-# Copyright (c) 2020 Cisco and/or its affiliates.
+# Copyright (c) 2023 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:
import logging
import csv
+import math
import re
from collections import OrderedDict
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
from pal_utils import mean, stdev, classify_anomalies, \
- convert_csv_to_pretty_txt, relative_change_stdev
+ convert_csv_to_pretty_txt, relative_change_stdev, relative_change
REGEX_NIC = re.compile(r'(\d*ge\dp\d\D*\d*[a-z]*)')
+NORM_FREQ = 2.0 # [GHz]
+
def generate_tables(spec, data):
"""Generate all tables specified in the specification file.
"""
generator = {
- u"table_merged_details": table_merged_details,
- u"table_perf_comparison": table_perf_comparison,
- u"table_perf_comparison_nic": table_perf_comparison_nic,
- u"table_nics_comparison": table_nics_comparison,
- u"table_soak_vs_ndr": table_soak_vs_ndr,
- u"table_perf_trending_dash": table_perf_trending_dash,
- u"table_perf_trending_dash_html": table_perf_trending_dash_html,
- u"table_last_failed_tests": table_last_failed_tests,
- u"table_failed_tests": table_failed_tests,
- u"table_failed_tests_html": table_failed_tests_html,
- u"table_oper_data_html": table_oper_data_html,
- u"table_comparison": table_comparison
+ "table_merged_details": table_merged_details,
+ "table_soak_vs_ndr": table_soak_vs_ndr,
+ "table_perf_trending_dash": table_perf_trending_dash,
+ "table_perf_trending_dash_html": table_perf_trending_dash_html,
+ "table_last_failed_tests": table_last_failed_tests,
+ "table_failed_tests": table_failed_tests,
+ "table_failed_tests_html": table_failed_tests_html,
+ "table_oper_data_html": table_oper_data_html,
+ "table_comparison": table_comparison,
+ "table_weekly_comparison": table_weekly_comparison,
+ "table_job_spec_duration": table_job_spec_duration
}
logging.info(u"Generating the tables ...")
+
+ norm_factor = dict()
+ for key, val in spec.environment.get("frequency", dict()).items():
+ norm_factor[key] = NORM_FREQ / val
+
for table in spec.tables:
try:
- generator[table[u"algorithm"]](table, data)
+ if table["algorithm"] == "table_weekly_comparison":
+ table["testbeds"] = spec.environment.get("testbeds", None)
+ if table["algorithm"] == "table_comparison":
+ table["norm_factor"] = norm_factor
+ generator[table["algorithm"]](table, data)
except NameError as err:
logging.error(
- f"Probably algorithm {table[u'algorithm']} is not defined: "
+ f"Probably algorithm {table['algorithm']} is not defined: "
f"{repr(err)}"
)
- logging.info(u"Done.")
+ logging.info("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):
)
data = input_data.filter_data(
table,
- params=[u"name", u"parent", u"show-run", u"type"],
+ params=[u"name", u"parent", u"telemetry-show-run", u"type"],
continue_on_error=True
)
if data.empty:
)
thead.text = u"\t"
- if tst_data.get(u"show-run", u"No Data") == u"No Data":
+ if tst_data.get(u"telemetry-show-run", None) is None or \
+ isinstance(tst_data[u"telemetry-show-run"], str):
trow = ET.SubElement(
tbl, u"tr", attrib=dict(bgcolor=colors[u"header"])
)
u"Average Vector Size"
)
- for dut_data in tst_data[u"show-run"].values():
+ for dut_data in tst_data[u"telemetry-show-run"].values():
trow = ET.SubElement(
tbl, u"tr", attrib=dict(bgcolor=colors[u"header"])
)
tcol = ET.SubElement(
trow, u"td", attrib=dict(align=u"left", colspan=u"6")
)
- if dut_data.get(u"threads", None) is None:
+ if dut_data.get(u"runtime", None) is None:
tcol.text = u"No Data"
continue
+ runtime = dict()
+ for item in dut_data[u"runtime"].get(u"data", tuple()):
+ tid = int(item[u"labels"][u"thread_id"])
+ if runtime.get(tid, None) is None:
+ runtime[tid] = dict()
+ gnode = item[u"labels"][u"graph_node"]
+ if runtime[tid].get(gnode, None) is None:
+ runtime[tid][gnode] = dict()
+ try:
+ runtime[tid][gnode][item[u"name"]] = float(item[u"value"])
+ except ValueError:
+ runtime[tid][gnode][item[u"name"]] = item[u"value"]
+
+ threads = dict({idx: list() for idx in range(len(runtime))})
+ for idx, run_data in runtime.items():
+ for gnode, gdata in run_data.items():
+ threads[idx].append([
+ gnode,
+ int(gdata[u"calls"]),
+ int(gdata[u"vectors"]),
+ int(gdata[u"suspends"]),
+ float(gdata[u"clocks"]),
+ float(gdata[u"vectors"] / gdata[u"calls"]) \
+ if gdata[u"calls"] else 0.0
+ ])
+
bold = ET.SubElement(tcol, u"b")
bold.text = (
f"Host IP: {dut_data.get(u'host', '')}, "
)
thead.text = u"\t"
- for thread_nr, thread in dut_data[u"threads"].items():
+ for thread_nr, thread in threads.items():
trow = ET.SubElement(
tbl, u"tr", attrib=dict(bgcolor=colors[u"header"])
)
suite_name = suite[u"name"]
table_lst = list()
for test in data.keys():
- if data[test][u"parent"] not in suite_name:
+ if data[test][u"status"] != u"PASS" or \
+ data[test][u"parent"] not in suite_name:
continue
row_lst = list()
for column in table[u"columns"]:
# Temporary solution: remove NDR results from message:
if bool(table.get(u'remove-ndr', False)):
try:
- col_data = col_data.split(u" |br| ", 1)[1]
+ col_data = col_data.split(u"\n", 1)[1]
except IndexError:
pass
+ col_data = col_data.replace(u'\n', u' |br| ').\
+ replace(u'\r', u'').replace(u'"', u"'")
col_data = f" |prein| {col_data} |preout| "
- elif column[u"data"].split(u" ")[1] in \
- (u"conf-history", u"show-run"):
- col_data = col_data.replace(u" |br| ", u"", 1)
+ elif column[u"data"].split(u" ")[1] in (u"conf-history", ):
+ col_data = col_data.replace(u'\n', u' |br| ')
col_data = f" |prein| {col_data[:-5]} |preout| "
row_lst.append(f'"{col_data}"')
except KeyError:
:rtype: str
"""
test_name_mod = test_name.\
- replace(u"-ndrpdrdisc", u""). \
replace(u"-ndrpdr", u"").\
- replace(u"-pdrdisc", u""). \
- replace(u"-ndrdisc", u"").\
- replace(u"-pdr", u""). \
- replace(u"-ndr", u""). \
replace(u"1t1c", u"1c").\
replace(u"2t1c", u"1c"). \
replace(u"2t2c", u"2c").\
"""Insert src data to the target structure.
:param target: Target structure where the data is placed.
- :param src: Source data to be placed into the target stucture.
+ :param src: Source data to be placed into the target structure.
:param include_tests: Which results will be included (MRR, NDR, PDR).
:type target: list
:type src: dict
"""
try:
if include_tests == u"MRR":
- target.append(
- (
- src[u"result"][u"receive-rate"],
- src[u"result"][u"receive-stdev"]
- )
- )
+ target[u"mean"] = src[u"result"][u"receive-rate"]
+ target[u"stdev"] = src[u"result"][u"receive-stdev"]
elif include_tests == u"PDR":
- target.append(src[u"throughput"][u"PDR"][u"LOWER"])
+ target[u"data"].append(src[u"throughput"][u"PDR"][u"LOWER"])
elif include_tests == u"NDR":
- target.append(src[u"throughput"][u"NDR"][u"LOWER"])
+ target[u"data"].append(src[u"throughput"][u"NDR"][u"LOWER"])
+ elif u"latency" in include_tests:
+ keys = include_tests.split(u"-")
+ if len(keys) == 4:
+ lat = src[keys[0]][keys[1]][keys[2]][keys[3]]
+ target[u"data"].append(
+ float(u"nan") if lat == -1 else lat * 1e6
+ )
+ elif include_tests == u"hoststack":
+ try:
+ target[u"data"].append(
+ float(src[u"result"][u"bits_per_second"])
+ )
+ except KeyError:
+ target[u"data"].append(
+ (float(src[u"result"][u"client"][u"tx_data"]) * 8) /
+ ((float(src[u"result"][u"client"][u"time"]) +
+ float(src[u"result"][u"server"][u"time"])) / 2)
+ )
+ elif include_tests == u"vsap":
+ try:
+ target[u"data"].append(src[u"result"][u"cps"])
+ except KeyError:
+ target[u"data"].append(src[u"result"][u"rps"])
except (KeyError, TypeError):
pass
-def _tpc_sort_table(table):
- """Sort the table this way:
-
- 1. Put "New in CSIT-XXXX" at the first place.
- 2. Put "See footnote" at the second place.
- 3. Sort the rest by "Delta".
-
- :param table: Table to sort.
- :type table: list
- :returns: Sorted table.
- :rtype: list
- """
-
- tbl_new = list()
- tbl_see = list()
- tbl_delta = list()
- for item in table:
- if isinstance(item[-1], str):
- if u"New in CSIT" in item[-1]:
- tbl_new.append(item)
- elif u"See footnote" in item[-1]:
- tbl_see.append(item)
- else:
- tbl_delta.append(item)
-
- # Sort the tables:
- tbl_new.sort(key=lambda rel: rel[0], reverse=False)
- tbl_see.sort(key=lambda rel: rel[0], reverse=False)
- tbl_see.sort(key=lambda rel: rel[-2], reverse=False)
- tbl_delta.sort(key=lambda rel: rel[0], reverse=False)
- tbl_delta.sort(key=lambda rel: rel[-2], reverse=True)
-
- # Put the tables together:
- table = list()
- # We do not want "New in CSIT":
- # table.extend(tbl_new)
- table.extend(tbl_see)
- table.extend(tbl_delta)
-
- return table
-
-
def _tpc_generate_html_table(header, data, out_file_name, legend=u"",
- footnote=u"", sort_data=True):
+ footnote=u"", sort_data=True, title=u"",
+ generate_rst=True):
"""Generate html table from input data with simple sorting possibility.
:param header: Table header.
:param legend: The legend to display below the table.
:param footnote: The footnote to display below the table (and legend).
:param sort_data: If True the data sorting is enabled.
+ :param title: The table (and file) title.
+ :param generate_rst: If True, wrapping rst file is generated.
