1 # Copyright (c) 2019 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 """Generation of Continuous Performance Trending and Analysis.
20 import plotly.offline as ploff
21 import plotly.graph_objs as plgo
22 import plotly.exceptions as plerr
24 from collections import OrderedDict
25 from datetime import datetime
26 from copy import deepcopy
28 from utils import archive_input_data, execute_command, classify_anomalies
31 # Command to build the html format of the report
32 HTML_BUILDER = 'sphinx-build -v -c conf_cpta -a ' \
35 '-D version="{date}" ' \
39 # .css file for the html format of the report
40 THEME_OVERRIDES = """/* override table width restrictions */
42 max-width: 1200px !important;
44 .rst-content blockquote {
50 display: inline-block;
58 .wy-menu-vertical li.current a {
60 border-right: solid 1px #c9c9c9;
63 .wy-menu-vertical li.toctree-l2.current > a {
67 .wy-menu-vertical li.toctree-l2.current li.toctree-l3 > a {
72 .wy-menu-vertical li.toctree-l3.current li.toctree-l4 > a {
77 .wy-menu-vertical li.on a, .wy-menu-vertical li.current > a {
84 border-top-width: medium;
85 border-bottom-width: medium;
86 border-top-style: none;
87 border-bottom-style: none;
88 border-top-color: currentcolor;
89 border-bottom-color: currentcolor;
90 padding-left: 2em -4px;
94 COLORS = ["SkyBlue", "Olive", "Purple", "Coral", "Indigo", "Pink",
95 "Chocolate", "Brown", "Magenta", "Cyan", "Orange", "Black",
96 "Violet", "Blue", "Yellow", "BurlyWood", "CadetBlue", "Crimson",
97 "DarkBlue", "DarkCyan", "DarkGreen", "Green", "GoldenRod",
98 "LightGreen", "LightSeaGreen", "LightSkyBlue", "Maroon",
99 "MediumSeaGreen", "SeaGreen", "LightSlateGrey",
100 "SkyBlue", "Olive", "Purple", "Coral", "Indigo", "Pink",
101 "Chocolate", "Brown", "Magenta", "Cyan", "Orange", "Black",
102 "Violet", "Blue", "Yellow", "BurlyWood", "CadetBlue", "Crimson",
103 "DarkBlue", "DarkCyan", "DarkGreen", "Green", "GoldenRod",
104 "LightGreen", "LightSeaGreen", "LightSkyBlue", "Maroon",
105 "MediumSeaGreen", "SeaGreen", "LightSlateGrey"
109 def generate_cpta(spec, data):
110 """Generate all formats and versions of the Continuous Performance Trending
113 :param spec: Specification read from the specification file.
114 :param data: Full data set.
115 :type spec: Specification
116 :type data: InputData
119 logging.info("Generating the Continuous Performance Trending and Analysis "
122 ret_code = _generate_all_charts(spec, data)
124 cmd = HTML_BUILDER.format(
125 date=datetime.utcnow().strftime('%Y-%m-%d %H:%M UTC'),
126 working_dir=spec.environment["paths"]["DIR[WORKING,SRC]"],
127 build_dir=spec.environment["paths"]["DIR[BUILD,HTML]"])
130 with open(spec.environment["paths"]["DIR[CSS_PATCH_FILE]"], "w") as \
132 css_file.write(THEME_OVERRIDES)
134 with open(spec.environment["paths"]["DIR[CSS_PATCH_FILE2]"], "w") as \
136 css_file.write(THEME_OVERRIDES)
138 if spec.configuration.get("archive-inputs", True):
139 archive_input_data(spec)
141 logging.info("Done.")
146 def _generate_trending_traces(in_data, job_name, build_info,
147 show_trend_line=True, name="", color=""):
148 """Generate the trending traces:
150 - outliers, regress, progress
151 - average of normal samples (trending line)
153 :param in_data: Full data set.
154 :param job_name: The name of job which generated the data.
155 :param build_info: Information about the builds.
156 :param show_trend_line: Show moving median (trending plot).
157 :param name: Name of the plot
158 :param color: Name of the color for the plot.
159 :type in_data: OrderedDict
161 :type build_info: dict
162 :type show_trend_line: bool
165 :returns: Generated traces (list) and the evaluated result.
