1 # Copyright (c) 2018 Cisco and/or its affiliates.
2 # Licensed under the Apache License, Version 2.0 (the "License");
3 # you may not use this file except in compliance with the License.
4 # You may obtain a copy of the License at:
6 # http://www.apache.org/licenses/LICENSE-2.0
8 # Unless required by applicable law or agreed to in writing, software
9 # distributed under the License is distributed on an "AS IS" BASIS,
10 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
11 # See the License for the specific language governing permissions and
12 # limitations under the License.
14 """General purpose utilities.
22 from os import walk, makedirs, environ
23 from os.path import join, isdir
24 from shutil import move, Error
27 from errors import PresentationError
31 """Calculate mean value from the items.
33 :param items: Mean value is calculated from these items.
39 return float(sum(items)) / len(items)
43 """Calculate stdev from the items.
45 :param items: Stdev is calculated from these items.
52 variance = [(x - avg) ** 2 for x in items]
53 stddev = sqrt(mean(variance))
57 def relative_change(nr1, nr2):
58 """Compute relative change of two values.
60 :param nr1: The first number.
61 :param nr2: The second number.
64 :returns: Relative change of nr1.
68 return float(((nr2 - nr1) / nr1) * 100)
71 def remove_outliers(input_list, outlier_const=1.5, window=14):
72 """Return list with outliers removed, using split_outliers.
74 :param input_list: Data from which the outliers will be removed.
75 :param outlier_const: Outlier constant.
76 :param window: How many preceding values to take into account.
77 :type input_list: list of floats
78 :type outlier_const: float
80 :returns: The input list without outliers.
81 :rtype: list of floats
84 data = np.array(input_list)
85 upper_quartile = np.percentile(data, 75)
86 lower_quartile = np.percentile(data, 25)
87 iqr = (upper_quartile - lower_quartile) * outlier_const
88 quartile_set = (lower_quartile - iqr, upper_quartile + iqr)
91 if quartile_set[0] <= y <= quartile_set[1]:
96 def split_outliers(input_series, outlier_const=1.5, window=14):
97 """Go through the input data and generate two pandas series:
98 - input data with outliers replaced by NAN
100 The function uses IQR to detect outliers.
102 :param input_series: Data to be examined for outliers.
103 :param outlier_const: Outlier constant.
104 :param window: How many preceding values to take into account.
105 :type input_series: pandas.Series
106 :type outlier_const: float
108 :returns: Input data with NAN outliers and Outliers.
109 :rtype: (pandas.Series, pandas.Series)
112 list_data = list(input_series.items())
113 head_size = min(window, len(list_data))
114 head_list = list_data[:head_size]
115 trimmed_data = pd.Series()
116 outliers = pd.Series()
117 for item_x, item_y in head_list:
118 item_pd = pd.Series([item_y, ], index=[item_x, ])
119 trimmed_data = trimmed_data.append(item_pd)
120 for index, (item_x, item_y) in list(enumerate(list_data))[head_size:]:
121 y_rolling_list = [y for (x, y) in list_data[index - head_size:index]]
122 y_rolling_array = np.array(y_rolling_list)
123 q1 = np.percentile(y_rolling_array, 25)
124 q3 = np.percentile(y_rolling_array, 75)
125 iqr = (q3 - q1) * outlier_const
127 item_pd = pd.Series([item_y, ], index=[item_x, ])
129 trimmed_data = trimmed_data.append(item_pd)
131 outliers = outliers.append(item_pd)
132 nan_pd = pd.Series([np.nan, ], index=[item_x, ])
133 trimmed_data = trimmed_data.append(nan_pd)
135 return trimmed_data, outliers
138 def get_files(path, extension=None, full_path=True):
139 """Generates the list of files to process.
141 :param path: Path to files.
142 :param extension: Extension of files to process. If it is the empty string,
143 all files will be processed.
144 :param full_path: If True, the files with full path are generated.
147 :type full_path: bool
148 :returns: List of files to process.
153 for root, _, files in walk(path):
154 for filename in files:
156 if filename.endswith(extension):
158 file_list.append(join(root, filename))
160 file_list.append(filename)
162 file_list.append(join(root, filename))
167 def get_rst_title_char(level):
168 """Return character used for the given title level in rst files.
170 :param level: Level of the title.
172 :returns: Character used for the given title level in rst files.
175 chars = ('=', '-', '`', "'", '.', '~', '*', '+', '^')
176 if level < len(chars):
182 def execute_command(cmd):
183 """Execute the command in a subprocess and log the stdout and stderr.
185 :param cmd: Command to execute.
187 :returns: Return code of the executed command.
192 proc = subprocess.Popen(
194 stdout=subprocess.PIPE,
195 stderr=subprocess.PIPE,
199 stdout, stderr = proc.communicate()
201 logging.debug(stdout)
202 logging.debug(stderr)
204 if proc.returncode != 0:
205 logging.error(" Command execution failed.")
206 return proc.returncode, stdout, stderr
209 def get_last_successful_build_number(jenkins_url, job_name):
210 """Get the number of the last successful build of the given job.
212 :param jenkins_url: Jenkins URL.
213 :param job_name: Job name.
214 :type jenkins_url: str
216 :returns: The build number as a string.
220 url = "{}/{}/lastSuccessfulBuild/buildNumber".format(jenkins_url, job_name)
221 cmd = "wget -qO- {url}".format(url=url)
223 return execute_command(cmd)
226 def get_last_completed_build_number(jenkins_url, job_name):
227 """Get the number of the last completed build of the given job.
229 :param jenkins_url: Jenkins URL.
230 :param job_name: Job name.
231 :type jenkins_url: str
233 :returns: The build number as a string.
237 url = "{}/{}/lastCompletedBuild/buildNumber".format(jenkins_url, job_name)
238 cmd = "wget -qO- {url}".format(url=url)
240 return execute_command(cmd)
243 def archive_input_data(spec):
244 """Archive the report.
246 :param spec: Specification read from the specification file.
247 :type spec: Specification
248 :raises PresentationError: If it is not possible to archive the input data.
251 logging.info(" Archiving the input data files ...")
253 extension = spec.input["file-format"]
254 data_files = get_files(spec.environment["paths"]["DIR[WORKING,DATA]"],
256 dst = spec.environment["paths"]["DIR[STATIC,ARCH]"]
257 logging.info(" Destination: {0}".format(dst))
263 for data_file in data_files:
264 logging.info(" Moving the file: {0} ...".format(data_file))
267 except (Error, OSError) as err:
268 raise PresentationError("Not possible to archive the input data.",
271 logging.info(" Done.")