' with dot notation. In case some levels are iterable (list, tuple) it checks every element. In case the full path is inaccessible raises AttributeError or KeyError. :param dict src: Input dictionary. Can contain nested dictionaries and lists. :param str key: Path to search with dot notation. :param any val: Value to match in some elements specified by path. :rtype: bool """ if any([x in kwargs for x in ['exclude_key', 'exclude_val']]) \ and not all([x in kwargs for x in ['exclude_key', 'exclude_val']]): raise AttributeError("If you use 'exclude' attributes you must specify both 'exclude_key' and 'exclude_val'") path_elements = key.split('.') # if src is iterable: iterate if isinstance(src, (list, tuple)): return any(recursive_matches_strict(x, key, val, **kwargs) for x in src) elif len(path_elements) > 1: return recursive_matches_strict(src[path_elements[0]], '.'.join(path_elements[1:]), val, **kwargs) elif len(path_elements) == 1: try: if kwargs.get('exclude_key') and src[kwargs['exclude_key']] == kwargs['exclude_val']: # logging.debug("Skipping element because it matches exclude parameters.") return False except KeyError: pass # There is a chance that the exclude key is simply missing. We ignore it then. return src[key] == val else: raise RuntimeError("Your function is stupid", src, key, val)
[docs]def recursive_matches_extract(src, key, separator=None, **kwargs): """ Searches the 'src' recursively for nested elements provided in 'key' with dot notation. In case some levels are iterable (list, tuple) it checks every element in it till finds it. Returns the first found element or None. In case the full path is inaccessible also returns None. If you are just checking if some elements exist, you might be interested in recursive_exists_strict() or recursive_exists_soft() helpers. .. :warninig: Please be aware that this method doesn't not check for duplicates in iterable elements on neither level during extraction. :param dict src: Input dictionary. Can contain nested dictionaries and lists. :param str key: Path to search with dot notation. :param str separator: Custom separator for recursive extraction. Default: `'.'` In order to filter out some specific elements, you might want to use the optional 'exclude' attributes. If attributes are specified and the last level element following the path (dot notation) will have a key-value, the check for the main key-value will be skipped. See unittests to understand the bahaviour better. :param str exclude_key: Key to check in last level element to exclude. :param str exclude_val: Value to match in last level element to exclude. :return: Value from structure extracted by specified path """ if any([x in kwargs for x in ['exclude_key', 'exclude_val']]) \ and not all([x in kwargs for x in ['exclude_key', 'exclude_val']]): raise AttributeError("If you use 'exclude' attributes you must specify both 'exclude_key' and 'exclude_val'") if not separator: separator = '.' else: assert isinstance(separator, str), "Separator must be a string." path_elements = key.split(separator) # logging.debug("Invoked func: ", src, key, path_elements) # if src is iterable: iterate recursively if isinstance(src, (list, tuple)): for element in src: v = recursive_matches_extract(element, key, separator=separator, **kwargs) if v: return v # We should try to dig deeper. elif len(path_elements) > 1: try: return recursive_matches_extract(src[path_elements[0]], separator.join(path_elements[1:]), **kwargs) except KeyError: pass # Last level of digging elif len(path_elements) == 1: try: if kwargs.get('exclude_key') and src[kwargs['exclude_key']] == kwargs['exclude_val']: # logging.debug("Skipping element because it matches exclude parameters.") return None except KeyError: pass # There is a chance that the exclude key is simply missing. We ignore it then. return src.get(key) else: raise RuntimeError("Your function is stupid") # If nothing found we return False return None