166 :rtype: tuple(traces, result)
169 data_x = list(in_data.keys())
170 data_y = list(in_data.values())
175 date = build_info[job_name][str(idx)][0]
176 hover_str = ("date: {date}<br>"
177 "value: {value:,}<br>"
178 "{sut}-ref: {build}<br>"
179 "csit-ref: mrr-{period}-build-{build_nr}<br>"
180 "testbed: {testbed}")
181 if "dpdk" in job_name:
182 hover_text.append(hover_str.format(
184 value=int(in_data[idx].avg),
186 build=build_info[job_name][str(idx)][1].rsplit('~', 1)[0],
189 testbed=build_info[job_name][str(idx)][2]))
190 elif "vpp" in job_name:
191 hover_text.append(hover_str.format(
193 value=int(in_data[idx].avg),
195 build=build_info[job_name][str(idx)][1].rsplit('~', 1)[0],
198 testbed=build_info[job_name][str(idx)][2]))
200 xaxis.append(datetime(int(date[0:4]), int(date[4:6]), int(date[6:8]),
201 int(date[9:11]), int(date[12:])))
203 data_pd = OrderedDict()
204 for key, value in zip(xaxis, data_y):
207 anomaly_classification, avgs = classify_anomalies(data_pd)
209 anomalies = OrderedDict()
210 anomalies_colors = list()
211 anomalies_avgs = list()
217 if anomaly_classification:
218 for idx, (key, value) in enumerate(data_pd.iteritems()):
219 if anomaly_classification[idx] in \
220 ("outlier", "regression", "progression"):
221 anomalies[key] = value
222 anomalies_colors.append(
223 anomaly_color[anomaly_classification[idx]])
224 anomalies_avgs.append(avgs[idx])
225 anomalies_colors.extend([0.0, 0.5, 1.0])
229 trace_samples = plgo.Scatter(
231 y=[y.avg for y in data_y],
238 name="{name}".format(name=name),
247 traces = [trace_samples, ]
250 trace_trend = plgo.Scatter(
261 name='{name}'.format(name=name),
262 text=["trend: {0:,}".format(int(avg)) for avg in avgs],
263 hoverinfo="text+name"
265 traces.append(trace_trend)
267 trace_anomalies = plgo.Scatter(
274 name="{name}-anomalies".format(name=name),
277 "symbol": "circle-open",
278 "color": anomalies_colors,
279 "colorscale": [[0.00, "red"],
292 "title": "Circles Marking Data Classification",
293 "titleside": 'right',
298 "tickvals": [0.167, 0.500, 0.833],
299 "ticktext": ["Regression", "Normal", "Progression"],
307 traces.append(trace_anomalies)
309 if anomaly_classification:
310 return traces, anomaly_classification[-1]
315 def _generate_all_charts(spec, input_data):
316 """Generate all charts specified in the specification file.
318 :param spec: Specification.
319 :param input_data: Full data set.
320 :type spec: Specification
321 :type input_data: InputData
324 def _generate_chart(graph):
325 """Generates the chart.
330 logs.append(("INFO", " Generating the chart '{0}' ...".
331 format(graph.get("title", ""))))
333 job_name = graph["data"].keys()[0]
339 logs.append(("INFO", " Creating the data set for the {0} '{1}'.".
340 format(graph.get("type", ""), graph.get("title", ""))))
341 data = input_data.filter_data(graph, continue_on_error=True)
343 logging.error("No data.")
348 for job, job_data in data.iteritems():
351 for index, bld in job_data.items():
352 for test_name, test in bld.items():
353 if chart_data.get(test_name, None) is None:
354 chart_data[test_name] = OrderedDict()
356 chart_data[test_name][int(index)] = \
357 test["result"]["receive-rate"]
358 chart_tags[test_name] = test.get("tags", None)
359 except (KeyError, TypeError):
362 # Add items to the csv table:
363 for tst_name, tst_data in chart_data.items():
365 for bld in builds_dict[job_name]:
366 itm = tst_data.get(int(bld), '')
367 if not isinstance(itm, str):
369 tst_lst.append(str(itm))
370 csv_tbl.append("{0},".format(tst_name) + ",".join(tst_lst) + '\n')
375 groups = graph.get("groups", None)
382 for tst_name, test_data in chart_data.items():
384 logs.append(("WARNING",
385 "No data for the test '{0}'".
388 if tag in chart_tags[tst_name]:
389 message = "index: {index}, test: {test}".format(
390 index=index, test=tst_name)
392 trace, rslt = _generate_trending_traces(
395 build_info=build_info,
396 name='-'.join(tst_name.split('.')[-1].
400 message = "Out of colors: {}".format(message)
401 logs.append(("ERROR", message))
402 logging.error(message)
406 visible.extend([True for _ in range(len(trace))])
410 visibility.append(visible)
412 for tst_name, test_data in chart_data.items():
414 logs.append(("WARNING", "No data for the test '{0}'".
