Continuous Performance Trending and Analysis
============================================
+VPP Performance Trending Dashboard
+----------------------------------
+
+1t1c
+````
+
+.. include:: ../../_build/_static/vpp/performance-trending-dashboard-1t1c.rst
+
+2t2c
+````
+
+.. include:: ../../_build/_static/vpp/performance-trending-dashboard-2t2c.rst
+
+4t4c
+````
+
+.. include:: ../../_build/_static/vpp/performance-trending-dashboard-4t4c.rst
+
+
.. toctree::
:maxdepth: 6
:numbered:
in_data = _select_data(in_data, period,
fill_missing=fill_missing,
use_first=use_first)
- try:
- data_x = ["{0}/{1}".format(key, build_info[str(key)][1].split("~")[-1])
- for key in in_data.keys()]
- except KeyError:
- data_x = [key for key in in_data.keys()]
- # hover_text = ["vpp-build: {0}".format(x[1].split("~")[-1])
- # for x in build_info.values()]
- # data_x = [key for key in in_data.keys()]
+ # try:
+ # data_x = ["{0}/{1}".format(key, build_info[str(key)][1].split("~")[-1])
+ # for key in in_data.keys()]
+ # except KeyError:
+ # data_x = [key for key in in_data.keys()]
+ hover_text = ["vpp-build: {0}".format(x[1].split("~")[-1])
+ for x in build_info.values()]
+ data_x = [key for key in in_data.keys()]
data_y = [val for val in in_data.values()]
data_pd = pd.Series(data_y, index=data_x)
anomalies = pd.Series()
anomalies_res = list()
for idx, item in enumerate(in_data.items()):
- item_pd = pd.Series([item[1], ],
- index=["{0}/{1}".
- format(item[0],
- build_info[str(item[0])][1].split("~")[-1]),
- ])
- #item_pd = pd.Series([item[1], ], index=[item[0], ])
+ # item_pd = pd.Series([item[1], ],
+ # index=["{0}/{1}".
+ # format(item[0],
+ # build_info[str(item[0])][1].split("~")[-1]),
+ # ])
+ item_pd = pd.Series([item[1], ], index=[item[0], ])
if item[0] in outliers.keys():
anomalies = anomalies.append(item_pd)
anomalies_res.append(0.0)
"color": color,
"symbol": "circle",
},
- # text=hover_text,
- # hoverinfo="x+y+text+name"
+ text=hover_text,
+ hoverinfo="x+y+text+name"
)
traces = [trace_samples, ]
from string import replace
from math import isnan
+from xml.etree import ElementTree as ET
from errors import PresentationError
from utils import mean, stdev, relative_change, remove_outliers, find_outliers
classification = "normal"
if not isnan(last) and not isnan(trend) and trend != 0:
- # Change:
- change = round(float(last - trend) / 1000000, 2)
# Relative change:
rel_change = int(relative_change(float(trend), float(last)))
tbl_lst.append([name,
round(float(trend) / 1000000, 2),
- last,
+ round(float(last) / 1000000, 2),
rel_change,
classification])
- # Sort the table according to the relative change
- # tbl_lst.sort(key=lambda rel: rel[-2], reverse=True)
-
# Sort the table according to the classification
tbl_sorted = list()
for classification in ("regression", "outlier", "progression", "normal"):
tbl_tmp.sort(key=lambda rel: rel[0])
tbl_sorted.extend(tbl_tmp)
- file_name = "{0}.{1}".format(table["output-file"], table["output-file-ext"])
+ 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:
txt_table.align["Test case"] = "l"
with open(txt_file_name, "w") as txt_file:
txt_file.write(str(txt_table))
+
+
+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: pandas.Series
+ :type input_data: InputData
+ """
+
+ 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:
+ dashboard = ET.Element("table", attrib=dict(width="100%", border='0'))
+
+ # Table header:
+ tr = ET.SubElement(dashboard, "tr", attrib=dict(bgcolor="#6699ff"))
+ for idx, item in enumerate(csv_lst[0]):
+ alignment = "left" if idx == 0 else "right"
+ th = ET.SubElement(tr, "th", attrib=dict(align=alignment))
+ th.text = item
+
+ # Rows:
+ for r_idx, row in enumerate(csv_lst[1:]):
+ background = "#D4E4F7" if r_idx % 2 else "white"
+ 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))
+ if c_idx == 4:
+ if item == "regression":
+ td.set("bgcolor", "#FF0000")
+ elif item == "outlier":
+ td.set("bgcolor", "#818181")
+ elif item == "progression":
+ td.set("bgcolor", "#008000")
+ 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<p><br><br></p>\n")
+ except KeyError:
+ logging.warning("The output file is not defined.")
