aboutsummaryrefslogtreecommitdiffstats
path: root/resources/tools/presentation/generator_tables.py
blob: 77243744f9997278d7136e0ac4c3a6006ae650c1 (plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
# Copyright (c) 2019 Cisco and/or its affiliates.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at:
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

"""Algorithms to generate tables.
"""


import logging
import csv
import re

from string import replace
from collections import OrderedDict
from numpy import nan, isnan
from xml.etree import ElementTree as ET
from datetime import datetime as dt
from datetime import timedelta

from utils import mean, stdev, relative_change, classify_anomalies, \
    convert_csv_to_pretty_txt


REGEX_NIC = re.compile(r'\d*ge\dp\d\D*\d*')


def generate_tables(spec, data):
    """Generate all tables specified in the specification file.

    :param spec: Specification read from the specification file.
    :param data: Data to process.
    :type spec: Specification
    :type data: InputData
    """

    logging.info("Generating the tables ...")
    for table in spec.tables:
        try:
            eval(table["algorithm"])(table, data)
        except NameError as err:
            logging.error("Probably algorithm '{alg}' is not defined: {err}".
                          format(alg=table["algorithm"], err=repr(err)))
    logging.info("Done.")


def table_details(table, input_data):
    """Generate the table(s) with algorithm: table_detailed_test_results
    specified in the specification file.

    :param table: Table to generate.
    :param input_data: Data to process.
    :type table: pandas.Series
    :type input_data: InputData
    """

    logging.info("  Generating the table {0} ...".
                 format(table.get("title", "")))

    # Transform the data
    logging.info("    Creating the data set for the {0} '{1}'.".
                 format(table.get("type", ""), table.get("title", "")))
    data = input_data.filter_data(table)

    # Prepare the header of the tables
    header = list()
    for column in table["columns"]:
        header.append('"{0}"'.format(str(column["title"]).replace('"', '""')))

    # Generate the data for the table according to the model in the table
    # specification
    job = table["data"].keys()[0]
    build = str(table["data"][job][0])
    try:
        suites = input_data.suites(job, build)
    except KeyError:
        logging.error("    No data available. The table will not be generated.")
        return

    for suite_longname, suite in suites.iteritems():
        # Generate data
        suite_name = suite["name"]
        table_lst = list()
        for test in data[job][build].keys():
            if data[job][build][test]["parent"] in suite_name:
                row_lst = list()
                for column in table["columns"]:
                    try:
                        col_data = str(data[job][build][test][column["data"].
                                       split(" ")[1]]).replace('"', '""')
                        if column["data"].split(" ")[1] in ("vat-history",
                                                            "show-run"):
                            col_data = replace(col_data, " |br| ", "",
                                               maxreplace=1)
                            col_data = " |prein| {0} |preout| ".\
                                format(col_data[:-5])
                        row_lst.append('"{0}"'.format(col_data))
                    except KeyError:
                        row_lst.append("No data")
                table_lst.append(row_lst)

        # Write the data to file
        if table_lst:
            file_name = "{0}_{1}{2}".format(table["output-file"], suite_name,
                                            table["output-file-ext"])
            logging.info("      Writing file: '{}'".format(file_name))
            with open(file_name, "w") as file_handler:
                file_handler.write(",".join(header) + "\n")
                for item in table_lst:
                    file_handler.write(",".join(item) + "\n")

    logging.info("  Done.")


def table_merged_details(table, input_data):
    """Generate the table(s) with algorithm: table_merged_details
    specified in the specification file.

