data_iterative=data["iterative"]
)
+ from .coverage.coverage import init_coverage
+ app = init_coverage(
+ app,
+ data_coverage=data["coverage"]
+ )
+
return app
from numpy import mean, std
from copy import deepcopy
+
from ..utils.constants import Constants as C
from ..utils.utils import relative_change_stdev
--- /dev/null
+# 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:
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
--- /dev/null
+# 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:
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""Instantiate the Coverage Dash application.
+"""
+import dash
+import pandas as pd
+
+from ..utils.constants import Constants as C
+from .layout import Layout
+
+
+def init_coverage(
+ server,
+ data_coverage: pd.DataFrame
+ ) -> dash.Dash:
+ """Create a Plotly Dash dashboard.
+
+ :param server: Flask server.
+ :type server: Flask
+ :returns: Dash app server.
+ :rtype: Dash
+ """
+
+ dash_app = dash.Dash(
+ server=server,
+ routes_pathname_prefix=C.COVERAGE_ROUTES_PATHNAME_PREFIX,
+ external_stylesheets=C.EXTERNAL_STYLESHEETS,
+ title=C.COVERAGE_TITLE
+ )
+
+ layout = Layout(
+ app=dash_app,
+ data_coverage=data_coverage,
+ html_layout_file=C.HTML_LAYOUT_FILE
+ )
+ dash_app.index_string = layout.html_layout
+ dash_app.layout = layout.add_content()
+
+ return dash_app.server
--- /dev/null
+# 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:
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""Plotly Dash HTML layout override.
+"""
+
+
+import pandas as pd
+import dash_bootstrap_components as dbc
+
+from flask import Flask
+from dash import dcc
+from dash import html
+from dash import callback_context, no_update, ALL
+from dash import Input, Output, State
+from dash.exceptions import PreventUpdate
+from ast import literal_eval
+
+from ..utils.constants import Constants as C
+from ..utils.control_panel import ControlPanel
+from ..utils.trigger import Trigger
+from ..utils.utils import label, gen_new_url, generate_options
+from ..utils.url_processing import url_decode
+from .tables import coverage_tables, select_coverage_data
+
+
+# Control panel partameters and their default values.
+CP_PARAMS = {
+ "rls-val": str(),
+ "dut-opt": list(),
+ "dut-dis": True,
+ "dut-val": str(),
+ "dutver-opt": list(),
+ "dutver-dis": True,
+ "dutver-val": str(),
+ "phy-opt": list(),
+ "phy-dis": True,
+ "phy-val": str(),
+ "area-opt": list(),
+ "area-dis": True,
+ "area-val": str()
+}
+
+
+class Layout:
+ """The layout of the dash app and the callbacks.
+ """
+
+ def __init__(
+ self,
+ app: Flask,
+ data_coverage: pd.DataFrame,
+ html_layout_file: str
+ ) -> None:
+ """Initialization:
+ - save the input parameters,
+ - prepare data for the control panel,
+ - read HTML layout file,
+
+ :param app: Flask application running the dash application.
+ :param html_layout_file: Path and name of the file specifying the HTML
+ layout of the dash application.
+ :type app: Flask
+ :type html_layout_file: str
+ """
+
+ # Inputs
+ self._app = app
+ self._html_layout_file = html_layout_file
+ self._data = data_coverage
+
+ # Get structure of tests:
+ tbs = dict()
+ cols = ["job", "test_id", "dut_version", "release", ]
+ for _, row in self._data[cols].drop_duplicates().iterrows():
+ rls = row["release"]
+ lst_job = row["job"].split("-")
+ dut = lst_job[1]
+ d_ver = row["dut_version"]
+ tbed = "-".join(lst_job[-2:])
+ lst_test_id = row["test_id"].split(".")