:type header: list
:type data: list of lists
:type out_file_name: str
:type legend: str
:type footnote: str
:type sort_data: bool
+ :type title: str
+ :type generate_rst: bool
"""
try:
idx = 0
params = {
u"align-hdr": (
- [u"left", u"center"],
- [u"left", u"left", u"center"],
- [u"left", u"left", u"left", u"center"]
+ [u"left", u"right"],
+ [u"left", u"left", u"right"],
+ [u"left", u"left", u"left", u"right"]
),
u"align-itm": (
[u"left", u"right"],
[u"left", u"left", u"right"],
[u"left", u"left", u"left", u"right"]
),
- u"width": ([28, 9], [4, 24, 10], [4, 4, 32, 10])
+ u"width": ([15, 9], [4, 24, 10], [4, 4, 32, 10])
}
df_data = pd.DataFrame(data, columns=header)
table_header = dict(
values=[f"<b>{item.replace(u',', u',<br>')}</b>" for item in header],
fill_color=u"#7eade7",
- align=params[u"align-hdr"][idx]
+ align=params[u"align-hdr"][idx],
+ font=dict(
+ family=u"Courier New",
+ size=12
+ )
)
fig = go.Figure()
cells=dict(
values=columns,
fill_color=fill_color,
- align=params[u"align-itm"][idx]
+ align=params[u"align-itm"][idx],
+ font=dict(
+ family=u"Courier New",
+ size=12
+ )
)
)
)
buttons = list()
menu_items = [f"<b>{itm}</b> (ascending)" for itm in header]
- menu_items_rev = [f"<b>{itm}</b> (descending)" for itm in header]
- menu_items.extend(menu_items_rev)
+ menu_items.extend([f"<b>{itm}</b> (descending)" for itm in header])
for idx, hdr in enumerate(menu_items):
visible = [False, ] * len(menu_items)
visible[idx] = True
label=hdr.replace(u" [Mpps]", u""),
method=u"update",
args=[{u"visible": visible}],
- )
- )
-
- fig.update_layout(
- updatemenus=[
- go.layout.Updatemenu(
- type=u"dropdown",
- direction=u"down",
- x=0.0,
- xanchor=u"left",
- y=1.045,
- yanchor=u"top",
- active=len(menu_items) - 1,
- buttons=list(buttons)
- )
- ],
- )
- else:
- fig.add_trace(
- go.Table(
- columnwidth=params[u"width"][idx],
- header=table_header,
- cells=dict(
- values=[df_sorted.get(col) for col in header],
- fill_color=fill_color,
- align=params[u"align-itm"][idx]
- )
- )
- )
-
- ploff.plot(
- fig,
- show_link=False,
- auto_open=False,
- filename=f"{out_file_name}_in.html"
- )
-
- file_name = out_file_name.split(u"/")[-1]
- if u"vpp" in out_file_name:
- path = u"_tmp/src/vpp_performance_tests/comparisons/"
- else:
- path = u"_tmp/src/dpdk_performance_tests/comparisons/"
- with open(f"{path}{file_name}.rst", u"wt") as rst_file:
- rst_file.write(
- u"\n"
- u".. |br| raw:: html\n\n <br />\n\n\n"
- u".. |prein| raw:: html\n\n <pre>\n\n\n"
- u".. |preout| raw:: html\n\n </pre>\n\n"
- )
- rst_file.write(
- u".. raw:: html\n\n"
- f' <iframe frameborder="0" scrolling="no" '
- f'width="1600" height="1200" '
- f'src="../..{out_file_name.replace(u"_build", u"")}_in.html">'
- f'</iframe>\n\n'
- )
- if legend:
- rst_file.write(legend[1:].replace(u"\n", u" |br| "))
- if footnote:
- rst_file.write(footnote.replace(u"\n", u" |br| ")[1:])
-
-
-def table_perf_comparison(table, input_data):
- """Generate the table(s) with algorithm: table_perf_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(f" Generating the table {table.get(u'title', u'')} ...")
-
- # Transform the data
- logging.info(
- f" Creating the data set for the {table.get(u'type', u'')} "
- f"{table.get(u'title', u'')}."
- )
- data = input_data.filter_data(table, continue_on_error=True)
-
- # Prepare the header of the tables
- try:
- header = [u"Test Case", ]
- legend = u"\nLegend:\n"
-
- rca_data = None
- rca = table.get(u"rca", None)
- if rca:
- try:
- with open(rca.get(u"data-file", u""), u"r") as rca_file:
- rca_data = load(rca_file, Loader=FullLoader)
- header.insert(0, rca.get(u"title", u"RCA"))
- legend += (
- u"RCA: Reference to the Root Cause Analysis, see below.\n"
- )
- except (YAMLError, IOError) as err:
- logging.warning(repr(err))
-
- history = table.get(u"history", list())
- for item in history:
- header.extend(
- [
- f"{item[u'title']} Avg({table[u'include-tests']})",
- f"{item[u'title']} Stdev({table[u'include-tests']})"
- ]
- )
- legend += (
- f"{item[u'title']} Avg({table[u'include-tests']}): "
- f"Mean value of {table[u'include-tests']} [Mpps] computed from "
- f"a series of runs of the listed tests executed against "
- f"{item[u'title']}.\n"
- f"{item[u'title']} Stdev({table[u'include-tests']}): "
- f"Standard deviation value of {table[u'include-tests']} [Mpps] "
- f"computed from a series of runs of the listed tests executed "
- f"against {item[u'title']}.\n"
- )
- header.extend(
- [
- f"{table[u'reference'][u'title']} "
- f"Avg({table[u'include-tests']})",
- f"{table[u'reference'][u'title']} "
- f"Stdev({table[u'include-tests']})",
- f"{table[u'compare'][u'title']} "
- f"Avg({table[u'include-tests']})",
- f"{table[u'compare'][u'title']} "
- f"Stdev({table[u'include-tests']})",
- f"Diff({table[u'reference'][u'title']},"
- f"{table[u'compare'][u'title']})",
- u"Stdev(Diff)"
- ]
- )
- header_str = u";".join(header) + u"\n"
- legend += (
- f"{table[u'reference'][u'title']} "
- f"Avg({table[u'include-tests']}): "
- f"Mean value of {table[u'include-tests']} [Mpps] computed from a "
- f"series of runs of the listed tests executed against "
- f"{table[u'reference'][u'title']}.\n"
- f"{table[u'reference'][u'title']} "
- f"Stdev({table[u'include-tests']}): "
- f"Standard deviation value of {table[u'include-tests']} [Mpps] "
- f"computed from a series of runs of the listed tests executed "
- f"against {table[u'reference'][u'title']}.\n"
- f"{table[u'compare'][u'title']} "
- f"Avg({table[u'include-tests']}): "
- f"Mean value of {table[u'include-tests']} [Mpps] computed from a "
- f"series of runs of the listed tests executed against "
- f"{table[u'compare'][u'title']}.\n"
- f"{table[u'compare'][u'title']} "
- f"Stdev({table[u'include-tests']}): "
- f"Standard deviation value of {table[u'include-tests']} [Mpps] "
- f"computed from a series of runs of the listed tests executed "
- f"against {table[u'compare'][u'title']}.\n"
- f"Diff({table[u'reference'][u'title']},"
- f"{table[u'compare'][u'title']}): "
- f"Percentage change calculated for mean values.\n"
- u"Stdev(Diff): "
- u"Standard deviation of percentage change calculated for mean "
- u"values.\n"
- u"NT: Not Tested\n"
- )
- except (AttributeError, KeyError) as err:
- logging.error(f"The model is invalid, missing parameter: {repr(err)}")
- return
-
- # Prepare data to the table:
- tbl_dict = dict()
- for job, builds in table[u"reference"][u"data"].items():
- for build in builds:
- for tst_name, tst_data in data[job][str(build)].items():
- tst_name_mod = _tpc_modify_test_name(tst_name)
- if (u"across topologies" in table[u"title"].lower() or
- (u" 3n-" in table[u"title"].lower() and
- u" 2n-" in table[u"title"].lower())):
- tst_name_mod = tst_name_mod.replace(u"2n1l-", u"")
- if tbl_dict.get(tst_name_mod, None) is None:
- name = tst_data[u'name'].rsplit(u'-', 1)[0]
- if u"across testbeds" in table[u"title"].lower() or \
- u"across topologies" in table[u"title"].lower():
- name = _tpc_modify_displayed_test_name(name)
- tbl_dict[tst_name_mod] = {
- u"name": name,
- u"replace-ref": True,
- u"replace-cmp": True,
- u"ref-data": list(),
- u"cmp-data": list()
- }
- _tpc_insert_data(target=tbl_dict[tst_name_mod][u"ref-data"],
- src=tst_data,
- include_tests=table[u"include-tests"])
-
- replacement = table[u"reference"].get(u"data-replacement", None)
- if replacement:
- rpl_data = input_data.filter_data(
- table, data=replacement, continue_on_error=True)
- for job, builds in replacement.items():
- for build in builds:
- for tst_name, tst_data in rpl_data[job][str(build)].items():
- tst_name_mod = _tpc_modify_test_name(tst_name)
- if (u"across topologies" in table[u"title"].lower() or
- (u" 3n-" in table[u"title"].lower() and
- u" 2n-" in table[u"title"].lower())):
- tst_name_mod = tst_name_mod.replace(u"2n1l-", u"")
- if tbl_dict.get(tst_name_mod, None) is None:
- name = tst_data[u'name'].rsplit(u'-', 1)[0]
- if u"across testbeds" in table[u"title"].lower() or \
- u"across topologies" in table[u"title"].lower():
- name = _tpc_modify_displayed_test_name(name)
- tbl_dict[tst_name_mod] = {
- u"name": name,
- u"replace-ref": False,
- u"replace-cmp": True,
- u"ref-data": list(),
- u"cmp-data": list()
- }
- if tbl_dict[tst_name_mod][u"replace-ref"]:
- tbl_dict[tst_name_mod][u"replace-ref"] = False
- tbl_dict[tst_name_mod][u"ref-data"] = list()
-
- _tpc_insert_data(
- target=tbl_dict[tst_name_mod][u"ref-data"],
- src=tst_data,
- include_tests=table[u"include-tests"]
- )
-
- for job, builds in table[u"compare"][u"data"].items():
- for build in builds:
- for tst_name, tst_data in data[job][str(build)].items():
- tst_name_mod = _tpc_modify_test_name(tst_name)
- if (u"across topologies" in table[u"title"].lower() or
- (u" 3n-" in table[u"title"].lower() and
- u" 2n-" in table[u"title"].lower())):
- tst_name_mod = tst_name_mod.replace(u"2n1l-", u"")
- if tbl_dict.get(tst_name_mod, None) is None:
- name = tst_data[u'name'].rsplit(u'-', 1)[0]
- if u"across testbeds" in table[u"title"].lower() or \
- u"across topologies" in table[u"title"].lower():
- name = _tpc_modify_displayed_test_name(name)
- tbl_dict[tst_name_mod] = {
- u"name": name,
- u"replace-ref": False,
- u"replace-cmp": True,
- u"ref-data": list(),
- u"cmp-data": list()
- }
- _tpc_insert_data(
- target=tbl_dict[tst_name_mod][u"cmp-data"],
- src=tst_data,
- include_tests=table[u"include-tests"]
- )
-
- replacement = table[u"compare"].get(u"data-replacement", None)
- if replacement:
- rpl_data = input_data.filter_data(
- table, data=replacement, continue_on_error=True)
- for job, builds in replacement.items():
- for build in builds:
- for tst_name, tst_data in rpl_data[job][str(build)].items():
- tst_name_mod = _tpc_modify_test_name(tst_name)
- if (u"across topologies" in table[u"title"].lower() or
- (u" 3n-" in table[u"title"].lower() and
- u" 2n-" in table[u"title"].lower())):
- tst_name_mod = tst_name_mod.replace(u"2n1l-", u"")
- if tbl_dict.get(tst_name_mod, None) is None:
- name = tst_data[u'name'].rsplit(u'-', 1)[0]
- if u"across testbeds" in table[u"title"].lower() or \
- u"across topologies" in table[u"title"].lower():
- name = _tpc_modify_displayed_test_name(name)
- tbl_dict[tst_name_mod] = {
- u"name": name,
- u"replace-ref": False,
- u"replace-cmp": False,
- u"ref-data": list(),
- u"cmp-data": list()
- }
- if tbl_dict[tst_name_mod][u"replace-cmp"]:
- tbl_dict[tst_name_mod][u"replace-cmp"] = False
- tbl_dict[tst_name_mod][u"cmp-data"] = list()
-
- _tpc_insert_data(
- target=tbl_dict[tst_name_mod][u"cmp-data"],
- src=tst_data,
- include_tests=table[u"include-tests"]
- )
-
- for item in history:
- for job, builds in item[u"data"].items():
- for build in builds:
- for tst_name, tst_data in data[job][str(build)].items():
- tst_name_mod = _tpc_modify_test_name(tst_name)
- if (u"across topologies" in table[u"title"].lower() or
- (u" 3n-" in table[u"title"].lower() and
- u" 2n-" in table[u"title"].lower())):
- tst_name_mod = tst_name_mod.replace(u"2n1l-", u"")
- if tbl_dict.get(tst_name_mod, None) is None:
- continue
- if tbl_dict[tst_name_mod].get(u"history", None) is None:
- tbl_dict[tst_name_mod][u"history"] = OrderedDict()
- if tbl_dict[tst_name_mod][u"history"].\
- get(item[u"title"], None) is None:
- tbl_dict[tst_name_mod][u"history"][item[
- u"title"]] = list()
- try:
- if table[u"include-tests"] == u"MRR":
- res = (tst_data[u"result"][u"receive-rate"],
- tst_data[u"result"][u"receive-stdev"])
- elif table[u"include-tests"] == u"PDR":
- res = tst_data[u"throughput"][u"PDR"][u"LOWER"]
- elif table[u"include-tests"] == u"NDR":
- res = tst_data[u"throughput"][u"NDR"][u"LOWER"]
- else:
- continue
- tbl_dict[tst_name_mod][u"history"][item[u"title"]].\
- append(res)
- except (TypeError, KeyError):
- pass
-
- tbl_lst = list()
- for tst_name in tbl_dict:
- item = [tbl_dict[tst_name][u"name"], ]
- if history:
- if tbl_dict[tst_name].get(u"history", None) is not None:
- for hist_data in tbl_dict[tst_name][u"history"].values():
- if hist_data:
- if table[u"include-tests"] == u"MRR":
- item.append(round(hist_data[0][0] / 1e6, 1))
- item.append(round(hist_data[0][1] / 1e6, 1))
- else:
- item.append(round(mean(hist_data) / 1e6, 1))
- item.append(round(stdev(hist_data) / 1e6, 1))
- else:
- item.extend([u"NT", u"NT"])
- else:
- item.extend([u"NT", u"NT"])
- data_r = tbl_dict[tst_name][u"ref-data"]
- if data_r:
- if table[u"include-tests"] == u"MRR":
- data_r_mean = data_r[0][0]
- data_r_stdev = data_r[0][1]
- else:
- data_r_mean = mean(data_r)
- data_r_stdev = stdev(data_r)
- item.append(round(data_r_mean / 1e6, 1))
- item.append(round(data_r_stdev / 1e6, 1))
- else:
- data_r_mean = None
- data_r_stdev = None
- item.extend([u"NT", u"NT"])
- data_c = tbl_dict[tst_name][u"cmp-data"]
- if data_c:
- if table[u"include-tests"] == u"MRR":
- data_c_mean = data_c[0][0]
- data_c_stdev = data_c[0][1]
- else:
- data_c_mean = mean(data_c)
- data_c_stdev = stdev(data_c)
- item.append(round(data_c_mean / 1e6, 1))
- item.append(round(data_c_stdev / 1e6, 1))
- else:
- data_c_mean = None
- data_c_stdev = None
- item.extend([u"NT", u"NT"])
- if item[-2] == u"NT":
- pass
- elif item[-4] == u"NT":
- item.append(u"New in CSIT-2001")
- item.append(u"New in CSIT-2001")
- elif data_r_mean is not None and data_c_mean is not None:
- delta, d_stdev = relative_change_stdev(
- data_r_mean, data_c_mean, data_r_stdev, data_c_stdev
- )
- try:
- item.append(round(delta))
- except ValueError:
- item.append(delta)
- try:
- item.append(round(d_stdev))
- except ValueError:
- item.append(d_stdev)
- if rca_data:
- rca_nr = rca_data.get(item[0], u"-")
- item.insert(0, f"[{rca_nr}]" if rca_nr != u"-" else u"-")
- if (len(item) == len(header)) and (item[-4] != u"NT"):
- tbl_lst.append(item)
-
- tbl_lst = _tpc_sort_table(tbl_lst)
-
- # Generate csv tables:
- csv_file = f"{table[u'output-file']}.csv"
- with open(csv_file, u"wt") as file_handler:
- file_handler.write(header_str)
- for test in tbl_lst:
- file_handler.write(u";".join([str(item) for item in test]) + u"\n")
-
- txt_file_name = f"{table[u'output-file']}.txt"
- convert_csv_to_pretty_txt(csv_file, txt_file_name, delimiter=u";")
-
- footnote = u""
- with open(txt_file_name, u'a') as txt_file:
- txt_file.write(legend)
- if rca_data:
- footnote = rca_data.get(u"footnote", u"")
- if footnote:
- txt_file.write(footnote)
- txt_file.write(u":END")
-
- # Generate html table:
- _tpc_generate_html_table(
- header,
- tbl_lst,
- table[u'output-file'],
- legend=legend,
- footnote=footnote
- )
-
-
-def table_perf_comparison_nic(table, input_data):
- """Generate the table(s) with algorithm: table_perf_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(f" Generating the table {table.get(u'title', u'')} ...")
-
- # Transform the data
- logging.info(
- f" Creating the data set for the {table.get(u'type', u'')} "
- f"{table.get(u'title', u'')}."
- )
- data = input_data.filter_data(table, continue_on_error=True)
-
- # Prepare the header of the tables
- try:
- header = [u"Test Case", ]
- legend = u"\nLegend:\n"
-
- rca_data = None
- rca = table.get(u"rca", None)
- if rca:
- try:
- with open(rca.get(u"data-file", ""), u"r") as rca_file:
- rca_data = load(rca_file, Loader=FullLoader)
- header.insert(0, rca.get(u"title", "RCA"))
- legend += (
- u"RCA: Reference to the Root Cause Analysis, see below.\n"
- )
- except (YAMLError, IOError) as err:
- logging.warning(repr(err))
-
- history = table.get(u"history", list())
- for item in history:
- header.extend(
- [
- f"{item[u'title']} Avg({table[u'include-tests']})",
- f"{item[u'title']} Stdev({table[u'include-tests']})"
- ]
- )
- legend += (
- f"{item[u'title']} Avg({table[u'include-tests']}): "
- f"Mean value of {table[u'include-tests']} [Mpps] computed from "
- f"a series of runs of the listed tests executed against "
- f"{item[u'title']}.\n"
- f"{item[u'title']} Stdev({table[u'include-tests']}): "
- f"Standard deviation value of {table[u'include-tests']} [Mpps] "
- f"computed from a series of runs of the listed tests executed "
- f"against {item[u'title']}.\n"
- )
- header.extend(
- [
- f"{table[u'reference'][u'title']} "
- f"Avg({table[u'include-tests']})",
- f"{table[u'reference'][u'title']} "
- f"Stdev({table[u'include-tests']})",
- f"{table[u'compare'][u'title']} "
- f"Avg({table[u'include-tests']})",
- f"{table[u'compare'][u'title']} "
- f"Stdev({table[u'include-tests']})",
- f"Diff({table[u'reference'][u'title']},"
- f"{table[u'compare'][u'title']})",
- u"Stdev(Diff)"
- ]
- )
- header_str = u";".join(header) + u"\n"
- legend += (
- f"{table[u'reference'][u'title']} "
- f"Avg({table[u'include-tests']}): "
- f"Mean value of {table[u'include-tests']} [Mpps] computed from a "
- f"series of runs of the listed tests executed against "
- f"{table[u'reference'][u'title']}.\n"
- f"{table[u'reference'][u'title']} "
- f"Stdev({table[u'include-tests']}): "
- f"Standard deviation value of {table[u'include-tests']} [Mpps] "
- f"computed from a series of runs of the listed tests executed "
- f"against {table[u'reference'][u'title']}.\n"
- f"{table[u'compare'][u'title']} "
- f"Avg({table[u'include-tests']}): "
- f"Mean value of {table[u'include-tests']} [Mpps] computed from a "
- f"series of runs of the listed tests executed against "
- f"{table[u'compare'][u'title']}.\n"
- f"{table[u'compare'][u'title']} "
- f"Stdev({table[u'include-tests']}): "
- f"Standard deviation value of {table[u'include-tests']} [Mpps] "
- f"computed from a series of runs of the listed tests executed "
- f"against {table[u'compare'][u'title']}.\n"
- f"Diff({table[u'reference'][u'title']},"
- f"{table[u'compare'][u'title']}): "
- f"Percentage change calculated for mean values.\n"
- u"Stdev(Diff): "
- u"Standard deviation of percentage change calculated for mean "
- u"values.\n"
- u"NT: Not Tested\n"
- )
- except (AttributeError, KeyError) as err:
- logging.error(f"The model is invalid, missing parameter: {repr(err)}")
- return
-
- # Prepare data to the table:
- tbl_dict = dict()
- for job, builds in table[u"reference"][u"data"].items():
- for build in builds:
- for tst_name, tst_data in data[job][str(build)].items():
- if table[u"reference"][u"nic"] not in tst_data[u"tags"]:
- continue
- tst_name_mod = _tpc_modify_test_name(tst_name)
- if (u"across topologies" in table[u"title"].lower() or
- (u" 3n-" in table[u"title"].lower() and
- u" 2n-" in table[u"title"].lower())):
- tst_name_mod = tst_name_mod.replace(u"2n1l-", u"")
- if tbl_dict.get(tst_name_mod, None) is None:
- name = tst_data[u'name'].rsplit(u'-', 1)[0]
- if u"across testbeds" in table[u"title"].lower() or \
- u"across topologies" in table[u"title"].lower():
- name = _tpc_modify_displayed_test_name(name)
- tbl_dict[tst_name_mod] = {
- u"name": name,
- u"replace-ref": True,
- u"replace-cmp": True,
- u"ref-data": list(),
- u"cmp-data": list()
- }
- _tpc_insert_data(
- target=tbl_dict[tst_name_mod][u"ref-data"],
- src=tst_data,
- include_tests=table[u"include-tests"]
- )
-
- replacement = table[u"reference"].get(u"data-replacement", None)
- if replacement:
- rpl_data = input_data.filter_data(
- table, data=replacement, continue_on_error=True)
- for job, builds in replacement.items():
- for build in builds:
- for tst_name, tst_data in rpl_data[job][str(build)].items():
- if table[u"reference"][u"nic"] not in tst_data[u"tags"]:
- continue
- tst_name_mod = _tpc_modify_test_name(tst_name)
- if (u"across topologies" in table[u"title"].lower() or
- (u" 3n-" in table[u"title"].lower() and
- u" 2n-" in table[u"title"].lower())):
- tst_name_mod = tst_name_mod.replace(u"2n1l-", u"")
- if tbl_dict.get(tst_name_mod, None) is None:
- name = tst_data[u'name'].rsplit(u'-', 1)[0]
- if u"across testbeds" in table[u"title"].lower() or \
- u"across topologies" in table[u"title"].lower():
- name = _tpc_modify_displayed_test_name(name)
- tbl_dict[tst_name_mod] = {
- u"name": name,
- u"replace-ref": False,
- u"replace-cmp": True,
- u"ref-data": list(),
- u"cmp-data": list()
- }
- if tbl_dict[tst_name_mod][u"replace-ref"]:
- tbl_dict[tst_name_mod][u"replace-ref"] = False
- tbl_dict[tst_name_mod][u"ref-data"] = list()
-
- _tpc_insert_data(
- target=tbl_dict[tst_name_mod][u"ref-data"],
- src=tst_data,
- include_tests=table[u"include-tests"]
- )
-
- for job, builds in table[u"compare"][u"data"].items():
- for build in builds:
- for tst_name, tst_data in data[job][str(build)].items():
- if table[u"compare"][u"nic"] not in tst_data[u"tags"]:
- continue
- tst_name_mod = _tpc_modify_test_name(tst_name)
- if (u"across topologies" in table[u"title"].lower() or
- (u" 3n-" in table[u"title"].lower() and
- u" 2n-" in table[u"title"].lower())):
- tst_name_mod = tst_name_mod.replace(u"2n1l-", u"")
- if tbl_dict.get(tst_name_mod, None) is None:
- name = tst_data[u'name'].rsplit(u'-', 1)[0]
- if u"across testbeds" in table[u"title"].lower() or \
- u"across topologies" in table[u"title"].lower():
- name = _tpc_modify_displayed_test_name(name)
- tbl_dict[tst_name_mod] = {
- u"name": name,
- u"replace-ref": False,
- u"replace-cmp": True,
- u"ref-data": list(),
- u"cmp-data": list()
- }
- _tpc_insert_data(
- target=tbl_dict[tst_name_mod][u"cmp-data"],
- src=tst_data,
- include_tests=table[u"include-tests"]
- )
-
- replacement = table[u"compare"].get(u"data-replacement", None)
- if replacement:
- rpl_data = input_data.filter_data(
- table, data=replacement, continue_on_error=True)
- for job, builds in replacement.items():
- for build in builds:
- for tst_name, tst_data in rpl_data[job][str(build)].items():
- if table[u"compare"][u"nic"] not in tst_data[u"tags"]:
- continue
- tst_name_mod = _tpc_modify_test_name(tst_name)
- if (u"across topologies" in table[u"title"].lower() or
- (u" 3n-" in table[u"title"].lower() and
- u" 2n-" in table[u"title"].lower())):
- tst_name_mod = tst_name_mod.replace(u"2n1l-", u"")
- if tbl_dict.get(tst_name_mod, None) is None:
- name = tst_data[u'name'].rsplit(u'-', 1)[0]
- if u"across testbeds" in table[u"title"].lower() or \
- u"across topologies" in table[u"title"].lower():
- name = _tpc_modify_displayed_test_name(name)
- tbl_dict[tst_name_mod] = {
- u"name": name,
- u"replace-ref": False,
- u"replace-cmp": False,
- u"ref-data": list(),
- u"cmp-data": list()
- }
- if tbl_dict[tst_name_mod][u"replace-cmp"]:
- tbl_dict[tst_name_mod][u"replace-cmp"] = False
- tbl_dict[tst_name_mod][u"cmp-data"] = list()
-
- _tpc_insert_data(
- target=tbl_dict[tst_name_mod][u"cmp-data"],
- src=tst_data,
- include_tests=table[u"include-tests"]
- )
-
- for item in history:
- for job, builds in item[u"data"].items():
- for build in builds:
- for tst_name, tst_data in data[job][str(build)].items():
