Mini Shell

"""
This module contains DecisionMaker class
"""
__package__ = 'ssa.modules'

import json
import logging
import os
from os.path import isfile

import numpy as np
from clcommon.lib.cledition import is_cl_solo_edition

from .common import Common
from ..internal.constants import report_path
from ..internal.utils import previous_day_date, sentry_init


class DecisionMaker(Common):
    """
    SSA Decision maker implementation.
    """

    def __init__(self):
        super().__init__()
        self.logger = logging.getLogger('decision_maker')
        self.logger.info('DecisionMaker enabled: %s', __package__)

    def __call__(self):
        self.logger.info('DecisionMaker started')
        data, _ = self.load_stats()
        self.logger.debug('DecisionMaker loaded config: %s', self.config)
        self.logger.debug('DecisionMaker loaded data: %s', data)
        report = self.data_processing(data)
        self.add_json_report(report)
        self.logger.info('DecisionMaker report: %s', report)
        return report

    @staticmethod
    def _report_file(name) -> str:
        """
        Full path to given filename in DM reports directory
        """
        return os.path.join(report_path, name)

    @property
    def current_report_file(self) -> str:
        """
        Full path to current DM report: report.json in DM reports directory
        """
        return self._report_file('report.json')

    @property
    def _empty_report(self) -> dict:
        """
        Returns empty report
        """
        return dict(date=previous_day_date(), domains=[])

    @property
    def solo_filtered_options(self) -> set:
        return {'correlation'}

    def data_processing(self, data: dict) -> dict:
        """
        Going through the list of domains, for each domain we go through
        the list of urls. During data processing, we will form
        the resulting dictionary.
        """
        report = self._empty_report
        for domain_name, domain_all_data in data.items():
            # goes through the list of domains
            urls_data = list()
            domain_slow_reqs = 0
            domain_total_reqs = domain_all_data['domain_total_reqs']
            for domain_data_key, domain_data_value in domain_all_data.items():
                if self.is_ignored(domain_data_key):
                    self.logger.debug('%s ignored', domain_data_key)
                    continue
                # goes through the list of urls, "domain_total_reqs" is also here
                if domain_data_key != 'domain_total_reqs':
                    # domain_data_key below - it is current url
                    correlation_value = self.get_correlation(
                        domain_data_value['url_total_reqs'], domain_total_reqs)
                    if (self.request_number_exceeded(
                            domain_data_value['url_slow_reqs']) and
                            self.correlation_conditions(correlation_value)):
                        average_duration_calculation = np.mean(
                            domain_data_value['durations'])
                        sum_url_slow_reqs = sum(
                            domain_data_value['url_slow_reqs'])
                        domain_slow_reqs += sum_url_slow_reqs
                        urls_data.append(dict(
                            name=domain_data_key, reqs_num=sum_url_slow_reqs,
                            average_duration=int(average_duration_calculation),
                            correlation=float(f'{correlation_value:.2f}')))
            if urls_data:
                sorted_urls = self.report_sorting(
                    list_to_sort=urls_data, leave_top=self.urls_number,
                    key_for_sorting='reqs_num')
                report['domains'].append(dict(
                    name=domain_name, slow_urls=len(sorted_urls),
                    slow_reqs=domain_slow_reqs,
                    total_reqs=sum(domain_total_reqs), urls=sorted_urls))
        if report['domains']:
            report['domains'] = self.report_sorting(
                list_to_sort=report['domains'], leave_top=self.domains_number,
                key_for_sorting='slow_reqs')
        return report

    def list_handling_considering_time(self, url_slow_reqs: list) -> list:
        """
        Based on the 'url_slow_reqs' list, a new list will be formed,
        where the elements of the original list will be iteratively
        summed by the number of elements equal to 'time'
        """
        time = self.time or 24
        return [sum(url_slow_reqs[i:time + i]) for i in
                range(0, len(url_slow_reqs), time)]

    def compare_elements_with_request_number(self,
                                             url_slow_reqs_by_time: list) -> bool:
        """
        This functions will check if any of elements is greater than "request_number"
        """
        for i in url_slow_reqs_by_time:
            if i >= self.request_number:
                return True
        return False

    def get_correlation(self, url_total_reqs: list, domain_total_reqs: list):
        """
        Calculates the correlation coefficient using the "url_total_reqs" and
        the "domain_total_reqs" lists
        """
        if not self.correlation:
            return 0
        return np.amin(np.corrcoef(url_total_reqs, domain_total_reqs))

    @staticmethod
    def report_sorting(list_to_sort: list, leave_top: int,
                       key_for_sorting: str) -> list:
        """
        Will sort the domain list by "slow_reqs", the goal is to leave only
        "domains_number" of uppers, also per each domain will sort urls by
        "reqs_num", the goal is to leave only "urls_number" of uppers.
        leave_top == 0 allows to keep the full list
        """
        list_to_sort.sort(key=lambda dict_: dict_[key_for_sorting],
                          reverse=True)
        if leave_top:
            return list_to_sort[:leave_top]
        else:
            return list_to_sort

    def rename_old_report(self):
        """
        Rename old report
        """
        old_report = self.current_report_file
        if isfile(old_report):
            with open(old_report) as json_data:
                d = json.load(json_data)
                date_from_report = d['date'].replace('.', '_')
            new_report_name = f'report__{date_from_report}.json'
            new_report = self._report_file(new_report_name)
            os.rename(old_report, new_report)

    def add_json_report(self, report: dict):
        """
        Makes json report
        """
        self.rename_old_report()
        with open(self.current_report_file, 'w', encoding='utf-8') as f:
            json.dump(report, f, ensure_ascii=False, indent=4)

    def get_json_report(self) -> dict:
        """
        Return contents of current report or empty report in case of error
        """
        if is_cl_solo_edition(skip_jwt_check=True):
            def _filtering_hook(value):
                """
                Filter decoded object by fields, given in solo_filtered_options
                property, e.g. 'correlation'
                """
                return {k: v for k, v in value.items() if
                        k not in self.solo_filtered_options}
        else:
            _filtering_hook = None

        try:
            with open(self.current_report_file) as report:
                report_dict = json.load(report, object_hook=_filtering_hook)
        except (OSError, json.JSONDecodeError):
            report_dict = self._empty_report
        return report_dict

    def correlation_conditions(self, correlation_value: int) -> bool:
        """
        If correlation flag is enabled - we'll compare correlation_coefficient
        from configuration with calculated correlation coefficient.
        If the calculated value exceeds the configuration value - we return
        True otherwise False. At the same time if correlation flag is disabled -
        we'll also return "True" since in this case the correlation coefficient
        is not checked and its value is specified as zero in final report.
        """
        if not self.correlation:
            return True
        return correlation_value > self.correlation_coefficient

    def request_number_exceeded(self, url_slow_reqs):
        """
        At least one element from the received list (url_slow_reqs_by_time)
        must be greater than request_number
        """
        url_slow_reqs_by_time = self.list_handling_considering_time(
            url_slow_reqs)
        return self.compare_elements_with_request_number(url_slow_reqs_by_time)


if __name__ == "__main__":
    sentry_init()
    logging.basicConfig(filename='decision_maker_standalone.log',
                        level=logging.INFO)
    dm = DecisionMaker()
    dm()