    :param table: Table to generate.
    :param input_data: Data to process.
    :type table: pandas.Series
    :type input_data: InputData
    """

    logging.info("  Generating the table {0} ...".
                 format(table.get("title", "")))

    # Transform the data
    logging.info("    Creating the data set for the {0} '{1}'.".
                 format(table.get("type", ""), table.get("title", "")))
    data = input_data.filter_data(table)
    data = input_data.merge_data(data)
    data.sort_index(inplace=True)

    logging.info("    Creating the data set for the {0} '{1}'.".
                 format(table.get("type", ""), table.get("title", "")))
    suites = input_data.filter_data(table, data_set="suites")
    suites = input_data.merge_data(suites)

    # Prepare the header of the tables
    header = list()
    for column in table["columns"]:
        header.append('"{0}"'.format(str(column["title"]).replace('"', '""')))

    for _, suite in suites.iteritems():
        # Generate data
        suite_name = suite["name"]
        table_lst = list()
        for test in data.keys():
            if data[test]["parent"] in suite_name:
                row_lst = list()
                for column in table["columns"]:
                    try:
                        col_data = str(data[test][column["data"].
                                       split(" ")[1]]).replace('"', '""')
                        if column["data"].split(" ")[1] in ("vat-history",
                                                            "show-run"):
                            col_data = replace(col_data, " |br| ", "",
                                               maxreplace=1)
                            col_data = " |prein| {0} |preout| ".\
                                format(col_data[:-5])
                        row_lst.append('"{0}"'.format(col_data))
                    except KeyError:
                        row_lst.append("No data")
                table_lst.append(row_lst)

        # Write the data to file
        if table_lst:
            file_name = "{0}_{1}{2}".format(table["output-file"], suite_name,
                                            table["output-file-ext"])
            logging.info("      Writing file: '{}'".format(file_name))
            with open(file_name, "w") as file_handler:
                file_handler.write(",".join(header) + "\n")
                for item in table_lst:
                    file_handler.write(",".join(item) + "\n")

    logging.info("  Done.")


def table_performance_comparison(table, input_data):
    """Generate the table(s) with algorithm: table_performance_comparison
    specified in the specification file.

    :param table: Table to generate.
    :param input_data: Data to process.
    :type table: pandas.Series
    :type input_data: InputData
    """

    logging.info("  Generating the table {0} ...".
                 format(table.get("title", "")))

    # Transform the data
    logging.info("    Creating the data set for the {0} '{1}'.".
                 format(table.get("type", ""), table.get("title", "")))
    data = input_data.filter_data(table, continue_on_error=True)

    # Prepare the header of the tables
    try:
        header = ["Test case", ]

        if table["include-tests"] == "MRR":
            hdr_param = "Receive Rate"
        else:
            hdr_param = "Throughput"

        history = table.get("history", None)
        if history:
            for item in history:
                header.extend(
                    ["{0} {1} [Mpps]".format(item["title"], hdr_param),
                     "{0} Stdev [Mpps]".format(item["title"])])
        header.extend(
            ["{0} {1} [Mpps]".format(table["reference"]["title"], hdr_param),
             "{0} Stdev [Mpps]".format(table["reference"]["title"]),
             "{0} {1} [Mpps]".format(table["compare"]["title"], hdr_param),
             "{0} Stdev [Mpps]".format(table["compare"]["title"]),
             "Delta [%]"])
        header_str = ",".join(header) + "\n"
    except (AttributeError, KeyError) as err:
        logging.error("The model is invalid, missing parameter: {0}".
                      format(err))
        return

