-# Copyright (c) 2023 Cisco and/or its affiliates.
+# Copyright (c) 2024 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 hdrh.codec
from math import sqrt
-from dash import dcc
+from dash import dcc, no_update, html
from datetime import datetime
from ..utils.constants import Constants as C
from ..utils.url_processing import url_encode
+from ..utils.trigger import Trigger
def get_color(idx: int) -> str:
fig.update_layout(layout_hdrh)
return fig
+
+
+def navbar_trending(active: tuple):
+ """Add nav element with navigation panel. It is placed on the top.
+
+ :param active: Tuple of boolean values defining the active items in the
+ navbar. True == active
+ :type active: tuple
+ :returns: Navigation bar.
+ :rtype: dbc.NavbarSimple
+ """
+ return dbc.NavbarSimple(
+ children=[
+ dbc.NavItem(dbc.NavLink(
+ C.TREND_TITLE,
+ active=active[0],
+ external_link=True,
+ href="/trending"
+ )),
+ dbc.NavItem(dbc.NavLink(
+ C.NEWS_TITLE,
+ active=active[1],
+ external_link=True,
+ href="/news"
+ )),
+ dbc.NavItem(dbc.NavLink(
+ C.STATS_TITLE,
+ active=active[2],
+ external_link=True,
+ href="/stats"
+ )),
+ dbc.NavItem(dbc.NavLink(
+ C.SEARCH_TITLE,
+ active=active[3],
+ external_link=True,
+ href="/search"
+ )),
+ dbc.NavItem(dbc.NavLink(
+ "Documentation",
+ id="btn-documentation",
+ ))
+ ],
+ id="navbarsimple-main",
+ brand=C.BRAND,
+ brand_href="/",
+ brand_external_link=True,
+ class_name="p-2",
+ fluid=True
+ )
+
+
+def navbar_report(active: tuple):
+ """Add nav element with navigation panel. It is placed on the top.
+
+ :param active: Tuple of boolean values defining the active items in the
+ navbar. True == active
+ :type active: tuple
+ :returns: Navigation bar.
+ :rtype: dbc.NavbarSimple
+ """
+ return dbc.NavbarSimple(
+ id="navbarsimple-main",
+ children=[
+ dbc.NavItem(dbc.NavLink(
+ C.REPORT_TITLE,
+ active=active[0],
+ external_link=True,
+ href="/report"
+ )),
+ dbc.NavItem(dbc.NavLink(
+ "Comparisons",
+ active=active[1],
+ external_link=True,
+ href="/comparisons"
+ )),
+ dbc.NavItem(dbc.NavLink(
+ "Coverage Data",
+ active=active[2],
+ external_link=True,
+ href="/coverage"
+ )),
+ dbc.NavItem(dbc.NavLink(
+ C.SEARCH_TITLE,
+ active=active[3],
+ external_link=True,
+ href="/search"
+ )),
+ dbc.NavItem(dbc.NavLink(
+ "Documentation",
+ id="btn-documentation",
+ ))
+ ],
+ brand=C.BRAND,
+ brand_href="/",
+ brand_external_link=True,
+ class_name="p-2",
+ fluid=True
+ )
+
+
+def filter_table_data(
+ store_table_data: list,
+ table_filter: str
+ ) -> list:
+ """Filter table data using user specified filter.
+
+ :param store_table_data: Table data represented as a list of records.
+ :param table_filter: User specified filter.
+ :type store_table_data: list
+ :type table_filter: str
+ :returns: A new table created by filtering of table data represented as
+ a list of records.
+ :rtype: list
+ """
+
+ # Checks:
+ if not any((table_filter, store_table_data, )):
+ return store_table_data
+
+ def _split_filter_part(filter_part: str) -> tuple:
+ """Split a part of filter into column name, operator and value.
+ A "part of filter" is a sting berween "&&" operator.
+
+ :param filter_part: A part of filter.
