-# Copyright (c) 2018 Cisco and/or its affiliates.
+# 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:
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 errors import PresentationError
from utils import mean, stdev, relative_change, classify_anomalies, \
- convert_csv_to_pretty_txt
+ convert_csv_to_pretty_txt, relative_change_stdev
+
+
+REGEX_NIC = re.compile(r'\d*ge\dp\d\D*\d*')
def generate_tables(spec, data):
try:
col_data = str(data[job][build][test][column["data"].
split(" ")[1]]).replace('"', '""')
- if column["data"].split(" ")[1] in ("vat-history",
+ if column["data"].split(" ")[1] in ("conf-history",
"show-run"):
col_data = replace(col_data, " |br| ", "",
maxreplace=1)
try:
col_data = str(data[test][column["data"].
split(" ")[1]]).replace('"', '""')
- if column["data"].split(" ")[1] in ("vat-history",
+ col_data = replace(col_data, "No Data",
+ "Not Captured ")
+ if column["data"].split(" ")[1] in ("conf-history",
"show-run"):
col_data = replace(col_data, " |br| ", "",
maxreplace=1)
format(col_data[:-5])
row_lst.append('"{0}"'.format(col_data))
except KeyError:
- row_lst.append("No data")
+ row_lst.append('"Not captured"')
table_lst.append(row_lst)
# Write the data to file
logging.info(" Done.")
-def table_performance_improvements(table, input_data):
- """Generate the table(s) with algorithm: table_performance_improvements
+def table_performance_comparison(table, input_data):
+ """Generate the table(s) with algorithm: table_performance_comparison
specified in the specification file.
- # FIXME: Not used now.
-
:param table: Table to generate.
:param input_data: Data to process.
:type table: pandas.Series
:type input_data: InputData
"""
- def _write_line_to_file(file_handler, data):
- """Write a line to the .csv file.
-
- :param file_handler: File handler for the csv file. It must be open for
- writing text.
- :param data: Item to be written to the file.
- :type file_handler: BinaryIO
- :type data: list
- """
-
- line_lst = list()
- for item in data:
- if isinstance(item["data"], str):
- # Remove -?drdisc from the end
- if item["data"].endswith("drdisc"):
- item["data"] = item["data"][:-8]
- line_lst.append(item["data"])
- elif isinstance(item["data"], float):
- line_lst.append("{:.1f}".format(item["data"]))
- elif item["data"] is None:
- line_lst.append("")
- file_handler.write(",".join(line_lst) + "\n")
-
logging.info(" Generating the table {0} ...".
format(table.get("title", "")))
- # Read the template
- file_name = table.get("template", None)
- if file_name:
- try:
- tmpl = _read_csv_template(file_name)
- except PresentationError:
- logging.error(" The template '{0}' does not exist. Skipping the "
- "table.".format(file_name))
- return None
- else:
- logging.error("The template is not defined. Skipping the table.")
- return None
-
# 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.filter_data(table, continue_on_error=True)
# Prepare the header of the tables
- header = list()
- for column in table["columns"]:
- header.append(column["title"])
+ try:
+ header = ["Test case", ]
- # Generate the data for the table according to the model in the table
- # specification
- tbl_lst = list()
- for tmpl_item in tmpl:
- tbl_item = list()
- for column in table["columns"]:
- cmd = column["data"].split(" ")[0]
- args = column["data"].split(" ")[1:]
- if cmd == "template":
+ 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:
+ groups = re.search(REGEX_NIC, tst_data["parent"])
+ nic = groups.group(0) if groups else ""
+ name = "{0}-{1}".format(nic, "-".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:
- val = float(tmpl_item[int(args[0])])
- except ValueError:
- val = tmpl_item[int(args[0])]
- tbl_item.append({"data": val})
- elif cmd == "data":
- jobs = args[0:-1]
- operation = args[-1]
- data_lst = list()
- for job in jobs:
- for build in data[job]:
- try:
- data_lst.append(float(build[tmpl_item[0]]
- ["throughput"]["value"]))
- except (KeyError, TypeError):
- # No data, ignore
- continue
- if data_lst:
- tbl_item.append({"data": (eval(operation)(data_lst)) /
- 1000000})
- else:
- tbl_item.append({"data": None})
- elif cmd == "operation":
- operation = args[0]
+ # 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:
- nr1 = float(tbl_item[int(args[1])]["data"])
- nr2 = float(tbl_item[int(args[2])]["data"])
- if nr1 and nr2:
- tbl_item.append({"data": eval(operation)(nr1, nr2)})
+ # 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:
- tbl_item.append({"data": None})
- except (IndexError, ValueError, TypeError):
- logging.error("No data for {0}".format(tbl_item[0]["data"]))
- tbl_item.append({"data": None})
- continue
+ 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:
- logging.error("Not supported command {0}. Skipping the table.".
