resources/tools/presentation/generator_CPTA.py

   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:
   5 #
   6 #     http://www.apache.org/licenses/LICENSE-2.0
   7 #
   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.
  13
  14 """Generation of Continuous Performance Trending and Analysis.
  15 """
  16
  17 import logging
  18 import csv
  19 import prettytable
  20 import plotly.offline as ploff
  21 import plotly.graph_objs as plgo
  22 import plotly.exceptions as plerr
  23
  24 from collections import OrderedDict
  25 from datetime import datetime
  26 from copy import deepcopy
  27
  28 from utils import archive_input_data, execute_command, classify_anomalies
  29
  30
  31 # Command to build the html format of the report
  32 HTML_BUILDER = 'sphinx-build -v -c conf_cpta -a ' \
  33                '-b html -E ' \
  34                '-t html ' \
  35                '-D version="{date}" ' \
  36                '{working_dir} ' \
  37                '{build_dir}/'
  38
  39 # .css file for the html format of the report
  40 THEME_OVERRIDES = """/* override table width restrictions */
  41 .wy-nav-content {
  42     max-width: 1200px !important;
  43 }
  44 .rst-content blockquote {
  45     margin-left: 0px;
  46     line-height: 18px;
  47     margin-bottom: 0px;
  48 }
  49 .wy-menu-vertical a {
  50     display: inline-block;
  51     line-height: 18px;
  52     padding: 0 2em;
  53     display: block;
  54     position: relative;
  55     font-size: 90%;
  56     color: #d9d9d9
  57 }
  58 .wy-menu-vertical li.current a {
  59     color: gray;
  60     border-right: solid 1px #c9c9c9;
  61     padding: 0 3em;
  62 }
  63 .wy-menu-vertical li.toctree-l2.current > a {
  64     background: #c9c9c9;
  65     padding: 0 3em;
  66 }
  67 .wy-menu-vertical li.toctree-l2.current li.toctree-l3 > a {
  68     display: block;
  69     background: #c9c9c9;
  70     padding: 0 4em;
  71 }
  72 .wy-menu-vertical li.toctree-l3.current li.toctree-l4 > a {
  73     display: block;
  74     background: #bdbdbd;
  75     padding: 0 5em;
  76 }
  77 .wy-menu-vertical li.on a, .wy-menu-vertical li.current > a {
  78     color: #404040;
  79     padding: 0 2em;
  80     font-weight: bold;
  81     position: relative;
  82     background: #fcfcfc;
  83     border: none;
  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;
  91 }
  92 """
  93
  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"
 106           ]
 107
 108
 109 def generate_cpta(spec, data):
 110     """Generate all formats and versions of the Continuous Performance Trending
 111     and Analysis.
 112
 113     :param spec: Specification read from the specification file.
 114     :param data: Full data set.
 115     :type spec: Specification
 116     :type data: InputData
 117     """
 118
 119     logging.info("Generating the Continuous Performance Trending and Analysis "
 120                  "...")
 121
 122     ret_code = _generate_all_charts(spec, data)
 123
 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]"])
 128     execute_command(cmd)
 129
 130     with open(spec.environment["paths"]["DIR[CSS_PATCH_FILE]"], "w") as \
 131             css_file:
 132         css_file.write(THEME_OVERRIDES)
 133
 134     with open(spec.environment["paths"]["DIR[CSS_PATCH_FILE2]"], "w") as \
 135             css_file:
 136         css_file.write(THEME_OVERRIDES)
 137
 138     if spec.configuration.get("archive-inputs", True):
 139         archive_input_data(spec)
 140
 141     logging.info("Done.")
 142
 143     return ret_code
 144
 145
 146 def _generate_trending_traces(in_data, job_name, build_info,
 147                               show_trend_line=True, name="", color=""):
 148     """Generate the trending traces:
 149      - samples,
 150      - outliers, regress, progress
 151      - average of normal samples (trending line)
 152
 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
 160     :type job_name: str
 161     :type build_info: dict
 162     :type show_trend_line: bool
 163     :type name: str
 164     :type color: str
 165     :returns: Generated traces (list) and the evaluated result.