[docs]def dunder_to_dict(data: dict, separator=None): """ Converts the flat dict with keys using dunder notation for nesting elements to regular nested dictionary. E.g.: .. code-block:: python data = {'a': 'v1', 'b__c': 'v2', 'b__d__e': 'v3'} result = dunder_to_dict(data) # result: { 'a': 'v1', 'b': { 'c': 'v2', 'd': {'e': 'v3'} } } :param data: A dictionary that is converted to Nested. :param str separator: Custom separator for recursive extraction. Default: `'.'` """ if not separator: separator = '__' else: if not isinstance(separator, str): raise TypeError(f"Separator must be a string.") result = defaultdict(dict) for k, v in data.items(): if separator not in k: # Just set the value if key is not separated result[k] = v else: if k.endswith(separator) or k.startswith(separator): raise ValueError(f"Your keys should not have {separator} on sides of keys. Only as separators: {k}") k_split = k.split(separator) main_key, nested_keys = k_split[0], k_split[1:] # Make sure that value is recursively parsed for separators as well. if isinstance(v, dict): v = dunder_to_dict(data=v, separator=separator) # Construct a nested dictionary embedding value to the deepest level. new_subdict = nested_dict_from_keys(nested_keys, value=v) # Just merge the new nested dictionary in the final result. result[main_key] = recursive_update(result[main_key], new_subdict) return dict(result)
[docs]def nested_dict_from_keys(keys: List, value: Optional = None) -> Dict: """ Constructs a nested dictionary using a list of keys to embed recursively. If `value` is provided it is assigned to the last subkey. Examples: .. code-block:: python nested_dict_from_keys(['a', 'b', 'c']) == {'a': {'b': {'c': None}}} nested_dict_from_keys(['a', 'b', 'c'], value=42) == {'a': {'b': {'c': 42}}} :param keys: List of keys to embed. :param value: Optional value to set to lowest level """ if len(keys) == 0: return value else: assert isinstance(keys[0], Hashable), f"Keys of dictionary must be hashable for nestify. Got: {type(keys[0])}" return {keys[0]: nested_dict_from_keys(keys[1:], value)}
[docs]def convert_string_to_words(string): """ Convert string to comma separated words. :param str string: String to convert into words. :rtype: str :return: Comma separated words. """ if not isinstance(string, str): raise TypeError(f"Input must be string, got {type(string)}") return re.sub('\s+', ',', string.lower().strip())
[docs]def construct_dates_from_event(event: dict) -> tuple: """ Processes given event dictionary for start and end points of time. Otherwise takes the default settings. The end date of the period may be specified as `en_date` in the event. The default value is today. Also the `event` should have either `st_date` or `days_back` numeric parameter. If provided the days_back it will be substracted from end date. Both `st_date` and `en_date` might be either `date`, `datetime` or `string` (`'YYYY-MM-DD'`) types. In case of `datetime`, the hours/minutes/etc are ignored. :param dict event: Lambda payload. :return: start_date, end_date as datetime.date """ en_date = validate_date_from_something(event.get('en_date', datetime.date.today())) st_date = event.get('st_date') days_back = event.get('days_back') if st_date and days_back: raise AttributeError(f"construct_dates_from_event() doesn't allow st_date and days_back simultaneously") if not st_date and not days_back: raise AttributeError(f"construct_dates_from_event() expects either st_date or days_back") if days_back: st_date = en_date - datetime.timedelta(days=int(days_back)) else: st_date = validate_date_from_something(st_date) assert st_date < en_date, "Start date must be earlier than end date." return st_date, en_date
[docs]def validate_list_of_words_from_csv_or_list(data: (str, list)) -> list: """ Splits a CSV string to list of stripped words. In case the `data` is already a list of strings - splits it's elements and flattens the result. All resulting elements must be single words, if any of the elements contains spaces (i.e. multiple words) the validation fails with `ValueError`. :param data: CSV string of list of strings (possibly CSV themselves) :return: List of stripped and split words """ def split_csv(row): if not isinstance(row, str): raise TypeError(f"Unsupported type of data for validate_list_of_words_from_csv_or_list(): {data}") return [x.strip() for x in row.split(',')] result = [] if isinstance(data, (list, tuple, set)): for element in data: result.extend(split_csv(element)) else: result = split_csv(data) if any(' ' in x for x in result): raise ValueError(f"data for validate_list_of_words_from_csv_or_list() should be csv of WORDS or list: {data}") return result
