resources/tools/presentation/generator_tables.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 """Algorithms to generate tables.
  15 """
  16
  17
  18 import logging
  19 import csv
  20 import re
  21
  22 from string import replace
  23 from collections import OrderedDict
  24 from numpy import nan, isnan
  25 from xml.etree import ElementTree as ET
  26 from datetime import datetime as dt
  27 from datetime import timedelta
  28
  29 from utils import mean, stdev, relative_change, classify_anomalies, \
  30     convert_csv_to_pretty_txt, relative_change_stdev
  31
  32
  33 REGEX_NIC = re.compile(r'\d*ge\dp\d\D*\d*')
  34
  35
  36 def generate_tables(spec, data):
  37     """Generate all tables specified in the specification file.
  38
  39     :param spec: Specification read from the specification file.
  40     :param data: Data to process.
  41     :type spec: Specification
  42     :type data: InputData
  43     """
  44
  45     logging.info("Generating the tables ...")
  46     for table in spec.tables:
  47         try:
  48             eval(table["algorithm"])(table, data)
  49         except NameError as err:
  50             logging.error("Probably algorithm '{alg}' is not defined: {err}".
  51                           format(alg=table["algorithm"], err=repr(err)))
  52     logging.info("Done.")
  53
  54
  55 def table_details(table, input_data):
  56     """Generate the table(s) with algorithm: table_detailed_test_results
  57     specified in the specification file.
  58
  59     :param table: Table to generate.
  60     :param input_data: Data to process.
  61     :type table: pandas.Series
  62     :type input_data: InputData
  63     """
  64
  65     logging.info("  Generating the table {0} ...".
  66                  format(table.get("title", "")))
  67
  68     # Transform the data
  69     logging.info("    Creating the data set for the {0} '{1}'.".
  70                  format(table.get("type", ""), table.get("title", "")))
  71     data = input_data.filter_data(table)
  72
  73     # Prepare the header of the tables
  74     header = list()
  75     for column in table["columns"]:
  76         header.append('"{0}"'.format(str(column["title"]).replace('"', '""')))
  77
  78     # Generate the data for the table according to the model in the table
  79     # specification
  80     job = table["data"].keys()[0]
  81     build = str(table["data"][job][0])
  82     try:
  83         suites = input_data.suites(job, build)
  84     except KeyError:
  85         logging.error("    No data available. The table will not be generated.")
  86         return
  87
  88     for suite_longname, suite in suites.iteritems():
  89         # Generate data
  90         suite_name = suite["name"]
  91         table_lst = list()
  92         for test in data[job][build].keys():
  93             if data[job][build][test]["parent"] in suite_name:
  94                 row_lst = list()
  95                 for column in table["columns"]:
  96                     try:
  97                         col_data = str(data[job][build][test][column["data"].
  98                                        split(" ")[1]]).replace('"', '""')
  99                         if column["data"].split(" ")[1] in ("conf-history",
 100                                                             "show-run"):
 101                             col_data = replace(col_data, " |br| ", "",
 102                                                maxreplace=1)
 103                             col_data = " |prein| {0} |preout| ".\
 104                                 format(col_data[:-5])
 105                         row_lst.append('"{0}"'.format(col_data))
 106                     except KeyError:
 107                         row_lst.append("No data")
 108                 table_lst.append(row_lst)
 109
 110         # Write the data to file
 111         if table_lst:
 112             file_name = "{0}_{1}{2}".format(table["output-file"], suite_name,
 113                                             table["output-file-ext"])
 114             logging.info("      Writing file: '{}'".format(file_name))
 115             with open(file_name, "w") as file_handler:
 116                 file_handler.write(",".join(header) + "\n")
 117                 for item in table_lst:
 118                     file_handler.write(",".join(item) + "\n")
 119
 120     logging.info("  Done.")
 121
 122
 123 def table_merged_details(table, input_data):
 124     """Generate the table(s) with algorithm: table_merged_details
 125     specified in the specification file.
 126
 127     :param table: Table to generate.
 128     :param input_data: Data to process.
 129     :type table: pandas.Series
 130     :type input_data: InputData
 131     """
 132
 133     logging.info("  Generating the table {0} ...".
 134                  format(table.get("title", "")))
 135
 136     # Transform the data
 137     logging.info("    Creating the data set for the {0} '{1}'.".
 138                  format(table.get("type", ""), table.get("title", "")))
 139     data = input_data.filter_data(table)
 140     data = input_data.merge_data(data)
 141     data.sort_index(inplace=True)
 142
 143     logging.info("    Creating the data set for the {0} '{1}'.".
 144                  format(table.get("type", ""), table.get("title", "")))
 145     suites = input_data.filter_data(table, data_set="suites")
 146     suites = input_data.merge_data(suites)
 147
 148     # Prepare the header of the tables
 149     header = list()
 150     for column in table["columns"]:
 151         header.append('"{0}"'.format(str(column["title"]).replace('"', '""')))
 152
 153     for _, suite in suites.iteritems():
 154         # Generate data
 155         suite_name = suite["name"]
 156         table_lst = list()
 157         for test in data.keys():
 158             if data[test]["parent"] in suite_name:
 159                 row_lst = list()
 160                 for column in table["columns"]:
 161                     try:
 162                         col_data = str(data[test][column["data"].
 163                                        split(" ")[1]]).replace('"', '""')
 164                         col_data = replace(col_data, "No Data",
 165                                            "Not Captured     ")
 166                         if column["data"].split(" ")[1] in ("conf-history",
 167                                                             "show-run"):
 168                             col_data = replace(col_data, " |br| ", "",
 169                                                maxreplace=1)
 170                             col_data = " |prein| {0} |preout| ".\
 171                                 format(col_data[:-5])
 172                         row_lst.append('"{0}"'.format(col_data))
 173                     except KeyError:
 174                         row_lst.append('"Not captured"')
 175                 table_lst.append(row_lst)
 176
 177         # Write the data to file
 178         if table_lst:
 179             file_name = "{0}_{1}{2}".format(table["output-file"], suite_name,
 180                                             table["output-file-ext"])
 181             logging.info("      Writing file: '{}'".format(file_name))
 182             with open(file_name, "w") as file_handler:
 183                 file_handler.write(",".join(header) + "\n")
 184                 for item in table_lst:
 185                     file_handler.write(",".join(item) + "\n")
 186
 187     logging.info("  Done.")