+ if dut == "dpdk":
+ area = "dpdk"
+ else:
+ area = "-".join(lst_test_id[3:-2])
+ suite = lst_test_id[-2].replace("2n1l-", "").replace("1n1l-", "").\
+ replace("2n-", "")
+ test = lst_test_id[-1]
+ nic = suite.split("-")[0]
+ for drv in C.DRIVERS:
+ if drv in test:
+ driver = drv.replace("-", "_")
+ test = test.replace(f"{drv}-", "")
+ break
+ else:
+ driver = "dpdk"
+ infra = "-".join((tbed, nic, driver))
+
+ if tbs.get(rls, None) is None:
+ tbs[rls] = dict()
+ if tbs[rls].get(dut, None) is None:
+ tbs[rls][dut] = dict()
+ if tbs[rls][dut].get(d_ver, None) is None:
+ tbs[rls][dut][d_ver] = dict()
+ if tbs[rls][dut][d_ver].get(infra, None) is None:
+ tbs[rls][dut][d_ver][infra] = list()
+ if area not in tbs[rls][dut][d_ver][infra]:
+ tbs[rls][dut][d_ver][infra].append(area)
+
+ self._spec_tbs = tbs
+
+ # Read from files:
+ self._html_layout = str()
+
+ try:
+ with open(self._html_layout_file, "r") as file_read:
+ self._html_layout = file_read.read()
+ except IOError as err:
+ raise RuntimeError(
+ f"Not possible to open the file {self._html_layout_file}\n{err}"
+ )
+
+ # Callbacks:
+ if self._app is not None and hasattr(self, "callbacks"):
+ self.callbacks(self._app)
+
+ @property
+ def html_layout(self):
+ return self._html_layout
+
+ def add_content(self):
+ """Top level method which generated the web page.
+
+ It generates:
+ - Store for user input data,
+ - Navigation bar,
+ - Main area with control panel and ploting area.
+
+ If no HTML layout is provided, an error message is displayed instead.
+
+ :returns: The HTML div with the whole page.
+ :rtype: html.Div
+ """
+
+ if self.html_layout and self._spec_tbs:
+ return html.Div(
+ id="div-main",
+ className="small",
+ children=[
+ dbc.Row(
+ id="row-navbar",
+ class_name="g-0",
+ children=[
+ self._add_navbar()
+ ]
+ ),
+ dbc.Row(
+ id="row-main",
+ class_name="g-0",
+ children=[
+ dcc.Store(id="store-selected-tests"),
+ dcc.Store(id="store-control-panel"),
+ dcc.Location(id="url", refresh=False),
+ self._add_ctrl_col(),
+ self._add_plotting_col()
+ ]
+ )
+ ]
+ )
+ else:
+ return html.Div(
+ id="div-main-error",
+ children=[
+ dbc.Alert(
+ [
+ "An Error Occured"
+ ],
+ color="danger"
+ )
+ ]
+ )
+
+ def _add_navbar(self):
+ """Add nav element with navigation panel. It is placed on the top.
+
+ :returns: Navigation bar.
+ :rtype: dbc.NavbarSimple
+ """
+ return dbc.NavbarSimple(
+ id="navbarsimple-main",
+ children=[
+ dbc.NavItem(
+ dbc.NavLink(
+ C.COVERAGE_TITLE,
+ disabled=True,
+ external_link=True,
+ href="#"
+ )
+ )
+ ],
+ brand=C.BRAND,
+ brand_href="/",
+ brand_external_link=True,
+ class_name="p-2",
+ fluid=True
+ )
+
+ def _add_ctrl_col(self) -> dbc.Col:
+ """Add column with controls. It is placed on the left side.
+
+ :returns: Column with the control panel.
+ :rtype: dbc.Col
+ """
+ return dbc.Col([
+ html.Div(
+ children=self._add_ctrl_panel(),
+ className="sticky-top"
+ )
+ ])
+
+ def _add_plotting_col(self) -> dbc.Col:
+ """Add column with plots. It is placed on the right side.
+
+ :returns: Column with plots.
+ :rtype: dbc.Col
+ """
+ return dbc.Col(
+ id="col-plotting-area",
+ children=[
+ dbc.Spinner(
+ children=[
+ dbc.Row(
+ id="plotting-area",
+ class_name="g-0 p-0",
+ children=[
+ C.PLACEHOLDER
+ ]
+ )
+ ]
+ )
+ ],
+ width=9
+ )
+
+ def _add_ctrl_panel(self) -> list:
+ """Add control panel.