[docs]def first_or_none(items: Iterable, condition: Callable = None): """ Return first element in iterable to match condition or None """ if not condition: def condition(*args, **kwargs): return True for item in items: if condition(item): return item return None
[docs]def recursive_update(d: Dict, u: Mapping) -> Dict: """ Recursively updates the dictionary `d` with another one `u`. Values of `u` overwrite in case of type conflict. List, set and tuple values of `d` and `u` are merged, preserving only unique values. Returned as List. """ new = deepcopy(d) for k, v in u.items(): if isinstance(v, collections.Mapping) and isinstance(d.get(k), (collections.Mapping, type(None))): new[k] = recursive_update(d.get(k, {}), v) elif isinstance(v, (set, list, tuple)): if isinstance(d.get(k), (set, list, tuple)): # Merge lists of uniques. I really want this helper to eat anything and return what it should. :) nv = list(set(d[k])) + list(v) try: # The types of values in list could be unhashable, so it is not that easy filter uniques. new[k] = list(set(nv)) except TypeError: # In this case we just merge lists as is. new[k] = nv else: new[k] = v else: new[k] = v return new
[docs]def trim_arn_to_name(arn: str) -> str: """ Extract just the name of function from full ARN. Supports versions, aliases or raw name (without ARN). More information about ARN Format: https://docs.aws.amazon.com/general/latest/gr/aws-arns-and-namespaces.html#genref-arns """ # Special handling for super global services (e.g. S3 buckets) if arn.count(':') < 6 and '/' not in arn: return arn.split(':')[-1] # Seems a little messy, but passes more/less any test of different ARNs we tried. pattern = "(arn:aws:[0-9a-zA-Z-]{2,20}:[0-9a-zA-Z-]{0,12}:[0-9]{12}:[0-9a-zA-Z-]{2,20}[:/])?" \ "(?P<name>[0-9a-zA-Z_=,[email protected]]*)(:)?([0-9a-zA-Z$]*)?" return re.search(pattern, arn).group('name')
[docs]def trim_arn_to_account(arn: str) -> str: """ Extract just the ACCOUNT_ID from full ARN. Supports versions, aliases or raw name (without ARN). More information about ARN Format: https://docs.aws.amazon.com/general/latest/gr/aws-arns-and-namespaces.html#genref-arns """ # Seems a little messy, but passes more/less any test of different ARNs we tried. pattern = "(arn:aws:[0-9a-zA-Z-]{2,20}:[0-9a-zA-Z-]{0,12}:)?(?P<acc>[0-9]{12})(:[0-9a-zA-Z-]{2,20}[:/])?" \ "(?P<name>[0-9a-zA-Z_=,[email protected]]*)(:)?([0-9a-zA-Z$]*)?" return re.search(pattern, arn).group('acc')
[docs]def make_hash(o): """ Makes a hash from a dictionary, list, tuple or set to any level, that contains only other hashable types (including any lists, tuples, sets, and dictionaries). Original idea from this user: https://stackoverflow.com/users/660554/jomido Plus some upgrades to work with sets and dicts having different types of keys appropriately. See source unittests of this function for some more details. """ if isinstance(o, (tuple, list)): return tuple([make_hash(e) for e in o]) # Set should be sorted (by hashes of elements) before returns elif isinstance(o, set): return tuple(sorted([make_hash(e) for e in o])) elif not isinstance(o, dict): return hash(o) # We are left with a dictionary new_o = dict() for k, v in o.items(): # hash both keys and values to make sure types and order doesn't affect. new_o[make_hash(k)] = make_hash(v) return hash(tuple(frozenset(sorted(new_o.items()))))
def to_bool(val): if isinstance(val, (bool, int, float)): return bool(val) elif isinstance(val, str): if val.lower() in ['true', '1']: return True elif val.lower() in ['false', '0']: return False raise Exception(f"Can't convert unexpected value to bool: {val}, type: {type(val)}")