- if item[u"nic"] not in tst_data[u"tags"]:
- continue
- tst_name_mod = _tpc_modify_test_name(tst_name)
- if (u"across topologies" in table[u"title"].lower() or
- (u" 3n-" in table[u"title"].lower() and
- u" 2n-" in table[u"title"].lower())):
- tst_name_mod = tst_name_mod.replace(u"2n1l-", u"")
- if tbl_dict.get(tst_name_mod, None) is None:
- continue
- if tbl_dict[tst_name_mod].get(u"history", None) is None:
- tbl_dict[tst_name_mod][u"history"] = OrderedDict()
- if tbl_dict[tst_name_mod][u"history"].\
- get(item[u"title"], None) is None:
- tbl_dict[tst_name_mod][u"history"][item[
- u"title"]] = list()
- try:
- if table[u"include-tests"] == u"MRR":
- res = (tst_data[u"result"][u"receive-rate"],
- tst_data[u"result"][u"receive-stdev"])
- elif table[u"include-tests"] == u"PDR":
- res = tst_data[u"throughput"][u"PDR"][u"LOWER"]
- elif table[u"include-tests"] == u"NDR":
- res = tst_data[u"throughput"][u"NDR"][u"LOWER"]
- else:
- continue
- tbl_dict[tst_name_mod][u"history"][item[u"title"]].\
- append(res)
- except (TypeError, KeyError):
- pass
-
- tbl_lst = list()
- for tst_name in tbl_dict:
- item = [tbl_dict[tst_name][u"name"], ]
- if history:
- if tbl_dict[tst_name].get(u"history", None) is not None:
- for hist_data in tbl_dict[tst_name][u"history"].values():
- if hist_data:
- if table[u"include-tests"] == u"MRR":
- item.append(round(hist_data[0][0] / 1e6, 1))
- item.append(round(hist_data[0][1] / 1e6, 1))
- else:
- item.append(round(mean(hist_data) / 1e6, 1))
- item.append(round(stdev(hist_data) / 1e6, 1))
- else:
- item.extend([u"NT", u"NT"])
- else:
- item.extend([u"NT", u"NT"])
- data_r = tbl_dict[tst_name][u"ref-data"]
- if data_r:
- if table[u"include-tests"] == u"MRR":
- data_r_mean = data_r[0][0]
- data_r_stdev = data_r[0][1]
- else:
- data_r_mean = mean(data_r)
- data_r_stdev = stdev(data_r)
- item.append(round(data_r_mean / 1e6, 1))
- item.append(round(data_r_stdev / 1e6, 1))
- else:
- data_r_mean = None
- data_r_stdev = None
- item.extend([u"NT", u"NT"])
- data_c = tbl_dict[tst_name][u"cmp-data"]
- if data_c:
- if table[u"include-tests"] == u"MRR":
- data_c_mean = data_c[0][0]
- data_c_stdev = data_c[0][1]
- else:
- data_c_mean = mean(data_c)
- data_c_stdev = stdev(data_c)
- item.append(round(data_c_mean / 1e6, 1))
- item.append(round(data_c_stdev / 1e6, 1))
- else:
- data_c_mean = None
- data_c_stdev = None
- item.extend([u"NT", u"NT"])
- if item[-2] == u"NT":
- pass
- elif item[-4] == u"NT":
- item.append(u"New in CSIT-2001")
- item.append(u"New in CSIT-2001")
- elif data_r_mean is not None and data_c_mean is not None:
- delta, d_stdev = relative_change_stdev(
- data_r_mean, data_c_mean, data_r_stdev, data_c_stdev
- )
- try:
- item.append(round(delta))
- except ValueError:
- item.append(delta)
- try:
- item.append(round(d_stdev))
- except ValueError:
- item.append(d_stdev)
- if rca_data:
- rca_nr = rca_data.get(item[0], u"-")
- item.insert(0, f"[{rca_nr}]" if rca_nr != u"-" else u"-")
- if (len(item) == len(header)) and (item[-4] != u"NT"):
- tbl_lst.append(item)
-
- tbl_lst = _tpc_sort_table(tbl_lst)
-
- # Generate csv tables:
- csv_file = f"{table[u'output-file']}.csv"
- with open(csv_file, u"wt") as file_handler:
- file_handler.write(header_str)
- for test in tbl_lst:
- file_handler.write(u";".join([str(item) for item in test]) + u"\n")
-
- txt_file_name = f"{table[u'output-file']}.txt"
- convert_csv_to_pretty_txt(csv_file, txt_file_name, delimiter=u";")
-
- footnote = u""
- with open(txt_file_name, u'a') as txt_file:
- txt_file.write(legend)
- if rca_data:
- footnote = rca_data.get(u"footnote", u"")
- if footnote:
- txt_file.write(footnote)
- txt_file.write(u":END")
-
- # Generate html table:
- _tpc_generate_html_table(
- header,
- tbl_lst,
- table[u'output-file'],
- legend=legend,
- footnote=footnote
- )
-
-
-def table_nics_comparison(table, input_data):
- """Generate the table(s) with algorithm: table_nics_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(f" Generating the table {table.get(u'title', u'')} ...")
-
- # Transform the data
- logging.info(
- f" Creating the data set for the {table.get(u'type', u'')} "
- f"{table.get(u'title', u'')}."
- )
- data = input_data.filter_data(table, continue_on_error=True)
-
- # Prepare the header of the tables
- try:
- header = [
- u"Test Case",
- f"{table[u'reference'][u'title']} "
- f"Avg({table[u'include-tests']})",
- f"{table[u'reference'][u'title']} "
- f"Stdev({table[u'include-tests']})",
- f"{table[u'compare'][u'title']} "
- f"Avg({table[u'include-tests']})",
- f"{table[u'compare'][u'title']} "
- f"Stdev({table[u'include-tests']})",
- f"Diff({table[u'reference'][u'title']},"
- f"{table[u'compare'][u'title']})",
- u"Stdev(Diff)"
- ]
- legend = (
- u"\nLegend:\n"
- f"{table[u'reference'][u'title']} "
- f"Avg({table[u'include-tests']}): "
- f"Mean value of {table[u'include-tests']} [Mpps] computed from a "
- f"series of runs of the listed tests executed using "
- f"{table[u'reference'][u'title']} NIC.\n"
- f"{table[u'reference'][u'title']} "
- f"Stdev({table[u'include-tests']}): "
- f"Standard deviation value of {table[u'include-tests']} [Mpps] "
- f"computed from a series of runs of the listed tests executed "
- f"using {table[u'reference'][u'title']} NIC.\n"
- f"{table[u'compare'][u'title']} "
- f"Avg({table[u'include-tests']}): "
- f"Mean value of {table[u'include-tests']} [Mpps] computed from a "
- f"series of runs of the listed tests executed using "
- f"{table[u'compare'][u'title']} NIC.\n"
- f"{table[u'compare'][u'title']} "
- f"Stdev({table[u'include-tests']}): "
- f"Standard deviation value of {table[u'include-tests']} [Mpps] "
- f"computed from a series of runs of the listed tests executed "
- f"using {table[u'compare'][u'title']} NIC.\n"
- f"Diff({table[u'reference'][u'title']},"
- f"{table[u'compare'][u'title']}): "
- f"Percentage change calculated for mean values.\n"
- u"Stdev(Diff): "
- u"Standard deviation of percentage change calculated for mean "
- u"values.\n"
- u":END"
- )
-
- except (AttributeError, KeyError) as err:
- logging.error(f"The model is invalid, missing parameter: {repr(err)}")
- return
-
- # Prepare data to the table:
- tbl_dict = dict()
- for job, builds in table[u"data"].items():
- for build in builds:
- for tst_name, tst_data in data[job][str(build)].items():
- tst_name_mod = _tpc_modify_test_name(tst_name, ignore_nic=True)
- if tbl_dict.get(tst_name_mod, None) is None:
- name = tst_data[u'name'].rsplit(u'-', 1)[0]
- tbl_dict[tst_name_mod] = {
- u"name": name,
- u"ref-data": list(),
- u"cmp-data": list()
- }
- try:
- if table[u"include-tests"] == u"MRR":
- result = (tst_data[u"result"][u"receive-rate"],
- tst_data[u"result"][u"receive-stdev"])
- elif table[u"include-tests"] == u"PDR":
- result = tst_data[u"throughput"][u"PDR"][u"LOWER"]
- elif table[u"include-tests"] == u"NDR":
- result = tst_data[u"throughput"][u"NDR"][u"LOWER"]
- else:
- continue
-
- if result and \
- table[u"reference"][u"nic"] in tst_data[u"tags"]:
- tbl_dict[tst_name_mod][u"ref-data"].append(result)
- elif result and \
- table[u"compare"][u"nic"] in tst_data[u"tags"]:
- tbl_dict[tst_name_mod][u"cmp-data"].append(result)
- except (TypeError, KeyError) as err:
- logging.debug(f"No data for {tst_name}\n{repr(err)}")
- # No data in output.xml for this test
-
- tbl_lst = list()
- for tst_name in tbl_dict:
- item = [tbl_dict[tst_name][u"name"], ]
- data_r = tbl_dict[tst_name][u"ref-data"]
- if data_r:
- if table[u"include-tests"] == u"MRR":
- data_r_mean = data_r[0][0]
- data_r_stdev = data_r[0][1]
- else:
- data_r_mean = mean(data_r)
- data_r_stdev = stdev(data_r)
- item.append(round(data_r_mean / 1e6, 1))
- item.append(round(data_r_stdev / 1e6, 1))
- else:
- data_r_mean = None
- data_r_stdev = None
- item.extend([None, None])
- data_c = tbl_dict[tst_name][u"cmp-data"]
- if data_c:
- if table[u"include-tests"] == u"MRR":
- data_c_mean = data_c[0][0]
- data_c_stdev = data_c[0][1]
- else:
- data_c_mean = mean(data_c)
- data_c_stdev = stdev(data_c)
- item.append(round(data_c_mean / 1e6, 1))
- item.append(round(data_c_stdev / 1e6, 1))
- else:
- data_c_mean = None
- data_c_stdev = None
- item.extend([None, None])
- if data_r_mean is not None and data_c_mean is not None:
- delta, d_stdev = relative_change_stdev(
- data_r_mean, data_c_mean, data_r_stdev, data_c_stdev
+ )
)
- try:
- item.append(round(delta))
- except ValueError:
- item.append(delta)
- try:
- item.append(round(d_stdev))
- except ValueError:
- item.append(d_stdev)
- tbl_lst.append(item)
- # Sort the table according to the relative change
- tbl_lst.sort(key=lambda rel: rel[-1], reverse=True)
+ fig.update_layout(
+ updatemenus=[
+ go.layout.Updatemenu(
+ type=u"dropdown",
+ direction=u"down",
+ x=0.0,
+ xanchor=u"left",
+ y=1.002,
+ yanchor=u"bottom",
+ active=len(menu_items) - 1,
+ buttons=list(buttons)
+ )
+ ],
+ )
+ else:
+ fig.add_trace(
+ go.Table(
+ columnwidth=params[u"width"][idx],
+ header=table_header,
+ cells=dict(
+ values=[df_sorted.get(col) for col in header],
+ fill_color=fill_color,
+ align=params[u"align-itm"][idx],
+ font=dict(
+ family=u"Courier New",
+ size=12
+ )
+ )
+ )
+ )
- # Generate csv tables:
- with open(f"{table[u'output-file']}.csv", u"wt") as file_handler:
- file_handler.write(u";".join(header) + u"\n")
- for test in tbl_lst:
- file_handler.write(u";".join([str(item) for item in test]) + u"\n")
+ ploff.plot(
+ fig,
+ show_link=False,
+ auto_open=False,
+ filename=f"{out_file_name}_in.html"
+ )
- convert_csv_to_pretty_txt(f"{table[u'output-file']}.csv",
- f"{table[u'output-file']}.txt",
- delimiter=u";")
+ if not generate_rst:
+ return
- with open(table[u'output-file'], u'a') as txt_file:
- txt_file.write(legend)
+ file_name = out_file_name.split(u"/")[-1]
+ if u"vpp" in out_file_name:
+ path = u"_tmp/src/vpp_performance_tests/comparisons/"
+ else:
+ path = u"_tmp/src/dpdk_performance_tests/comparisons/"
+ logging.info(f" Writing the HTML file to {path}{file_name}.rst")
+ with open(f"{path}{file_name}.rst", u"wt") as rst_file:
+ rst_file.write(
+ u"\n"
+ u".. |br| raw:: html\n\n <br />\n\n\n"
+ u".. |prein| raw:: html\n\n <pre>\n\n\n"
+ u".. |preout| raw:: html\n\n </pre>\n\n"
+ )
+ if title:
+ rst_file.write(f"{title}\n")
+ rst_file.write(f"{u'`' * len(title)}\n\n")
+ rst_file.write(
+ u".. raw:: html\n\n"
+ f' <iframe frameborder="0" scrolling="no" '
+ f'width="1600" height="1200" '
+ f'src="../..{out_file_name.replace(u"_build", u"")}_in.html">'
+ f'</iframe>\n\n'
+ )
- # Generate html table:
- _tpc_generate_html_table(
- header,
- tbl_lst,
- table[u'output-file'],
- legend=legend
- )
+ if legend:
+ try:
+ itm_lst = legend[1:-2].split(u"\n")
+ rst_file.write(
+ f"{itm_lst[0]}\n\n- " + u'\n- '.join(itm_lst[1:]) + u"\n\n"
+ )
+ except IndexError as err:
+ logging.error(f"Legend cannot be written to html file\n{err}")
+ if footnote:
+ try:
+ itm_lst = footnote[1:].split(u"\n")
+ rst_file.write(
+ f"{itm_lst[0]}\n\n- " + u'\n- '.join(itm_lst[1:]) + u"\n\n"
+ )
+ except IndexError as err:
+ logging.error(f"Footnote cannot be written to html file\n{err}")
def table_soak_vs_ndr(table, input_data):
f"Percentage change calculated for mean values.\n"
u"Stdev(Diff): "
u"Standard deviation of percentage change calculated for mean "
- u"values.\n"
- u":END"
+ u"values."
