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 = list()
 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 test_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(test_name)))
 387                             continue
 388                         if tag in chart_tags[test_name]:
 389                             message = "index: {index}, test: {test}".format(
 390                                 index=index, test=test_name)
 391                             test_name = test_name.split('.')[-1]
 392                             try:
 393                                 trace, rslt = _generate_trending_traces(
 394                                     test_data,
 395                                     job_name=job_name,
 396                                     build_info=build_info,
 397                                     name='-'.join(test_name.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.append(rslt)
 408                             index += 1
 409                             break
 410                 visibility.append(visible)
 411         else:
 412             for test_name, test_data in chart_data.items():
 413                 if not test_data:
 414                     logs.append(("WARNING", "No data for the test '{0}'".
 415                                  format(test_name)))
 416                     continue
 417                 message = "index: {index}, test: {test}".format(
 418                     index=index, test=test_name)
 419                 test_name = test_name.split('.')[-1]
 420                 try:
 421                     trace, rslt = _generate_trending_traces(
 422                         test_data,
 423                         job_name=job_name,
 424                         build_info=build_info,
 425                         name='-'.join(test_name.split('-')[2:-1]),
 426                         color=COLORS[index])
 427                 except IndexError:
 428                     message = "Out of colors: {}".format(message)
 429                     logs.append(("ERROR", message))
 430                     logging.error(message)
 431                     index += 1
 432                     continue
 433                 traces.extend(trace)
 434                 res.append(rslt)
 435                 index += 1
 436
 437         if traces:
 438             # Generate the chart:
 439             try:
 440                 layout = deepcopy(graph["layout"])
 441             except KeyError as err:
 442                 logging.error("Finished with error: No layout defined")
 443                 logging.error(repr(err))
 444                 return
 445             if groups:
 446                 show = list()
 447                 for i in range(len(visibility)):
 448                     visible = list()
 449                     for r in range(len(visibility)):
 450                         for _ in range(len(visibility[r])):
 451                             visible.append(i == r)
 452                     show.append(visible)
 453
 454                 buttons = list()
 455                 buttons.append(dict(
 456                     label="All",
 457                     method="update",
 458                     args=[{"visible": [True for _ in range(len(show[0]))]}, ]
 459                 ))
 460                 for i in range(len(groups)):
 461                     try:
 462                         label = graph["group-names"][i]
 463                     except (IndexError, KeyError):
 464                         label = "Group {num}".format(num=i + 1)
 465                     buttons.append(dict(
 466                         label=label,
 467                         method="update",
 468                         args=[{"visible": show[i]}, ]
 469                     ))
 470
 471                 layout['updatemenus'] = list([
 472                     dict(
 473                         active=0,
 474                         type="dropdown",
 475                         direction="down",
 476                         xanchor="left",
 477                         yanchor="bottom",
 478                         x=-0.12,
 479                         y=1.0,
 480                         buttons=buttons
 481                     )
 482                 ])
 483
 484             name_file = "{0}-{1}{2}".format(spec.cpta["output-file"],
 485                                             graph["output-file-name"],
 486                                             spec.cpta["output-file-type"])
 487
 488             logs.append(("INFO", "    Writing the file '{0}' ...".
 489                          format(name_file)))
 490             plpl = plgo.Figure(data=traces, layout=layout)
 491             try:
 492                 ploff.plot(plpl, show_link=False, auto_open=False,
 493                            filename=name_file)
 494             except plerr.PlotlyEmptyDataError:
 495                 logs.append(("WARNING", "No data for the plot. Skipped."))