- format(cmd))
- return None
- tbl_lst.append(tbl_item)
+ 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]["data"], reverse=True)
-
- # Create the tables and write them to the files
- file_names = [
- "{0}_ndr_top{1}".format(table["output-file"], table["output-file-ext"]),
- "{0}_pdr_top{1}".format(table["output-file"], table["output-file-ext"]),
- "{0}_ndr_low{1}".format(table["output-file"], table["output-file-ext"]),
- "{0}_pdr_low{1}".format(table["output-file"], table["output-file-ext"])
- ]
-
- for file_name in file_names:
- logging.info(" Writing the file '{0}'".format(file_name))
- with open(file_name, "w") as file_handler:
- file_handler.write(",".join(header) + "\n")
- for item in tbl_lst:
- if isinstance(item[-1]["data"], float):
- rel_change = round(item[-1]["data"], 1)
- else:
- rel_change = item[-1]["data"]
- if "ndr_top" in file_name \
- and "ndr" in item[0]["data"] \
- and rel_change >= 10.0:
- _write_line_to_file(file_handler, item)
- elif "pdr_top" in file_name \
- and "pdr" in item[0]["data"] \
- and rel_change >= 10.0:
- _write_line_to_file(file_handler, item)
- elif "ndr_low" in file_name \
- and "ndr" in item[0]["data"] \
- and rel_change < 10.0:
- _write_line_to_file(file_handler, item)
- elif "pdr_low" in file_name \
- and "pdr" in item[0]["data"] \
- and rel_change < 10.0:
- _write_line_to_file(file_handler, item)
-
- logging.info(" Done.")
-
-
-def _read_csv_template(file_name):
- """Read the template from a .csv file.
-
- # FIXME: Not used now.
+ tbl_lst.sort(key=lambda rel: rel[-1], reverse=True)
- :param file_name: Name / full path / relative path of the file to read.
- :type file_name: str
- :returns: Data from the template as list (lines) of lists (items on line).
- :rtype: list
- :raises: PresentationError if it is not possible to read the file.
- """
+ # 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")
- try:
- with open(file_name, 'r') as csv_file:
- tmpl_data = list()
- for line in csv_file:
- tmpl_data.append(line[:-1].split(","))
- return tmpl_data
- except IOError as err:
- raise PresentationError(str(err), level="ERROR")
+ convert_csv_to_pretty_txt(csv_file, "{0}.txt".format(table["output-file"]))
-def table_performance_comparison(table, input_data):
+def table_performance_comparison_nic(table, input_data):
"""Generate the table(s) with algorithm: table_performance_comparison
specified in the specification file.
"{0} Stdev [Mpps]".format(table["reference"]["title"]),
"{0} {1} [Mpps]".format(table["compare"]["title"], hdr_param),
"{0} Stdev [Mpps]".format(table["compare"]["title"]),
- "Change [%]"])
+ "Delta [%]"])
header_str = ",".join(header) + "\n"
except (AttributeError, KeyError) as err:
logging.error("The model is invalid, missing parameter: {0}".
