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