+ :type filter_part: str
+ :returns: Column name, operator, value
+ :rtype: tuple[str, str, str|float]
+ """
+ for operator_type in C.OPERATORS:
+ for operator in operator_type:
+ if operator in filter_part:
+ name_p, val_p = filter_part.split(operator, 1)
+ name = name_p[name_p.find("{") + 1 : name_p.rfind("}")]
+ val_p = val_p.strip()
+ if (val_p[0] == val_p[-1] and val_p[0] in ("'", '"', '`')):
+ value = val_p[1:-1].replace("\\" + val_p[0], val_p[0])
+ else:
+ try:
+ value = float(val_p)
+ except ValueError:
+ value = val_p
+
+ return name, operator_type[0].strip(), value
+ return (None, None, None)
+
+ df = pd.DataFrame.from_records(store_table_data)
+ for filter_part in table_filter.split(" && "):
+ col_name, operator, filter_value = _split_filter_part(filter_part)
+ if operator == "contains":
+ df = df.loc[df[col_name].str.contains(filter_value, regex=True)]
+ elif operator in ("eq", "ne", "lt", "le", "gt", "ge"):
+ # These operators match pandas series operator method names.
+ df = df.loc[getattr(df[col_name], operator)(filter_value)]
+ elif operator == "datestartswith":
+ # This is a simplification of the front-end filtering logic,
+ # only works with complete fields in standard format.
+ # Currently not used in comparison tables.
+ df = df.loc[df[col_name].str.startswith(filter_value)]
+
+ return df.to_dict("records")
+
+
+def show_trending_graph_data(
+ trigger: Trigger,
+ data: dict,
+ graph_layout: dict
+ ) -> tuple:
+ """Generates the data for the offcanvas displayed when a particular point in
+ a trending graph (daily data) is clicked on.
+
+ :param trigger: The information from trigger when the data point is clicked
+ on.
+ :param graph: The data from the clicked point in the graph.
+ :param graph_layout: The layout of the HDRH latency graph.
+ :type trigger: Trigger
+ :type graph: dict
+ :type graph_layout: dict
+ :returns: The data to be displayed on the offcanvas and the information to
+ show the offcanvas.
+ :rtype: tuple(list, list, bool)
+ """
+
+ if trigger.idx == "tput":
+ idx = 0
+ elif trigger.idx == "bandwidth":
+ idx = 1
+ elif trigger.idx == "lat":
+ idx = len(data) - 1
+ else:
+ return list(), list(), False
+ try:
+ data = data[idx]["points"][0]
+ except (IndexError, KeyError, ValueError, TypeError):
+ return list(), list(), False
+
+ metadata = no_update
+ graph = list()
+
+ list_group_items = list()
+ for itm in data.get("text", None).split("<br>"):
+ if not itm:
+ continue
+ lst_itm = itm.split(": ")
+ if lst_itm[0] == "csit-ref":
+ list_group_item = dbc.ListGroupItem([
+ dbc.Badge(lst_itm[0]),
+ html.A(
+ lst_itm[1],
+ href=f"{C.URL_JENKINS}{lst_itm[1]}",
+ target="_blank"
+ )
+ ])
+ else:
+ list_group_item = dbc.ListGroupItem([
+ dbc.Badge(lst_itm[0]),
+ lst_itm[1]
+ ])
+ list_group_items.append(list_group_item)
+
+ if trigger.idx == "tput":
+ title = "Throughput"
+ elif trigger.idx == "bandwidth":
+ title = "Bandwidth"
+ elif trigger.idx == "lat":
+ title = "Latency"
+ hdrh_data = data.get("customdata", None)
+ if hdrh_data:
+ graph = [dbc.Card(
+ class_name="gy-2 p-0",
+ children=[
+ dbc.CardHeader(hdrh_data.pop("name")),
+ dbc.CardBody(
+ dcc.Graph(
+ id="hdrh-latency-graph",
+ figure=graph_hdrh_latency(hdrh_data, graph_layout)
+ )
+ )
+ ])
+ ]
+
+ metadata = [
+ dbc.Card(
+ class_name="gy-2 p-0",
+ children=[
+ dbc.CardHeader(children=[
+ dcc.Clipboard(
+ target_id="tput-lat-metadata",
+ title="Copy",
+ style={"display": "inline-block"}
+ ),
+ title
+ ]),
+ dbc.CardBody(
+ dbc.ListGroup(list_group_items, flush=True),
+ id="tput-lat-metadata",
+ class_name="p-0",
+ )
+ ]
+ )
+ ]
+
+ return metadata, graph, True
+
+
+def show_iterative_graph_data(
+ trigger: Trigger,
+ data: dict,
+ graph_layout: dict
+ ) -> tuple:
+ """Generates the data for the offcanvas displayed when a particular point in
+ a box graph (iterative data) is clicked on.