    # Prepare data to the table:
    tbl_dict = dict()
    for job, builds in table["reference"]["data"].items():
        for build in builds:
            for tst_name, tst_data in data[job][str(build)].iteritems():
                tst_name_mod = tst_name.replace("-ndrpdrdisc", "").\
                    replace("-ndrpdr", "").replace("-pdrdisc", "").\
                    replace("-ndrdisc", "").replace("-pdr", "").\
                    replace("-ndr", "").\
                    replace("1t1c", "1c").replace("2t1c", "1c").\
                    replace("2t2c", "2c").replace("4t2c", "2c").\
                    replace("4t4c", "4c").replace("8t4c", "4c")
                if "across topologies" in table["title"].lower():
                    tst_name_mod = tst_name_mod.replace("2n1l-", "")
                if tbl_dict.get(tst_name_mod, None) is None:
                    name = "{0}-{1}".format(tst_data["parent"].split("-")[0],
                                            "-".join(tst_data["name"].
                                                     split("-")[:-1]))
                    if "across testbeds" in table["title"].lower() or \
                            "across topologies" in table["title"].lower():
                        name = name.\
                            replace("1t1c", "1c").replace("2t1c", "1c").\
                            replace("2t2c", "2c").replace("4t2c", "2c").\
                            replace("4t4c", "4c").replace("8t4c", "4c")
                    tbl_dict[tst_name_mod] = {"name": name,
                                              "ref-data": list(),
                                              "cmp-data": list()}
                try:
                    # TODO: Re-work when NDRPDRDISC tests are not used
                    if table["include-tests"] == "MRR":
                        tbl_dict[tst_name_mod]["ref-data"]. \
                            append(tst_data["result"]["receive-rate"].avg)
                    elif table["include-tests"] == "PDR":
                        if tst_data["type"] == "PDR":
                            tbl_dict[tst_name_mod]["ref-data"]. \
                                append(tst_data["throughput"]["value"])
                        elif tst_data["type"] == "NDRPDR":
                            tbl_dict[tst_name_mod]["ref-data"].append(
                                tst_data["throughput"]["PDR"]["LOWER"])
                    elif table["include-tests"] == "NDR":
                        if tst_data["type"] == "NDR":
                            tbl_dict[tst_name_mod]["ref-data"]. \
                                append(tst_data["throughput"]["value"])
                        elif tst_data["type"] == "NDRPDR":
                            tbl_dict[tst_name_mod]["ref-data"].append(
                                tst_data["throughput"]["NDR"]["LOWER"])
                    else:
                        continue
                except TypeError:
                    pass  # No data in output.xml for this test

    for job, builds in table["compare"]["data"].items():
        for build in builds:
            for tst_name, tst_data in data[job][str(build)].iteritems():
                tst_name_mod = tst_name.replace("-ndrpdrdisc", ""). \
                    replace("-ndrpdr", "").replace("-pdrdisc", ""). \
                    replace("-ndrdisc", "").replace("-pdr", ""). \
                    replace("-ndr", "").\
                    replace("1t1c", "1c").replace("2t1c", "1c").\
                    replace("2t2c", "2c").replace("4t2c", "2c").\
                    replace("4t4c", "4c").replace("8t4c", "4c")
                if "across topologies" in table["title"].lower():
                    tst_name_mod = tst_name_mod.replace("2n1l-", "")
                try:
                    # TODO: Re-work when NDRPDRDISC tests are not used
                    if table["include-tests"] == "MRR":
                        tbl_dict[tst_name_mod]["cmp-data"]. \
                            append(tst_data["result"]["receive-rate"].avg)
                    elif table["include-tests"] == "PDR":
                        if tst_data["type"] == "PDR":
                            tbl_dict[tst_name_mod]["cmp-data"]. \
                                append(tst_data["throughput"]["value"])
                        elif tst_data["type"] == "NDRPDR":
                            tbl_dict[tst_name_mod]["cmp-data"].append(
                                tst_data["throughput"]["PDR"]["LOWER"])
                    elif table["include-tests"] == "NDR":
                        if tst_data["type"] == "NDR":
                            tbl_dict[tst_name_mod]["cmp-data"]. \
                                append(tst_data["throughput"]["value"])
                        elif tst_data["type"] == "NDRPDR":
                            tbl_dict[tst_name_mod]["cmp-data"].append(
                                tst_data["throughput"]["NDR"]["LOWER"])
                    else:
                        continue
                except KeyError:
                    pass
                except TypeError:
                    tbl_dict.pop(tst_name_mod, None)
    if history:
        for item in history:
            for job, builds in item["data"].items():
                for build in builds:
                    for tst_name, tst_data in data[job][str(build)].iteritems():
                        tst_name_mod = tst_name.replace("-ndrpdrdisc", ""). \
                            replace("-ndrpdr", "").replace("-pdrdisc", ""). \
                            replace("-ndrdisc", "").replace("-pdr", ""). \
                            replace("-ndr", "").\
                            replace("1t1c", "1c").replace("2t1c", "1c").\
                            replace("2t2c", "2c").replace("4t2c", "2c").\
                            replace("4t4c", "4c").replace("8t4c", "4c")
                        if "across topologies" in table["title"].lower():
                            tst_name_mod = tst_name_mod.replace("2n1l-", "")
                        if tbl_dict.get(tst_name_mod, None) is None:
                            continue
                        if tbl_dict[tst_name_mod].get("history", None) is None:
                            tbl_dict[tst_name_mod]["history"] = OrderedDict()
                        if tbl_dict[tst_name_mod]["history"].get(item["title"],
                                                             None) is None:
                            tbl_dict[tst_name_mod]["history"][item["title"]] = \
                                list()
                        try:
                            # TODO: Re-work when NDRPDRDISC tests are not used
                            if table["include-tests"] == "MRR":
                                tbl_dict[tst_name_mod]["history"][item["title"
                                ]].append(tst_data["result"]["receive-rate"].
                                          avg)
                            elif table["include-tests"] == "PDR":
                                if tst_data["type"] == "PDR":
                                    tbl_dict[tst_name_mod]["history"][
                                        item["title"]].\
                                        append(tst_data["throughput"]["value"])
                                elif tst_data["type"] == "NDRPDR":
                                    tbl_dict[tst_name_mod]["history"][item[
                                        "title"]].append(tst_data["throughput"][
                                        "PDR"]["LOWER"])
                            elif table["include-tests"] == "NDR":
                                if tst_data["type"] == "NDR":
                                    tbl_dict[tst_name_mod]["history"][
                                        item["title"]].\
                                        append(tst_data["throughput"]["value"])
                                elif tst_data["type"] == "NDRPDR":
                                    tbl_dict[tst_name_mod]["history"][item[
                                        "title"]].append(tst_data["throughput"][
                                        "NDR"]["LOWER"])
                            else:
                                continue
                        except (TypeError, KeyError):
                            pass