 188
 189
 190 def table_performance_comparison(table, input_data):
 191     """Generate the table(s) with algorithm: table_performance_comparison
 192     specified in the specification file.
 193
 194     :param table: Table to generate.
 195     :param input_data: Data to process.
 196     :type table: pandas.Series
 197     :type input_data: InputData
 198     """
 199
 200     logging.info("  Generating the table {0} ...".
 201                  format(table.get("title", "")))
 202
 203     # Transform the data
 204     logging.info("    Creating the data set for the {0} '{1}'.".
 205                  format(table.get("type", ""), table.get("title", "")))
 206     data = input_data.filter_data(table, continue_on_error=True)
 207
 208     # Prepare the header of the tables
 209     try:
 210         header = ["Test case", ]
 211
 212         if table["include-tests"] == "MRR":
 213             hdr_param = "Receive Rate"
 214         else:
 215             hdr_param = "Throughput"
 216
 217         history = table.get("history", None)
 218         if history:
 219             for item in history:
 220                 header.extend(
 221                     ["{0} {1} [Mpps]".format(item["title"], hdr_param),
 222                      "{0} Stdev [Mpps]".format(item["title"])])
 223         header.extend(
 224             ["{0} {1} [Mpps]".format(table["reference"]["title"], hdr_param),
 225              "{0} Stdev [Mpps]".format(table["reference"]["title"]),
 226              "{0} {1} [Mpps]".format(table["compare"]["title"], hdr_param),
 227              "{0} Stdev [Mpps]".format(table["compare"]["title"]),
 228              "Delta [%]"])
 229         header_str = ",".join(header) + "\n"
 230     except (AttributeError, KeyError) as err:
 231         logging.error("The model is invalid, missing parameter: {0}".
 232                       format(err))
 233         return
 234
 235     # Prepare data to the table:
 236     tbl_dict = dict()
 237     for job, builds in table["reference"]["data"].items():
 238         for build in builds:
 239             for tst_name, tst_data in data[job][str(build)].iteritems():
 240                 tst_name_mod = tst_name.replace("-ndrpdrdisc", "").\
 241                     replace("-ndrpdr", "").replace("-pdrdisc", "").\
 242                     replace("-ndrdisc", "").replace("-pdr", "").\
 243                     replace("-ndr", "").\
 244                     replace("1t1c", "1c").replace("2t1c", "1c").\
 245                     replace("2t2c", "2c").replace("4t2c", "2c").\
 246                     replace("4t4c", "4c").replace("8t4c", "4c")
 247                 if "across topologies" in table["title"].lower():
 248                     tst_name_mod = tst_name_mod.replace("2n1l-", "")
 249                 if tbl_dict.get(tst_name_mod, None) is None:
 250                     groups = re.search(REGEX_NIC, tst_data["parent"])
 251                     nic = groups.group(0) if groups else ""
 252                     name = "{0}-{1}".format(nic, "-".join(tst_data["name"].
 253                                                           split("-")[:-1]))
 254                     if "across testbeds" in table["title"].lower() or \
 255                             "across topologies" in table["title"].lower():
 256                         name = name.\
 257                             replace("1t1c", "1c").replace("2t1c", "1c").\
 258                             replace("2t2c", "2c").replace("4t2c", "2c").\
 259                             replace("4t4c", "4c").replace("8t4c", "4c")
 260                     tbl_dict[tst_name_mod] = {"name": name,
 261                                               "ref-data": list(),
 262                                               "cmp-data": list()}
 263                 try:
 264                     # TODO: Re-work when NDRPDRDISC tests are not used
 265                     if table["include-tests"] == "MRR":
 266                         tbl_dict[tst_name_mod]["ref-data"]. \
 267                             append(tst_data["result"]["receive-rate"].avg)
 268                     elif table["include-tests"] == "PDR":
 269                         if tst_data["type"] == "PDR":
 270                             tbl_dict[tst_name_mod]["ref-data"]. \
 271                                 append(tst_data["throughput"]["value"])
 272                         elif tst_data["type"] == "NDRPDR":
 273                             tbl_dict[tst_name_mod]["ref-data"].append(
 274                                 tst_data["throughput"]["PDR"]["LOWER"])
 275                     elif table["include-tests"] == "NDR":
 276                         if tst_data["type"] == "NDR":
 277                             tbl_dict[tst_name_mod]["ref-data"]. \
 278                                 append(tst_data["throughput"]["value"])
 279                         elif tst_data["type"] == "NDRPDR":
 280                             tbl_dict[tst_name_mod]["ref-data"].append(
 281                                 tst_data["throughput"]["NDR"]["LOWER"])
 282                     else:
 283                         continue
 284                 except TypeError:
 285                     pass  # No data in output.xml for this test
 286
 287     for job, builds in table["compare"]["data"].items():
 288         for build in builds:
 289             for tst_name, tst_data in data[job][str(build)].iteritems():
 290                 tst_name_mod = tst_name.replace("-ndrpdrdisc", ""). \
 291                     replace("-ndrpdr", "").replace("-pdrdisc", ""). \
 292                     replace("-ndrdisc", "").replace("-pdr", ""). \
 293                     replace("-ndr", "").\
 294                     replace("1t1c", "1c").replace("2t1c", "1c").\
 295                     replace("2t2c", "2c").replace("4t2c", "2c").\
 296                     replace("4t4c", "4c").replace("8t4c", "4c")
 297                 if "across topologies" in table["title"].lower():
 298                     tst_name_mod = tst_name_mod.replace("2n1l-", "")
 299                 try:
 300                     # TODO: Re-work when NDRPDRDISC tests are not used
 301                     if table["include-tests"] == "MRR":
 302                         tbl_dict[tst_name_mod]["cmp-data"]. \
 303                             append(tst_data["result"]["receive-rate"].avg)
 304                     elif table["include-tests"] == "PDR":
 305                         if tst_data["type"] == "PDR":
 306                             tbl_dict[tst_name_mod]["cmp-data"]. \
 307                                 append(tst_data["throughput"]["value"])
 308                         elif tst_data["type"] == "NDRPDR":
 309                             tbl_dict[tst_name_mod]["cmp-data"].append(
