X-Git-Url: https://gerrit.fd.io/r/gitweb?p=csit.git;a=blobdiff_plain;f=resources%2Ftools%2Fpresentation%2Fgenerator_tables.py;h=7590daa8fecd52fc1b409da979e62818ce942e73;hp=195380f7fbdca17e53f5eef271b6ebe7f17c6fb5;hb=c7790170533bd47ffc0e9001db92127356756c11;hpb=d08498d06de775723a32597d109b537abf34a7e9
diff --git a/resources/tools/presentation/generator_tables.py b/resources/tools/presentation/generator_tables.py
index 195380f7fb..7590daa8fe 100644
--- a/resources/tools/presentation/generator_tables.py
+++ b/resources/tools/presentation/generator_tables.py
@@ -1,4 +1,4 @@
-# Copyright (c) 2017 Cisco and/or its affiliates.
+# Copyright (c) 2018 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:
@@ -16,10 +16,21 @@
import logging
+import csv
+import re
+
from string import replace
+from collections import OrderedDict
+from numpy import nan, isnan
+from xml.etree import ElementTree as ET
+from datetime import datetime as dt
+from datetime import timedelta
+
+from utils import mean, stdev, relative_change, classify_anomalies, \
+ convert_csv_to_pretty_txt
+
-from errors import PresentationError
-from utils import mean, stdev, relative_change
+REGEX_NIC = re.compile(r'\d*ge\dp\d\D*\d*')
def generate_tables(spec, data):
@@ -35,9 +46,9 @@ def generate_tables(spec, data):
for table in spec.tables:
try:
eval(table["algorithm"])(table, data)
- except NameError:
- logging.error("The algorithm '{0}' is not defined.".
- format(table["algorithm"]))
+ except NameError as err:
+ logging.error("Probably algorithm '{alg}' is not defined: {err}".
+ format(alg=table["algorithm"], err=repr(err)))
logging.info("Done.")
@@ -55,6 +66,8 @@ def table_details(table, input_data):
format(table.get("title", "")))
# Transform the data
+ logging.info(" Creating the data set for the {0} '{1}'.".
+ format(table.get("type", ""), table.get("title", "")))
data = input_data.filter_data(table)
# Prepare the header of the tables
@@ -64,7 +77,6 @@ def table_details(table, input_data):
# Generate the data for the table according to the model in the table
# specification
-
job = table["data"].keys()[0]
build = str(table["data"][job][0])
try:
@@ -108,8 +120,8 @@ def table_details(table, input_data):
logging.info(" Done.")
-def table_performance_improvements(table, input_data):
- """Generate the table(s) with algorithm: table_performance_improvements
+def table_merged_details(table, input_data):
+ """Generate the table(s) with algorithm: table_merged_details
specified in the specification file.
:param table: Table to generate.
@@ -118,145 +130,775 @@ def table_performance_improvements(table, input_data):
: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):
- line_lst.append(item["data"])
- elif isinstance(item["data"], float):
- line_lst.append("{:.1f}".format(item["data"]))
- 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.merge_data(data)
+ data.sort_index(inplace=True)
+
+ logging.info(" Creating the data set for the {0} '{1}'.".
+ format(table.get("type", ""), table.get("title", "")))
+ suites = input_data.filter_data(table, data_set="suites")
+ suites = input_data.merge_data(suites)
# Prepare the header of the tables
header = list()
for column in table["columns"]:
- header.append(column["title"])
+ header.append('"{0}"'.format(str(column["title"]).replace('"', '""')))
- # 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":
- try:
- val = float(tmpl_item[int(args[0])])
- except ValueError:
- val = tmpl_item[int(args[0])]
- tbl_item.append({"data": val})
- elif cmd == "data":
- job = args[0]
- operation = args[1]
- data_lst = list()
- for build in data[job]:
+ for _, suite in suites.iteritems():
+ # Generate data
+ suite_name = suite["name"]
+ table_lst = list()
+ for test in data.keys():
+ if data[test]["parent"] in suite_name:
+ row_lst = list()
+ for column in table["columns"]:
try:
- data_lst.append(float(build[tmpl_item[0]]["throughput"]
- ["value"]) / 1000000)
- except (KeyError, TypeError):
- # No data, ignore
- pass
- if data_lst:
- tbl_item.append({"data": eval(operation)(data_lst)})
- elif cmd == "operation":
- operation = args[0]
+ col_data = str(data[test][column["data"].
+ split(" ")[1]]).replace('"', '""')
+ if column["data"].split(" ")[1] in ("vat-history",
+ "show-run"):
+ col_data = replace(col_data, " |br| ", "",
+ maxreplace=1)
+ col_data = " |prein| {0} |preout| ".\
+ format(col_data[:-5])
+ row_lst.append('"{0}"'.format(col_data))
+ except KeyError:
+ row_lst.append("No data")
+ table_lst.append(row_lst)
+
+ # Write the data to file
+ if table_lst:
+ file_name = "{0}_{1}{2}".format(table["output-file"], suite_name,
+ table["output-file-ext"])
+ logging.info(" Writing file: '{}'".format(file_name))
+ with open(file_name, "w") as file_handler:
+ file_handler.write(",".join(header) + "\n")
+ for item in table_lst:
+ file_handler.write(",".join(item) + "\n")
+
+ logging.info(" Done.")
+
+
+def table_performance_comparison(table, input_data):
+ """Generate the table(s) with algorithm: table_performance_comparison
+ specified in the specification file.
+
+ :param table: Table to generate.
+ :param input_data: Data to process.
+ :type table: pandas.Series
+ :type input_data: InputData
+ """
+
+ logging.info(" Generating the table {0} ...".
+ format(table.get("title", "")))
+
+ # Transform the data
+ logging.info(" Creating the data set for the {0} '{1}'.".
+ format(table.get("type", ""), table.get("title", "")))
+ data = input_data.filter_data(table, continue_on_error=True)
+
+ # Prepare the header of the tables
+ try:
+ header = ["Test case", ]
+
+ if table["include-tests"] == "MRR":
+ hdr_param = "Receive Rate"
+ else:
+ hdr_param = "Throughput"
+
+ history = table.get("history", None)
+ if history:
+ for item in history:
+ header.extend(
+ ["{0} {1} [Mpps]".format(item["title"], hdr_param),
+ "{0} Stdev [Mpps]".format(item["title"])])
+ header.extend(
+ ["{0} {1} [Mpps]".format(table["reference"]["title"], hdr_param),
+ "{0} Stdev [Mpps]".format(table["reference"]["title"]),
+ "{0} {1} [Mpps]".format(table["compare"]["title"], hdr_param),
+ "{0} Stdev [Mpps]".format(table["compare"]["title"]),
+ "Delta [%]"])
+ header_str = ",".join(header) + "\n"
+ except (AttributeError, KeyError) as err:
+ logging.error("The model is invalid, missing parameter: {0}".
+ format(err))
+ return
+
+ # Prepare data to the table:
+ tbl_dict = dict()
+ for job, builds in table["reference"]["data"].items():
+ for build in builds:
+ for tst_name, tst_data in data[job][str(build)].iteritems():
+ tst_name_mod = tst_name.replace("-ndrpdrdisc", "").\
+ replace("-ndrpdr", "").replace("-pdrdisc", "").\
+ replace("-ndrdisc", "").replace("-pdr", "").\
+ replace("-ndr", "").\
+ replace("1t1c", "1c").replace("2t1c", "1c").\
+ replace("2t2c", "2c").replace("4t2c", "2c").\
+ replace("4t4c", "4c").replace("8t4c", "4c")
+ if "across topologies" in table["title"].lower():
+ tst_name_mod = tst_name_mod.replace("2n1l-", "")
+ if tbl_dict.get(tst_name_mod, None) is None:
+ name = "{0}-{1}".format(tst_data["parent"].split("-")[0],
+ "-".join(tst_data["name"].
+ split("-")[:-1]))
+ if "across testbeds" in table["title"].lower() or \
+ "across topologies" in table["title"].lower():
+ name = name.\
+ replace("1t1c", "1c").replace("2t1c", "1c").\
+ replace("2t2c", "2c").replace("4t2c", "2c").\
+ replace("4t4c", "4c").replace("8t4c", "4c")
+ tbl_dict[tst_name_mod] = {"name": name,
+ "ref-data": list(),
+ "cmp-data": list()}
try:
- nr1 = tbl_item[int(args[1])]["data"]
- nr2 = 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]["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:
- tbl_item.append({"data": None})
- except IndexError:
- logging.error("No data for {0}".format(tbl_item[0]))
- tbl_item.append({"data": None})
- continue
+ continue
+ except TypeError:
+ pass # No data in output.xml for this test
+
+ for job, builds in table["compare"]["data"].items():
+ for build in builds:
+ for tst_name, tst_data in data[job][str(build)].iteritems():
+ tst_name_mod = tst_name.replace("-ndrpdrdisc", ""). \
+ replace("-ndrpdr", "").replace("-pdrdisc", ""). \
+ replace("-ndrdisc", "").replace("-pdr", ""). \
+ replace("-ndr", "").\
+ replace("1t1c", "1c").replace("2t1c", "1c").\
+ replace("2t2c", "2c").replace("4t2c", "2c").\
+ replace("4t4c", "4c").replace("8t4c", "4c")
+ if "across topologies" in table["title"].lower():
+ tst_name_mod = tst_name_mod.replace("2n1l-", "")
+ try:
+ # TODO: Re-work when NDRPDRDISC tests are not used
+ if table["include-tests"] == "MRR":
+ tbl_dict[tst_name_mod]["cmp-data"]. \
+ append(tst_data["result"]["receive-rate"].avg)
+ elif table["include-tests"] == "PDR":
+ if tst_data["type"] == "PDR":
+ tbl_dict[tst_name_mod]["cmp-data"]. \
+ append(tst_data["throughput"]["value"])
+ elif tst_data["type"] == "NDRPDR":
+ tbl_dict[tst_name_mod]["cmp-data"].append(
+ tst_data["throughput"]["PDR"]["LOWER"])
+ elif table["include-tests"] == "NDR":
+ if tst_data["type"] == "NDR":
+ tbl_dict[tst_name_mod]["cmp-data"]. \
+ append(tst_data["throughput"]["value"])
+ elif tst_data["type"] == "NDRPDR":
+ tbl_dict[tst_name_mod]["cmp-data"].append(
+ tst_data["throughput"]["NDR"]["LOWER"])
+ else:
+ continue
+ except KeyError:
+ pass
+ except TypeError:
+ tbl_dict.pop(tst_name_mod, None)
+ if history:
+ for item in history:
+ for job, builds in item["data"].items():
+ for build in builds:
+ for tst_name, tst_data in data[job][str(build)].iteritems():
+ tst_name_mod = tst_name.replace("-ndrpdrdisc", ""). \
+ replace("-ndrpdr", "").replace("-pdrdisc", ""). \
+ replace("-ndrdisc", "").replace("-pdr", ""). \
+ replace("-ndr", "").\
+ replace("1t1c", "1c").replace("2t1c", "1c").\
+ replace("2t2c", "2c").replace("4t2c", "2c").\
+ replace("4t4c", "4c").replace("8t4c", "4c")
+ if "across topologies" in table["title"].lower():
+ tst_name_mod = tst_name_mod.replace("2n1l-", "")
+ if tbl_dict.get(tst_name_mod, None) is None:
+ continue
+ if tbl_dict[tst_name_mod].get("history", None) is None:
+ tbl_dict[tst_name_mod]["history"] = OrderedDict()
+ if tbl_dict[tst_name_mod]["history"].get(item["title"],
+ None) is None:
+ tbl_dict[tst_name_mod]["history"][item["title"]] = \
+ list()
+ try:
+ # TODO: Re-work when NDRPDRDISC tests are not used
+ if table["include-tests"] == "MRR":
+ tbl_dict[tst_name_mod]["history"][item["title"
+ ]].append(tst_data["result"]["receive-rate"].
+ avg)
+ elif table["include-tests"] == "PDR":
+ if tst_data["type"] == "PDR":
+ tbl_dict[tst_name_mod]["history"][
+ item["title"]].\
+ append(tst_data["throughput"]["value"])
+ elif tst_data["type"] == "NDRPDR":
+ tbl_dict[tst_name_mod]["history"][item[
+ "title"]].append(tst_data["throughput"][
+ "PDR"]["LOWER"])
+ elif table["include-tests"] == "NDR":
+ if tst_data["type"] == "NDR":
+ tbl_dict[tst_name_mod]["history"][
+ item["title"]].\
+ append(tst_data["throughput"]["value"])
+ elif tst_data["type"] == "NDRPDR":
+ tbl_dict[tst_name_mod]["history"][item[
+ "title"]].append(tst_data["throughput"][
+ "NDR"]["LOWER"])
+ else:
+ continue
+ except (TypeError, KeyError):
+ pass
+
+ tbl_lst = list()
+ for tst_name in tbl_dict.keys():
+ item = [tbl_dict[tst_name]["name"], ]
+ if history:
+ if tbl_dict[tst_name].get("history", None) is not None:
+ for hist_data in tbl_dict[tst_name]["history"].values():
+ if hist_data:
+ item.append(round(mean(hist_data) / 1000000, 2))
+ item.append(round(stdev(hist_data) / 1000000, 2))
+ else:
+ item.extend([None, None])
else:
- 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 "ndr_top" in file_name \
- and "ndr" in item[1]["data"] \
- and item[-1]["data"] >= 10:
- _write_line_to_file(file_handler, item)
- elif "pdr_top" in file_name \
- and "pdr" in item[1]["data"] \
- and item[-1]["data"] >= 10:
- _write_line_to_file(file_handler, item)
- elif "ndr_low" in file_name \
- and "ndr" in item[1]["data"] \
- and item[-1]["data"] < 10:
- _write_line_to_file(file_handler, item)
- elif "pdr_low" in file_name \
- and "pdr" in item[1]["data"] \
- and item[-1]["data"] < 10:
- _write_line_to_file(file_handler, item)
+ tbl_lst.sort(key=lambda rel: rel[-1], reverse=True)
- logging.info(" Done.")
+ # 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 _read_csv_template(file_name):
- """Read the template from a .csv file.
+def table_performance_trending_dashboard(table, input_data):
+ """Generate the table(s) with algorithm:
+ table_performance_trending_dashboard
+ specified in the specification file.
- :param 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.
+ :param table: Table to generate.
+ :param input_data: Data to process.
+ :type table: pandas.Series
+ :type input_data: InputData
"""
+ logging.info(" Generating the table {0} ...".
+ format(table.get("title", "")))
+
+ # Transform the data
+ logging.info(" Creating the data set for the {0} '{1}'.".
+ format(table.get("type", ""), table.get("title", "")))
+ data = input_data.filter_data(table, continue_on_error=True)
+
+ # Prepare the header of the tables
+ header = ["Test Case",
+ "Trend [Mpps]",
+ "Short-Term Change [%]",
+ "Long-Term Change [%]",
+ "Regressions [#]",
+ "Progressions [#]"
+ ]
+ header_str = ",".join(header) + "\n"
+
+ # Prepare data to the table:
+ tbl_dict = dict()
+ for job, builds in table["data"].items():
+ for build in builds:
+ for tst_name, tst_data in data[job][str(build)].iteritems():
+ if tst_name.lower() in table["ignore-list"]:
+ continue
+ if tbl_dict.get(tst_name, None) is None:
+ groups = re.search(REGEX_NIC, tst_data["parent"])
+ if not groups:
+ continue
+ nic = groups.group(0)
+ tbl_dict[tst_name] = {
+ "name": "{0}-{1}".format(nic, tst_data["name"]),
+ "data": OrderedDict()}
+ try:
+ tbl_dict[tst_name]["data"][str(build)] = \
+ tst_data["result"]["receive-rate"]
+ except (TypeError, KeyError):
+ pass # No data in output.xml for this test
+
+ tbl_lst = list()
+ for tst_name in tbl_dict.keys():
+ data_t = tbl_dict[tst_name]["data"]
+ if len(data_t) < 2:
+ continue
+
+ classification_lst, avgs = classify_anomalies(data_t)
+
+ win_size = min(len(data_t), table["window"])
+ long_win_size = min(len(data_t), table["long-trend-window"])
+
+ try:
+ max_long_avg = max(
+ [x for x in avgs[-long_win_size:-win_size]
+ if not isnan(x)])
+ except ValueError:
+ max_long_avg = nan
+ last_avg = avgs[-1]
+ avg_week_ago = avgs[max(-win_size, -len(avgs))]
+
+ if isnan(last_avg) or isnan(avg_week_ago) or avg_week_ago == 0.0:
+ rel_change_last = nan
+ else:
+ rel_change_last = round(
+ ((last_avg - avg_week_ago) / avg_week_ago) * 100, 2)
+
+ if isnan(max_long_avg) or isnan(last_avg) or max_long_avg == 0.0:
+ rel_change_long = nan
+ else:
+ rel_change_long = round(
+ ((last_avg - max_long_avg) / max_long_avg) * 100, 2)
+
+ if classification_lst:
+ if isnan(rel_change_last) and isnan(rel_change_long):
+ continue
+ 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,
+ classification_lst[-win_size:].count("regression"),
+ classification_lst[-win_size:].count("progression")])
+
+ tbl_lst.sort(key=lambda rel: rel[0])
+
+ tbl_sorted = list()
+ for nrr in range(table["window"], -1, -1):
+ tbl_reg = [item for item in tbl_lst if item[4] == nrr]
+ for nrp in range(table["window"], -1, -1):
+ tbl_out = [item for item in tbl_reg if item[5] == nrp]
+ tbl_out.sort(key=lambda rel: rel[2])
+ tbl_sorted.extend(tbl_out)
+
+ file_name = "{0}{1}".format(table["output-file"], table["output-file-ext"])
+
+ logging.info(" Writing file: '{0}'".format(file_name))
+ with open(file_name, "w") as file_handler:
+ file_handler.write(header_str)
+ for test in tbl_sorted:
+ file_handler.write(",".join([str(item) for item in test]) + '\n')
+
+ txt_file_name = "{0}.txt".format(table["output-file"])
+ logging.info(" Writing file: '{0}'".format(txt_file_name))
+ convert_csv_to_pretty_txt(file_name, txt_file_name)
+
+
+def _generate_url(base, testbed, test_name):
+ """Generate URL to a trending plot from the name of the test case.
+
+ :param base: The base part of URL common to all test cases.
+ :param testbed: The testbed used for testing.
+ :param test_name: The name of the test case.
+ :type base: str
+ :type testbed: str
+ :type test_name: str
+ :returns: The URL to the plot with the trending data for the given test
+ case.
+ :rtype str
+ """
+
+ url = base
+ file_name = ""
+ anchor = ".html#"
+ feature = ""
+
+ if "lbdpdk" in test_name or "lbvpp" in test_name:
+ file_name = "link_bonding"
+
+ elif "114b" in test_name and "vhost" in test_name:
+ file_name = "vts"
+
+ elif "testpmd" in test_name or "l3fwd" in test_name:
+ file_name = "dpdk"
+
+ elif "memif" in test_name:
+ file_name = "container_memif"
+ feature = "-base"
+
+ elif "srv6" in test_name:
+ file_name = "srv6"
+
+ elif "vhost" in test_name:
+ if "l2xcbase" in test_name or "l2bdbasemaclrn" in test_name:
+ file_name = "vm_vhost_l2"
+ if "114b" in test_name:
+ feature = ""
+ elif "l2xcbase" in test_name:
+ feature = "-base-l2xc"
+ elif "l2bdbasemaclrn" in test_name:
+ feature = "-base-l2bd"
+ else:
+ feature = "-base"
+ elif "ip4base" in test_name:
+ file_name = "vm_vhost_ip4"
+ feature = "-base"
+
+ elif "ipsec" in test_name:
+ file_name = "ipsec"
+ feature = "-base-scale"
+
+ elif "ethip4lispip" in test_name or "ethip4vxlan" in test_name:
+ file_name = "ip4_tunnels"
+ feature = "-base"
+
+ elif "ip4base" in test_name or "ip4scale" in test_name:
+ file_name = "ip4"
+ if "xl710" in test_name:
+ feature = "-base-scale-features"
+ elif "iacl" in test_name:
+ feature = "-features-iacl"
+ elif "oacl" in test_name:
+ feature = "-features-oacl"
+ elif "snat" in test_name or "cop" in test_name:
+ feature = "-features"
+ else:
+ feature = "-base-scale"
+
+ elif "ip6base" in test_name or "ip6scale" in test_name:
+ file_name = "ip6"
+ feature = "-base-scale"
+
+ elif "l2xcbase" in test_name or "l2xcscale" in test_name \
+ or "l2bdbasemaclrn" in test_name or "l2bdscale" in test_name \
+ or "l2dbbasemaclrn" in test_name or "l2dbscale" in test_name:
+ file_name = "l2"
+ if "macip" in test_name:
+ feature = "-features-macip"
+ elif "iacl" in test_name:
+ feature = "-features-iacl"
+ elif "oacl" in test_name:
+ feature = "-features-oacl"
+ else:
+ feature = "-base-scale"
+
+ if "x520" in test_name:
+ nic = "x520-"
+ elif "x710" in test_name:
+ nic = "x710-"
+ elif "xl710" in test_name:
+ nic = "xl710-"
+ elif "xxv710" in test_name:
+ nic = "xxv710-"
+ else:
+ nic = ""
+ anchor += nic
+
+ if "64b" in test_name:
+ framesize = "64b"
+ elif "78b" in test_name:
+ framesize = "78b"
+ elif "imix" in test_name:
+ framesize = "imix"
+ elif "9000b" in test_name:
+ framesize = "9000b"
+ elif "1518b" in test_name:
+ framesize = "1518b"
+ elif "114b" in test_name:
+ framesize = "114b"
+ else:
+ framesize = ""
+ anchor += framesize + '-'
+
+ if "1t1c" in test_name:
+ anchor += "1t1c"
+ elif "2t2c" in test_name:
+ anchor += "2t2c"
+ elif "4t4c" in test_name:
+ anchor += "4t4c"
+ elif "2t1c" in test_name:
+ anchor += "2t1c"
+ elif "4t2c" in test_name:
+ anchor += "4t2c"
+ elif "8t4c" in test_name:
+ anchor += "8t4c"
+
+ return url + file_name + '-' + testbed + '-' + nic + framesize + feature + \
+ anchor + feature
+
+
+def table_performance_trending_dashboard_html(table, input_data):
+ """Generate the table(s) with algorithm:
+ table_performance_trending_dashboard_html specified in the specification
+ file.
+
+ :param table: Table to generate.
+ :param input_data: Data to process.
+ :type table: dict
+ :type input_data: InputData
+ """
+
+ testbed = table.get("testbed", None)
+ if testbed is None:
+ logging.error("The testbed is not defined for the table '{0}'.".
+ format(table.get("title", "")))
+ return
+
+ logging.info(" Generating the table {0} ...".
+ format(table.get("title", "")))
+
try:
- with open(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")
+ with open(table["input-file"], 'rb') as csv_file:
+ csv_content = csv.reader(csv_file, delimiter=',', quotechar='"')
+ csv_lst = [item for item in csv_content]
+ except KeyError:
+ logging.warning("The input file is not defined.")
+ return
+ except csv.Error as err:
+ logging.warning("Not possible to process the file '{0}'.\n{1}".
+ format(table["input-file"], err))
+ return
+
+ # Table:
+ dashboard = ET.Element("table", attrib=dict(width="100%", border='0'))
+
+ # Table header:
+ tr = ET.SubElement(dashboard, "tr", attrib=dict(bgcolor="#7eade7"))
+ for idx, item in enumerate(csv_lst[0]):
+ alignment = "left" if idx == 0 else "center"
+ th = ET.SubElement(tr, "th", attrib=dict(align=alignment))
+ th.text = item
+
+ # Rows:
+ colors = {"regression": ("#ffcccc", "#ff9999"),
+ "progression": ("#c6ecc6", "#9fdf9f"),
+ "normal": ("#e9f1fb", "#d4e4f7")}
+ for r_idx, row in enumerate(csv_lst[1:]):
+ if int(row[4]):
+ color = "regression"
+ elif int(row[5]):
+ color = "progression"
+ else:
+ color = "normal"
+ background = colors[color][r_idx % 2]
+ tr = ET.SubElement(dashboard, "tr", attrib=dict(bgcolor=background))
+
+ # Columns:
+ for c_idx, item in enumerate(row):
+ alignment = "left" if c_idx == 0 else "center"
+ td = ET.SubElement(tr, "td", attrib=dict(align=alignment))
+ # Name:
+ if c_idx == 0:
+ url = _generate_url("../trending/", testbed, item)
+ ref = ET.SubElement(td, "a", attrib=dict(href=url))
+ ref.text = item
+ else:
+ td.text = item
+ try:
+ with open(table["output-file"], 'w') as html_file:
+ logging.info(" Writing file: '{0}'".format(table["output-file"]))
+ html_file.write(".. raw:: html\n\n\t")
+ html_file.write(ET.tostring(dashboard))
+ html_file.write("\n\t
\n")
+ except KeyError:
+ logging.warning("The output file is not defined.")
+ return
+
+
+def table_failed_tests(table, input_data):
+ """Generate the table(s) with algorithm: table_failed_tests
+ specified in the specification file.
+
+ :param table: Table to generate.
+ :param input_data: Data to process.
+ :type table: pandas.Series
+ :type input_data: InputData
+ """
+
+ logging.info(" Generating the table {0} ...".
+ format(table.get("title", "")))
+
+ # Transform the data
+ logging.info(" Creating the data set for the {0} '{1}'.".
+ format(table.get("type", ""), table.get("title", "")))
+ data = input_data.filter_data(table, continue_on_error=True)
+
+ # Prepare the header of the tables
+ header = ["Test Case",
+ "Failures [#]",
+ "Last Failure [Time]",
+ "Last Failure [VPP-Build-Id]",
+ "Last Failure [CSIT-Job-Build-Id]"]
+
+ # Generate the data for the table according to the model in the table
+ # specification
+
+ now = dt.utcnow()
+ timeperiod = timedelta(int(table.get("window", 7)))
+
+ tbl_dict = dict()
+ for job, builds in table["data"].items():
+ for build in builds:
+ build = str(build)
+ for tst_name, tst_data in data[job][build].iteritems():
+ if tst_name.lower() in table["ignore-list"]:
+ continue
+ if tbl_dict.get(tst_name, None) is None:
+ groups = re.search(REGEX_NIC, tst_data["parent"])
+ if not groups:
+ continue
+ nic = groups.group(0)
+ tbl_dict[tst_name] = {
+ "name": "{0}-{1}".format(nic, tst_data["name"]),
+ "data": OrderedDict()}
+ try:
+ generated = input_data.metadata(job, build).\
+ get("generated", "")
+ if not generated:
+ continue
+ then = dt.strptime(generated, "%Y%m%d %H:%M")
+ if (now - then) <= timeperiod:
+ tbl_dict[tst_name]["data"][build] = (
+ tst_data["status"],
+ generated,
+ input_data.metadata(job, build).get("version", ""),
+ build)
+ except (TypeError, KeyError):
+ pass # No data in output.xml for this test
+
+ tbl_lst = list()
+ for tst_data in tbl_dict.values():
+ fails_nr = 0
+ for val in tst_data["data"].values():
+ if val[0] == "FAIL":
+ fails_nr += 1
+ fails_last_date = val[1]
+ fails_last_vpp = val[2]
+ fails_last_csit = val[3]
+ if fails_nr:
+ tbl_lst.append([tst_data["name"],
+ fails_nr,
+ fails_last_date,
+ fails_last_vpp,
+ "mrr-daily-build-{0}".format(fails_last_csit)])
+
+ tbl_lst.sort(key=lambda rel: rel[2], reverse=True)
+ tbl_sorted = list()
+ for nrf in range(table["window"], -1, -1):
+ tbl_fails = [item for item in tbl_lst if item[1] == nrf]
+ tbl_sorted.extend(tbl_fails)
+ file_name = "{0}{1}".format(table["output-file"], table["output-file-ext"])
+
+ logging.info(" Writing file: '{0}'".format(file_name))
+ with open(file_name, "w") as file_handler:
+ file_handler.write(",".join(header) + "\n")
+ for test in tbl_sorted:
+ file_handler.write(",".join([str(item) for item in test]) + '\n')
+
+ txt_file_name = "{0}.txt".format(table["output-file"])
+ logging.info(" Writing file: '{0}'".format(txt_file_name))
+ convert_csv_to_pretty_txt(file_name, txt_file_name)
+
+
+def table_failed_tests_html(table, input_data):
+ """Generate the table(s) with algorithm: table_failed_tests_html
+ specified in the specification file.
+
+ :param table: Table to generate.
+ :param input_data: Data to process.
+ :type table: pandas.Series
+ :type input_data: InputData
+ """
+
+ testbed = table.get("testbed", None)
+ if testbed is None:
+ logging.error("The testbed is not defined for the table '{0}'.".
+ format(table.get("title", "")))
+ return
+
+ logging.info(" Generating the table {0} ...".
+ format(table.get("title", "")))
+
+ try:
+ with open(table["input-file"], 'rb') as csv_file:
+ csv_content = csv.reader(csv_file, delimiter=',', quotechar='"')
+ csv_lst = [item for item in csv_content]
+ except KeyError:
+ logging.warning("The input file is not defined.")
+ return
+ except csv.Error as err:
+ logging.warning("Not possible to process the file '{0}'.\n{1}".
+ format(table["input-file"], err))
+ return
+
+ # Table:
+ failed_tests = ET.Element("table", attrib=dict(width="100%", border='0'))
+
+ # Table header:
+ tr = ET.SubElement(failed_tests, "tr", attrib=dict(bgcolor="#7eade7"))
+ for idx, item in enumerate(csv_lst[0]):
+ alignment = "left" if idx == 0 else "center"
+ th = ET.SubElement(tr, "th", attrib=dict(align=alignment))
+ th.text = item
+
+ # Rows:
+ colors = ("#e9f1fb", "#d4e4f7")
+ for r_idx, row in enumerate(csv_lst[1:]):
+ background = colors[r_idx % 2]
+ tr = ET.SubElement(failed_tests, "tr", attrib=dict(bgcolor=background))
+
+ # Columns:
+ for c_idx, item in enumerate(row):
+ alignment = "left" if c_idx == 0 else "center"
+ td = ET.SubElement(tr, "td", attrib=dict(align=alignment))
+ # Name:
+ if c_idx == 0:
+ url = _generate_url("../trending/", testbed, item)
+ ref = ET.SubElement(td, "a", attrib=dict(href=url))
+ ref.text = item
+ else:
+ td.text = item
+ try:
+ with open(table["output-file"], 'w') as html_file:
+ logging.info(" Writing file: '{0}'".format(table["output-file"]))
+ html_file.write(".. raw:: html\n\n\t")
+ html_file.write(ET.tostring(failed_tests))
+ html_file.write("\n\t
\n")
+ except KeyError:
+ logging.warning("The output file is not defined.")
+ return