    tbl_lst = list()
    for tst_name in tbl_dict.keys():
        item = [tbl_dict[tst_name]["name"], ]
        if history:
            if tbl_dict[tst_name].get("history", None) is not None:
                for hist_data in tbl_dict[tst_name]["history"].values():
                    if hist_data:
                        item.append(round(mean(hist_data) / 1000000, 2))
                        item.append(round(stdev(hist_data) / 1000000, 2))
                    else:
                        item.extend([None, None])
            else:
                item.extend([None, None])
        data_t = tbl_dict[tst_name]["ref-data"]
        if data_t:
            item.append(round(mean(data_t) / 1000000, 2))
            item.append(round(stdev(data_t) / 1000000, 2))
        else:
            item.extend([None, None])
        data_t = tbl_dict[tst_name]["cmp-data"]
        if data_t:
            item.append(round(mean(data_t) / 1000000, 2))
            item.append(round(stdev(data_t) / 1000000, 2))
        else:
            item.extend([None, None])
        if item[-4] is not None and item[-2] is not None and item[-4] != 0:
            item.append(int(relative_change(float(item[-4]), float(item[-2]))))
        if len(item) == len(header):
            tbl_lst.append(item)

    # Sort the table according to the relative change
    tbl_lst.sort(key=lambda rel: rel[-1], reverse=True)

    # Generate csv tables:
    csv_file = "{0}.csv".format(table["output-file"])
    with open(csv_file, "w") as file_handler:
        file_handler.write(header_str)
        for test in tbl_lst:
            file_handler.write(",".join([str(item) for item in test]) + "\n")

    convert_csv_to_pretty_txt(csv_file, "{0}.txt".format(table["output-file"]))


def table_performance_trending_dashboard(table, input_data):
    """Generate the table(s) with algorithm:
    table_performance_trending_dashboard
    specified in the specification file.