 310                                 tst_data["throughput"]["PDR"]["LOWER"])
 311                     elif table["include-tests"] == "NDR":
 312                         if tst_data["type"] == "NDR":
 313                             tbl_dict[tst_name_mod]["cmp-data"]. \
 314                                 append(tst_data["throughput"]["value"])
 315                         elif tst_data["type"] == "NDRPDR":
 316                             tbl_dict[tst_name_mod]["cmp-data"].append(
 317                                 tst_data["throughput"]["NDR"]["LOWER"])
 318                     else:
 319                         continue
 320                 except KeyError:
 321                     pass
 322                 except TypeError:
 323                     tbl_dict.pop(tst_name_mod, None)
 324     if history:
 325         for item in history:
 326             for job, builds in item["data"].items():
 327                 for build in builds:
 328                     for tst_name, tst_data in data[job][str(build)].iteritems():
 329                         tst_name_mod = tst_name.replace("-ndrpdrdisc", ""). \
 330                             replace("-ndrpdr", "").replace("-pdrdisc", ""). \
 331                             replace("-ndrdisc", "").replace("-pdr", ""). \
 332                             replace("-ndr", "").\
 333                             replace("1t1c", "1c").replace("2t1c", "1c").\
 334                             replace("2t2c", "2c").replace("4t2c", "2c").\
 335                             replace("4t4c", "4c").replace("8t4c", "4c")
 336                         if "across topologies" in table["title"].lower():
 337                             tst_name_mod = tst_name_mod.replace("2n1l-", "")
 338                         if tbl_dict.get(tst_name_mod, None) is None:
 339                             continue
 340                         if tbl_dict[tst_name_mod].get("history", None) is None:
 341                             tbl_dict[tst_name_mod]["history"] = OrderedDict()
 342                         if tbl_dict[tst_name_mod]["history"].get(item["title"],
 343                                                              None) is None:
 344                             tbl_dict[tst_name_mod]["history"][item["title"]] = \
 345                                 list()
 346                         try:
 347                             # TODO: Re-work when NDRPDRDISC tests are not used
 348                             if table["include-tests"] == "MRR":
 349                                 tbl_dict[tst_name_mod]["history"][item["title"
 350                                 ]].append(tst_data["result"]["receive-rate"].
 351                                           avg)
 352                             elif table["include-tests"] == "PDR":
 353                                 if tst_data["type"] == "PDR":
 354                                     tbl_dict[tst_name_mod]["history"][
 355                                         item["title"]].\
 356                                         append(tst_data["throughput"]["value"])
 357                                 elif tst_data["type"] == "NDRPDR":
 358                                     tbl_dict[tst_name_mod]["history"][item[
 359                                         "title"]].append(tst_data["throughput"][
 360                                         "PDR"]["LOWER"])
 361                             elif table["include-tests"] == "NDR":
 362                                 if tst_data["type"] == "NDR":
 363                                     tbl_dict[tst_name_mod]["history"][
 364                                         item["title"]].\
 365                                         append(tst_data["throughput"]["value"])
 366                                 elif tst_data["type"] == "NDRPDR":
 367                                     tbl_dict[tst_name_mod]["history"][item[
 368                                         "title"]].append(tst_data["throughput"][
 369                                         "NDR"]["LOWER"])
 370                             else:
 371                                 continue
 372                         except (TypeError, KeyError):
 373                             pass
 374
 375     tbl_lst = list()
 376     for tst_name in tbl_dict.keys():
 377         item = [tbl_dict[tst_name]["name"], ]
 378         if history:
 379             if tbl_dict[tst_name].get("history", None) is not None:
 380                 for hist_data in tbl_dict[tst_name]["history"].values():
 381                     if hist_data:
 382                         item.append(round(mean(hist_data) / 1000000, 2))
 383                         item.append(round(stdev(hist_data) / 1000000, 2))
 384                     else:
 385                         item.extend([None, None])
 386             else:
 387                 item.extend([None, None])
 388         data_t = tbl_dict[tst_name]["ref-data"]
 389         if data_t:
 390             item.append(round(mean(data_t) / 1000000, 2))
 391             item.append(round(stdev(data_t) / 1000000, 2))
 392         else:
 393             item.extend([None, None])
 394         data_t = tbl_dict[tst_name]["cmp-data"]
 395         if data_t:
 396             item.append(round(mean(data_t) / 1000000, 2))
 397             item.append(round(stdev(data_t) / 1000000, 2))
 398         else:
 399             item.extend([None, None])
 400         if item[-4] is not None and item[-2] is not None and item[-4] != 0:
 401             item.append(int(relative_change(float(item[-4]), float(item[-2]))))
 402         if len(item) == len(header):
 403             tbl_lst.append(item)
 404
 405     # Sort the table according to the relative change
 406     tbl_lst.sort(key=lambda rel: rel[-1], reverse=True)
 407
 408     # Generate csv tables:
 409     csv_file = "{0}.csv".format(table["output-file"])
 410     with open(csv_file, "w") as file_handler:
 411         file_handler.write(header_str)
 412         for test in tbl_lst:
 413             file_handler.write(",".join([str(item) for item in test]) + "\n")
 414
 415     convert_csv_to_pretty_txt(csv_file, "{0}.txt".format(table["output-file"]))
 416
 417
 418 def table_nics_comparison(table, input_data):
 419     """Generate the table(s) with algorithm: table_nics_comparison
 420     specified in the specification file.
 421
 422     :param table: Table to generate.
 423     :param input_data: Data to process.
 424     :type table: pandas.Series
 425     :type input_data: InputData
 426     """
 427
 428     logging.info("  Generating the table {0} ...".
 429                  format(table.get("title", "")))
 430
 431     # Transform the data
 432     logging.info("    Creating the data set for the {0} '{1}'.".