 496
 497         for level, line in logs:
 498             if level == "INFO":
 499                 logging.info(line)
 500             elif level == "ERROR":
 501                 logging.error(line)
 502             elif level == "DEBUG":
 503                 logging.debug(line)
 504             elif level == "CRITICAL":
 505                 logging.critical(line)
 506             elif level == "WARNING":
 507                 logging.warning(line)
 508
 509         return {"job_name": job_name, "csv_table": csv_tbl, "results": res}
 510
 511     builds_dict = dict()
 512     for job in spec.input["builds"].keys():
 513         if builds_dict.get(job, None) is None:
 514             builds_dict[job] = list()
 515         for build in spec.input["builds"][job]:
 516             status = build["status"]
 517             if status != "failed" and status != "not found" and \
 518                 status != "removed":
 519                 builds_dict[job].append(str(build["build"]))
 520
 521     # Create "build ID": "date" dict:
 522     build_info = dict()
 523     tb_tbl = spec.environment.get("testbeds", None)
 524     for job_name, job_data in builds_dict.items():
 525         if build_info.get(job_name, None) is None:
 526             build_info[job_name] = OrderedDict()
 527         for build in job_data:
 528             testbed = ""
 529             tb_ip = input_data.metadata(job_name, build).get("testbed", "")
 530             if tb_ip and tb_tbl:
 531                 testbed = tb_tbl.get(tb_ip, "")
 532             build_info[job_name][build] = (
 533                 input_data.metadata(job_name, build).get("generated", ""),
 534                 input_data.metadata(job_name, build).get("version", ""),
 535                 testbed
 536             )
 537
 538     anomaly_classifications = list()
 539
 540     # Create the header:
 541     csv_tables = dict()
 542     for job_name in builds_dict.keys():
 543         if csv_tables.get(job_name, None) is None:
 544             csv_tables[job_name] = list()
 545         header = "Build Number:," + ",".join(builds_dict[job_name]) + '\n'
 546         csv_tables[job_name].append(header)
 547         build_dates = [x[0] for x in build_info[job_name].values()]
 548         header = "Build Date:," + ",".join(build_dates) + '\n'
 549         csv_tables[job_name].append(header)
 550         versions = [x[1] for x in build_info[job_name].values()]
 551         header = "Version:," + ",".join(versions) + '\n'
 552         csv_tables[job_name].append(header)
 553
 554     for chart in spec.cpta["plots"]:
 555         result = _generate_chart(chart)
 556
 557         anomaly_classifications.extend(result["results"])
 558         csv_tables[result["job_name"]].extend(result["csv_table"])
 559
 560     # Write the tables:
 561     for job_name, csv_table in csv_tables.items():
 562         file_name = spec.cpta["output-file"] + "-" + job_name + "-trending"
 563         with open("{0}.csv".format(file_name), 'w') as file_handler:
 564             file_handler.writelines(csv_table)
 565
 566         txt_table = None
 567         with open("{0}.csv".format(file_name), 'rb') as csv_file:
 568             csv_content = csv.reader(csv_file, delimiter=',', quotechar='"')
 569             line_nr = 0
 570             for row in csv_content:
 571                 if txt_table is None:
 572                     txt_table = prettytable.PrettyTable(row)
 573                 else:
 574                     if line_nr > 1:
 575                         for idx, item in enumerate(row):
 576                             try:
 577                                 row[idx] = str(round(float(item) / 1000000, 2))
 578                             except ValueError:
 579                                 pass
 580                     try:
 581                         txt_table.add_row(row)
 582                     except Exception as err:
 583                         logging.warning("Error occurred while generating TXT "
 584                                         "table:\n{0}".format(err))
 585                 line_nr += 1
 586             txt_table.align["Build Number:"] = "l"
 587         with open("{0}.txt".format(file_name), "w") as txt_file:
 588             txt_file.write(str(txt_table))
 589
 590     # Evaluate result:
 591     if anomaly_classifications:
 592         result = "PASS"
 593         for classification in anomaly_classifications:
 594             if classification == "regression" or classification == "outlier":
 595                 result = "FAIL"
 596                 break
 597     else:
 598         result = "FAIL"
 599
 600     logging.info("Partial results: {0}".format(anomaly_classifications))
 601     logging.info("Result: {0}".format(result))
 602
 603     return result