    :param table: Table to generate.
    :param input_data: Data to process.
    :type table: pandas.Series
    :type input_data: InputData
    """

    logging.info("  Generating the table {0} ...".
                 format(table.get("title", "")))

    # Transform the data
    logging.info("    Creating the data set for the {0} '{1}'.".
                 format(table.get("type", ""), table.get("title", "")))
    data = input_data.filter_data(table, continue_on_error=True)

    # Prepare the header of the tables
    header = ["Test Case",
              "Trend [Mpps]",
              "Short-Term Change [%]",
              "Long-Term Change [%]",
              "Regressions [#]",
              "Progressions [#]"
              ]
    header_str = ",".join(header) + "\n"

    # Prepare data to the table:
    tbl_dict = dict()
    for job, builds in table["data"].items():
        for build in builds:
            for tst_name, tst_data in data[job][str(build)].iteritems():
                if tst_name.lower() in table["ignore-list"]:
                    continue
                if tbl_dict.get(tst_name, None) is None:
                    groups = re.search(REGEX_NIC, tst_data["parent"])
                    if not groups:
                        continue
                    nic = groups.group(0)
                    tbl_dict[tst_name] = {
                        "name": "{0}-{1}".format(nic, tst_data["name"]),
                        "data": OrderedDict()}
                try:
                    tbl_dict[tst_name]["data"][str(build)] = \
                        tst_data["result"]["receive-rate"]
                except (TypeError, KeyError):
                    pass  # No data in output.xml for this test

    tbl_lst = list()
    for tst_name in tbl_dict.keys():
        data_t = tbl_dict[tst_name]["data"]
        if len(data_t) < 2:
            continue

        classification_lst, avgs = classify_anomalies(data_t)

        win_size = min(len(data_t), table["window"])
        long_win_size = min(len(data_t), table["long-trend-window"])

        try:
            max_long_avg = max(
                [x for x in avgs[-long_win_size:-win_size]
                 if not isnan(x)])
        except ValueError:
            max_long_avg = nan
        last_avg = avgs[-1]
        avg_week_ago = avgs[max(-win_size, -len(avgs))]

        if isnan(last_avg) or isnan(avg_week_ago) or avg_week_ago == 0.0:
            rel_change_last = nan
        else:
            rel_change_last = round(
                ((last_avg - avg_week_ago) / avg_week_ago) * 100, 2)

        if isnan(max_long_avg) or isnan(last_avg) or max_long_avg == 0.0:
            rel_change_long = nan
        else:
            rel_change_long = round(
                ((last_avg - max_long_avg) / max_long_avg) * 100, 2)

        if classification_lst:
            if isnan(rel_change_last) and isnan(rel_change_long):
                continue
            if (isnan(last_avg) or
                isnan(rel_change_last) or
                isnan(rel_change_long)):
                continue
            tbl_lst.append(
                [tbl_dict[tst_name]["name"],
                 round(last_avg / 1000000, 2),
                 rel_change_last,
                 rel_change_long,
                 classification_lst[-win_size:].count("regression"),
                 classification_lst[-win_size:].count("progression")])

    tbl_lst.sort(key=lambda rel: rel[0])

    tbl_sorted = list()
    for nrr in range(table["window"], -1, -1):
        tbl_reg = [item for item in tbl_lst if item[4] == nrr]
        for nrp in range(table["window"], -1, -1):
            tbl_out = [item for item in tbl_reg if item[5] == nrp]
            tbl_out.sort(key=lambda rel: rel[2])
            tbl_sorted.extend(tbl_out)

    file_name = "{0}{1}".format(table["output-file"], table["output-file-ext"])

    logging.info("    Writing file: '{0}'".format(file_name))
    with open(file_name, "w") as file_handler:
        file_handler.write(header_str)
        for test in tbl_sorted:
            file_handler.write(",".join([str(item) for item in test]) + '\n')

    txt_file_name = "{0}.txt".format(table["output-file"])
    logging.info("    Writing file: '{0}'".format(txt_file_name))
    convert_csv_to_pretty_txt(file_name, txt_file_name)


def _generate_url(base, testbed, test_name):
    """Generate URL to a trending plot from the name of the test case.

    :param base: The base part of URL common to all test cases.
    :param testbed: The testbed used for testing.
    :param test_name: The name of the test case.
    :type base: str
    :type testbed: str
    :type test_name: str
    :returns: The URL to the plot with the trending data for the given test
        case.
    :rtype str
    """

    url = base
    file_name = ""
    anchor = ".html#"
    feature = ""

    if "lbdpdk" in test_name or "lbvpp" in test_name:
        file_name = "link_bonding"

    elif "114b" in test_name and "vhost" in test_name:
        file_name = "vts"

    elif "testpmd" in test_name or "l3fwd" in test_name:
        file_name = "dpdk"

    elif "memif" in test_name:
        file_name = "container_memif"
        feature = "-base"

    elif "srv6" in test_name:
        file_name = "srv6"

    elif "vhost" in test_name:
        if "l2xcbase" in test_name or "l2bdbasemaclrn" in test_name:
            file_name = "vm_vhost_l2"
            if "114b" in test_name:
                feature = ""
            elif "l2xcbase" in test_name:
                feature = "-base-l2xc"
            elif "l2bdbasemaclrn" in test_name:
                feature = "-base-l2bd"
            else:
                feature = "-base"
        elif "ip4base" in test_name:
            file_name = "vm_vhost_ip4"
            feature = "-base"

    elif "ipsec" in test_name:
        file_name = "ipsec"
        feature = "-base-scale"

    elif "ethip4lispip" in test_name or "ethip4vxlan" in test_name:
        file_name = "ip4_tunnels"
        feature = "-base"

    elif "ip4base" in test_name or "ip4scale" in test_name:
        file_name = "ip4"
        if "xl710" in test_name:
            feature = "-base-scale-features"
        elif "iacl" in test_name:
            feature = "-features-iacl"
        elif "oacl" in test_name:
            feature = "-features-oacl"
        elif "snat" in test_name or "cop" in test_name:
            feature = "-features"
        else:
            feature = "-base-scale"

    elif "ip6base" in test_name or "ip6scale" in test_name:
        file_name = "ip6"
        feature = "-base-scale"

    elif "l2xcbase" in test_name or "l2xcscale" in test_name \
            or "l2bdbasemaclrn" in test_name or "l2bdscale" in test_name \
            or "l2dbbasemaclrn" in test_name or "l2dbscale" in test_name:
        file_name = "l2"
        if "macip" in test_name:
            feature = "-features-macip"
        elif "iacl" in test_name:
            feature = "-features-iacl"
        elif "oacl" in test_name:
            feature = "-features-oacl"
        else:
            feature = "-base-scale"

    if "x520" in test_name:
        nic = "x520-"
    elif "x710" in test_name:
        nic = "x710-"
    elif "xl710" in test_name:
        nic = "xl710-"
    elif "xxv710" in test_name:
        nic = "xxv710-"
    else:
        nic = ""
    anchor += nic

    if "64b" in test_name:
        framesize = "64b"
    elif "78b" in test_name:
        framesize = "78b"
    elif "imix" in test_name:
        framesize = "imix"
    elif "9000b" in test_name:
        framesize = "9000b"
    elif "1518b" in test_name:
        framesize = "1518b"
    elif "114b" in test_name:
        framesize = "114b"
    else:
        framesize = ""
    anchor += framesize + '-'

    if "1t1c" in test_name:
        anchor += "1t1c"
    elif "2t2c" in test_name:
        anchor += "2t2c"
    elif "4t4c" in test_name:
        anchor += "4t4c"
    elif "2t1c" in test_name:
        anchor += "2t1c"
    elif "4t2c" in test_name:
        anchor += "4t2c"
    elif "8t4c" in test_name:
        anchor += "8t4c"

    return url + file_name + '-' + testbed + '-' + nic + framesize + feature + \
           anchor + feature


def table_performance_trending_dashboard_html(table, input_data):
    """Generate the table(s) with algorithm:
    table_performance_trending_dashboard_html specified in the specification
    file.

