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# Copyright (c) 2017 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 subprocess
import numpy as np
import pandas as pd
import logging
from os import walk, makedirs, environ
from os.path import join, isdir
from shutil import copy, Error
from math import sqrt
from errors import PresentationError
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 remove_outliers(input_data, outlier_const):
"""
:param input_data: Data from which the outliers will be removed.
:param outlier_const: Outlier constant.
:type input_data: list
:type outlier_const: float
:returns: The input list without outliers.
:rtype: list
"""
data = np.array(input_data)
upper_quartile = np.percentile(data, 75)
lower_quartile = np.percentile(data, 25)
iqr = (upper_quartile - lower_quartile) * outlier_const
quartile_set = (lower_quartile - iqr, upper_quartile + iqr)
result_lst = list()
for y in data.tolist():
if quartile_set[0] <= y <= quartile_set[1]:
result_lst.append(y)
return result_lst
def find_outliers(input_data, outlier_const=1.5):
"""Go through the input data and generate two pandas series:
- input data without outliers
- outliers.
The function uses IQR to detect outliers.
:param input_data: Data to be examined for outliers.
:param outlier_const: Outlier constant.
:type input_data: pandas.Series
:type outlier_const: float
:returns: Tuple: input data with outliers removed; Outliers.
:rtype: tuple (trimmed_data, outliers)
"""
upper_quartile = input_data.quantile(q=0.75)
lower_quartile = input_data.quantile(q=0.25)
iqr = (upper_quartile - lower_quartile) * outlier_const
low = lower_quartile - iqr
high = upper_quartile + iqr
trimmed_data = pd.Series()
outliers = pd.Series()
for item in input_data.items():
item_pd = pd.Series([item[1], ], index=[item[0], ])
if low <= item[1] <= high:
trimmed_data = trimmed_data.append(item_pd)
else:
trimmed_data = trimmed_data.append(pd.Series([np.nan, ],
index=[item[0], ]))
outliers = outliers.append(item_pd)
return trimmed_data, outliers
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.
:rtype: int
"""
env = environ.copy()
proc = subprocess.Popen(
[cmd],
stdout=subprocess.PIPE,
stderr=subprocess.PIPE,
shell=True,
env=env)
stdout, stderr = proc.communicate()
logging.info(stdout)
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 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 ...")
if spec.is_debug:
extension = spec.debug["input-format"]
else:
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(" Copying the file: {0} ...".format(data_file))
copy(data_file, dst)
except (Error, OSError) as err:
raise PresentationError("Not possible to archive the input data.",
str(err))
logging.info(" Done.")
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