)
except (AttributeError, KeyError) as err:
logging.error(f"The model is invalid, missing parameter: {repr(err)}")
else:
data_c_mean = mean(data_c)
data_c_stdev = stdev(data_c)
- item.append(round(data_c_mean / 1e6, 1))
- item.append(round(data_c_stdev / 1e6, 1))
+ item.append(round(data_c_mean / 1e6, 2))
+ item.append(round(data_c_stdev / 1e6, 2))
else:
data_c_mean = None
data_c_stdev = None
delta, d_stdev = relative_change_stdev(
data_r_mean, data_c_mean, data_r_stdev, data_c_stdev)
try:
- item.append(round(delta))
+ item.append(round(delta, 2))
except ValueError:
item.append(delta)
try:
- item.append(round(d_stdev))
+ item.append(round(d_stdev, 2))
except ValueError:
item.append(d_stdev)
tbl_lst.append(item)
tbl_lst.sort(key=lambda rel: rel[-1], reverse=True)
# Generate csv tables:
- csv_file = f"{table[u'output-file']}.csv"
- with open(csv_file, u"wt") as file_handler:
+ csv_file_name = f"{table[u'output-file']}.csv"
+ with open(csv_file_name, u"wt") as file_handler:
file_handler.write(header_str)
for test in tbl_lst:
file_handler.write(u";".join([str(item) for item in test]) + u"\n")
convert_csv_to_pretty_txt(
- csv_file, f"{table[u'output-file']}.txt", delimiter=u";"
+ csv_file_name, f"{table[u'output-file']}.txt", delimiter=u";"
)
- with open(f"{table[u'output-file']}.txt", u'a') as txt_file:
- txt_file.write(legend)
+ with open(f"{table[u'output-file']}.txt", u'a') as file_handler:
+ file_handler.write(legend)
# Generate html table:
_tpc_generate_html_table(
header,
tbl_lst,
table[u'output-file'],
- legend=legend
+ legend=legend,
+ title=table.get(u"title", u"")
)
header = [
u"Test Case",
u"Trend [Mpps]",
- u"Short-Term Change [%]",
+ u"Runs [#]",
u"Long-Term Change [%]",
u"Regressions [#]",
u"Progressions [#]"
]
header_str = u",".join(header) + u"\n"
+ incl_tests = table.get(u"include-tests", u"MRR")
+
# Prepare data to the table:
tbl_dict = dict()
for job, builds in table[u"data"].items():
u"data": OrderedDict()
}
try:
- tbl_dict[tst_name][u"data"][str(build)] = \
- tst_data[u"result"][u"receive-rate"]
+ if incl_tests == u"MRR":
+ tbl_dict[tst_name][u"data"][str(build)] = \
+ tst_data[u"result"][u"receive-rate"]
+ elif incl_tests == u"NDR":
+ tbl_dict[tst_name][u"data"][str(build)] = \
+ tst_data[u"throughput"][u"NDR"][u"LOWER"]
+ elif incl_tests == u"PDR":
+ tbl_dict[tst_name][u"data"][str(build)] = \
+ tst_data[u"throughput"][u"PDR"][u"LOWER"]
except (TypeError, KeyError):
pass # No data in output.xml for this test
if len(data_t) < 2:
continue
- classification_lst, avgs = classify_anomalies(data_t)
+ try:
+ classification_lst, avgs, _ = classify_anomalies(data_t)
+ except ValueError as err:
+ logging.info(f"{err} Skipping")
+ return
win_size = min(len(data_t), table[u"window"])
long_win_size = min(len(data_t), table[u"long-trend-window"])
last_avg = avgs[-1]
avg_week_ago = avgs[max(-win_size, -len(avgs))]
+ nr_of_last_avgs = 0;
+ for x in reversed(avgs):
+ if x == last_avg:
+ nr_of_last_avgs += 1
+ else:
+ break
+
if isnan(last_avg) or isnan(avg_week_ago) or avg_week_ago == 0.0:
rel_change_last = nan
else:
tbl_lst.append(
[tbl_dict[tst_name][u"name"],
round(last_avg / 1e6, 2),
- rel_change_last,
+ nr_of_last_avgs,
rel_change_long,
- classification_lst[-win_size:].count(u"regression"),
- classification_lst[-win_size:].count(u"progression")])
+ classification_lst[-win_size+1:].count(u"regression"),
+ classification_lst[-win_size+1:].count(u"progression")])
tbl_lst.sort(key=lambda rel: rel[0])
-
- tbl_sorted = list()
- for nrr in range(table[u"window"], -1, -1):
- tbl_reg = [item for item in tbl_lst if item[4] == nrr]
- for nrp in range(table[u"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)
+ tbl_lst.sort(key=lambda rel: rel[2])
+ tbl_lst.sort(key=lambda rel: rel[3])
+ tbl_lst.sort(key=lambda rel: rel[5], reverse=True)
+ tbl_lst.sort(key=lambda rel: rel[4], reverse=True)
file_name = f"{table[u'output-file']}{table[u'output-file-ext']}"
logging.info(f" Writing file: {file_name}")
with open(file_name, u"wt") as file_handler:
file_handler.write(header_str)
- for test in tbl_sorted:
+ for test in tbl_lst:
file_handler.write(u",".join([str(item) for item in test]) + u'\n')
logging.info(f" Writing file: {table[u'output-file']}.txt")
nic = u"x553"
elif u"cx556" in test_name or u"cx556a" in test_name:
nic = u"cx556a"
+ elif u"ena" in test_name:
+ nic = u"nitro50g"
else:
nic = u""
frame_size = u""
if u"1t1c" in test_name or \
- (u"-1c-" in test_name and
- testbed in (u"3n-hsw", u"3n-tsh", u"2n-dnv", u"3n-dnv")):
+ (u"-1c-" in test_name and testbed in (u"3n-tsh", u"2n-tx2")):
cores = u"1t1c"
elif u"2t2c" in test_name or \
- (u"-2c-" in test_name and
- testbed in (u"3n-hsw", u"3n-tsh", u"2n-dnv", u"3n-dnv")):
+ (u"-2c-" in test_name and testbed in (u"3n-tsh", u"2n-tx2")):
cores = u"2t2c"
elif u"4t4c" in test_name or \
- (u"-4c-" in test_name and
- testbed in (u"3n-hsw", u"3n-tsh", u"2n-dnv", u"3n-dnv")):
+ (u"-4c-" in test_name and testbed in (u"3n-tsh", u"2n-tx2")):
cores = u"4t4c"
elif u"2t1c" in test_name or \
(u"-1c-" in test_name and
- testbed in (u"2n-skx", u"3n-skx", u"2n-clx")):
+ testbed in (u"2n-icx", u"3n-icx", u"2n-clx", u"2n-zn2", u"2n-aws")):
cores = u"2t1c"
elif u"4t2c" in test_name or \
(u"-2c-" in test_name and
- testbed in (u"2n-skx", u"3n-skx", u"2n-clx")):
+ testbed in (u"2n-icx", u"3n-icx", u"2n-clx", u"2n-zn2", u"2n-aws")):
cores = u"4t2c"
elif u"8t4c" in test_name or \
(u"-4c-" in test_name and
- testbed in (u"2n-skx", u"3n-skx", u"2n-clx")):
+ testbed in (u"2n-icx", u"3n-icx", u"2n-clx", u"2n-zn2", u"2n-aws")):
cores = u"8t4c"
else:
cores = u""
driver = u"l3fwd"
elif u"avf" in test_name:
driver = u"avf"
+ elif u"af-xdp" in test_name or u"af_xdp" in test_name:
+ driver = u"af_xdp"
elif u"rdma" in test_name:
driver = u"rdma"
- elif u"dnv" in testbed or u"tsh" in testbed:
+ elif u"tsh" in testbed:
driver = u"ixgbe"
+ elif u"ena" in test_name:
+ driver = u"ena"
else:
driver = u"dpdk"
- if u"acl" in test_name or \
- u"macip" in test_name or \
- u"nat" in test_name or \
- u"policer" in test_name or \
- u"cop" in test_name:
+ if u"macip-iacl1s" in test_name:
+ bsf = u"features-macip-iacl1"
+ elif u"macip-iacl10s" in test_name:
+ bsf = u"features-macip-iacl10"
+ elif u"macip-iacl50s" in test_name:
+ bsf = u"features-macip-iacl50"
+ elif u"iacl1s" in test_name:
+ bsf = u"features-iacl1"
+ elif u"iacl10s" in test_name:
+ bsf = u"features-iacl10"
+ elif u"iacl50s" in test_name:
+ bsf = u"features-iacl50"
+ elif u"oacl1s" in test_name:
+ bsf = u"features-oacl1"
+ elif u"oacl10s" in test_name:
+ bsf = u"features-oacl10"
+ elif u"oacl50s" in test_name:
+ bsf = u"features-oacl50"
+ elif u"nat44det" in test_name:
+ bsf = u"nat44det-bidir"
+ elif u"nat44ed" in test_name and u"udir" in test_name:
+ bsf = u"nat44ed-udir"
+ elif u"-cps" in test_name and u"ethip4udp" in test_name:
+ bsf = u"udp-cps"
+ elif u"-cps" in test_name and u"ethip4tcp" in test_name:
+ bsf = u"tcp-cps"
+ elif u"-pps" in test_name and u"ethip4udp" in test_name:
+ bsf = u"udp-pps"
+ elif u"-pps" in test_name and u"ethip4tcp" in test_name:
+ bsf = u"tcp-pps"
+ elif u"-tput" in test_name and u"ethip4udp" in test_name:
+ bsf = u"udp-tput"
+ elif u"-tput" in test_name and u"ethip4tcp" in test_name:
+ bsf = u"tcp-tput"
+ elif u"udpsrcscale" in test_name:
+ bsf = u"features-udp"
+ elif u"iacl" in test_name:
+ bsf = u"features"
+ elif u"policer" in test_name:
+ bsf = u"features"
+ elif u"adl" in test_name:
+ bsf = u"features"
+ elif u"cop" in test_name:
+ bsf = u"features"
+ elif u"nat" in test_name:
+ bsf = u"features"
+ elif u"macip" in test_name:
bsf = u"features"
elif u"scale" in test_name:
bsf = u"scale"
if u"114b" in test_name and u"vhost" in test_name:
domain = u"vts"
+ elif u"nat44" in test_name or u"-pps" in test_name or u"-cps" in test_name:
+ domain = u"nat44"
+ if u"nat44det" in test_name:
+ domain += u"-det-bidir"
+ else:
+ domain += u"-ed"
+ if u"udir" in test_name:
+ domain += u"-unidir"
+ elif u"-ethip4udp-" in test_name:
+ domain += u"-udp"
+ elif u"-ethip4tcp-" in test_name:
+ domain += u"-tcp"
+ if u"-cps" in test_name:
+ domain += u"-cps"
+ elif u"-pps" in test_name:
+ domain += u"-pps"
+ elif u"-tput" in test_name:
+ domain += u"-tput"
elif u"testpmd" in test_name or u"l3fwd" in test_name:
domain = u"dpdk"
elif u"memif" in test_name:
bsf += u"-sw"
elif u"hw" in test_name:
bsf += u"-hw"
+ elif u"spe" in test_name:
+ bsf += u"-spe"
elif u"ethip4vxlan" in test_name:
domain = u"ip4_tunnels"
+ elif u"ethip4udpgeneve" in test_name:
+ domain = u"ip4_tunnels"
elif u"ip4base" in test_name or u"ip4scale" in test_name:
domain = u"ip4"
elif u"ip6base" in test_name or u"ip6scale" in test_name:
if not table.get(u"testbed", None):
logging.error(
f"The testbed is not defined for the table "
- f"{table.get(u'title', u'')}."
+ f"{table.get(u'title', u'')}. Skipping."
+ )
+ return
+
+ test_type = table.get(u"test-type", u"MRR")
+ if test_type not in (u"MRR", u"NDR", u"PDR"):
+ logging.error(
+ f"Test type {table.get(u'test-type', u'MRR')} is not defined. "
+ f"Skipping."
)
return
+ if test_type in (u"NDR", u"PDR"):
+ lnk_dir = u"../ndrpdr_trending/"
+ lnk_sufix = f"-{test_type.lower()}"
+ else:
+ lnk_dir = u"../trending/"
+ lnk_sufix = u""
+
logging.info(f" Generating the table {table.get(u'title', u'')} ...")
try:
with open(table[u"input-file"], u'rt') as csv_file:
csv_lst = list(csv.reader(csv_file, delimiter=u',', quotechar=u'"'))
+ except FileNotFoundError as err:
+ logging.warning(f"{err}")
+ return
except KeyError:
logging.warning(u"The input file is not defined.")
return
attrib=dict(align=u"left" if c_idx == 0 else u"center")
)
# Name:
- if c_idx == 0:
+ if c_idx == 0 and table.get(u"add-links", True):
ref = ET.SubElement(
tdata,
u"a",
attrib=dict(
- href=f"../trending/"
- f"{_generate_url(table.get(u'testbed', ''), item)}"
+ href=f"{lnk_dir}"
+ f"{_generate_url(table.get(u'testbed', ''), item)}"
+ f"{lnk_sufix}"
)
)
ref.text = item
build = str(build)
try:
version = input_data.metadata(job, build).get(u"version", u"")
+ duration = \
+ input_data.metadata(job, build).get(u"elapsedtime", u"")
except KeyError:
logging.error(f"Data for {job}: {build} is not present.")
return
if not groups:
continue
nic = groups.group(0)
- failed_tests.append(f"{nic}-{tst_data[u'name']}")
- tbl_list.append(str(passed))
- tbl_list.append(str(failed))
+ msg = tst_data[u'msg'].replace(u"\n", u"")
+ msg = re.sub(r'(\d{1,3}\.\d{1,3}\.\d{1,3}\.\d{1,3})',
+ 'xxx.xxx.xxx.xxx', msg)
+ msg = msg.split(u'Also teardown failed')[0]
+ failed_tests.append(f"{nic}-{tst_data[u'name']}###{msg}")
+ tbl_list.append(passed)
+ tbl_list.append(failed)
+ tbl_list.append(duration)
tbl_list.extend(failed_tests)
file_name = f"{table[u'output-file']}{table[u'output-file-ext']}"
logging.info(f" Writing file: {file_name}")
with open(file_name, u"wt") as file_handler:
for test in tbl_list:
- file_handler.write(test + u'\n')
+ file_handler.write(f"{test}\n")
def table_failed_tests(table, input_data):
)
data = input_data.filter_data(table, continue_on_error=True)
+ test_type = u"MRR"
+ if u"NDRPDR" in table.get(u"filter", list()):
+ test_type = u"NDRPDR"
+
# Prepare the header of the tables
header = [
u"Test Case",
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[u"name"],
- fails_nr,
- fails_last_date,
- fails_last_vpp,
- f"mrr-daily-build-{fails_last_csit}"
- ]
- )
+ tbl_lst.append([
+ tst_data[u"name"],
+ fails_nr,
+ fails_last_date,
+ fails_last_vpp,
+ f"{u'mrr-daily' if test_type == u'MRR' else u'ndrpdr-weekly'}"
+ f"-build-{fails_last_csit}"
+ ])
tbl_lst.sort(key=lambda rel: rel[2], reverse=True)
tbl_sorted = list()
if not table.get(u"testbed", None):
logging.error(
f"The testbed is not defined for the table "
- f"{table.get(u'title', u'')}."
+ f"{table.get(u'title', u'')}. Skipping."
+ )
+ return
+
+ test_type = table.get(u"test-type", u"MRR")
+ if test_type not in (u"MRR", u"NDR", u"PDR", u"NDRPDR"):
+ logging.error(
+ f"Test type {table.get(u'test-type', u'MRR')} is not defined. "
+ f"Skipping."
)
return
+ if test_type in (u"NDRPDR", u"NDR", u"PDR"):
+ lnk_dir = u"../ndrpdr_trending/"
+ lnk_sufix = u"-pdr"
+ else:
+ lnk_dir = u"../trending/"
+ lnk_sufix = u""
+
logging.info(f" Generating the table {table.get(u'title', u'')} ...")
try:
attrib=dict(align=u"left" if c_idx == 0 else u"center")
)
# Name:
- if c_idx == 0:
+ if c_idx == 0 and table.get(u"add-links", True):
ref = ET.SubElement(
tdata,
u"a",
attrib=dict(
- href=f"../trending/"
- f"{_generate_url(table.get(u'testbed', ''), item)}"
+ href=f"{lnk_dir}"
+ f"{_generate_url(table.get(u'testbed', ''), item)}"
+ f"{lnk_sufix}"
)
)
ref.text = item
:type table: pandas.Series
:type input_data: InputData
"""
- logging.info(f" Generating the table {table.get(u'title', u'')} ...")
+ logging.info(f" Generating the table {table.get('title', '')} ...")
# Transform the data
logging.info(
- f" Creating the data set for the {table.get(u'type', u'')} "
- f"{table.get(u'title', u'')}."
+ f" Creating the data set for the {table.get('type', '')} "
+ f"{table.get('title', '')}."
)
- columns = table.get(u"columns", None)
+ columns = table.get("columns", None)
if not columns:
logging.error(
- f"No columns specified for {table.get(u'title', u'')}. Skipping."
+ f"No columns specified for {table.get('title', '')}. Skipping."
)
return
cols = list()
for idx, col in enumerate(columns):
- if col.get(u"data", None) is None:
- logging.warning(f"No data for column {col.get(u'title', u'')}")
+ if col.get("data-set", None) is None:
+ logging.warning(f"No data for column {col.get('title', '')}")
continue
+ tag = col.get("tag", None)
data = input_data.filter_data(
table,
- params=[u"throughput", u"result", u"name", u"parent", u"tags"],
- data=col[u"data"],
+ params=[
+ "throughput",
+ "result",
+ "latency",
+ "name",
+ "parent",
+ "tags"
+ ],
+ data=col["data-set"],
continue_on_error=True
)
col_data = {
- u"title": col.get(u"title", f"Column{idx}"),
- u"data": dict()
+ "title": col.get("title", f"Column{idx}"),
+ "data": dict()
}
for builds in data.values:
for build in builds:
for tst_name, tst_data in build.items():
+ if tag and tag not in tst_data["tags"]:
+ continue
tst_name_mod = \
- _tpc_modify_test_name(tst_name).replace(u"2n1l-", u"")
- if col_data[u"data"].get(tst_name_mod, None) is None:
- name = tst_data[u'name'].rsplit(u'-', 1)[0]
- if u"across testbeds" in table[u"title"].lower() or \
- u"across topologies" in table[u"title"].lower():
+ _tpc_modify_test_name(tst_name, ignore_nic=True).\
+ replace("2n1l-", "")
+ if col_data["data"].get(tst_name_mod, None) is None:
+ name = tst_data['name'].rsplit('-', 1)[0]
+ if "across testbeds" in table["title"].lower() or \
+ "across topologies" in table["title"].lower():
name = _tpc_modify_displayed_test_name(name)
- col_data[u"data"][tst_name_mod] = {
- u"name": name,
- u"replace": True,
- u"data": list(),
- u"mean": None,
- u"stdev": None
+ col_data["data"][tst_name_mod] = {
+ "name": name,
+ "replace": True,
+ "data": list(),
+ "mean": None,
+ "stdev": None
}
_tpc_insert_data(
- target=col_data[u"data"][tst_name_mod][u"data"],
+ target=col_data["data"][tst_name_mod],
src=tst_data,
- include_tests=table[u"include-tests"]
+ include_tests=table["include-tests"]
)
- replacement = col.get(u"data-replacement", None)
+ replacement = col.get("data-replacement", None)
if replacement:
rpl_data = input_data.filter_data(
table,
- params=[u"throughput", u"result", u"name", u"parent", u"tags"],
+ params=[
+ "throughput",
+ "result",
+ "latency",
+ "name",
+ "parent",
+ "tags"
+ ],
data=replacement,
continue_on_error=True
)
for builds in rpl_data.values:
for build in builds:
for tst_name, tst_data in build.items():
+ if tag and tag not in tst_data["tags"]:
+ continue
tst_name_mod = \
- _tpc_modify_test_name(tst_name).\
- replace(u"2n1l-", u"")
- if col_data[u"data"].get(tst_name_mod, None) is None:
- name = tst_data[u'name'].rsplit(u'-', 1)[0]
- if u"across testbeds" in table[u"title"].lower() \
- or u"across topologies" in \
- table[u"title"].lower():
+ _tpc_modify_test_name(tst_name, ignore_nic=True).\
+ replace("2n1l-", "")
+ if col_data["data"].get(tst_name_mod, None) is None:
+ name = tst_data['name'].rsplit('-', 1)[0]
+ if "across testbeds" in table["title"].lower() \
+ or "across topologies" in \
+ table["title"].lower():
name = _tpc_modify_displayed_test_name(name)
- col_data[u"data"][tst_name_mod] = {
- u"name": name,
- u"replace": False,
- u"data": list(),
- u"mean": None,
- u"stdev": None
+ col_data["data"][tst_name_mod] = {
+ "name": name,
+ "replace": False,
+ "data": list(),
+ "mean": None,
+ "stdev": None
}
- if col_data[u"data"][tst_name_mod][u"replace"]:
- col_data[u"data"][tst_name_mod][u"replace"] = False
- col_data[u"data"][tst_name_mod][u"data"] = list()
+ if col_data["data"][tst_name_mod]["replace"]:
+ col_data["data"][tst_name_mod]["replace"] = False
+ col_data["data"][tst_name_mod]["data"] = list()
_tpc_insert_data(
- target=col_data[u"data"][tst_name_mod][u"data"],
+ target=col_data["data"][tst_name_mod],
src=tst_data,
- include_tests=table[u"include-tests"]
+ include_tests=table["include-tests"]
)
- if table[u"include-tests"] in (u"NDR", u"PDR"):
- for tst_name, tst_data in col_data[u"data"].items():
- if tst_data[u"data"]:
- tst_data[u"mean"] = mean(tst_data[u"data"])
- tst_data[u"stdev"] = stdev(tst_data[u"data"])
- elif table[u"include-tests"] in (u"MRR", ):
- for tst_name, tst_data in col_data[u"data"].items():
- if tst_data[u"data"]:
- tst_data[u"mean"] = tst_data[u"data"][0]
- tst_data[u"stdev"] = tst_data[u"data"][0]
+ if table["include-tests"] in ("NDR", "PDR", "hoststack", "vsap") \
+ or "latency" in table["include-tests"]:
+ for tst_name, tst_data in col_data["data"].items():
+ if tst_data["data"]:
+ tst_data["mean"] = mean(tst_data["data"])
+ tst_data["stdev"] = stdev(tst_data["data"])
cols.append(col_data)
tbl_dict = dict()
for col in cols:
- for tst_name, tst_data in col[u"data"].items():
+ for tst_name, tst_data in col["data"].items():
if tbl_dict.get(tst_name, None) is None:
tbl_dict[tst_name] = {
- "name": tst_data[u"name"]
+ "name": tst_data["name"]
}
- tbl_dict[tst_name][col[u"title"]] = {
- u"mean": tst_data[u"mean"],
- u"stdev": tst_data[u"stdev"]
+ tbl_dict[tst_name][col["title"]] = {
+ "mean": tst_data["mean"],
+ "stdev": tst_data["stdev"]
}
+ if not tbl_dict:
+ logging.warning(f"No data for table {table.get('title', '')}!")