    :param table: Table to generate.
    :param input_data: Data to process.
    :type table: dict
    :type input_data: InputData
    """

    testbed = table.get("testbed", None)
    if testbed is None:
        logging.error("The testbed is not defined for the table '{0}'.".
                      format(table.get("title", "")))
        return

    logging.info("  Generating the table {0} ...".
                 format(table.get("title", "")))

    try:
        with open(table["input-file"], 'rb') as csv_file:
            csv_content = csv.reader(csv_file, delimiter=',', quotechar='"')
            csv_lst = [item for item in csv_content]
    except KeyError:
        logging.warning("The input file is not defined.")
        return
    except csv.Error as err:
        logging.warning("Not possible to process the file '{0}'.\n{1}".
                        format(table["input-file"], err))
        return

    # Table:
    dashboard = ET.Element("table", attrib=dict(width="100%", border='0'))

    # Table header:
    tr = ET.SubElement(dashboard, "tr", attrib=dict(bgcolor="#7eade7"))
    for idx, item in enumerate(csv_lst[0]):
        alignment = "left" if idx == 0 else "center"
        th = ET.SubElement(tr, "th", attrib=dict(align=alignment))
        th.text = item

    # Rows:
    colors = {"regression": ("#ffcccc", "#ff9999"),
              "progression": ("#c6ecc6", "#9fdf9f"),
              "normal": ("#e9f1fb", "#d4e4f7")}
    for r_idx, row in enumerate(csv_lst[1:]):
        if int(row[4]):
            color = "regression"
        elif int(row[5]):
            color = "progression"
        else:
            color = "normal"
        background = colors[color][r_idx % 2]
        tr = ET.SubElement(dashboard, "tr", attrib=dict(bgcolor=background))

        # Columns:
        for c_idx, item in enumerate(row):
            alignment = "left" if c_idx == 0 else "center"
            td = ET.SubElement(tr, "td", attrib=dict(align=alignment))
            # Name:
            if c_idx == 0:
                url = _generate_url("../trending/", testbed, item)
                ref = ET.SubElement(td, "a", attrib=dict(href=url))
                ref.text = item
            else:
                td.text = item
    try:
        with open(table["output-file"], 'w') as html_file:
            logging.info("    Writing file: '{0}'".format(table["output-file"]))
            html_file.write(".. raw:: html\n\n\t")
            html_file.write(ET.tostring(dashboard))
            html_file.write("\n\t<p><br><br></p>\n")
    except KeyError:
        logging.warning("The output file is not defined.")
        return


def table_failed_tests(table, input_data):
    """Generate the table(s) with algorithm: table_failed_tests
    specified in the specification file.

    :param table: Table to generate.
    :param input_data: Data to process.
    :type table: pandas.Series
    :type input_data: InputData
    """

    logging.info("  Generating the table {0} ...".
                 format(table.get("title", "")))

    # Transform the data
    logging.info("    Creating the data set for the {0} '{1}'.".
                 format(table.get("type", ""), table.get("title", "")))
    data = input_data.filter_data(table, continue_on_error=True)

    # Prepare the header of the tables
    header = ["Test Case",
              "Failures [#]",
              "Last Failure [Time]",
              "Last Failure [VPP-Build-Id]",
              "Last Failure [CSIT-Job-Build-Id]"]

    # Generate the data for the table according to the model in the table
    # specification

    now = dt.utcnow()
    timeperiod = timedelta(int(table.get("window", 7)))

    tbl_dict = dict()
    for job, builds in table["data"].items():
        for build in builds:
            build = str(build)
            for tst_name, tst_data in data[job][build].iteritems():
                if tst_name.lower() in table["ignore-list"]:
                    continue
                if tbl_dict.get(tst_name, None) is None:
                    groups = re.search(REGEX_NIC, tst_data["parent"])
                    if not groups:
                        continue
                    nic = groups.group(0)
                    tbl_dict[tst_name] = {
                        "name": "{0}-{1}".format(nic, tst_data["name"]),
                        "data": OrderedDict()}
                try:
                    generated = input_data.metadata(job, build).\
                        get("generated", "")
                    if not generated:
                        continue
                    then = dt.strptime(generated, "%Y%m%d %H:%M")
                    if (now - then) <= timeperiod:
                        tbl_dict[tst_name]["data"][build] = (
                            tst_data["status"],
                            generated,
                            input_data.metadata(job, build).get("version", ""),
                            build)
                except (TypeError, KeyError) as err:
                    logging.warning("tst_name: {} - err: {}".
                                    format(tst_name, repr(err)))