+
+ :returns: Control panel.
+ :rtype: list
+ """
+ return [
+ dbc.Row(
+ class_name="g-0 p-1",
+ children=[
+ dbc.InputGroup(
+ [
+ dbc.InputGroupText("CSIT Release"),
+ dbc.Select(
+ id={"type": "ctrl-dd", "index": "rls"},
+ placeholder="Select a Release...",
+ options=sorted(
+ [
+ {"label": k, "value": k} \
+ for k in self._spec_tbs.keys()
+ ],
+ key=lambda d: d["label"]
+ )
+ )
+ ],
+ size="sm"
+ )
+ ]
+ ),
+ dbc.Row(
+ class_name="g-0 p-1",
+ children=[
+ dbc.InputGroup(
+ [
+ dbc.InputGroupText("DUT"),
+ dbc.Select(
+ id={"type": "ctrl-dd", "index": "dut"},
+ placeholder="Select a Device under Test..."
+ )
+ ],
+ size="sm"
+ )
+ ]
+ ),
+ dbc.Row(
+ class_name="g-0 p-1",
+ children=[
+ dbc.InputGroup(
+ [
+ dbc.InputGroupText("DUT Version"),
+ dbc.Select(
+ id={"type": "ctrl-dd", "index": "dutver"},
+ placeholder=\
+ "Select a Version of Device under Test..."
+ )
+ ],
+ size="sm"
+ )
+ ]
+ ),
+ dbc.Row(
+ class_name="g-0 p-1",
+ children=[
+ dbc.InputGroup(
+ [
+ dbc.InputGroupText("Infra"),
+ dbc.Select(
+ id={"type": "ctrl-dd", "index": "phy"},
+ placeholder=\
+ "Select a Physical Test Bed Topology..."
+ )
+ ],
+ size="sm"
+ )
+ ]
+ ),
+ dbc.Row(
+ class_name="g-0 p-1",
+ children=[
+ dbc.InputGroup(
+ [
+ dbc.InputGroupText("Area"),
+ dbc.Select(
+ id={"type": "ctrl-dd", "index": "area"},
+ placeholder="Select an Area..."
+ )
+ ],
+ size="sm"
+ )
+ ]
+ )
+ ]
+
+ def _get_plotting_area(self, selected: dict, url: str) -> list:
+ """Generate the plotting area with all its content.
+
+ :param selected: Selected parameters of tests.
+ :param url: URL to be displayed in the modal window.
+ :type selected: dict
+ :type url: str
+ :returns: List of rows with elements to be displayed in the plotting
+ area.
+ :rtype: list
+ """
+ if not selected:
+ return C.PLACEHOLDER
+
+ return [
+ dbc.Row(
+ children=coverage_tables(self._data, selected),
+ class_name="g-0 p-0",
+ ),
+ dbc.Row(
+ children=C.PLACEHOLDER,
+ class_name="g-0 p-1"
+ ),
+ dbc.Row(
+ [
+ dbc.Col([html.Div(
+ [
+ dbc.Button(
+ id="plot-btn-url",
+ children="Show URL",
+ class_name="me-1",
+ color="info",
+ style={
+ "text-transform": "none",
+ "padding": "0rem 1rem"
+ }
+ ),
+ dbc.Modal(
+ [
+ dbc.ModalHeader(dbc.ModalTitle("URL")),
+ dbc.ModalBody(url)
+ ],
+ id="plot-mod-url",
+ size="xl",
+ is_open=False,
+ scrollable=True
+ ),
+ dbc.Button(
+ id="plot-btn-download",
+ children="Download Data",
+ class_name="me-1",
+ color="info",
+ style={
+ "text-transform": "none",
+ "padding": "0rem 1rem"
+ }
+ ),
+ dcc.Download(id="download-iterative-data")
+ ],
+ className=\
+ "d-grid gap-0 d-md-flex justify-content-md-end"
+ )])
+ ],
+ class_name="g-0 p-0"
+ ),
+ dbc.Row(
+ children=C.PLACEHOLDER,
+ class_name="g-0 p-1"
+ )
+ ]
+
+ def callbacks(self, app):
+ """Callbacks for the whole application.
