+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))
+
+
Code Review / csit.git / blobdiff