+ return
+
tbl_lst = list()
for tst_data in tbl_dict.values():
row = [tst_data[u"name"], ]
row.append(tst_data.get(col[u"title"], None))
tbl_lst.append(row)
- comparisons = table.get(u"comparisons", None)
+ comparisons = table.get("comparisons", None)
+ rcas = list()
if comparisons and isinstance(comparisons, list):
for idx, comp in enumerate(comparisons):
try:
- col_ref = int(comp[u"reference"])
- col_cmp = int(comp[u"compare"])
+ col_ref = int(comp["reference"])
+ col_cmp = int(comp["compare"])
except KeyError:
- logging.warning(u"Comparison: No references defined! Skipping.")
+ logging.warning("Comparison: No references defined! Skipping.")
comparisons.pop(idx)
continue
- if not (0 < col_ref <= len(cols) and
- 0 < col_cmp <= len(cols)) or \
- col_ref == col_cmp:
+ if not (0 < col_ref <= len(cols) and 0 < col_cmp <= len(cols) or
+ col_ref == col_cmp):
logging.warning(f"Wrong values of reference={col_ref} "
f"and/or compare={col_cmp}. Skipping.")
comparisons.pop(idx)
continue
+ rca_file_name = comp.get("rca-file", None)
+ if rca_file_name:
+ try:
+ with open(rca_file_name, "r") as file_handler:
+ rcas.append(
+ {
+ "title": f"RCA{idx + 1}",
+ "data": load(file_handler, Loader=FullLoader)
+ }
+ )
+ except (YAMLError, IOError) as err:
+ logging.warning(
+ f"The RCA file {rca_file_name} does not exist or "
+ f"it is corrupted!"
+ )
+ logging.debug(repr(err))
+ rcas.append(None)
+ else:
+ rcas.append(None)
+ else:
+ comparisons = None
tbl_cmp_lst = list()
if comparisons:
for row in tbl_lst:
new_row = deepcopy(row)
- add_to_tbl = False
for comp in comparisons:
- ref_itm = row[int(comp[u"reference"])]
+ ref_itm = row[int(comp["reference"])]
if ref_itm is None and \
- comp.get(u"reference-alt", None) is not None:
- ref_itm = row[int(comp[u"reference-alt"])]
+ comp.get("reference-alt", None) is not None:
+ ref_itm = row[int(comp["reference-alt"])]
cmp_itm = row[int(comp[u"compare"])]
if ref_itm is not None and cmp_itm is not None and \
- ref_itm[u"mean"] is not None and \
- cmp_itm[u"mean"] is not None and \
- ref_itm[u"stdev"] is not None and \
- cmp_itm[u"stdev"] is not None:
- delta, d_stdev = relative_change_stdev(
- ref_itm[u"mean"], cmp_itm[u"mean"],
- ref_itm[u"stdev"], cmp_itm[u"stdev"]
+ ref_itm["mean"] is not None and \
+ cmp_itm["mean"] is not None and \
+ ref_itm["stdev"] is not None and \
+ cmp_itm["stdev"] is not None:
+ norm_factor_ref = table["norm_factor"].get(
+ comp.get("norm-ref", ""),
+ 1.0
)
- new_row.append(
- {
- u"mean": delta * 1e6,
- u"stdev": d_stdev * 1e6
- }
+ norm_factor_cmp = table["norm_factor"].get(
+ comp.get("norm-cmp", ""),
+ 1.0
)
- add_to_tbl = True
+ try:
+ delta, d_stdev = relative_change_stdev(
+ ref_itm["mean"] * norm_factor_ref,
+ cmp_itm["mean"] * norm_factor_cmp,
+ ref_itm["stdev"] * norm_factor_ref,
+ cmp_itm["stdev"] * norm_factor_cmp
+ )
+ except ZeroDivisionError:
+ break
+ if delta is None or math.isnan(delta):
+ break
+ new_row.append({
+ "mean": delta * 1e6,
+ "stdev": d_stdev * 1e6
+ })
else:
- new_row.append(None)
- if add_to_tbl:
+ break
+ else:
tbl_cmp_lst.append(new_row)
- tbl_cmp_lst.sort(key=lambda rel: rel[0], reverse=False)
- tbl_cmp_lst.sort(key=lambda rel: rel[-1][u'mean'], reverse=True)
-
- rcas = list()
- rca_in = table.get(u"rca", None)
- if rca_in and isinstance(rca_in, list):
- for idx, itm in enumerate(rca_in):
- try:
- with open(itm.get(u"data", u""), u"r") as rca_file:
- rcas.append(
- {
- u"title": itm.get(u"title", f"RCA{idx}"),
- u"data": load(rca_file, Loader=FullLoader)
- }
- )
- except (YAMLError, IOError) as err:
- logging.warning(
- f"The RCA file {itm.get(u'data', u'')} does not exist or "
- f"it is corrupted!"
- )
- logging.debug(repr(err))
+ try:
+ tbl_cmp_lst.sort(key=lambda rel: rel[0], reverse=False)
+ tbl_cmp_lst.sort(key=lambda rel: rel[-1]['mean'], reverse=True)
+ except TypeError as err:
+ logging.warning(f"Empty data element in table\n{tbl_cmp_lst}\n{err}")
tbl_for_csv = list()
for line in tbl_cmp_lst:
-
row = [line[0], ]
-
- for idx, rca in enumerate(rcas):
- rca_nr = rca[u"data"].get(row[0 + idx], u"-")
- row.insert(idx, f"[{rca_nr}]" if rca_nr != u"-" else u"-")
-
for idx, itm in enumerate(line[1:]):
- if itm is None:
- row.append(u"NT")
- row.append(u"NT")
+ if itm is None or not isinstance(itm, dict) or\
+ itm.get('mean', None) is None or \
+ itm.get('stdev', None) is None:
+ row.append("NT")
+ row.append("NT")
else:
- row.append(round(float(itm[u'mean']) / 1e6, 3))
- row.append(round(float(itm[u'stdev']) / 1e6, 3))
+ row.append(round(float(itm['mean']) / 1e6, 3))
+ row.append(round(float(itm['stdev']) / 1e6, 3))
+ for rca in rcas:
+ if rca is None:
+ continue
+ rca_nr = rca["data"].get(row[0], "-")
+ row.append(f"[{rca_nr}]" if rca_nr != "-" else "-")
tbl_for_csv.append(row)
- header_csv = [rca[u"title"] for rca in rcas]
- header_csv.append(u"Test Case")
+ header_csv = ["Test Case", ]
for col in cols:
- header_csv.append(f"Avg({col[u'title']})")
- header_csv.append(f"Stdev({col[u'title']})")
+ header_csv.append(f"Avg({col['title']})")
+ header_csv.append(f"Stdev({col['title']})")
for comp in comparisons:
header_csv.append(
- f"Avg({cols[comp[u'reference'] - 1][u'title']},"
- f"{cols[comp[u'compare'] - 1][u'title']})"
+ f"Avg({comp.get('title', '')})"
)
header_csv.append(
- f"Stdev({cols[comp[u'reference'] - 1][u'title']},"
- f"{cols[comp[u'compare'] - 1][u'title']})"
+ f"Stdev({comp.get('title', '')})"
)
+ for rca in rcas:
+ if rca:
+ header_csv.append(rca["title"])
+
+ legend_lst = table.get("legend", None)
+ if legend_lst is None:
+ legend = ""
+ else:
+ legend = "\n" + "\n".join(legend_lst) + "\n"
- csv_file = f"{table[u'output-file']}-csv.csv"
- with open(csv_file, u"wt", encoding='utf-8') as file_handler:
- file_handler.write(u";".join(header_csv) + u"\n")
+ footnote = ""
+ if rcas and any(rcas):
+ footnote += "\nRoot Cause Analysis:\n"
+ for rca in rcas:
+ if rca:
+ footnote += f"{rca['data'].get('footnote', '')}\n"
+
+ csv_file_name = f"{table['output-file']}-csv.csv"
+ with open(csv_file_name, "wt", encoding='utf-8') as file_handler:
+ file_handler.write(
+ ",".join([f'"{itm}"' for itm in header_csv]) + "\n"
+ )
for test in tbl_for_csv:
- file_handler.write(u";".join([str(item) for item in test]) + u"\n")
+ file_handler.write(
+ ",".join([f'"{item}"' for item in test]) + "\n"
+ )
+ if legend_lst:
+ for item in legend_lst:
+ file_handler.write(f'"{item}"\n')
+ if footnote:
+ for itm in footnote.split("\n"):
+ file_handler.write(f'"{itm}"\n')
- tbl_final = list()
+ tbl_tmp = list()
+ max_lens = [0, ] * len(tbl_cmp_lst[0])
for line in tbl_cmp_lst:
row = [line[0], ]
- for idx, rca in enumerate(rcas):
- rca_nr = rca[u"data"].get(row[0 + idx], u"-")
- row.insert(idx, f"[{rca_nr}]" if rca_nr != u"-" else u"-")
for idx, itm in enumerate(line[1:]):
- if itm is None:
- row.append(u"NT")
+ if itm is None or not isinstance(itm, dict) or \
+ itm.get('mean', None) is None or \
+ itm.get('stdev', None) is None:
+ new_itm = "NT"
else:
if idx < len(cols):
- row.append(
- f"{round(float(itm[u'mean']) / 1e6, 1)} "
- f"\u00B1{round(float(itm[u'stdev']) / 1e6, 1)}".
- replace(u"nan", u"NaN")
+ new_itm = (
+ f"{round(float(itm['mean']) / 1e6, 2)} "
+ f"\u00B1{round(float(itm['stdev']) / 1e6, 2)}".
+ replace("nan", "NaN")
)
else:
- row.append(
- f"{round(float(itm[u'mean']) / 1e6, 1):+} "
- f"\u00B1{round(float(itm[u'stdev']) / 1e6, 1)}".
- replace(u"nan", u"NaN")
+ new_itm = (
+ f"{round(float(itm['mean']) / 1e6, 2):+} "
+ f"\u00B1{round(float(itm['stdev']) / 1e6, 2)}".