+ return
return 1
ret_code = 0
- # try:
- env = Environment(spec.environment, args.force)
- env.set_environment()
-
- if spec.is_debug:
- if spec.debug["input-format"] == "zip":
- unzip_files(spec)
- else:
- download_data_files(spec)
-
- prepare_static_content(spec)
-
- data = InputData(spec)
- data.read_data()
-
- generate_tables(spec, data)
- generate_plots(spec, data)
- generate_files(spec, data)
-
- if spec.output["output"] == "report":
- generate_report(args.release, spec)
- logging.info("Successfully finished.")
- elif spec.output["output"] == "CPTA":
- sys.stdout.write(generate_cpta(spec, data))
- logging.info("Successfully finished.")
- else:
- logging.critical("The output '{0}' is not supported.".
- format(spec.output["output"]))
+ try:
+ env = Environment(spec.environment, args.force)
+ env.set_environment()
+
+ if spec.is_debug:
+ if spec.debug["input-format"] == "zip":
+ unzip_files(spec)
+ else:
+ download_data_files(spec)
+
+ prepare_static_content(spec)
+
+ data = InputData(spec)
+ data.read_data()
+
+ generate_tables(spec, data)
+ generate_plots(spec, data)
+ generate_files(spec, data)
+
+ if spec.output["output"] == "report":
+ generate_report(args.release, spec)
+ logging.info("Successfully finished.")
+ elif spec.output["output"] == "CPTA":
+ sys.stdout.write(generate_cpta(spec, data))
+ logging.info("Successfully finished.")
+ else:
+ logging.critical("The output '{0}' is not supported.".
+ format(spec.output["output"]))
+ ret_code = 1
+
+ except (KeyError, ValueError, PresentationError) as err:
+ logging.info("Finished with an error.")
+ logging.critical(str(err))
ret_code = 1
-
- # except (KeyError, ValueError, PresentationError) as err:
- # logging.info("Finished with an error.")
- # logging.critical(str(err))
- # ret_code = 1
- # except Exception as err:
- # logging.info("Finished with an unexpected error.")
- # logging.critical(str(err))
- # ret_code = 1
- # finally:
- # if spec is not None and not spec.is_debug:
- # clean_environment(spec.environment)
- # return ret_code
+ except Exception as err:
+ logging.info("Finished with an unexpected error.")
+ logging.critical(str(err))
+ ret_code = 1
+ finally:
+ if spec is not None and not spec.is_debug:
+ clean_environment(spec.environment)
+ return ret_code
if __name__ == '__main__':
autotick: True
margin:
r: 20
- b: 150
+ b: 50
t: 5
l: 70
legend:
outlier-const: 1.5
window: 10
+-
+ type: "table"
+ title: "HTML performance trending dashboard 1t1c"
+ algorithm: "table_performance_trending_dashboard_html"
+ input-file: "{DIR[STATIC,VPP]}/performance-trending-dashboard-1t1c.csv"
+ output-file: "{DIR[STATIC,VPP]}/performance-trending-dashboard-1t1c.rst"
+
+-
+ type: "table"
+ title: "HTML performance trending dashboard 2t2c"
+ algorithm: "table_performance_trending_dashboard_html"
+ input-file: "{DIR[STATIC,VPP]}/performance-trending-dashboard-2t2c.csv"
+ output-file: "{DIR[STATIC,VPP]}/performance-trending-dashboard-2t2c.rst"
+
+-
+ type: "table"
+ title: "HTML performance trending dashboard 4t4c"
+ algorithm: "table_performance_trending_dashboard_html"
+ input-file: "{DIR[STATIC,VPP]}/performance-trending-dashboard-4t4c.csv"
+ output-file: "{DIR[STATIC,VPP]}/performance-trending-dashboard-4t4c.rst"
+
################################################################################
### C P T A ###
except KeyError:
pass
+ try:
+ element["input-file"] = self._replace_tags(
+ element["input-file"],
+ self._specification["environment"]["paths"])
+ except KeyError:
+ pass
+
# add data sets to the elements:
if isinstance(element.get("data", None), str):
data_set = element["data"]
stdout, stderr = proc.communicate()
- logging.debug(stdout)
- logging.debug(stderr)
+ logging.info(stdout)
+ logging.info(stderr)
if proc.returncode != 0:
logging.error(" Command execution failed.")
Code Review / csit.git / commitdiff