 166     :rtype: tuple(traces, result)
 167     """
 168
 169     data_x = list(in_data.keys())
 170     data_y = list(in_data.values())
 171
 172     hover_text = list()
 173     xaxis = list()
 174     for idx in data_x:
 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(
 183                 date=date,
 184                 value=int(in_data[idx].avg),
 185                 sut="dpdk",
 186                 build=build_info[job_name][str(idx)][1].rsplit('~', 1)[0],
 187                 period="weekly",
 188                 build_nr=idx,
 189                 testbed=build_info[job_name][str(idx)][2]))
 190         elif "vpp" in job_name:
 191             hover_text.append(hover_str.format(
 192                 date=date,
 193                 value=int(in_data[idx].avg),
 194                 sut="vpp",
 195                 build=build_info[job_name][str(idx)][1].rsplit('~', 1)[0],
 196                 period="daily",
 197                 build_nr=idx,
 198                 testbed=build_info[job_name][str(idx)][2]))
 199
 200         xaxis.append(datetime(int(date[0:4]), int(date[4:6]), int(date[6:8]),
 201                               int(date[9:11]), int(date[12:])))
 202
 203     data_pd = OrderedDict()
 204     for key, value in zip(xaxis, data_y):
 205         data_pd[key] = value
 206
 207     anomaly_classification, avgs = classify_anomalies(data_pd)
 208
 209     anomalies = OrderedDict()
 210     anomalies_colors = list()
 211     anomalies_avgs = list()
 212     anomaly_color = {
 213         "regression": 0.0,
 214         "normal": 0.5,
 215         "progression": 1.0
 216     }
 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])
 226
 227     # Create traces
 228
 229     trace_samples = plgo.Scatter(
 230         x=xaxis,
 231         y=[y.avg for y in data_y],
 232         mode='markers',
 233         line={
 234             "width": 1
 235         },
 236         showlegend=True,
 237         legendgroup=name,
 238         name="{name}".format(name=name),
 239         marker={
 240             "size": 5,
 241             "color": color,
 242             "symbol": "circle",
 243         },
 244         text=hover_text,
 245         hoverinfo="text"
 246     )
 247     traces = [trace_samples, ]
 248
 249     if show_trend_line:
 250         trace_trend = plgo.Scatter(
 251             x=xaxis,
 252             y=avgs,
 253             mode='lines',
 254             line={
 255                 "shape": "linear",
 256                 "width": 1,
 257                 "color": color,
 258             },
 259             showlegend=False,
 260             legendgroup=name,
 261             name='{name}'.format(name=name),
 262             text=["trend: {0:,}".format(int(avg)) for avg in avgs],
 263             hoverinfo="text+name"
 264         )
 265         traces.append(trace_trend)
 266
 267     trace_anomalies = plgo.Scatter(
 268         x=anomalies.keys(),
 269         y=anomalies_avgs,
 270         mode='markers',
 271         hoverinfo="none",
 272         showlegend=False,
 273         legendgroup=name,
 274         name="{name}-anomalies".format(name=name),
 275         marker={
 276             "size": 15,
 277             "symbol": "circle-open",
 278             "color": anomalies_colors,
 279             "colorscale": [[0.00, "red"],
 280                            [0.33, "red"],
 281                            [0.33, "white"],
 282                            [0.66, "white"],
 283                            [0.66, "green"],
 284                            [1.00, "green"]],
 285             "showscale": True,
 286             "line": {
 287                 "width": 2
 288             },
 289             "colorbar": {
 290                 "y": 0.5,
 291                 "len": 0.8,
 292                 "title": "Circles Marking Data Classification",
 293                 "titleside": 'right',
 294                 "titlefont": {
 295                     "size": 14
 296                 },
 297                 "tickmode": 'array',
 298                 "tickvals": [0.167, 0.500, 0.833],
 299                 "ticktext": ["Regression", "Normal", "Progression"],
 300                 "ticks": "",
 301                 "ticklen": 0,
 302                 "tickangle": -90,
 303                 "thickness": 10
 304             }
 305         }
 306     )
 307     traces.append(trace_anomalies)
 308
 309     if anomaly_classification:
 310         return traces, anomaly_classification[-1]
 311     else:
 312         return traces, None
 313
 314
 315 def _generate_all_charts(spec, input_data):
 316     """Generate all charts specified in the specification file.
