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
  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 [%]"]
 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             item.append(round(stdev(data_r) / 1000000, 2))
 616         else:
 617             data_r_mean = None
 618             item.extend([None, None])
 619         data_c = tbl_dict[tst_name]["cmp-data"]
 620         if data_c:
 621             data_c_mean = mean(data_c)
 622             item.append(round(data_c_mean / 1000000, 2))
 623             item.append(round(stdev(data_c) / 1000000, 2))
 624         else:
 625             data_c_mean = None
 626             item.extend([None, None])
 627         if data_r_mean and data_c_mean is not None:
 628             item.append(round(relative_change(data_r_mean, data_c_mean), 2))
 629             tbl_lst.append(item)
 630
 631     # Sort the table according to the relative change
 632     tbl_lst.sort(key=lambda rel: rel[-1], reverse=True)
 633
 634     # Generate csv tables:
 635     csv_file = "{0}.csv".format(table["output-file"])
 636     with open(csv_file, "w") as file_handler:
 637         file_handler.write(header_str)
 638         for test in tbl_lst:
 639             file_handler.write(",".join([str(item) for item in test]) + "\n")
 640
 641     convert_csv_to_pretty_txt(csv_file, "{0}.txt".format(table["output-file"]))
 642
 643
 644 def table_performance_trending_dashboard(table, input_data):
 645     """Generate the table(s) with algorithm:
 646     table_performance_trending_dashboard
 647     specified in the specification file.
 648
 649     :param table: Table to generate.
 650     :param input_data: Data to process.
 651     :type table: pandas.Series
 652     :type input_data: InputData
 653     """
 654
 655     logging.info("  Generating the table {0} ...".
 656                  format(table.get("title", "")))
 657
 658     # Transform the data
 659     logging.info("    Creating the data set for the {0} '{1}'.".
 660                  format(table.get("type", ""), table.get("title", "")))
 661     data = input_data.filter_data(table, continue_on_error=True)
 662
 663     # Prepare the header of the tables
 664     header = ["Test Case",
 665               "Trend [Mpps]",
 666               "Short-Term Change [%]",
 667               "Long-Term Change [%]",
 668               "Regressions [#]",
 669               "Progressions [#]"
 670               ]
 671     header_str = ",".join(header) + "\n"
 672
 673     # Prepare data to the table:
 674     tbl_dict = dict()
 675     for job, builds in table["data"].items():
 676         for build in builds:
 677             for tst_name, tst_data in data[job][str(build)].iteritems():
 678                 if tst_name.lower() in table["ignore-list"]:
 679                     continue
 680                 if tbl_dict.get(tst_name, None) is None:
 681                     groups = re.search(REGEX_NIC, tst_data["parent"])
 682                     if not groups:
 683                         continue
 684                     nic = groups.group(0)
 685                     tbl_dict[tst_name] = {
 686                         "name": "{0}-{1}".format(nic, tst_data["name"]),
 687                         "data": OrderedDict()}
 688                 try:
 689                     tbl_dict[tst_name]["data"][str(build)] = \
 690                         tst_data["result"]["receive-rate"]
 691                 except (TypeError, KeyError):
 692                     pass  # No data in output.xml for this test
 693
 694     tbl_lst = list()
 695     for tst_name in tbl_dict.keys():
 696         data_t = tbl_dict[tst_name]["data"]
 697         if len(data_t) < 2:
 698             continue
 699
 700         classification_lst, avgs = classify_anomalies(data_t)
 701
 702         win_size = min(len(data_t), table["window"])
 703         long_win_size = min(len(data_t), table["long-trend-window"])
 704
 705         try:
 706             max_long_avg = max(
 707                 [x for x in avgs[-long_win_size:-win_size]
 708                  if not isnan(x)])
 709         except ValueError:
 710             max_long_avg = nan
 711         last_avg = avgs[-1]
 712         avg_week_ago = avgs[max(-win_size, -len(avgs))]
 713
 714         if isnan(last_avg) or isnan(avg_week_ago) or avg_week_ago == 0.0:
 715             rel_change_last = nan
 716         else:
 717             rel_change_last = round(
 718                 ((last_avg - avg_week_ago) / avg_week_ago) * 100, 2)
 719
 720         if isnan(max_long_avg) or isnan(last_avg) or max_long_avg == 0.0:
 721             rel_change_long = nan
 722         else:
 723             rel_change_long = round(
 724                 ((last_avg - max_long_avg) / max_long_avg) * 100, 2)
 725
 726         if classification_lst:
 727             if isnan(rel_change_last) and isnan(rel_change_long):
 728                 continue
 729             if (isnan(last_avg) or
 730                 isnan(rel_change_last) or
 731                 isnan(rel_change_long)):
 732                 continue
 733             tbl_lst.append(
 734                 [tbl_dict[tst_name]["name"],
 735                  round(last_avg / 1000000, 2),
 736                  rel_change_last,
 737                  rel_change_long,
 738                  classification_lst[-win_size:].count("regression"),
 739                  classification_lst[-win_size:].count("progression")])
 740
 741     tbl_lst.sort(key=lambda rel: rel[0])
 742
 743     tbl_sorted = list()
 744     for nrr in range(table["window"], -1, -1):
 745         tbl_reg = [item for item in tbl_lst if item[4] == nrr]
 746         for nrp in range(table["window"], -1, -1):
 747             tbl_out = [item for item in tbl_reg if item[5] == nrp]
 748             tbl_out.sort(key=lambda rel: rel[2])
 749             tbl_sorted.extend(tbl_out)
 750
 751     file_name = "{0}{1}".format(table["output-file"], table["output-file-ext"])
 752
 753     logging.info("    Writing file: '{0}'".format(file_name))
 754     with open(file_name, "w") as file_handler:
 755         file_handler.write(header_str)
 756         for test in tbl_sorted:
 757             file_handler.write(",".join([str(item) for item in test]) + '\n')
 758
 759     txt_file_name = "{0}.txt".format(table["output-file"])
 760     logging.info("    Writing file: '{0}'".format(txt_file_name))
 761     convert_csv_to_pretty_txt(file_name, txt_file_name)
 762
 763
 764 def _generate_url(base, testbed, test_name):
 765     """Generate URL to a trending plot from the name of the test case.
 766
 767     :param base: The base part of URL common to all test cases.
 768     :param testbed: The testbed used for testing.
 769     :param test_name: The name of the test case.
 770     :type base: str
 771     :type testbed: str
 772     :type test_name: str
 773     :returns: The URL to the plot with the trending data for the given test
 774         case.
 775     :rtype str
 776     """
 777
 778     url = base
 779     file_name = ""
 780     anchor = ".html#"
 781     feature = ""
 782
 783     if "lbdpdk" in test_name or "lbvpp" in test_name:
 784         file_name = "link_bonding"
 785
 786     elif "114b" in test_name and "vhost" in test_name:
 787         file_name = "vts"
 788
 789     elif "testpmd" in test_name or "l3fwd" in test_name:
 790         file_name = "dpdk"
 791
 792     elif "memif" in test_name:
 793         file_name = "container_memif"
 794         feature = "-base"
 795
 796     elif "srv6" in test_name:
 797         file_name = "srv6"
 798
 799     elif "vhost" in test_name:
 800         if "l2xcbase" in test_name or "l2bdbasemaclrn" in test_name:
 801             file_name = "vm_vhost_l2"
 802             if "114b" in test_name:
 803                 feature = ""
 804             elif "l2xcbase" in test_name and "x520" in test_name:
 805                 feature = "-base-l2xc"
 806             elif "l2bdbasemaclrn" in test_name and "x520" in test_name:
 807                 feature = "-base-l2bd"
 808             else:
 809                 feature = "-base"
 810         elif "ip4base" in test_name:
 811             file_name = "vm_vhost_ip4"
 812             feature = "-base"
 813
 814     elif "ipsecbasetnlsw" in test_name:
 815         file_name = "ipsecsw"
 816         feature = "-base-scale"
 817
 818     elif "ipsec" in test_name:
 819         file_name = "ipsec"
 820         feature = "-base-scale"
 821
 822     elif "ethip4lispip" in test_name or "ethip4vxlan" in test_name:
 823         file_name = "ip4_tunnels"
 824         feature = "-base"
 825
 826     elif "ip4base" in test_name or "ip4scale" in test_name:
 827         file_name = "ip4"
 828         if "xl710" in test_name:
 829             feature = "-base-scale-features"
 830         elif "iacl" in test_name:
 831             feature = "-features-iacl"
 832         elif "oacl" in test_name:
 833             feature = "-features-oacl"
 834         elif "snat" in test_name or "cop" in test_name:
 835             feature = "-features"
 836         else:
 837             feature = "-base-scale"
 838
 839     elif "ip6base" in test_name or "ip6scale" in test_name:
 840         file_name = "ip6"
 841         feature = "-base-scale"
 842
 843     elif "l2xcbase" in test_name or "l2xcscale" in test_name \
 844             or "l2bdbasemaclrn" in test_name or "l2bdscale" in test_name \
 845             or "l2dbbasemaclrn" in test_name or "l2dbscale" in test_name:
 846         file_name = "l2"
 847         if "macip" in test_name:
 848             feature = "-features-macip"
 849         elif "iacl" in test_name:
 850             feature = "-features-iacl"
 851         elif "oacl" in test_name:
 852             feature = "-features-oacl"
 853         else:
 854             feature = "-base-scale"
 855
 856     if "x520" in test_name:
 857         nic = "x520-"
 858     elif "x710" in test_name:
 859         nic = "x710-"
 860     elif "xl710" in test_name:
 861         nic = "xl710-"
 862     elif "xxv710" in test_name:
 863         nic = "xxv710-"
 864     elif "vic1227" in test_name:
 865         nic = "vic1227-"
 866     elif "vic1385" in test_name:
 867         nic = "vic1385-"
 868     else:
 869         nic = ""
 870     anchor += nic
 871
 872     if "64b" in test_name:
 873         framesize = "64b"
 874     elif "78b" in test_name:
 875         framesize = "78b"
 876     elif "imix" in test_name:
 877         framesize = "imix"
 878     elif "9000b" in test_name:
 879         framesize = "9000b"
 880     elif "1518b" in test_name:
 881         framesize = "1518b"
 882     elif "114b" in test_name:
 883         framesize = "114b"
 884     else:
 885         framesize = ""
 886     anchor += framesize + '-'
 887
 888     if "1t1c" in test_name:
 889         anchor += "1t1c"
 890     elif "2t2c" in test_name:
 891         anchor += "2t2c"
 892     elif "4t4c" in test_name:
 893         anchor += "4t4c"
 894     elif "2t1c" in test_name:
 895         anchor += "2t1c"
 896     elif "4t2c" in test_name:
 897         anchor += "4t2c"
 898     elif "8t4c" in test_name:
 899         anchor += "8t4c"
 900
 901     return url + file_name + '-' + testbed + '-' + nic + framesize + feature + \
 902            anchor + feature
 903
 904
 905 def table_performance_trending_dashboard_html(table, input_data):
 906     """Generate the table(s) with algorithm:
 907     table_performance_trending_dashboard_html specified in the specification
 908     file.
 909
 910     :param table: Table to generate.
 911     :param input_data: Data to process.
 912     :type table: dict
 913     :type input_data: InputData
 914     """
 915
 916     testbed = table.get("testbed", None)
 917     if testbed is None:
 918         logging.error("The testbed is not defined for the table '{0}'.".
 919                       format(table.get("title", "")))
 920         return
 921
 922     logging.info("  Generating the table {0} ...".
 923                  format(table.get("title", "")))
 924
 925     try:
 926         with open(table["input-file"], 'rb') as csv_file:
 927             csv_content = csv.reader(csv_file, delimiter=',', quotechar='"')
 928             csv_lst = [item for item in csv_content]
 929     except KeyError:
 930         logging.warning("The input file is not defined.")
 931         return
 932     except csv.Error as err:
 933         logging.warning("Not possible to process the file '{0}'.\n{1}".
 934                         format(table["input-file"], err))
 935         return
 936
 937     # Table:
 938     dashboard = ET.Element("table", attrib=dict(width="100%", border='0'))
 939
 940     # Table header:
 941     tr = ET.SubElement(dashboard, "tr", attrib=dict(bgcolor="#7eade7"))
 942     for idx, item in enumerate(csv_lst[0]):
 943         alignment = "left" if idx == 0 else "center"
 944         th = ET.SubElement(tr, "th", attrib=dict(align=alignment))
 945         th.text = item
 946
 947     # Rows:
 948     colors = {"regression": ("#ffcccc", "#ff9999"),
 949               "progression": ("#c6ecc6", "#9fdf9f"),
 950               "normal": ("#e9f1fb", "#d4e4f7")}
 951     for r_idx, row in enumerate(csv_lst[1:]):
 952         if int(row[4]):
 953             color = "regression"
 954         elif int(row[5]):
 955             color = "progression"
 956         else:
 957             color = "normal"
 958         background = colors[color][r_idx % 2]
 959         tr = ET.SubElement(dashboard, "tr", attrib=dict(bgcolor=background))
 960
 961         # Columns:
 962         for c_idx, item in enumerate(row):
 963             alignment = "left" if c_idx == 0 else "center"
 964             td = ET.SubElement(tr, "td", attrib=dict(align=alignment))
 965             # Name:
 966             if c_idx == 0:
 967                 url = _generate_url("../trending/", testbed, item)
 968                 ref = ET.SubElement(td, "a", attrib=dict(href=url))
 969                 ref.text = item
 970             else:
 971                 td.text = item
 972     try:
 973         with open(table["output-file"], 'w') as html_file:
 974             logging.info("    Writing file: '{0}'".format(table["output-file"]))
 975             html_file.write(".. raw:: html\n\n\t")
 976             html_file.write(ET.tostring(dashboard))
 977             html_file.write("\n\t<p><br><br></p>\n")
 978     except KeyError:
 979         logging.warning("The output file is not defined.")
 980         return
 981
 982
 983 def table_last_failed_tests(table, input_data):
 984     """Generate the table(s) with algorithm: table_last_failed_tests
 985     specified in the specification file.
 986
 987     :param table: Table to generate.
 988     :param input_data: Data to process.
 989     :type table: pandas.Series
 990     :type input_data: InputData
 991     """
 992
 993     logging.info("  Generating the table {0} ...".
 994                  format(table.get("title", "")))
 995
 996     # Transform the data
 997     logging.info("    Creating the data set for the {0} '{1}'.".
 998                  format(table.get("type", ""), table.get("title", "")))
 999     data = input_data.filter_data(table, continue_on_error=True)
1000
1001     if data is None or data.empty:
1002         logging.warn("    No data for the {0} '{1}'.".
1003                      format(table.get("type", ""), table.get("title", "")))
1004         return
1005
1006     tbl_list = list()
1007     for job, builds in table["data"].items():
1008         for build in builds:
1009             build = str(build)
1010             try:
1011                 version = input_data.metadata(job, build).get("version", "")
1012             except KeyError:
1013                 logging.error("Data for {job}: {build} is not present.".
1014                               format(job=job, build=build))
1015                 return
1016             tbl_list.append(build)
1017             tbl_list.append(version)
1018             for tst_name, tst_data in data[job][build].iteritems():
1019                 if tst_data["status"] != "FAIL":
1020                     continue
1021                 groups = re.search(REGEX_NIC, tst_data["parent"])
1022                 if not groups:
1023                     continue
1024                 nic = groups.group(0)
1025                 tbl_list.append("{0}-{1}".format(nic, tst_data["name"]))
1026
1027     file_name = "{0}{1}".format(table["output-file"], table["output-file-ext"])
1028     logging.info("    Writing file: '{0}'".format(file_name))
1029     with open(file_name, "w") as file_handler:
1030         for test in tbl_list:
1031             file_handler.write(test + '\n')
1032
1033
1034 def table_failed_tests(table, input_data):
1035     """Generate the table(s) with algorithm: table_failed_tests
1036     specified in the specification file.
1037
1038     :param table: Table to generate.
1039     :param input_data: Data to process.
1040     :type table: pandas.Series
1041     :type input_data: InputData
1042     """
1043
1044     logging.info("  Generating the table {0} ...".
1045                  format(table.get("title", "")))
1046
1047     # Transform the data
1048     logging.info("    Creating the data set for the {0} '{1}'.".
1049                  format(table.get("type", ""), table.get("title", "")))
1050     data = input_data.filter_data(table, continue_on_error=True)
1051
1052     # Prepare the header of the tables
1053     header = ["Test Case",
1054               "Failures [#]",
1055               "Last Failure [Time]",
1056               "Last Failure [VPP-Build-Id]",
1057               "Last Failure [CSIT-Job-Build-Id]"]
1058
1059     # Generate the data for the table according to the model in the table
1060     # specification
1061
1062     now = dt.utcnow()
1063     timeperiod = timedelta(int(table.get("window", 7)))
1064
1065     tbl_dict = dict()
1066     for job, builds in table["data"].items():
1067         for build in builds:
1068             build = str(build)
1069             for tst_name, tst_data in data[job][build].iteritems():
1070                 if tst_name.lower() in table["ignore-list"]:
1071                     continue
1072                 if tbl_dict.get(tst_name, None) is None:
1073                     groups = re.search(REGEX_NIC, tst_data["parent"])
1074                     if not groups:
1075                         continue
1076                     nic = groups.group(0)
1077                     tbl_dict[tst_name] = {
1078                         "name": "{0}-{1}".format(nic, tst_data["name"]),
1079                         "data": OrderedDict()}
1080                 try:
1081                     generated = input_data.metadata(job, build).\
1082                         get("generated", "")
1083                     if not generated:
1084                         continue
1085                     then = dt.strptime(generated, "%Y%m%d %H:%M")
1086                     if (now - then) <= timeperiod:
1087                         tbl_dict[tst_name]["data"][build] = (
1088                             tst_data["status"],
1089                             generated,
1090                             input_data.metadata(job, build).get("version", ""),
1091                             build)
1092                 except (TypeError, KeyError) as err:
1093                     logging.warning("tst_name: {} - err: {}".
1094                                     format(tst_name, repr(err)))
1095
1096     max_fails = 0
1097     tbl_lst = list()
1098     for tst_data in tbl_dict.values():
1099         fails_nr = 0
1100         for val in tst_data["data"].values():
1101             if val[0] == "FAIL":
1102                 fails_nr += 1
1103                 fails_last_date = val[1]
1104                 fails_last_vpp = val[2]
1105                 fails_last_csit = val[3]
1106         if fails_nr:
1107             max_fails = fails_nr if fails_nr > max_fails else max_fails
1108             tbl_lst.append([tst_data["name"],
1109                             fails_nr,
1110                             fails_last_date,
1111                             fails_last_vpp,
1112                             "mrr-daily-build-{0}".format(fails_last_csit)])
1113
1114     tbl_lst.sort(key=lambda rel: rel[2], reverse=True)
1115     tbl_sorted = list()
1116     for nrf in range(max_fails, -1, -1):
1117         tbl_fails = [item for item in tbl_lst if item[1] == nrf]
1118         tbl_sorted.extend(tbl_fails)
1119     file_name = "{0}{1}".format(table["output-file"], table["output-file-ext"])
1120
1121     logging.info("    Writing file: '{0}'".format(file_name))
1122     with open(file_name, "w") as file_handler:
1123         file_handler.write(",".join(header) + "\n")
1124         for test in tbl_sorted:
1125             file_handler.write(",".join([str(item) for item in test]) + '\n')
1126
1127     txt_file_name = "{0}.txt".format(table["output-file"])
1128     logging.info("    Writing file: '{0}'".format(txt_file_name))
1129     convert_csv_to_pretty_txt(file_name, txt_file_name)
1130
1131
1132 def table_failed_tests_html(table, input_data):
1133     """Generate the table(s) with algorithm: table_failed_tests_html
1134     specified in the specification file.
1135
1136     :param table: Table to generate.
1137     :param input_data: Data to process.
1138     :type table: pandas.Series
1139     :type input_data: InputData
1140     """
1141
1142     testbed = table.get("testbed", None)
1143     if testbed is None:
1144         logging.error("The testbed is not defined for the table '{0}'.".
1145                       format(table.get("title", "")))
1146         return
1147
1148     logging.info("  Generating the table {0} ...".
1149                  format(table.get("title", "")))
1150
1151     try:
1152         with open(table["input-file"], 'rb') as csv_file:
1153             csv_content = csv.reader(csv_file, delimiter=',', quotechar='"')
1154             csv_lst = [item for item in csv_content]
1155     except KeyError:
1156         logging.warning("The input file is not defined.")
1157         return
1158     except csv.Error as err:
1159         logging.warning("Not possible to process the file '{0}'.\n{1}".
1160                         format(table["input-file"], err))
1161         return
1162
1163     # Table:
1164     failed_tests = ET.Element("table", attrib=dict(width="100%", border='0'))
1165
1166     # Table header:
1167     tr = ET.SubElement(failed_tests, "tr", attrib=dict(bgcolor="#7eade7"))
1168     for idx, item in enumerate(csv_lst[0]):
1169         alignment = "left" if idx == 0 else "center"
1170         th = ET.SubElement(tr, "th", attrib=dict(align=alignment))
1171         th.text = item
1172
1173     # Rows:
1174     colors = ("#e9f1fb", "#d4e4f7")
1175     for r_idx, row in enumerate(csv_lst[1:]):
1176         background = colors[r_idx % 2]
1177         tr = ET.SubElement(failed_tests, "tr", attrib=dict(bgcolor=background))
1178
1179         # Columns:
1180         for c_idx, item in enumerate(row):
1181             alignment = "left" if c_idx == 0 else "center"
1182             td = ET.SubElement(tr, "td", attrib=dict(align=alignment))
1183             # Name:
1184             if c_idx == 0:
1185                 url = _generate_url("../trending/", testbed, item)
1186                 ref = ET.SubElement(td, "a", attrib=dict(href=url))
1187                 ref.text = item
1188             else:
1189                 td.text = item
1190     try:
1191         with open(table["output-file"], 'w') as html_file:
1192             logging.info("    Writing file: '{0}'".format(table["output-file"]))
1193             html_file.write(".. raw:: html\n\n\t")
1194             html_file.write(ET.tostring(failed_tests))
1195             html_file.write("\n\t<p><br><br></p>\n")
1196     except KeyError:
1197         logging.warning("The output file is not defined.")
1198         return