+
+ :param trigger: The information from trigger when the data point is clicked
+ on.
+ :param graph: The data from the clicked point in the graph.
+ :param graph_layout: The layout of the HDRH latency graph.
+ :type trigger: Trigger
+ :type graph: dict
+ :type graph_layout: dict
+ :returns: The data to be displayed on the offcanvas and the information to
+ show the offcanvas.
+ :rtype: tuple(list, list, bool)
+ """
+
+ if trigger.idx == "tput":
+ idx = 0
+ elif trigger.idx == "bandwidth":
+ idx = 1
+ elif trigger.idx == "lat":
+ idx = len(data) - 1
+ else:
+ return list(), list(), False
+
+ try:
+ data = data[idx]["points"]
+ except (IndexError, KeyError, ValueError, TypeError):
+ return list(), list(), False
+
+ def _process_stats(data: list, param: str) -> list:
+ """Process statistical data provided by plot.ly box graph.
+
+ :param data: Statistical data provided by plot.ly box graph.
+ :param param: Parameter saying if the data come from "tput" or
+ "lat" graph.
+ :type data: list
+ :type param: str
+ :returns: Listo of tuples where the first value is the
+ statistic's name and the secont one it's value.
+ :rtype: list
+ """
+ if len(data) == 7:
+ stats = ("max", "upper fence", "q3", "median", "q1",
+ "lower fence", "min")
+ elif len(data) == 9:
+ stats = ("outlier", "max", "upper fence", "q3", "median",
+ "q1", "lower fence", "min", "outlier")
+ elif len(data) == 1:
+ if param == "lat":
+ stats = ("average latency at 50% PDR", )
+ elif param == "bandwidth":
+ stats = ("bandwidth", )
+ else:
+ stats = ("throughput", )
+ else:
+ return list()
+ unit = " [us]" if param == "lat" else str()
+ return [(f"{stat}{unit}", f"{value['y']:,.0f}")
+ for stat, value in zip(stats, data)]
+
+ customdata = data[0].get("customdata", dict())
+ datapoint = customdata.get("metadata", dict())
+ hdrh_data = customdata.get("hdrh", dict())
+
+ list_group_items = list()
+ for k, v in datapoint.items():
+ if k == "csit-ref":
+ if len(data) > 1:
+ continue
+ list_group_item = dbc.ListGroupItem([
+ dbc.Badge(k),
+ html.A(v, href=f"{C.URL_JENKINS}{v}", target="_blank")
+ ])
+ else:
+ list_group_item = dbc.ListGroupItem([dbc.Badge(k), v])
+ list_group_items.append(list_group_item)
+
+ graph = list()
+ if trigger.idx == "tput":
+ title = "Throughput"
+ elif trigger.idx == "bandwidth":
+ title = "Bandwidth"
+ elif trigger.idx == "lat":
+ title = "Latency"
+ if len(data) == 1:
+ if hdrh_data:
+ graph = [dbc.Card(
+ class_name="gy-2 p-0",
+ children=[
+ dbc.CardHeader(hdrh_data.pop("name")),
+ dbc.CardBody(dcc.Graph(
+ id="hdrh-latency-graph",
+ figure=graph_hdrh_latency(hdrh_data, graph_layout)
+ ))
+ ])
+ ]
+
+ for k, v in _process_stats(data, trigger.idx):
+ list_group_items.append(dbc.ListGroupItem([dbc.Badge(k), v]))
+
+ metadata = [
+ dbc.Card(
+ class_name="gy-2 p-0",
+ children=[
+ dbc.CardHeader(children=[
+ dcc.Clipboard(
+ target_id="tput-lat-metadata",
+ title="Copy",
+ style={"display": "inline-block"}
+ ),
+ title
+ ]),
+ dbc.CardBody(
+ dbc.ListGroup(list_group_items, flush=True),
+ id="tput-lat-metadata",
+ class_name="p-0"
+ )
+ ]
+ )
+ ]
+
+ return metadata, graph, True
Code Review / csit.git / blobdiff