for job, builds in table["reference"]["data"].items():
for build in builds:
for tst_name, tst_data in data[job][str(build)].iteritems():
+ if table["reference"]["nic"] not in tst_data["tags"]:
+ continue
tst_name_mod = tst_name.replace("-ndrpdrdisc", "").\
replace("-ndrpdr", "").replace("-pdrdisc", "").\
replace("-ndrdisc", "").replace("-pdr", "").\
- replace("-ndr", "")
+ replace("-ndr", "").\
+ replace("1t1c", "1c").replace("2t1c", "1c").\
+ replace("2t2c", "2c").replace("4t2c", "2c").\
+ replace("4t4c", "4c").replace("8t4c", "4c")
+ tst_name_mod = re.sub(REGEX_NIC, "", tst_name_mod)
+ 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]))
+ name = "{0}".format("-".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()}
for job, builds in table["compare"]["data"].items():
for build in builds:
for tst_name, tst_data in data[job][str(build)].iteritems():
+ if table["compare"]["nic"] not in tst_data["tags"]:
+ continue
tst_name_mod = tst_name.replace("-ndrpdrdisc", ""). \
replace("-ndrpdr", "").replace("-pdrdisc", ""). \
replace("-ndrdisc", "").replace("-pdr", ""). \
- replace("-ndr", "")
+ replace("-ndr", "").\
+ replace("1t1c", "1c").replace("2t1c", "1c").\
+ replace("2t2c", "2c").replace("4t2c", "2c").\
+ replace("4t4c", "4c").replace("8t4c", "4c")
+ tst_name_mod = re.sub(REGEX_NIC, "", tst_name_mod)
+ 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":
for job, builds in item["data"].items():
for build in builds:
for tst_name, tst_data in data[job][str(build)].iteritems():
+ if item["nic"] not in tst_data["tags"]:
+ continue
tst_name_mod = tst_name.replace("-ndrpdrdisc", ""). \
replace("-ndrpdr", "").replace("-pdrdisc", ""). \
replace("-ndrdisc", "").replace("-pdr", ""). \
- replace("-ndr", "")
+ replace("-ndr", "").\
+ replace("1t1c", "1c").replace("2t1c", "1c").\
+ replace("2t2c", "2c").replace("4t2c", "2c").\
+ replace("4t4c", "4c").replace("8t4c", "4c")
+ tst_name_mod = re.sub(REGEX_NIC, "", tst_name_mod)
+ 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:
convert_csv_to_pretty_txt(csv_file, "{0}.txt".format(table["output-file"]))
+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(" 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"
+
+ 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["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")
+ tst_name_mod = re.sub(REGEX_NIC, "", tst_name_mod)
+ if tbl_dict.get(tst_name_mod, None) is None:
+ name = "-".join(tst_data["name"].split("-")[:-1])
+ tbl_dict[tst_name_mod] = {"name": name,
+ "ref-data": list(),
+ "cmp-data": list()}
+ try:
+ if table["include-tests"] == "MRR":
+ result = tst_data["result"]["receive-rate"].avg
+ elif table["include-tests"] == "PDR":
+ result = tst_data["throughput"]["PDR"]["LOWER"]
+ elif table["include-tests"] == "NDR":
+ result = tst_data["throughput"]["NDR"]["LOWER"]
+ else:
+ result = None
+
+ if result:
+ if table["reference"]["nic"] in tst_data["tags"]:
+ tbl_dict[tst_name_mod]["ref-data"].append(result)
+ elif table["compare"]["nic"] in tst_data["tags"]:
+ tbl_dict[tst_name_mod]["cmp-data"].append(result)
+ except (TypeError, KeyError) as err:
+ logging.debug("No data for {0}".format(tst_name))
+ logging.debug(repr(err))
+ # No data in output.xml for this test
+
+ tbl_lst = list()
+ for tst_name in tbl_dict.keys():
+ item = [tbl_dict[tst_name]["name"], ]
+ 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_soak_vs_ndr(table, input_data):
+ """Generate the table(s) with algorithm: table_soak_vs_ndr
+ 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 table
+ try:
+ header = [
+ "Test case",
+ "{0} Throughput [Mpps]".format(table["reference"]["title"]),
+ "{0} Stdev [Mpps]".format(table["reference"]["title"]),
+ "{0} Throughput [Mpps]".format(table["compare"]["title"]),
+ "{0} Stdev [Mpps]".format(table["compare"]["title"]),
+ "Delta [%]", "Stdev of delta [%]"]
+ header_str = ",".join(header) + "\n"
+ except (AttributeError, KeyError) as err:
+ logging.error("The model is invalid, missing parameter: {0}".
+ format(err))
+ return
+
+ # Create a list of available SOAK test results:
+ tbl_dict = dict()
+ for job, builds in table["compare"]["data"].items():
+ for build in builds:
+ for tst_name, tst_data in data[job][str(build)].iteritems():
+ if tst_data["type"] == "SOAK":
+ tst_name_mod = tst_name.replace("-soak", "")
+ if tbl_dict.get(tst_name_mod, None) is None:
+ groups = re.search(REGEX_NIC, tst_data["parent"])
+ nic = groups.group(0) if groups else ""
+ name = "{0}-{1}".format(nic, "-".join(tst_data["name"].
