SkillAegis/inject_evaluator.py

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#!/usr/bin/env python3
from typing import Union
import jq
import re
import operator
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from config import logger
def jq_extract(path: str, data: dict, extract_type='first'):
query = jq.compile(path).input_value(data)
try:
return query.first() if extract_type == 'first' else query.all()
except StopIteration:
return None
# Replace the substring `{{variable}}` by context[variable] in the provided string
def apply_replacement_from_context(string: str, context: dict) -> str:
replacement_regex = r"{{(\w+)}}"
matches = re.fullmatch(replacement_regex, string, re.MULTILINE)
if not matches:
return string
subst_str = matches.groups()[0]
subst = str(context.get(subst_str, ''))
return re.sub(replacement_regex, subst, string)
##
## Data Filtering
##
def condition_satisfied(evaluation_config: dict, data_to_validate: Union[dict, list, str], context: dict) -> bool:
if type(data_to_validate) is bool:
data_to_validate = "1" if data_to_validate else "0"
if type(data_to_validate) is str:
return eval_condition_str(evaluation_config, data_to_validate, context)
elif type(data_to_validate) is list:
return eval_condition_list(evaluation_config, data_to_validate, context)
elif type(data_to_validate) is dict:
# Not sure how we could have condition on this
return eval_condition_dict(evaluation_config, data_to_validate, context)
return False
def eval_condition_str(evaluation_config: dict, data_to_validate: str, context: dict) -> bool:
comparison_type = evaluation_config['comparison']
values = evaluation_config['values']
if len(values) == 0:
return False
values = [apply_replacement_from_context(v, context) for v in values]
if comparison_type == 'contains':
values = [v.lower() for v in values]
data_to_validate = data_to_validate.lower()
data_to_validate_set = set(data_to_validate.split())
values_set = set(values)
intersection = data_to_validate_set & values_set
return len(intersection) == len(values_set)
elif comparison_type == 'equals':
return data_to_validate == values[0]
elif comparison_type == 'equals_any':
return data_to_validate in values
elif comparison_type == 'regex':
return re.fullmatch(values[0], data_to_validate)
elif comparison_type == 'count':
return len(data_to_validate) == values[0]
return False
def eval_condition_list(evaluation_config: dict, data_to_validate: str, context: dict) -> bool:
comparison_type = evaluation_config['comparison']
values = evaluation_config['values']
comparators = {
'<': operator.lt,
'<=': operator.le,
'>': operator.gt,
'>=': operator.ge,
'=': operator.eq,
}
if len(values) == 0:
return False
values = [apply_replacement_from_context(v, context) for v in values]
if comparison_type == 'contains' or comparison_type == 'equals':
data_to_validate_set = set(data_to_validate)
values_set = set(values)
intersection = data_to_validate_set & values_set
if comparison_type == 'contains':
return len(intersection) == len(values_set)
elif comparison_type == 'equals':
return len(intersection) == len(values_set) and len(intersection) == len(data_to_validate_set)
if comparison_type == 'contains-regex':
regex = re.compile(values[0])
for candidate in data_to_validate:
if regex.match(candidate):
return True
return False
elif comparison_type == 'count':
value = values[0]
if value.isdigit():
return len(data_to_validate) == value
elif value[:2] in comparators.keys():
count = len(data_to_validate)
value_operator = values[0][:2]
value = int(value[2:])
return comparators[value_operator](count, value)
elif value[0] in comparators.keys():
count = len(data_to_validate)
value_operator = value[0]
value = int(value[1:])
return comparators[value_operator](count, value)
return False
def eval_condition_dict(evaluation_config: dict, data_to_validate: str, context: dict) -> bool:
comparison_type = evaluation_config['comparison']
values = evaluation_config['values']
comparators = {
'<': operator.lt,
'<=': operator.le,
'>': operator.gt,
'>=': operator.ge,
'=': operator.eq,
}
if len(values) == 0:
return False
values = [apply_replacement_from_context(v, context) for v in values]
comparison_type = evaluation_config['comparison']
if comparison_type == 'contains':
pass
elif comparison_type == 'equals':
pass
elif comparison_type == 'count':
if values[0].isdigit():
return len(data_to_validate) == values[0]
elif values[0][0] in comparators.keys():
count = len(data_to_validate)
value_operator = values[0][0]
value = int(values[0][1:])
return comparators[value_operator](count, value)
return False
def eval_data_filtering(user_id: int, inject_evaluation: dict, data: dict, context: dict) -> bool:
for evaluation_params in inject_evaluation['parameters']:
for evaluation_path, evaluation_config in evaluation_params.items():
evaluation_path = apply_replacement_from_context(evaluation_path, context)
data_to_validate = jq_extract(evaluation_path, data, evaluation_config.get('extract_type', 'first'))
if data_to_validate is None:
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logger.debug('Could not extract data')
return False
if not condition_satisfied(evaluation_config, data_to_validate, context):
return False
return True
##
## Query mirror
##
def eval_query_mirror(user_id: int, expected_data, data_to_validate, context: dict) -> bool:
return expected_data == data_to_validate
##
## Query search
##
def eval_query_search(user_id: int, inject_evaluation: dict, data: dict, context: dict) -> bool:
return eval_data_filtering(user_id, inject_evaluation, data, context)