diff options
Diffstat (limited to 'resources/tools/presentation/generator_tables.py')
| -rw-r--r-- | resources/tools/presentation/generator_tables.py | 94 |
1 files changed, 93 insertions, 1 deletions
diff --git a/resources/tools/presentation/generator_tables.py b/resources/tools/presentation/generator_tables.py index 8b88a52a79..1e1307b5bc 100644 --- a/resources/tools/presentation/generator_tables.py +++ b/resources/tools/presentation/generator_tables.py @@ -29,6 +29,7 @@ from copy import deepcopy import plotly.graph_objects as go import plotly.offline as ploff import pandas as pd +import prettytable from numpy import nan, isnan from yaml import load, FullLoader, YAMLError @@ -59,7 +60,8 @@ def generate_tables(spec, data): u"table_failed_tests_html": table_failed_tests_html, u"table_oper_data_html": table_oper_data_html, u"table_comparison": table_comparison, - u"table_weekly_comparison": table_weekly_comparison + u"table_weekly_comparison": table_weekly_comparison, + u"table_job_spec_duration": table_job_spec_duration } logging.info(u"Generating the tables ...") @@ -76,6 +78,96 @@ def generate_tables(spec, data): logging.info(u"Done.") +def table_job_spec_duration(table, input_data): + """Generate the table(s) with algorithm: table_job_spec_duration + specified in the specification file. + + :param table: Table to generate. + :param input_data: Data to process. + :type table: pandas.Series + :type input_data: InputData + """ + + _ = input_data + + logging.info(f" Generating the table {table.get(u'title', u'')} ...") + + jb_type = table.get(u"jb-type", None) + + tbl_lst = list() + if jb_type == u"iterative": + for line in table.get(u"lines", tuple()): + tbl_itm = { + u"name": line.get(u"job-spec", u""), + u"data": list() + } + for job, builds in line.get(u"data-set", dict()).items(): + for build_nr in builds: + try: + minutes = input_data.metadata( + job, str(build_nr) + )[u"elapsedtime"] // 60000 + except (KeyError, IndexError, ValueError, AttributeError): + continue + tbl_itm[u"data"].append(minutes) + tbl_itm[u"mean"] = mean(tbl_itm[u"data"]) + tbl_itm[u"stdev"] = stdev(tbl_itm[u"data"]) + tbl_lst.append(tbl_itm) + elif jb_type == u"coverage": + job = table.get(u"data", None) + if not job: + return + for line in table.get(u"lines", tuple()): + try: + tbl_itm = { + u"name": line.get(u"job-spec", u""), + u"mean": input_data.metadata( + list(job.keys())[0], str(line[u"build"]) + )[u"elapsedtime"] // 60000, + u"stdev": float(u"nan") + } + tbl_itm[u"data"] = [tbl_itm[u"mean"], ] + except (KeyError, IndexError, ValueError, AttributeError): + continue + tbl_lst.append(tbl_itm) + else: + logging.warning(f"Wrong type of job-spec: {jb_type}. Skipping.") + return + + for line in tbl_lst: + line[u"mean"] = \ + f"{int(line[u'mean'] // 60):02d}:{int(line[u'mean'] % 60):02d}" + if math.isnan(line[u"stdev"]): + line[u"stdev"] = u"" + else: + line[u"stdev"] = \ + f"{int(line[u'stdev'] //60):02d}:{int(line[u'stdev'] % 60):02d}" + + if not tbl_lst: + return + + rows = list() + for itm in tbl_lst: + rows.append([ + itm[u"name"], + f"{len(itm[u'data'])}", + f"{itm[u'mean']} +- {itm[u'stdev']}" + if itm[u"stdev"] != u"" else f"{itm[u'mean']}" + ]) + + txt_table = prettytable.PrettyTable( + [u"Job Specification", u"Nr of Runs", u"Duration [HH:MM]"] + ) + for row in rows: + txt_table.add_row(row) + txt_table.align = u"r" + txt_table.align[u"Job Specification"] = u"l" + + file_name = f"{table.get(u'output-file', u'')}.txt" + with open(file_name, u"wt", encoding='utf-8') as txt_file: + txt_file.write(str(txt_table)) + + def table_oper_data_html(table, input_data): """Generate the table(s) with algorithm: html_table_oper_data specified in the specification file. |