 433                  format(table.get("type", ""), table.get("title", "")))
 434     data = input_data.filter_data(table, continue_on_error=True)
 435
 436     # Prepare the header of the tables
 437     try:
 438         header = ["Test case", ]
 439
 440         if table["include-tests"] == "MRR":
 441             hdr_param = "Receive Rate"
 442         else:
 443             hdr_param = "Throughput"
 444
 445         header.extend(
 446             ["{0} {1} [Mpps]".format(table["reference"]["title"], hdr_param),
 447              "{0} Stdev [Mpps]".format(table["reference"]["title"]),
 448              "{0} {1} [Mpps]".format(table["compare"]["title"], hdr_param),
 449              "{0} Stdev [Mpps]".format(table["compare"]["title"]),
 450              "Delta [%]"])
 451         header_str = ",".join(header) + "\n"
 452     except (AttributeError, KeyError) as err:
 453         logging.error("The model is invalid, missing parameter: {0}".
 454                       format(err))
 455         return
 456
 457     # Prepare data to the table:
 458     tbl_dict = dict()
 459     for job, builds in table["data"].items():
 460         for build in builds:
 461             for tst_name, tst_data in data[job][str(build)].iteritems():
 462                 tst_name_mod = tst_name.replace("-ndrpdrdisc", "").\
 463                     replace("-ndrpdr", "").replace("-pdrdisc", "").\
 464                     replace("-ndrdisc", "").replace("-pdr", "").\
 465                     replace("-ndr", "").\
 466                     replace("1t1c", "1c").replace("2t1c", "1c").\
 467                     replace("2t2c", "2c").replace("4t2c", "2c").\
 468                     replace("4t4c", "4c").replace("8t4c", "4c")
 469                 tst_name_mod = re.sub(REGEX_NIC, "", tst_name_mod)
 470                 if tbl_dict.get(tst_name_mod, None) is None:
 471                     name = "-".join(tst_data["name"].split("-")[:-1])
 472                     tbl_dict[tst_name_mod] = {"name": name,
 473                                               "ref-data": list(),
 474                                               "cmp-data": list()}
 475                 try:
 476                     if table["include-tests"] == "MRR":
 477                         result = tst_data["result"]["receive-rate"].avg
 478                     elif table["include-tests"] == "PDR":
 479                         result = tst_data["throughput"]["PDR"]["LOWER"]
 480                     elif table["include-tests"] == "NDR":
 481                         result = tst_data["throughput"]["NDR"]["LOWER"]
 482                     else:
 483                         result = None
 484
 485                     if result:
 486                         if table["reference"]["nic"] in tst_data["tags"]:
 487                             tbl_dict[tst_name_mod]["ref-data"].append(result)
 488                         elif table["compare"]["nic"] in tst_data["tags"]:
 489                             tbl_dict[tst_name_mod]["cmp-data"].append(result)
 490                 except (TypeError, KeyError) as err:
 491                     logging.debug("No data for {0}".format(tst_name))
 492                     logging.debug(repr(err))
 493                     # No data in output.xml for this test
 494
 495     tbl_lst = list()
 496     for tst_name in tbl_dict.keys():
 497         item = [tbl_dict[tst_name]["name"], ]
 498         data_t = tbl_dict[tst_name]["ref-data"]
 499         if data_t:
 500             item.append(round(mean(data_t) / 1000000, 2))
 501             item.append(round(stdev(data_t) / 1000000, 2))
 502         else:
 503             item.extend([None, None])
 504         data_t = tbl_dict[tst_name]["cmp-data"]
 505         if data_t:
 506             item.append(round(mean(data_t) / 1000000, 2))
 507             item.append(round(stdev(data_t) / 1000000, 2))
 508         else:
 509             item.extend([None, None])
 510         if item[-4] is not None and item[-2] is not None and item[-4] != 0:
 511             item.append(int(relative_change(float(item[-4]), float(item[-2]))))
 512         if len(item) == len(header):
 513             tbl_lst.append(item)
 514
 515     # Sort the table according to the relative change
 516     tbl_lst.sort(key=lambda rel: rel[-1], reverse=True)
 517
 518     # Generate csv tables:
 519     csv_file = "{0}.csv".format(table["output-file"])
 520     with open(csv_file, "w") as file_handler:
 521         file_handler.write(header_str)
 522         for test in tbl_lst:
 523             file_handler.write(",".join([str(item) for item in test]) + "\n")
 524
 525     convert_csv_to_pretty_txt(csv_file, "{0}.txt".format(table["output-file"]))
 526
 527
 528 def table_soak_vs_ndr(table, input_data):
 529     """Generate the table(s) with algorithm: table_soak_vs_ndr
 530     specified in the specification file.
 531
 532     :param table: Table to generate.
 533     :param input_data: Data to process.
 534     :type table: pandas.Series
 535     :type input_data: InputData
 536     """
 537
 538     logging.info("  Generating the table {0} ...".
 539                  format(table.get("title", "")))
 540
 541     # Transform the data
 542     logging.info("    Creating the data set for the {0} '{1}'.".
 543                  format(table.get("type", ""), table.get("title", "")))
 544     data = input_data.filter_data(table, continue_on_error=True)
 545
 546     # Prepare the header of the table
 547     try:
 548         header = [
 549             "Test case",
 550             "{0} Throughput [Mpps]".format(table["reference"]["title"]),
 551             "{0} Stdev [Mpps]".format(table["reference"]["title"]),
 552             "{0} Throughput [Mpps]".format(table["compare"]["title"]),
 553             "{0} Stdev [Mpps]".format(table["compare"]["title"]),
 554             "Delta [%]", "Stdev of delta [%]"]
 555         header_str = ",".join(header) + "\n"
 556     except (AttributeError, KeyError) as err:
 557         logging.error("The model is invalid, missing parameter: {0}".
 558                       format(err))
 559         return
 560
 561     # Create a list of available SOAK test results:
 562     tbl_dict = dict()
 563     for job, builds in table["compare"]["data"].items():
 564         for build in builds:
 565             for tst_name, tst_data in data[job][str(build)].iteritems():
 566                 if tst_data["type"] == "SOAK":
 567                     tst_name_mod = tst_name.replace("-soak", "")
 568                     if tbl_dict.get(tst_name_mod, None) is None:
 569                         groups = re.search(REGEX_NIC, tst_data["parent"])
 570                         nic = groups.group(0) if groups else ""
 571                         name = "{0}-{1}".format(nic, "-".join(tst_data["name"].
 572                                                               split("-")[:-1]))
 573                         tbl_dict[tst_name_mod] = {
 574                             "name": name,
 575                             "ref-data": list(),
 576                             "cmp-data": list()
 577                         }
 578                     try:
 579                         tbl_dict[tst_name_mod]["cmp-data"].append(
 580                             tst_data["throughput"]["LOWER"])
 581                     except (KeyError, TypeError):
 582                         pass
 583     tests_lst = tbl_dict.keys()
 584
 585     # Add corresponding NDR test results:
 586     for job, builds in table["reference"]["data"].items():
 587         for build in builds:
 588             for tst_name, tst_data in data[job][str(build)].iteritems():
 589                 tst_name_mod = tst_name.replace("-ndrpdr", "").\
 590                     replace("-mrr", "")
 591                 if tst_name_mod in tests_lst:
 592                     try:
 593                         if tst_data["type"] in ("NDRPDR", "MRR", "BMRR"):
 594                             if table["include-tests"] == "MRR":
 595                                 result = tst_data["result"]["receive-rate"].avg
 596                             elif table["include-tests"] == "PDR":
 597                                 result = tst_data["throughput"]["PDR"]["LOWER"]
 598                             elif table["include-tests"] == "NDR":
 599                                 result = tst_data["throughput"]["NDR"]["LOWER"]
 600                             else:
 601                                 result = None
 602                             if result is not None:
 603                                 tbl_dict[tst_name_mod]["ref-data"].append(
 604                                     result)
 605                     except (KeyError, TypeError):
 606                         continue
 607
 608     tbl_lst = list()
 609     for tst_name in tbl_dict.keys():
 610         item = [tbl_dict[tst_name]["name"], ]
 611         data_r = tbl_dict[tst_name]["ref-data"]
 612         if data_r:
 613             data_r_mean = mean(data_r)
 614             item.append(round(data_r_mean / 1000000, 2))
 615             data_r_stdev = stdev(data_r)
 616             item.append(round(data_r_stdev / 1000000, 2))
 617         else:
 618             data_r_mean = None
 619             data_r_stdev = None
 620             item.extend([None, None])
 621         data_c = tbl_dict[tst_name]["cmp-data"]
 622         if data_c:
 623             data_c_mean = mean(data_c)
 624             item.append(round(data_c_mean / 1000000, 2))
 625             data_c_stdev = stdev(data_c)
 626             item.append(round(data_c_stdev / 1000000, 2))
 627         else:
 628             data_c_mean = None
 629             data_c_stdev = None
 630             item.extend([None, None])
 631         if data_r_mean and data_c_mean:
 632             delta, d_stdev = relative_change_stdev(
 633                 data_r_mean, data_c_mean, data_r_stdev, data_c_stdev)
 634             item.append(round(delta, 2))
 635             item.append(round(d_stdev, 2))
 636             tbl_lst.append(item)
 637
 638     # Sort the table according to the relative change
 639     tbl_lst.sort(key=lambda rel: rel[-1], reverse=True)
 640
 641     # Generate csv tables:
 642     csv_file = "{0}.csv".format(table["output-file"])
 643     with open(csv_file, "w") as file_handler:
 644         file_handler.write(header_str)
 645         for test in tbl_lst:
 646             file_handler.write(",".join([str(item) for item in test]) + "\n")
 647
 648     convert_csv_to_pretty_txt(csv_file, "{0}.txt".format(table["output-file"]))
 649
 650
 651 def table_performance_trending_dashboard(table, input_data):
 652     """Generate the table(s) with algorithm:
 653     table_performance_trending_dashboard
 654     specified in the specification file.
 655
 656     :param table: Table to generate.
 657     :param input_data: Data to process.
 658     :type table: pandas.Series
 659     :type input_data: InputData
 660     """
 661
 662     logging.info("  Generating the table {0} ...".
 663                  format(table.get("title", "")))
 664
 665     # Transform the data
 666     logging.info("    Creating the data set for the {0} '{1}'.".
 667                  format(table.get("type", ""), table.get("title", "")))
 668     data = input_data.filter_data(table, continue_on_error=True)
 669
 670     # Prepare the header of the tables
 671     header = ["Test Case",
 672               "Trend [Mpps]",
 673               "Short-Term Change [%]",
 674               "Long-Term Change [%]",
 675               "Regressions [#]",
 676               "Progressions [#]"
 677               ]
 678     header_str = ",".join(header) + "\n"
 679
 680     # Prepare data to the table:
 681     tbl_dict = dict()
 682     for job, builds in table["data"].items():
 683         for build in builds:
 684             for tst_name, tst_data in data[job][str(build)].iteritems():
 685                 if tst_name.lower() in table["ignore-list"]:
 686                     continue
 687                 if tbl_dict.get(tst_name, None) is None:
 688                     groups = re.search(REGEX_NIC, tst_data["parent"])
 689                     if not groups:
 690                         continue
 691                     nic = groups.group(0)
 692                     tbl_dict[tst_name] = {
 693                         "name": "{0}-{1}".format(nic, tst_data["name"]),
 694                         "data": OrderedDict()}
 695                 try:
 696                     tbl_dict[tst_name]["data"][str(build)] = \
 697                         tst_data["result"]["receive-rate"]
 698                 except (TypeError, KeyError):
 699                     pass  # No data in output.xml for this test
 700
 701     tbl_lst = list()
 702     for tst_name in tbl_dict.keys():
 703         data_t = tbl_dict[tst_name]["data"]
 704         if len(data_t) < 2:
 705             continue
 706
 707         classification_lst, avgs = classify_anomalies(data_t)
 708
 709         win_size = min(len(data_t), table["window"])
 710         long_win_size = min(len(data_t), table["long-trend-window"])
 711
 712         try:
 713             max_long_avg = max(
 714                 [x for x in avgs[-long_win_size:-win_size]
 715                  if not isnan(x)])
 716         except ValueError:
 717             max_long_avg = nan
 718         last_avg = avgs[-1]
 719         avg_week_ago = avgs[max(-win_size, -len(avgs))]
 720
 721         if isnan(last_avg) or isnan(avg_week_ago) or avg_week_ago == 0.0:
 722             rel_change_last = nan
 723         else:
 724             rel_change_last = round(
 725                 ((last_avg - avg_week_ago) / avg_week_ago) * 100, 2)
 726
 727         if isnan(max_long_avg) or isnan(last_avg) or max_long_avg == 0.0:
 728             rel_change_long = nan
 729         else:
 730             rel_change_long = round(
 731                 ((last_avg - max_long_avg) / max_long_avg) * 100, 2)
 732
 733         if classification_lst:
 734             if isnan(rel_change_last) and isnan(rel_change_long):
 735                 continue
 736             if (isnan(last_avg) or
 737                 isnan(rel_change_last) or
 738                 isnan(rel_change_long)):
 739                 continue
 740             tbl_lst.append(
 741                 [tbl_dict[tst_name]["name"],
 742                  round(last_avg / 1000000, 2),
 743                  rel_change_last,
 744                  rel_change_long,
 745                  classification_lst[-win_size:].count("regression"),
 746                  classification_lst[-win_size:].count("progression")])
 747
 748     tbl_lst.sort(key=lambda rel: rel[0])
 749
 750     tbl_sorted = list()
 751     for nrr in range(table["window"], -1, -1):
 752         tbl_reg = [item for item in tbl_lst if item[4] == nrr]
 753         for nrp in range(table["window"], -1, -1):
 754             tbl_out = [item for item in tbl_reg if item[5] == nrp]
 755             tbl_out.sort(key=lambda rel: rel[2])
 756             tbl_sorted.extend(tbl_out)
 757
 758     file_name = "{0}{1}".format(table["output-file"], table["output-file-ext"])
 759
 760     logging.info("    Writing file: '{0}'".format(file_name))
 761     with open(file_name, "w") as file_handler:
 762         file_handler.write(header_str)
 763         for test in tbl_sorted:
 764             file_handler.write(",".join([str(item) for item in test]) + '\n')
 765
 766     txt_file_name = "{0}.txt".format(table["output-file"])
 767     logging.info("    Writing file: '{0}'".format(txt_file_name))
 768     convert_csv_to_pretty_txt(file_name, txt_file_name)
 769
 770
 771 def _generate_url(base, testbed, test_name):
 772     """Generate URL to a trending plot from the name of the test case.
 773
 774     :param base: The base part of URL common to all test cases.
 775     :param testbed: The testbed used for testing.
 776     :param test_name: The name of the test case.
 777     :type base: str
 778     :type testbed: str
 779     :type test_name: str
 780     :returns: The URL to the plot with the trending data for the given test
 781         case.
 782     :rtype str
 783     """
 784
 785     url = base
 786     file_name = ""
 787     anchor = ".html#"
 788     feature = ""
 789
 790     if "lbdpdk" in test_name or "lbvpp" in test_name:
 791         file_name = "link_bonding"
 792
 793     elif "114b" in test_name and "vhost" in test_name:
 794         file_name = "vts"
 795
 796     elif "testpmd" in test_name or "l3fwd" in test_name:
 797         file_name = "dpdk"
 798
 799     elif "memif" in test_name:
 800         file_name = "container_memif"
 801         feature = "-base"
 802
 803     elif "srv6" in test_name:
 804         file_name = "srv6"
 805
 806     elif "vhost" in test_name:
 807         if "l2xcbase" in test_name or "l2bdbasemaclrn" in test_name:
 808             file_name = "vm_vhost_l2"
 809             if "114b" in test_name:
 810                 feature = ""
 811             elif "l2xcbase" in test_name and "x520" in test_name:
 812                 feature = "-base-l2xc"
 813             elif "l2bdbasemaclrn" in test_name and "x520" in test_name:
 814                 feature = "-base-l2bd"
 815             else:
 816                 feature = "-base"
 817         elif "ip4base" in test_name:
 818             file_name = "vm_vhost_ip4"
 819             feature = "-base"
 820
 821     elif "ipsecbasetnlsw" in test_name:
 822         file_name = "ipsecsw"
 823         feature = "-base-scale"
 824
 825     elif "ipsec" in test_name:
 826         file_name = "ipsec"
 827         feature = "-base-scale"
 828
 829     elif "ethip4lispip" in test_name or "ethip4vxlan" in test_name:
 830         file_name = "ip4_tunnels"
 831         feature = "-base"
 832
 833     elif "ip4base" in test_name or "ip4scale" in test_name:
 834         file_name = "ip4"
 835         if "xl710" in test_name:
 836             feature = "-base-scale-features"
 837         elif "iacl" in test_name:
 838             feature = "-features-iacl"
 839         elif "oacl" in test_name:
 840             feature = "-features-oacl"
 841         elif "snat" in test_name or "cop" in test_name:
 842             feature = "-features"
 843         else:
 844             feature = "-base-scale"
 845
 846     elif "ip6base" in test_name or "ip6scale" in test_name:
 847         file_name = "ip6"
 848         feature = "-base-scale"
 849
 850     elif "l2xcbase" in test_name or "l2xcscale" in test_name \
 851             or "l2bdbasemaclrn" in test_name or "l2bdscale" in test_name \
 852             or "l2dbbasemaclrn" in test_name or "l2dbscale" in test_name:
 853         file_name = "l2"
 854         if "macip" in test_name:
 855             feature = "-features-macip"
 856         elif "iacl" in test_name:
 857             feature = "-features-iacl"
 858         elif "oacl" in test_name:
 859             feature = "-features-oacl"
 860         else:
 861             feature = "-base-scale"
 862
 863     if "x520" in test_name:
 864         nic = "x520-"
 865     elif "x710" in test_name:
 866         nic = "x710-"
 867     elif "xl710" in test_name:
 868         nic = "xl710-"
 869     elif "xxv710" in test_name:
 870         nic = "xxv710-"
 871     elif "vic1227" in test_name:
 872         nic = "vic1227-"
 873     elif "vic1385" in test_name:
 874         nic = "vic1385-"
 875     else:
 876         nic = ""
 877     anchor += nic
 878
 879     if "64b" in test_name:
 880         framesize = "64b"
 881     elif "78b" in test_name:
 882         framesize = "78b"
 883     elif "imix" in test_name:
 884         framesize = "imix"
 885     elif "9000b" in test_name:
 886         framesize = "9000b"
 887     elif "1518b" in test_name:
 888         framesize = "1518b"
 889     elif "114b" in test_name:
 890         framesize = "114b"
 891     else:
 892         framesize = ""
 893     anchor += framesize + '-'
 894
 895     if "1t1c" in test_name:
 896         anchor += "1t1c"
 897     elif "2t2c" in test_name:
 898         anchor += "2t2c"
 899     elif "4t4c" in test_name:
 900         anchor += "4t4c"
 901     elif "2t1c" in test_name:
 902         anchor += "2t1c"
 903     elif "4t2c" in test_name:
 904         anchor += "4t2c"
 905     elif "8t4c" in test_name:
 906         anchor += "8t4c"
 907
 908     return url + file_name + '-' + testbed + '-' + nic + framesize + feature + \
 909            anchor + feature
 910
 911
 912 def table_performance_trending_dashboard_html(table, input_data):
 913     """Generate the table(s) with algorithm:
 914     table_performance_trending_dashboard_html specified in the specification
 915     file.
 916
 917     :param table: Table to generate.
 918     :param input_data: Data to process.
 919     :type table: dict
 920     :type input_data: InputData
 921     """
 922
 923     testbed = table.get("testbed", None)
 924     if testbed is None:
 925         logging.error("The testbed is not defined for the table '{0}'.".
 926                       format(table.get("title", "")))
 927         return
 928
 929     logging.info("  Generating the table {0} ...".
 930                  format(table.get("title", "")))
 931
 932     try:
 933         with open(table["input-file"], 'rb') as csv_file:
 934             csv_content = csv.reader(csv_file, delimiter=',', quotechar='"')
 935             csv_lst = [item for item in csv_content]
 936     except KeyError:
 937         logging.warning("The input file is not defined.")
 938         return
 939     except csv.Error as err:
 940         logging.warning("Not possible to process the file '{0}'.\n{1}".
 941                         format(table["input-file"], err))
 942         return
 943
 944     # Table:
 945     dashboard = ET.Element("table", attrib=dict(width="100%", border='0'))
 946
 947     # Table header:
 948     tr = ET.SubElement(dashboard, "tr", attrib=dict(bgcolor="#7eade7"))
 949     for idx, item in enumerate(csv_lst[0]):
 950         alignment = "left" if idx == 0 else "center"
 951         th = ET.SubElement(tr, "th", attrib=dict(align=alignment))
 952         th.text = item
 953
 954     # Rows:
 955     colors = {"regression": ("#ffcccc", "#ff9999"),
 956               "progression": ("#c6ecc6", "#9fdf9f"),
 957               "normal": ("#e9f1fb", "#d4e4f7")}
 958     for r_idx, row in enumerate(csv_lst[1:]):
 959         if int(row[4]):
 960             color = "regression"
 961         elif int(row[5]):
 962             color = "progression"
 963         else:
 964             color = "normal"
 965         background = colors[color][r_idx % 2]
 966         tr = ET.SubElement(dashboard, "tr", attrib=dict(bgcolor=background))
 967
 968         # Columns:
 969         for c_idx, item in enumerate(row):
 970             alignment = "left" if c_idx == 0 else "center"
 971             td = ET.SubElement(tr, "td", attrib=dict(align=alignment))
 972             # Name:
 973             if c_idx == 0:
 974                 url = _generate_url("../trending/", testbed, item)
 975                 ref = ET.SubElement(td, "a", attrib=dict(href=url))
 976                 ref.text = item
 977             else:
 978                 td.text = item
 979     try:
 980         with open(table["output-file"], 'w') as html_file:
 981             logging.info("    Writing file: '{0}'".format(table["output-file"]))
 982             html_file.write(".. raw:: html\n\n\t")
 983             html_file.write(ET.tostring(dashboard))
 984             html_file.write("\n\t<p><br><br></p>\n")
 985     except KeyError:
 986         logging.warning("The output file is not defined.")
 987         return
 988
 989
 990 def table_last_failed_tests(table, input_data):
 991     """Generate the table(s) with algorithm: table_last_failed_tests
 992     specified in the specification file.
 993
 994     :param table: Table to generate.
 995     :param input_data: Data to process.
 996     :type table: pandas.Series
 997     :type input_data: InputData
 998     """
 999
1000     logging.info("  Generating the table {0} ...".
1001                  format(table.get("title", "")))
1002
1003     # Transform the data
1004     logging.info("    Creating the data set for the {0} '{1}'.".
1005                  format(table.get("type", ""), table.get("title", "")))
1006     data = input_data.filter_data(table, continue_on_error=True)
1007
1008     if data is None or data.empty:
1009         logging.warn("    No data for the {0} '{1}'.".
1010                      format(table.get("type", ""), table.get("title", "")))
1011         return
1012
1013     tbl_list = list()
1014     for job, builds in table["data"].items():
1015         for build in builds:
1016             build = str(build)
1017             try:
1018                 version = input_data.metadata(job, build).get("version", "")
1019             except KeyError:
1020                 logging.error("Data for {job}: {build} is not present.".
1021                               format(job=job, build=build))
1022                 return
1023             tbl_list.append(build)
1024             tbl_list.append(version)
1025             for tst_name, tst_data in data[job][build].iteritems():
1026                 if tst_data["status"] != "FAIL":
1027                     continue
1028                 groups = re.search(REGEX_NIC, tst_data["parent"])
1029                 if not groups:
1030                     continue
1031                 nic = groups.group(0)
1032                 tbl_list.append("{0}-{1}".format(nic, tst_data["name"]))
1033
1034     file_name = "{0}{1}".format(table["output-file"], table["output-file-ext"])
1035     logging.info("    Writing file: '{0}'".format(file_name))
1036     with open(file_name, "w") as file_handler:
1037         for test in tbl_list:
1038             file_handler.write(test + '\n')
1039
1040
1041 def table_failed_tests(table, input_data):
1042     """Generate the table(s) with algorithm: table_failed_tests
1043     specified in the specification file.
1044
1045     :param table: Table to generate.
1046     :param input_data: Data to process.
1047     :type table: pandas.Series
1048     :type input_data: InputData
1049     """
1050
1051     logging.info("  Generating the table {0} ...".
1052                  format(table.get("title", "")))
1053
1054     # Transform the data
1055     logging.info("    Creating the data set for the {0} '{1}'.".