    max_fails = 0
    tbl_lst = list()
    for tst_data in tbl_dict.values():
        fails_nr = 0
        for val in tst_data["data"].values():
            if val[0] == "FAIL":
                fails_nr += 1
                fails_last_date = val[1]
                fails_last_vpp = val[2]
                fails_last_csit = val[3]
        if fails_nr:
            max_fails = fails_nr if fails_nr > max_fails else max_fails
            tbl_lst.append([tst_data["name"],
                            fails_nr,
                            fails_last_date,
                            fails_last_vpp,
                            "mrr-daily-build-{0}".format(fails_last_csit)])

    tbl_lst.sort(key=lambda rel: rel[2], reverse=True)
    tbl_sorted = list()
    for nrf in range(max_fails, -1, -1):
        tbl_fails = [item for item in tbl_lst if item[1] == nrf]
        tbl_sorted.extend(tbl_fails)
    file_name = "{0}{1}".format(table["output-file"], table["output-file-ext"])

    logging.info("    Writing file: '{0}'".format(file_name))
    with open(file_name, "w") as file_handler:
        file_handler.write(",".join(header) + "\n")
        for test in tbl_sorted:
            file_handler.write(",".join([str(item) for item in test]) + '\n')

    txt_file_name = "{0}.txt".format(table["output-file"])
    logging.info("    Writing file: '{0}'".format(txt_file_name))
    convert_csv_to_pretty_txt(file_name, txt_file_name)


def table_failed_tests_html(table, input_data):
    """Generate the table(s) with algorithm: table_failed_tests_html
    specified in the specification file.

    :param table: Table to generate.
    :param input_data: Data to process.
    :type table: pandas.Series
    :type input_data: InputData
    """

    testbed = table.get("testbed", None)
    if testbed is None:
        logging.error("The testbed is not defined for the table '{0}'.".
                      format(table.get("title", "")))
        return

    logging.info("  Generating the table {0} ...".
                 format(table.get("title", "")))

    try:
        with open(table["input-file"], 'rb') as csv_file:
            csv_content = csv.reader(csv_file, delimiter=',', quotechar='"')
            csv_lst = [item for item in csv_content]
    except KeyError:
        logging.warning("The input file is not defined.")
        return
    except csv.Error as err:
        logging.warning("Not possible to process the file '{0}'.\n{1}".
                        format(table["input-file"], err))
        return

    # Table:
    failed_tests = ET.Element("table", attrib=dict(width="100%", border='0'))

    # Table header:
    tr = ET.SubElement(failed_tests, "tr", attrib=dict(bgcolor="#7eade7"))
    for idx, item in enumerate(csv_lst[0]):
        alignment = "left" if idx == 0 else "center"
        th = ET.SubElement(tr, "th", attrib=dict(align=alignment))
        th.text = item

    # Rows:
    colors = ("#e9f1fb", "#d4e4f7")
    for r_idx, row in enumerate(csv_lst[1:]):
        background = colors[r_idx % 2]
        tr = ET.SubElement(failed_tests, "tr", attrib=dict(bgcolor=background))

        # Columns:
        for c_idx, item in enumerate(row):
            alignment = "left" if c_idx == 0 else "center"
            td = ET.SubElement(tr, "td", attrib=dict(align=alignment))
            # Name:
            if c_idx == 0:
                url = _generate_url("../trending/", testbed, item)
                ref = ET.SubElement(td, "a", attrib=dict(href=url))
                ref.text = item
            else:
                td.text = item
    try:
        with open(table["output-file"], 'w') as html_file:
            logging.info("    Writing file: '{0}'".format(table["output-file"]))
            html_file.write(".. raw:: html\n\n\t")
            html_file.write(ET.tostring(failed_tests))
            html_file.write("\n\t<p><br><br></p>\n")
    except KeyError:
        logging.warning("The output file is not defined.")
        return