 317
 318     :param spec: Specification.
 319     :param input_data: Full data set.
 320     :type spec: Specification
 321     :type input_data: InputData
 322     """
 323
 324     def _generate_chart(graph):
 325         """Generates the chart.
 326         """
 327
 328         logs = list()
 329
 330         logs.append(("INFO", "  Generating the chart '{0}' ...".
 331                      format(graph.get("title", ""))))
 332
 333         job_name = graph["data"].keys()[0]
 334
 335         csv_tbl = list()
 336         res = dict()
 337
 338         # Transform the data
 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)
 342         if data is None:
 343             logging.error("No data.")
 344             return
 345
 346         chart_data = dict()
 347         chart_tags = dict()
 348         for job, job_data in data.iteritems():
 349             if job != job_name:
 350                 continue
 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()
 355                     try:
 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):
 360                         pass
 361
 362         # Add items to the csv table:
 363         for tst_name, tst_data in chart_data.items():
 364             tst_lst = list()
 365             for bld in builds_dict[job_name]:
 366                 itm = tst_data.get(int(bld), '')
 367                 if not isinstance(itm, str):
 368                     itm = itm.avg
 369                 tst_lst.append(str(itm))
 370             csv_tbl.append("{0},".format(tst_name) + ",".join(tst_lst) + '\n')
 371
 372         # Generate traces:
 373         traces = list()
 374         index = 0
 375         groups = graph.get("groups", None)
 376         visibility = list()
 377
 378         if groups:
 379             for group in groups:
 380                 visible = list()
 381                 for tag in group:
 382                     for tst_name, test_data in chart_data.items():
 383                         if not test_data:
 384                             logs.append(("WARNING",
 385                                          "No data for the test '{0}'".
 386                                          format(tst_name)))
 387                             continue
 388                         if tag in chart_tags[tst_name]:
 389                             message = "index: {index}, test: {test}".format(
 390                                 index=index, test=tst_name)
 391                             try:
 392                                 trace, rslt = _generate_trending_traces(
 393                                     test_data,
 394                                     job_name=job_name,
 395                                     build_info=build_info,
 396                                     name='-'.join(tst_name.split('.')[-1].
 397                                                   split('-')[2:-1]),
 398                                     color=COLORS[index])
 399                             except IndexError:
 400                                 message = "Out of colors: {}".format(message)
 401                                 logs.append(("ERROR", message))
 402                                 logging.error(message)
 403                                 index += 1
 404                                 continue
 405                             traces.extend(trace)
 406                             visible.extend([True for _ in range(len(trace))])
 407                             res[tst_name] = rslt
 408                             index += 1
 409                             break
 410                 visibility.append(visible)
 411         else:
 412             for tst_name, test_data in chart_data.items():
 413                 if not test_data:
 414                     logs.append(("WARNING", "No data for the test '{0}'".