1056                  format(table.get("type", ""), table.get("title", "")))
1057     data = input_data.filter_data(table, continue_on_error=True)
1058
1059     # Prepare the header of the tables
1060     header = ["Test Case",
1061               "Failures [#]",
1062               "Last Failure [Time]",
1063               "Last Failure [VPP-Build-Id]",
1064               "Last Failure [CSIT-Job-Build-Id]"]
1065
1066     # Generate the data for the table according to the model in the table
1067     # specification
1068
1069     now = dt.utcnow()
1070     timeperiod = timedelta(int(table.get("window", 7)))
1071
1072     tbl_dict = dict()
1073     for job, builds in table["data"].items():
1074         for build in builds:
1075             build = str(build)
1076             for tst_name, tst_data in data[job][build].iteritems():
1077                 if tst_name.lower() in table["ignore-list"]:
1078                     continue
1079                 if tbl_dict.get(tst_name, None) is None:
1080                     groups = re.search(REGEX_NIC, tst_data["parent"])
1081                     if not groups:
1082                         continue
1083                     nic = groups.group(0)
1084                     tbl_dict[tst_name] = {
1085                         "name": "{0}-{1}".format(nic, tst_data["name"]),
1086                         "data": OrderedDict()}
1087                 try:
1088                     generated = input_data.metadata(job, build).\
1089                         get("generated", "")
1090                     if not generated:
1091                         continue
1092                     then = dt.strptime(generated, "%Y%m%d %H:%M")
1093                     if (now - then) <= timeperiod:
1094                         tbl_dict[tst_name]["data"][build] = (
1095                             tst_data["status"],
1096                             generated,
1097                             input_data.metadata(job, build).get("version", ""),
1098                             build)
1099                 except (TypeError, KeyError) as err:
1100                     logging.warning("tst_name: {} - err: {}".
1101                                     format(tst_name, repr(err)))
1102
1103     max_fails = 0
1104     tbl_lst = list()
1105     for tst_data in tbl_dict.values():
1106         fails_nr = 0
1107         for val in tst_data["data"].values():
1108             if val[0] == "FAIL":
1109                 fails_nr += 1
1110                 fails_last_date = val[1]
1111                 fails_last_vpp = val[2]
1112                 fails_last_csit = val[3]
1113         if fails_nr:
1114             max_fails = fails_nr if fails_nr > max_fails else max_fails
1115             tbl_lst.append([tst_data["name"],
1116                             fails_nr,
1117                             fails_last_date,
1118                             fails_last_vpp,
1119                             "mrr-daily-build-{0}".format(fails_last_csit)])
1120
1121     tbl_lst.sort(key=lambda rel: rel[2], reverse=True)
1122     tbl_sorted = list()
1123     for nrf in range(max_fails, -1, -1):
1124         tbl_fails = [item for item in tbl_lst if item[1] == nrf]
1125         tbl_sorted.extend(tbl_fails)
1126     file_name = "{0}{1}".format(table["output-file"], table["output-file-ext"])
1127
1128     logging.info("    Writing file: '{0}'".format(file_name))
1129     with open(file_name, "w") as file_handler:
1130         file_handler.write(",".join(header) + "\n")
1131         for test in tbl_sorted:
1132             file_handler.write(",".join([str(item) for item in test]) + '\n')
1133
1134     txt_file_name = "{0}.txt".format(table["output-file"])
1135     logging.info("    Writing file: '{0}'".format(txt_file_name))
1136     convert_csv_to_pretty_txt(file_name, txt_file_name)
1137
1138
1139 def table_failed_tests_html(table, input_data):
1140     """Generate the table(s) with algorithm: table_failed_tests_html
1141     specified in the specification file.
1142
1143     :param table: Table to generate.
1144     :param input_data: Data to process.
1145     :type table: pandas.Series
1146     :type input_data: InputData
1147     """
1148
1149     testbed = table.get("testbed", None)
1150     if testbed is None:
1151         logging.error("The testbed is not defined for the table '{0}'.".
1152                       format(table.get("title", "")))
1153         return
1154
1155     logging.info("  Generating the table {0} ...".
1156                  format(table.get("title", "")))
1157
1158     try:
1159         with open(table["input-file"], 'rb') as csv_file:
1160             csv_content = csv.reader(csv_file, delimiter=',', quotechar='"')
1161             csv_lst = [item for item in csv_content]
1162     except KeyError:
1163         logging.warning("The input file is not defined.")
1164         return
1165     except csv.Error as err:
1166         logging.warning("Not possible to process the file '{0}'.\n{1}".
1167                         format(table["input-file"], err))
1168         return
1169
1170     # Table:
1171     failed_tests = ET.Element("table", attrib=dict(width="100%", border='0'))
1172
1173     # Table header:
1174     tr = ET.SubElement(failed_tests, "tr", attrib=dict(bgcolor="#7eade7"))
1175     for idx, item in enumerate(csv_lst[0]):
1176         alignment = "left" if idx == 0 else "center"
1177         th = ET.SubElement(tr, "th", attrib=dict(align=alignment))
1178         th.text = item
1179
1180     # Rows:
1181     colors = ("#e9f1fb", "#d4e4f7")
1182     for r_idx, row in enumerate(csv_lst[1:]):
1183         background = colors[r_idx % 2]
1184         tr = ET.SubElement(failed_tests, "tr", attrib=dict(bgcolor=background))
1185
1186         # Columns:
1187         for c_idx, item in enumerate(row):
1188             alignment = "left" if c_idx == 0 else "center"
1189             td = ET.SubElement(tr, "td", attrib=dict(align=alignment))
1190             # Name:
1191             if c_idx == 0:
1192                 url = _generate_url("../trending/", testbed, item)
1193                 ref = ET.SubElement(td, "a", attrib=dict(href=url))
1194                 ref.text = item
1195             else:
1196                 td.text = item
1197     try:
1198         with open(table["output-file"], 'w') as html_file:
1199             logging.info("    Writing file: '{0}'".format(table["output-file"]))
1200             html_file.write(".. raw:: html\n\n\t")
1201             html_file.write(ET.tostring(failed_tests))
1202             html_file.write("\n\t<p><br><br></p>\n")
1203     except KeyError:
1204         logging.warning("The output file is not defined.")
1205         return