+ split("-")[:-1]))
+ tbl_dict[tst_name_mod] = {
+ "name": name,
+ "ref-data": list(),
+ "cmp-data": list()
+ }
+ try:
+ tbl_dict[tst_name_mod]["cmp-data"].append(
+ tst_data["throughput"]["LOWER"])
+ except (KeyError, TypeError):
+ pass
+ tests_lst = tbl_dict.keys()
+
+ # Add corresponding NDR test results:
+ 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("-ndrpdr", "").\
+ replace("-mrr", "")
+ if tst_name_mod in tests_lst:
+ try:
+ if tst_data["type"] in ("NDRPDR", "MRR", "BMRR"):
+ if table["include-tests"] == "MRR":
+ result = tst_data["result"]["receive-rate"].avg
+ elif table["include-tests"] == "PDR":
+ result = tst_data["throughput"]["PDR"]["LOWER"]
+ elif table["include-tests"] == "NDR":
+ result = tst_data["throughput"]["NDR"]["LOWER"]
+ else:
+ result = None
+ if result is not None:
+ tbl_dict[tst_name_mod]["ref-data"].append(
+ result)
+ except (KeyError, TypeError):
+ continue
+
+ tbl_lst = list()
+ for tst_name in tbl_dict.keys():
+ item = [tbl_dict[tst_name]["name"], ]
+ data_r = tbl_dict[tst_name]["ref-data"]
+ if data_r:
+ data_r_mean = mean(data_r)
+ item.append(round(data_r_mean / 1000000, 2))
+ data_r_stdev = stdev(data_r)
+ item.append(round(data_r_stdev / 1000000, 2))
+ else:
+ data_r_mean = None
+ data_r_stdev = None
+ item.extend([None, None])
+ data_c = tbl_dict[tst_name]["cmp-data"]
+ if data_c:
+ data_c_mean = mean(data_c)
+ item.append(round(data_c_mean / 1000000, 2))
+ data_c_stdev = stdev(data_c)
+ item.append(round(data_c_stdev / 1000000, 2))
+ else:
+ data_c_mean = None
+ data_c_stdev = None
+ item.extend([None, None])
+ if data_r_mean and data_c_mean:
+ delta, d_stdev = relative_change_stdev(
+ data_r_mean, data_c_mean, data_r_stdev, data_c_stdev)
+ item.append(round(delta, 2))
+ item.append(round(d_stdev, 2))
+ 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
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"]:
+ if tst_name.lower() in table.get("ignore-list", list()):
continue
if tbl_dict.get(tst_name, None) is None:
- name = "{0}-{1}".format(tst_data["parent"].split("-")[0],
- tst_data["name"])
- tbl_dict[tst_name] = {"name": name,
- "data": OrderedDict()}
+ 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"]
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"],
- '-' if isnan(last_avg) else
round(last_avg / 1000000, 2),
- '-' if isnan(rel_change_last) else rel_change_last,
- '-' if isnan(rel_change_long) else rel_change_long,
+ rel_change_last,
+ rel_change_long,
classification_lst[-win_size:].count("regression"),
classification_lst[-win_size:].count("progression")])
convert_csv_to_pretty_txt(file_name, txt_file_name)
-def _generate_url(base, test_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.
url = base
file_name = ""
- anchor = "#"
+ anchor = ".html#"
feature = ""
if "lbdpdk" in test_name or "lbvpp" in test_name:
- file_name = "link_bonding.html"
+ 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.html"
+ file_name = "dpdk"
elif "memif" in test_name:
- file_name = "container_memif.html"
+ file_name = "container_memif"
+ feature = "-base"
elif "srv6" in test_name:
- file_name = "srv6.html"
+ file_name = "srv6"
elif "vhost" in test_name:
if "l2xcbase" in test_name or "l2bdbasemaclrn" in test_name:
- file_name = "vm_vhost_l2.html"
+ file_name = "vm_vhost_l2"
+ if "114b" in test_name:
+ feature = ""
+ elif "l2xcbase" in test_name and "x520" in test_name:
+ feature = "-base-l2xc"
+ elif "l2bdbasemaclrn" in test_name and "x520" in test_name:
+ feature = "-base-l2bd"
+ else:
+ feature = "-base"
elif "ip4base" in test_name:
- file_name = "vm_vhost_ip4.html"
+ file_name = "vm_vhost_ip4"
+ feature = "-base"
+
+ elif "ipsecbasetnlsw" in test_name:
+ file_name = "ipsecsw"
+ feature = "-base-scale"
elif "ipsec" in test_name:
- file_name = "ipsec.html"
+ file_name = "ipsec"
+ feature = "-base-scale"
+ if "hw-" in test_name:
+ file_name = "ipsechw"
+ elif "sw-" in test_name:
+ file_name = "ipsecsw"
+ if "-int-" in test_name:
+ feature = "-base-scale-int"
+ elif "tnl" in test_name:
+ feature = "-base-scale-tnl"
elif "ethip4lispip" in test_name or "ethip4vxlan" in test_name:
- file_name = "ip4_tunnels.html"
+ file_name = "ip4_tunnels"
+ feature = "-base"
elif "ip4base" in test_name or "ip4scale" in test_name:
- file_name = "ip4.html"
- if "iacl" in test_name or "snat" in test_name or "cop" 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.html"
+ 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.html"
- if "iacl" in test_name:
- feature = "-features"
+ 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:
- anchor += "x520-"
+ nic = "x520-"
elif "x710" in test_name:
- anchor += "x710-"
+ nic = "x710-"
elif "xl710" in test_name:
- anchor += "xl710-"
+ nic = "xl710-"
+ elif "xxv710" in test_name:
+ nic = "xxv710-"
+ elif "vic1227" in test_name:
+ nic = "vic1227-"
+ elif "vic1385" in test_name:
+ nic = "vic1385-"
+ elif "x553" in test_name:
+ nic = "x553-"
+ else:
+ nic = ""
+ anchor += nic
if "64b" in test_name:
- anchor += "64b-"
+ framesize = "64b"
elif "78b" in test_name:
- anchor += "78b-"
+ framesize = "78b"
elif "imix" in test_name:
- anchor += "imix-"
+ framesize = "imix"
elif "9000b" in test_name:
- anchor += "9000b-"
- elif "1518" in test_name:
- anchor += "1518b-"
+ 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"
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 + anchor + feature
+ return url + file_name + '-' + testbed + '-' + nic + framesize + \
+ feature.replace("-int", "").replace("-tnl", "") + anchor + feature
def table_performance_trending_dashboard_html(table, input_data):
:param table: Table to generate.
:param input_data: Data to process.
- :type table: pandas.Series
+ :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", "")))
td = ET.SubElement(tr, "td", attrib=dict(align=alignment))
# Name:
if c_idx == 0:
- url = _generate_url("../trending/", item)
+ url = _generate_url("../trending/", testbed, item)
ref = ET.SubElement(td, "a", attrib=dict(href=url))
ref.text = item
else:
return
+def table_last_failed_tests(table, input_data):
+ """Generate the table(s) with algorithm: table_last_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)
+
+ if data is None or data.empty:
+ logging.warn(" No data for the {0} '{1}'.".
+ format(table.get("type", ""), table.get("title", "")))
+ return
+
+ tbl_list = list()
+ for job, builds in table["data"].items():
+ for build in builds:
+ build = str(build)
+ try:
+ version = input_data.metadata(job, build).get("version", "")
+ except KeyError:
+ logging.error("Data for {job}: {build} is not present.".
+ format(job=job, build=build))
+ return
+ tbl_list.append(build)
+ tbl_list.append(version)
+ for tst_name, tst_data in data[job][build].iteritems():
+ if tst_data["status"] != "FAIL":
+ continue
+ groups = re.search(REGEX_NIC, tst_data["parent"])
+ if not groups:
+ continue
+ nic = groups.group(0)
+ tbl_list.append("{0}-{1}".format(nic, tst_data["name"]))
+
+ 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:
+ for test in tbl_list:
+ file_handler.write(test + '\n')
+
+
def table_failed_tests(table, input_data):
"""Generate the table(s) with algorithm: table_failed_tests
specified in the specification file.
# 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"]:
+ if tst_name.lower() in table.get("ignore-list", list()):
continue
if tbl_dict.get(tst_name, None) is None:
- name = "{0}-{1}".format(tst_data["parent"].split("-")[0],
- tst_data["name"])
- tbl_dict[tst_name] = {"name": name,
- "data": OrderedDict()}
+ 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"][build] = (
- tst_data["status"],
- input_data.metadata(job, build).get("generated", ""),
- input_data.metadata(job, build).get("version", ""),
- build)
- except (TypeError, KeyError):
- pass # No data in output.xml for this test
-
+ 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():
- win_size = min(len(tst_data["data"]), table["window"])
fails_nr = 0
- for val in tst_data["data"].values()[-win_size:]:
+ 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,
tbl_lst.sort(key=lambda rel: rel[2], reverse=True)
tbl_sorted = list()
- for nrf in range(table["window"], -1, -1):
+ 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"])
: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", "")))
td = ET.SubElement(tr, "td", attrib=dict(align=alignment))
# Name:
if c_idx == 0:
- url = _generate_url("../trending/", item)
+ url = _generate_url("../trending/", testbed, item)
ref = ET.SubElement(td, "a", attrib=dict(href=url))
ref.text = item
else: