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Diffstat (limited to 'resources/tools/presentation_new/utils.py')
| -rw-r--r-- | resources/tools/presentation_new/utils.py | 341 |
1 files changed, 0 insertions, 341 deletions
diff --git a/resources/tools/presentation_new/utils.py b/resources/tools/presentation_new/utils.py deleted file mode 100644 index 3fdec85774..0000000000 --- a/resources/tools/presentation_new/utils.py +++ /dev/null @@ -1,341 +0,0 @@ -# Copyright (c) 2018 Cisco and/or its affiliates. -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at: -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -"""General purpose utilities. -""" - -import multiprocessing -import subprocess -import numpy as np -import logging -import csv -import prettytable - -from os import walk, makedirs, environ -from os.path import join, isdir -from shutil import move, Error -from math import sqrt -from datetime import datetime - -from errors import PresentationError -from jumpavg.BitCountingClassifier import BitCountingClassifier - - -def mean(items): - """Calculate mean value from the items. - - :param items: Mean value is calculated from these items. - :type items: list - :returns: MEan value. - :rtype: float - """ - - return float(sum(items)) / len(items) - - -def stdev(items): - """Calculate stdev from the items. - - :param items: Stdev is calculated from these items. - :type items: list - :returns: Stdev. - :rtype: float - """ - - avg = mean(items) - variance = [(x - avg) ** 2 for x in items] - stddev = sqrt(mean(variance)) - return stddev - - -def relative_change(nr1, nr2): - """Compute relative change of two values. - - :param nr1: The first number. - :param nr2: The second number. - :type nr1: float - :type nr2: float - :returns: Relative change of nr1. - :rtype: float - """ - - return float(((nr2 - nr1) / nr1) * 100) - - -def get_files(path, extension=None, full_path=True): - """Generates the list of files to process. - - :param path: Path to files. - :param extension: Extension of files to process. If it is the empty string, - all files will be processed. - :param full_path: If True, the files with full path are generated. - :type path: str - :type extension: str - :type full_path: bool - :returns: List of files to process. - :rtype: list - """ - - file_list = list() - for root, _, files in walk(path): - for filename in files: - if extension: - if filename.endswith(extension): - if full_path: - file_list.append(join(root, filename)) - else: - file_list.append(filename) - else: - file_list.append(join(root, filename)) - - return file_list - - -def get_rst_title_char(level): - """Return character used for the given title level in rst files. - - :param level: Level of the title. - :type: int - :returns: Character used for the given title level in rst files. - :rtype: str - """ - chars = ('=', '-', '`', "'", '.', '~', '*', '+', '^') - if level < len(chars): - return chars[level] - else: - return chars[-1] - - -def execute_command(cmd): - """Execute the command in a subprocess and log the stdout and stderr. - - :param cmd: Command to execute. - :type cmd: str - :returns: Return code of the executed command, stdout and stderr. - :rtype: tuple(int, str, str) - """ - - env = environ.copy() - proc = subprocess.Popen( - [cmd], - stdout=subprocess.PIPE, - stderr=subprocess.PIPE, - shell=True, - env=env) - - stdout, stderr = proc.communicate() - - if stdout: - logging.info(stdout) - if stderr: - logging.info(stderr) - - if proc.returncode != 0: - logging.error(" Command execution failed.") - return proc.returncode, stdout, stderr - - -def get_last_successful_build_number(jenkins_url, job_name): - """Get the number of the last successful build of the given job. - - :param jenkins_url: Jenkins URL. - :param job_name: Job name. - :type jenkins_url: str - :type job_name: str - :returns: The build number as a string. - :rtype: str - """ - - url = "{}/{}/lastSuccessfulBuild/buildNumber".format(jenkins_url, job_name) - cmd = "wget -qO- {url}".format(url=url) - - return execute_command(cmd) - - -def get_last_completed_build_number(jenkins_url, job_name): - """Get the number of the last completed build of the given job. - - :param jenkins_url: Jenkins URL. - :param job_name: Job name. - :type jenkins_url: str - :type job_name: str - :returns: The build number as a string. - :rtype: str - """ - - url = "{}/{}/lastCompletedBuild/buildNumber".format(jenkins_url, job_name) - cmd = "wget -qO- {url}".format(url=url) - - return execute_command(cmd) - - -def get_build_timestamp(jenkins_url, job_name, build_nr): - """Get the timestamp of the build of the given