+
+ :param app: The application.
+ :type app: Flask
+ """
+
+ @app.callback(
+ [
+ Output("store-control-panel", "data"),
+ Output("store-selected-tests", "data"),
+ Output("plotting-area", "children"),
+ Output({"type": "ctrl-dd", "index": "rls"}, "value"),
+ Output({"type": "ctrl-dd", "index": "dut"}, "options"),
+ Output({"type": "ctrl-dd", "index": "dut"}, "disabled"),
+ Output({"type": "ctrl-dd", "index": "dut"}, "value"),
+ Output({"type": "ctrl-dd", "index": "dutver"}, "options"),
+ Output({"type": "ctrl-dd", "index": "dutver"}, "disabled"),
+ Output({"type": "ctrl-dd", "index": "dutver"}, "value"),
+ Output({"type": "ctrl-dd", "index": "phy"}, "options"),
+ Output({"type": "ctrl-dd", "index": "phy"}, "disabled"),
+ Output({"type": "ctrl-dd", "index": "phy"}, "value"),
+ Output({"type": "ctrl-dd", "index": "area"}, "options"),
+ Output({"type": "ctrl-dd", "index": "area"}, "disabled"),
+ Output({"type": "ctrl-dd", "index": "area"}, "value"),
+ ],
+ [
+ State("store-control-panel", "data"),
+ State("store-selected-tests", "data")
+ ],
+ [
+ Input("url", "href"),
+ Input({"type": "ctrl-dd", "index": ALL}, "value")
+ ]
+ )
+ def _update_application(
+ control_panel: dict,
+ selected: dict,
+ href: str,
+ *_
+ ) -> tuple:
+ """Update the application when the event is detected.
+ """
+
+ ctrl_panel = ControlPanel(CP_PARAMS, control_panel)
+ plotting_area = no_update
+ on_draw = False
+ if selected is None:
+ selected = dict()
+
+ # Parse the url:
+ parsed_url = url_decode(href)
+ if parsed_url:
+ url_params = parsed_url["params"]
+ else:
+ url_params = None
+
+ trigger = Trigger(callback_context.triggered)
+
+ if trigger.type == "url" and url_params:
+ try:
+ selected = literal_eval(url_params["selection"][0])
+ except (KeyError, IndexError):
+ pass
+ if selected:
+ ctrl_panel.set({
+ "rls-val": selected["rls"],
+ "dut-val": selected["dut"],
+ "dut-opt": generate_options(
+ self._spec_tbs[selected["rls"]].keys()
+ ),
+ "dut-dis": False,
+ "dutver-val": selected["dutver"],
+ "dutver-opt": generate_options(
+ self._spec_tbs[selected["rls"]]\
+ [selected["dut"]].keys()
+ ),
+ "dutver-dis": False,
+ "phy-val": selected["phy"],
+ "phy-opt": generate_options(
+ self._spec_tbs[selected["rls"]][selected["dut"]]\
+ [selected["dutver"]].keys()
+ ),
+ "phy-dis": False,
+ "area-val": selected["area"],
+ "area-opt": [
+ {"label": label(v), "value": v} for v in sorted(
+ self._spec_tbs[selected["rls"]]\
+ [selected["dut"]][selected["dutver"]]\
+ [selected["phy"]]
+ )
+ ],
+ "area-dis": False
+ })
+ on_draw = True
+ elif trigger.type == "ctrl-dd":
+ if trigger.idx == "rls":
+ try:
+ options = generate_options(
+ self._spec_tbs[trigger.value].keys()
+ )
+ disabled = False
+ except KeyError:
+ options = list()
+ disabled = True
+ ctrl_panel.set({
+ "rls-val": trigger.value,
+ "dut-val": str(),
+ "dut-opt": options,
+ "dut-dis": disabled,
+ "dutver-val": str(),