 415                                  format(tst_name)))
 416                     continue
 417                 message = "index: {index}, test: {test}".format(
 418                     index=index, test=tst_name)
 419                 try:
 420                     trace, rslt = _generate_trending_traces(
 421                         test_data,
 422                         job_name=job_name,
 423                         build_info=build_info,
 424                         name='-'.join(tst_name.split('.')[-1].split('-')[2:-1]),
 425                         color=COLORS[index])
 426                 except IndexError:
 427                     message = "Out of colors: {}".format(message)
 428                     logs.append(("ERROR", message))
 429                     logging.error(message)
 430                     index += 1
 431                     continue
 432                 traces.extend(trace)
 433                 res[tst_name] = rslt
 434                 index += 1
 435
 436         if traces:
 437             # Generate the chart:
 438             try:
 439                 layout = deepcopy(graph["layout"])
 440             except KeyError as err:
 441                 logging.error("Finished with error: No layout defined")
 442                 logging.error(repr(err))
 443                 return
 444             if groups:
 445                 show = list()
 446                 for i in range(len(visibility)):
 447                     visible = list()
 448                     for r in range(len(visibility)):
 449                         for _ in range(len(visibility[r])):
 450                             visible.append(i == r)
 451                     show.append(visible)
 452
 453                 buttons = list()
 454                 buttons.append(dict(
 455                     label="All",
 456                     method="update",
 457                     args=[{"visible": [True for _ in range(len(show[0]))]}, ]
 458                 ))
 459                 for i in range(len(groups)):
 460                     try:
 461                         label = graph["group-names"][i]
 462                     except (IndexError, KeyError):
 463                         label = "Group {num}".format(num=i + 1)
 464                     buttons.append(dict(
 465                         label=label,
 466                         method="update",
 467                         args=[{"visible": show[i]}, ]
 468                     ))
 469
 470                 layout['updatemenus'] = list([
 471                     dict(
 472                         active=0,
 473                         type="dropdown",
 474                         direction="down",
 475                         xanchor="left",
 476                         yanchor="bottom",
 477                         x=-0.12,
 478                         y=1.0,
 479                         buttons=buttons
 480                     )
 481                 ])
 482
 483             name_file = "{0}-{1}{2}".format(spec.cpta["output-file"],
 484                                             graph["output-file-name"],
 485                                             spec.cpta["output-file-type"])
 486
 487             logs.append(("INFO", "    Writing the file '{0}' ...".
 488                          format(name_file)))
 489             plpl = plgo.Figure(data=traces, layout=layout)
 490             try:
 491                 ploff.plot(plpl, show_link=False, auto_open=False,
 492                            filename=name_file)
 493             except plerr.PlotlyEmptyDataError:
 494                 logs.append(("WARNING", "No data for the plot. Skipped."))
 495
 496         for level, line in logs:
 497             if level == "INFO":
 498                 logging.info(line)
 499             elif level == "ERROR":
 500                 logging.error(line)
 501             elif level == "DEBUG":
 502                 logging.debug(line)
 503             elif level == "CRITICAL":
 504                 logging.critical(line)
 505             elif level == "WARNING":
 506                 logging.warning(line)
 507
 508         return {"job_name": job_name, "csv_table": csv_tbl, "results": res}
 509
 510     builds_dict = dict()
 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 \
 517                 status != "removed":
 518                 builds_dict[job].append(str(build["build"]))
 519
 520     # Create "build ID": "date" dict:
 521     build_info = 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:
 527             testbed = ""
 528             tb_ip = input_data.metadata(job_name, build).get("testbed", "")
 529             if tb_ip and tb_tbl:
 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", ""),
 534                 testbed
 535             )
 536
 537     anomaly_classifications = dict()
 538
 539     # Create the header:
 540     csv_tables = 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)
 552
 553     for chart in spec.cpta["plots"]:
 554         result = _generate_chart(chart)
 555
 556         csv_tables[result["job_name"]].extend(result["csv_table"])
 557
 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"])
 561
 562     # Write the tables:
 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)
 567
 568         txt_table = None
 569         with open("{0}.csv".format(file_name), 'rb') as csv_file:
 570             csv_content = csv.reader(csv_file, delimiter=',', quotechar='"')
 571             line_nr = 0
 572             for row in csv_content:
 573                 if txt_table is None:
 574                     txt_table = prettytable.PrettyTable(row)
 575                 else:
 576                     if line_nr > 1:
 577                         for idx, item in enumerate(row):
 578                             try:
 579                                 row[idx] = str(round(float(item) / 1000000, 2))
 580                             except ValueError:
 581                                 pass
 582                     try:
 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))
 587                 line_nr += 1
 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))
 591
 592     # Evaluate result:
 593     if anomaly_classifications:
 594         result = "PASS"
 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":
 604                         result = "FAIL"
 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')
 611     else:
 612         result = "FAIL"
 613
 614     logging.info("Partial results: {0}".format(anomaly_classifications))
 615     logging.info("Result: {0}".format(result))
 616
 617     return result