job. - - :param jenkins_url: Jenkins URL. - :param job_name: Job name. - :param build_nr: Build number. - :type jenkins_url: str - :type job_name: str - :type build_nr: int - :returns: The timestamp. - :rtype: datetime.datetime - """ - - url = "{jenkins_url}/{job_name}/{build_nr}".format(jenkins_url=jenkins_url, - job_name=job_name, - build_nr=build_nr) - cmd = "wget -qO- {url}".format(url=url) - - timestamp = execute_command(cmd) - - return datetime.fromtimestamp(timestamp/1000) - - -def archive_input_data(spec): - """Archive the report. - - :param spec: Specification read from the specification file. - :type spec: Specification - :raises PresentationError: If it is not possible to archive the input data. - """ - - logging.info(" Archiving the input data files ...") - - extension = spec.input["file-format"] - data_files = get_files(spec.environment["paths"]["DIR[WORKING,DATA]"], - extension=extension) - dst = spec.environment["paths"]["DIR[STATIC,ARCH]"] - logging.info(" Destination: {0}".format(dst)) - - try: - if not isdir(dst): - makedirs(dst) - - for data_file in data_files: - logging.info(" Moving the file: {0} ...".format(data_file)) - move(data_file, dst) - - except (Error, OSError) as err: - raise PresentationError("Not possible to archive the input data.", - str(err)) - - logging.info(" Done.") - - -def classify_anomalies(data): - """Process the data and return anomalies and trending values. - - Gather data into groups with average as trend value. - Decorate values within groups to be normal, - the first value of changed average as a regression, or a progression. - - :param data: Full data set with unavailable samples replaced by nan. - :type data: OrderedDict - :returns: Classification and trend values - :rtype: 2-tuple, list of strings and list of floats - """ - # Nan mean something went wrong. - # Use 0.0 to cause that being reported as a severe regression. - bare_data = [0.0 if np.isnan(sample.avg) else sample - for _, sample in data.iteritems()] - # TODO: Put analogous iterator into jumpavg library. - groups = BitCountingClassifier().classify(bare_data) - groups.reverse() # Just to use .pop() for FIFO. - classification = [] - avgs = [] - active_group = None - values_left = 0 - avg = 0.0 - for _, sample in data.iteritems(): - if np.isnan(sample.avg): - classification.append("outlier") - avgs.append(sample.avg) - continue - if values_left < 1 or active_group is None: - values_left = 0 - while values_left < 1: # Ignore empty groups (should not happen). - active_group = groups.pop() - values_left = len(active_group.values) - avg = active_group.metadata.avg - classification.append(active_group.metadata.classification) - avgs.append(avg) - values_left -= 1 - continue - classification.append("normal") - avgs.append(avg) - values_left -= 1 - return classification, avgs - - -def convert_csv_to_pretty_txt(csv_file, txt_file): - """Convert the given csv table to pretty text table. - - :param csv_file: The path to the input csv file. - :param txt_file: The path to the output pretty text file. - :type csv_file: str - :type txt_file: str - """ - - txt_table = None - with open(csv_file, 'rb') as csv_file: - csv_content = csv.reader(csv_file, delimiter=',', quotechar='"') - for row in csv_content: - if txt_table is None: - txt_table = prettytable.PrettyTable(row) - else: - txt_table.add_row(row) - txt_table.align["Test case"] = "l" - if txt_table: - with open(txt_file, "w") as txt_file: - txt_file.write(str(txt_table)) - - -class Worker(multiprocessing.Process): - """Worker class used to process tasks in separate parallel processes. - """ - - def __init__(self, work_queue, data_queue, func): - """Initialization. - - :param work_queue: Queue with items to process. - :param data_queue: Shared memory between processes. Queue which keeps - the result data. This data is then read by the main process and used - in further processing. - :param func: Function which is executed by the worker. - :type work_queue: multiprocessing.JoinableQueue - :type data_queue: multiprocessing.Manager().Queue() - :type func: Callable object - """ - super(Worker, self).__init__() - self._work_queue = work_queue - self._data_queue = data_queue - self._func = func - - def run(self): - """Method representing the process's activity. - """ - - while True: - try: - self.process(self._work_queue.get()) - finally: - self._work_queue.task_done() - - def process(self, item_to_process): - """Method executed by the runner. - - :param item_to_process: Data to be processed by the function. - :type item_to_process: tuple - """ - self._func(self.pid, self._data_queue, *item_to_process) |