+ "dutver-opt": list(),
+ "dutver-dis": True,
+ "phy-val": str(),
+ "phy-opt": list(),
+ "phy-dis": True,
+ "area-val": str(),
+ "area-opt": list(),
+ "area-dis": True
+ })
+ elif trigger.idx == "dut":
+ try:
+ rls = ctrl_panel.get("rls-val")
+ dut = self._spec_tbs[rls][trigger.value]
+ options = generate_options(dut.keys())
+ disabled = False
+ except KeyError:
+ options = list()
+ disabled = True
+ ctrl_panel.set({
+ "dut-val": trigger.value,
+ "dutver-val": str(),
+ "dutver-opt": options,
+ "dutver-dis": disabled,
+ "phy-val": str(),
+ "phy-opt": list(),
+ "phy-dis": True,
+ "area-val": str(),
+ "area-opt": list(),
+ "area-dis": True
+ })
+ elif trigger.idx == "dutver":
+ try:
+ rls = ctrl_panel.get("rls-val")
+ dut = ctrl_panel.get("dut-val")
+ dutver = self._spec_tbs[rls][dut][trigger.value]
+ options = generate_options(dutver.keys())
+ disabled = False
+ except KeyError:
+ options = list()
+ disabled = True
+ ctrl_panel.set({
+ "dutver-val": trigger.value,
+ "phy-val": str(),
+ "phy-opt": options,
+ "phy-dis": disabled,
+ "area-val": str(),
+ "area-opt": list(),
+ "area-dis": True
+ })
+ elif trigger.idx == "phy":
+ try:
+ rls = ctrl_panel.get("rls-val")
+ dut = ctrl_panel.get("dut-val")
+ dutver = ctrl_panel.get("dutver-val")
+ phy = self._spec_tbs[rls][dut][dutver][trigger.value]
+ options = [
+ {"label": label(v), "value": v} for v in sorted(phy)
+ ]
+ disabled = False
+ except KeyError:
+ options = list()
+ disabled = True
+ ctrl_panel.set({
+ "phy-val": trigger.value,
+ "area-val": str(),
+ "area-opt": options,
+ "area-dis": disabled
+ })
+ elif trigger.idx == "area":
+ ctrl_panel.set({"area-val": trigger.value})
+ selected = {
+ "rls": ctrl_panel.get("rls-val"),
+ "dut": ctrl_panel.get("dut-val"),
+ "dutver": ctrl_panel.get("dutver-val"),
+ "phy": ctrl_panel.get("phy-val"),
+ "area": ctrl_panel.get("area-val"),
+ }
+ on_draw = True
+
+ if on_draw:
+ if selected:
+ plotting_area = self._get_plotting_area(
+ selected,
+ gen_new_url(parsed_url, {"selection": selected})
+ )
+ else:
+ plotting_area = C.PLACEHOLDER
+ selected = dict()
+
+ ret_val = [
+ ctrl_panel.panel,
+ selected,
+ plotting_area,
+ ]
+ ret_val.extend(ctrl_panel.values)
+ return ret_val
+
+ @app.callback(
+ Output("plot-mod-url", "is_open"),
+ [Input("plot-btn-url", "n_clicks")],
+ [State("plot-mod-url", "is_open")],
+ )
+ def toggle_plot_mod_url(n, is_open):
+ """Toggle the modal window with url.
+ """
+ if n:
+ return not is_open
+ return is_open
+
+ @app.callback(
+ Output("download-iterative-data", "data"),
+ State("store-selected-tests", "data"),
+ Input("plot-btn-download", "n_clicks"),
+ prevent_initial_call=True
+ )
+ def _download_coverage_data(selection, _):
+ """Download the data
+
+ :param selection: List of tests selected by user stored in the
+ browser.
+ :type selection: dict
+ :returns: dict of data frame content (base64 encoded) and meta data
+ used by the Download component.