417 message = "index: {index}, test: {test}".format(
418 index=index, test=tst_name)
420 trace, rslt = _generate_trending_traces(
423 build_info=build_info,
424 name='-'.join(tst_name.split('.')[-1].split('-')[2:-1]),
427 message = "Out of colors: {}".format(message)
428 logs.append(("ERROR", message))
429 logging.error(message)
437 # Generate the chart:
439 layout = deepcopy(graph["layout"])
440 except KeyError as err:
441 logging.error("Finished with error: No layout defined")
442 logging.error(repr(err))
446 for i in range(len(visibility)):
448 for r in range(len(visibility)):
449 for _ in range(len(visibility[r])):
450 visible.append(i == r)
457 args=[{"visible": [True for _ in range(len(show[0]))]}, ]
459 for i in range(len(groups)):
461 label = graph["group-names"][i]
462 except (IndexError, KeyError):
463 label = "Group {num}".format(num=i + 1)
467 args=[{"visible": show[i]}, ]
470 layout['updatemenus'] = list([
483 name_file = "{0}-{1}{2}".format(spec.cpta["output-file"],
484 graph["output-file-name"],
485 spec.cpta["output-file-type"])
487 logs.append(("INFO", " Writing the file '{0}' ...".
489 plpl = plgo.Figure(data=traces, layout=layout)
491 ploff.plot(plpl, show_link=False, auto_open=False,
493 except plerr.PlotlyEmptyDataError:
494 logs.append(("WARNING", "No data for the plot. Skipped."))
496 for level, line in logs:
499 elif level == "ERROR":
501 elif level == "DEBUG":
503 elif level == "CRITICAL":
504 logging.critical(line)
505 elif level == "WARNING":
506 logging.warning(line)
508 return {"job_name": job_name, "csv_table": csv_tbl, "results": res}
511 for job in spec.input["builds"].keys():
512 if builds_dict.get(job, None) is None:
513 builds_dict[job] = list()
514 for build in spec.input["builds"][job]:
515 status = build["status"]
516 if status != "failed" and status != "not found" and \
518 builds_dict[job].append(str(build["build"]))
520 # Create "build ID": "date" dict:
522 tb_tbl = spec.environment.get("testbeds", None)
523 for job_name, job_data in builds_dict.items():
524 if build_info.get(job_name, None) is None:
525 build_info[job_name] = OrderedDict()
526 for build in job_data:
528 tb_ip = input_data.metadata(job_name, build).get("testbed", "")
530 testbed = tb_tbl.get(tb_ip, "")
531 build_info[job_name][build] = (
532 input_data.metadata(job_name, build).get("generated", ""),
533 input_data.metadata(job_name, build).get("version", ""),
537 anomaly_classifications = dict()
541 for job_name in builds_dict.keys():
542 if csv_tables.get(job_name, None) is None:
543 csv_tables[job_name] = list()
544 header = "Build Number:," + ",".join(builds_dict[job_name]) + '\n'
545 csv_tables[job_name].append(header)
546 build_dates = [x[0] for x in build_info[job_name].values()]
547 header = "Build Date:," + ",".join(build_dates) + '\n'
548 csv_tables[job_name].append(header)
549 versions = [x[1] for x in build_info[job_name].values()]
550 header = "Version:," + ",".join(versions) + '\n'
551 csv_tables[job_name].append(header)
553 for chart in spec.cpta["plots"]:
554 result = _generate_chart(chart)
556 csv_tables[result["job_name"]].extend(result["csv_table"])
558 if anomaly_classifications.get(result["job_name"], None) is None:
559 anomaly_classifications[result["job_name"]] = dict()
560 anomaly_classifications[result["job_name"]].update(result["results"])
563 for job_name, csv_table in csv_tables.items():
564 file_name = spec.cpta["output-file"] + "-" + job_name + "-trending"
565 with open("{0}.csv".format(file_name), 'w') as file_handler:
566 file_handler.writelines(csv_table)
569 with open("{0}.csv".format(file_name), 'rb') as csv_file:
570 csv_content = csv.reader(csv_file, delimiter=',', quotechar='"')
572 for row in csv_content:
573 if txt_table is None:
574 txt_table = prettytable.PrettyTable(row)
577 for idx, item in enumerate(row):
579 row[idx] = str(round(float(item) / 1000000, 2))
583 txt_table.add_row(row)
584 except Exception as err:
585 logging.warning("Error occurred while generating TXT "
586 "table:\n{0}".format(err))
588 txt_table.align["Build Number:"] = "l"
589 with open("{0}.txt".format(file_name), "w") as txt_file:
590 txt_file.write(str(txt_table))
593 if anomaly_classifications:
595 for job_name, job_data in anomaly_classifications.iteritems():
596 file_name = "{0}-regressions-{1}.txt".\
597 format(spec.cpta["output-file"], job_name)
598 with open(file_name, 'w') as txt_file:
599 for test_name, classification in job_data.iteritems():
600 if classification == "regression":
601 txt_file.write(test_name + '\n')
602 if classification == "regression" or \
603 classification == "outlier":
605 file_name = "{0}-progressions-{1}.txt".\
606 format(spec.cpta["output-file"], job_name)
607 with open(file_name, 'w') as txt_file:
608 for test_name, classification in job_data.iteritems():
609 if classification == "progression":
610 txt_file.write(test_name + '\n')
614 logging.info("Partial results: {0}".format(anomaly_classifications))
615 logging.info("Result: {0}".format(result))