+ replace("nan", "NaN")
)
- tbl_final.append(row)
+ if len(new_itm.rsplit(" ", 1)[-1]) > max_lens[idx]:
+ max_lens[idx] = len(new_itm.rsplit(" ", 1)[-1])
+ row.append(new_itm)
- header = [rca[u"title"] for rca in rcas]
- header.append(u"Test Case")
- header.extend([col[u"title"] for col in cols])
- header.extend(
- [f"Diff({cols[comp[u'reference'] - 1][u'title']},"
- f"{cols[comp[u'compare'] - 1][u'title']})"
- for comp in comparisons]
- )
+ tbl_tmp.append(row)
+
+ header = ["Test Case", ]
+ header.extend([col["title"] for col in cols])
+ header.extend([comp.get("title", "") for comp in comparisons])
+
+ tbl_final = list()
+ for line in tbl_tmp:
+ row = [line[0], ]
+ for idx, itm in enumerate(line[1:]):
+ if itm in ("NT", "NaN"):
+ row.append(itm)
+ continue
+ itm_lst = itm.rsplit("\u00B1", 1)
+ itm_lst[-1] = \
+ f"{' ' * (max_lens[idx] - len(itm_lst[-1]))}{itm_lst[-1]}"
+ itm_str = "\u00B1".join(itm_lst)
+
+ if idx >= len(cols):
+ # Diffs
+ rca = rcas[idx - len(cols)]
+ if rca:
+ # Add rcas to diffs
+ rca_nr = rca["data"].get(row[0], None)
+ if rca_nr:
+ hdr_len = len(header[idx + 1]) - 1
+ if hdr_len < 19:
+ hdr_len = 19
+ rca_nr = f"[{rca_nr}]"
+ itm_str = (
+ f"{' ' * (4 - len(rca_nr))}{rca_nr}"
+ f"{' ' * (hdr_len - 4 - len(itm_str))}"
+ f"{itm_str}"
+ )
+ row.append(itm_str)
+ tbl_final.append(row)
# Generate csv tables:
- csv_file = f"{table[u'output-file']}.csv"
- with open(csv_file, u"wt", encoding='utf-8') as file_handler:
- file_handler.write(u";".join(header) + u"\n")
+ csv_file_name = f"{table['output-file']}.csv"
+ logging.info(f" Writing the file {csv_file_name}")
+ with open(csv_file_name, "wt", encoding='utf-8') as file_handler:
+ file_handler.write(";".join(header) + "\n")
for test in tbl_final:
- file_handler.write(u";".join([str(item) for item in test]) + u"\n")
+ file_handler.write(";".join([str(item) for item in test]) + "\n")
# Generate txt table:
- txt_file_name = f"{table[u'output-file']}.txt"
- convert_csv_to_pretty_txt(csv_file, txt_file_name, delimiter=u";")
+ txt_file_name = f"{table['output-file']}.txt"
+ logging.info(f" Writing the file {txt_file_name}")
+ convert_csv_to_pretty_txt(csv_file_name, txt_file_name, delimiter=";")
- # Generate rst table:
- file_name = table[u'output-file'].split(u"/")[-1]
- if u"vpp" in table[u'output-file']:
- path = u"_tmp/src/vpp_performance_tests/comparisons/"
- else:
- path = u"_tmp/src/dpdk_performance_tests/comparisons/"
- rst_file_name = f"{path}{file_name}-txt.rst"
- csv_file_name = f"{path}{file_name}.csv"
- with open(csv_file_name, u"wt", encoding='utf-8') as file_handler:
- file_handler.write(
- u",".join(
- [f'"{itm}"' for itm in header]
- ) + u"\n"
+ with open(txt_file_name, 'a', encoding='utf-8') as file_handler:
+ file_handler.write(legend)
+ file_handler.write(footnote)
+
+ # Generate html table:
+ _tpc_generate_html_table(
+ header,
+ tbl_final,
+ table['output-file'],
+ legend=legend,
+ footnote=footnote,
+ sort_data=False,
+ title=table.get("title", "")
+ )
+
+
+def table_weekly_comparison(table, in_data):
+ """Generate the table(s) with algorithm: table_weekly_comparison
+ specified in the specification file.
+
+ :param table: Table to generate.
+ :param in_data: Data to process.
+ :type table: pandas.Series
+ :type in_data: InputData
+ """
+ logging.info(f" Generating the table {table.get(u'title', u'')} ...")
+
+ # Transform the data
+ logging.info(
+ f" Creating the data set for the {table.get(u'type', u'')} "
+ f"{table.get(u'title', u'')}."
+ )
+
+ incl_tests = table.get(u"include-tests", None)
+ if incl_tests not in (u"NDR", u"PDR"):
+ logging.error(f"Wrong tests to include specified ({incl_tests}).")
+ return
+
+ nr_cols = table.get(u"nr-of-data-columns", None)
+ if not nr_cols or nr_cols < 2:
+ logging.error(
+ f"No columns specified for {table.get(u'title', u'')}. Skipping."
)
- for test in tbl_final:
- file_handler.write(
- u",".join(
- [f'"{itm}"' for itm in test]
- ) + u"\n"
- )
+ return
- convert_csv_to_pretty_txt(csv_file_name, rst_file_name, delimiter=u",")
+ data = in_data.filter_data(
+ table,
+ params=[u"throughput", u"result", u"name", u"parent", u"tags"],
+ continue_on_error=True
+ )
- legend = u"\nLegend:\n"
- for idx, rca in enumerate(rcas):
- try:
- desc = (
- f"Diff({cols[comparisons[idx][u'reference'] - 1][u'title']},"
- f"{cols[comparisons[idx][u'compare'] - 1][u'title']})\n"
+ header = [
+ [u"VPP Version", ],
+ [u"Start Timestamp", ],
+ [u"CSIT Build", ],
+ [u"CSIT Testbed", ]
+ ]
+ tbl_dict = dict()
+ idx = 0
+ tb_tbl = table.get(u"testbeds", None)
+ for job_name, job_data in data.items():
+ for build_nr, build in job_data.items():
+ if idx >= nr_cols:
+ break
+ if build.empty:
+ continue
+
+ tb_ip = in_data.metadata(job_name, build_nr).get(u"testbed", u"")
+ if tb_ip and tb_tbl:
+ testbed = tb_tbl.get(tb_ip, u"")
+ else:
+ testbed = u""
+ header[2].insert(1, build_nr)
+ header[3].insert(1, testbed)
+ header[1].insert(
+ 1, in_data.metadata(job_name, build_nr).get(u"generated", u"")
+ )
+ logging.info(
+ in_data.metadata(job_name, build_nr).get(u"version", u"ERROR"))
+ header[0].insert(
+ 1, in_data.metadata(job_name, build_nr).get("version", build_nr)
)
- except (KeyError, IndexError):
- desc = u"\n"
- legend += f"{rca[u'title']}: Root Cause Analysis for {desc}"
- legend += (
- u"First part of the result is a mean value [Mpps].\n"
- f"Second part of the result following '\u00B1' is a standard "
- u"deviation [Mpps].\n"
- u"First part of Diff is a relative change of mean values [%].\n"
- f"Second part of Diff following '\u00B1' is a standard deviation "
- u"of the Diff [percentual points].\n"
- u"NT: Not tested.\n"
- )
- footnote = u""
- for rca in rcas:
- footnote += f"\n{rca[u'title']}:\n"
- footnote += rca[u"data"].get(u"footnote", u"")
+ for tst_name, tst_data in build.items():
+ tst_name_mod = \
+ _tpc_modify_test_name(tst_name).replace(u"2n1l-", u"")
+ if not tbl_dict.get(tst_name_mod, None):
+ tbl_dict[tst_name_mod] = dict(
+ name=tst_data[u'name'].rsplit(u'-', 1)[0],
+ )
+ try:
+ tbl_dict[tst_name_mod][-idx - 1] = \
+ tst_data[u"throughput"][incl_tests][u"LOWER"]
+ except (TypeError, IndexError, KeyError, ValueError):
+ pass
+ idx += 1
+
+ if idx < nr_cols:
+ logging.error(u"Not enough data to build the table! Skipping")
+ return
- with open(txt_file_name, u'a', encoding='utf-8') as txt_file:
- txt_file.write(legend)
- if footnote:
- txt_file.write(footnote)
- txt_file.write(u":END")
+ cmp_dict = dict()
+ for idx, cmp in enumerate(table.get(u"comparisons", list())):
+ idx_ref = cmp.get(u"reference", None)
+ idx_cmp = cmp.get(u"compare", None)
+ if idx_ref is None or idx_cmp is None:
+ continue
+ header[0].append(
+ f"Diff({header[0][idx_ref - idx].split(u'~')[-1]} vs "
+ f"{header[0][idx_cmp - idx].split(u'~')[-1]})"
+ )
+ header[1].append(u"")
+ header[2].append(u"")
+ header[3].append(u"")
+ for tst_name, tst_data in tbl_dict.items():
+ if not cmp_dict.get(tst_name, None):
+ cmp_dict[tst_name] = list()
+ ref_data = tst_data.get(idx_ref, None)
+ cmp_data = tst_data.get(idx_cmp, None)
+ if ref_data is None or cmp_data is None:
+ cmp_dict[tst_name].append(float(u'nan'))
+ else:
+ cmp_dict[tst_name].append(relative_change(ref_data, cmp_data))
- with open(rst_file_name, u'a', encoding='utf-8') as txt_file:
- txt_file.write(legend.replace(u"\n", u" |br| "))
- if footnote:
- txt_file.write(footnote.replace(u"\n", u" |br| "))
- txt_file.write(u":END")
+ tbl_lst_none = list()
+ tbl_lst = list()
+ for tst_name, tst_data in tbl_dict.items():
+ itm_lst = [tst_data[u"name"], ]
+ for idx in range(nr_cols):
+ item = tst_data.get(-idx - 1, None)
+ if item is None:
+ itm_lst.insert(1, None)
+ else:
+ itm_lst.insert(1, round(item / 1e6, 1))
+ itm_lst.extend(
+ [
+ None if itm is None else round(itm, 1)
+ for itm in cmp_dict[tst_name]
+ ]
+ )
+ if str(itm_lst[-1]) == u"nan" or itm_lst[-1] is None:
+ tbl_lst_none.append(itm_lst)
+ else:
+ tbl_lst.append(itm_lst)
+
+ tbl_lst_none.sort(key=lambda rel: rel[0], reverse=False)
+ tbl_lst.sort(key=lambda rel: rel[0], reverse=False)
+ tbl_lst.sort(key=lambda rel: rel[-1], reverse=False)
+ tbl_lst.extend(tbl_lst_none)
+
+ # Generate csv table:
+ csv_file_name = f"{table[u'output-file']}.csv"
+ logging.info(f" Writing the file {csv_file_name}")
+ with open(csv_file_name, u"wt", encoding='utf-8') as file_handler:
+ for hdr in header:
+ file_handler.write(u",".join(hdr) + u"\n")
+ for test in tbl_lst:
+ file_handler.write(u",".join(
+ [
+ str(item).replace(u"None", u"-").replace(u"nan", u"-").
+ replace(u"null", u"-") for item in test
+ ]
+ ) + u"\n")
+
+ txt_file_name = f"{table[u'output-file']}.txt"
+ logging.info(f" Writing the file {txt_file_name}")
+ try:
+ convert_csv_to_pretty_txt(csv_file_name, txt_file_name, delimiter=u",")
+ except Exception as err:
+ logging.error(repr(err))
+ for hdr in header:
+ logging.info(",".join(hdr))
+ for test in tbl_lst:
+ logging.info(",".join(
+ [
+ str(item).replace(u"None", u"-").replace(u"nan", u"-").
+ replace(u"null", u"-") for item in test
+ ]
+ ))
+
+ # Reorganize header in txt table
+ txt_table = list()
+ try:
+ with open(txt_file_name, u"rt", encoding='utf-8') as file_handler:
+ for line in list(file_handler):
+ txt_table.append(line)
+ txt_table.insert(5, txt_table.pop(2))
+ with open(txt_file_name, u"wt", encoding='utf-8') as file_handler:
+ file_handler.writelines(txt_table)
+ except FileNotFoundError as err:
+ logging.error(repr(err))
+ except IndexError:
+ pass
# Generate html table:
+ hdr_html = [
+ u"<br>".join(row) for row in zip(*header)
+ ]
_tpc_generate_html_table(
- header,
- tbl_final,
+ hdr_html,
+ tbl_lst,
table[u'output-file'],
- legend=legend,
- footnote=footnote,
- sort_data=False
+ sort_data=True,
+ title=table.get(u"title", u""),
+ generate_rst=False
)