+ :rtype: dict
+ """
+
+ if not selection:
+ raise PreventUpdate
+
+ df = select_coverage_data(self._data, selection, csv=True)
+
+ return dcc.send_data_frame(df.to_csv, C.COVERAGE_DOWNLOAD_FILE_NAME)
--- /dev/null
+# 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:
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""The coverage data tables.
+"""
+
+import hdrh.histogram
+import hdrh.codec
+import pandas as pd
+import dash_bootstrap_components as dbc
+
+from dash import dash_table
+from dash.dash_table.Format import Format, Scheme
+
+from ..utils.constants import Constants as C
+
+
+def select_coverage_data(
+ data: pd.DataFrame,
+ selected: dict,
+ csv: bool=False
+ ) -> list:
+ """Select coverage data for the tables and generate tables as pandas data
+ frames.
+
+ :param data: Coverage data.
+ :param selected: Dictionary with user selection.
+ :param csv: If True, pandas data frame with selected coverage data is
+ returned for "Download Data" feature.
+ :type data: pandas.DataFrame
+ :type selected: dict
+ :type csv: bool
+ :returns: List of tuples with suite name (str) and data (pandas dataframe)
+ or pandas dataframe if csv is True.
+ :rtype: list[tuple[str, pandas.DataFrame], ] or pandas.DataFrame
+ """
+
+ l_data = list()
+
+ # Filter data selected by the user.
+ phy = selected["phy"].split("-")
+ if len(phy) == 4:
+ topo, arch, nic, drv = phy
+ drv = "" if drv == "dpdk" else drv.replace("_", "-")
+ else:
+ return l_data
+
+ df = pd.DataFrame(data.loc[(
+ (data["passed"] == True) &
+ (data["dut_type"] == selected["dut"]) &
+ (data["dut_version"] == selected["dutver"]) &
+ (data["release"] == selected["rls"])
+ )])
+ df = df[
+ (df.job.str.endswith(f"{topo}-{arch}")) &
+ (df.test_id.str.contains(
+ f"^.*\.{selected['area']}\..*{nic}.*{drv}.*$",
+ regex=True
+ ))
+ ]
+ if drv == "dpdk":
+ for driver in C.DRIVERS:
+ df.drop(
+ df[df.test_id.str.contains(f"-{driver}-")].index,
+ inplace=True
+ )
+
+ # Prepare the coverage data
+ def _latency(hdrh_string: str, percentile: float) -> int:
+ """Get latency from HDRH string for given percentile.
+
+ :param hdrh_string: Encoded HDRH string.
+ :param percentile: Given percentile.
+ :type hdrh_string: str
+ :type percentile: float
+ :returns: The latency value for the given percentile from the encoded
+ HDRH string.
+ :rtype: int
+ """
+ try:
+ hdr_lat = hdrh.histogram.HdrHistogram.decode(hdrh_string)
+ return hdr_lat.get_value_at_percentile(percentile)
+ except (hdrh.codec.HdrLengthException, TypeError):
+ return None
+
+ def _get_suite(test_id: str) -> str:
+ """Get the suite name from the test ID.
+ """
+ return test_id.split(".")[-2].replace("2n1l-", "").\
+ replace("1n1l-", "").replace("2n-", "").replace("-ndrpdr", "")
+
+ def _get_test(test_id: str) -> str:
+ """Get the test name from the test ID.
+ """
+ return test_id.split(".")[-1].replace("-ndrpdr", "")
+
+ cov = pd.DataFrame()
+ cov["suite"] = df.apply(lambda row: _get_suite(row["test_id"]), axis=1)
+ cov["Test Name"] = df.apply(lambda row: _get_test(row["test_id"]), axis=1)
+ cov["Throughput_Unit"] = df["result_pdr_lower_rate_unit"]
+ cov["Throughput_NDR"] = df.apply(
+ lambda row: row["result_ndr_lower_rate_value"] / 1e6, axis=1
+ )
+ cov["Throughput_NDR_Mbps"] = df.apply(
+ lambda row: row["result_ndr_lower_bandwidth_value"] /1e9, axis=1
+ )
+ cov["Throughput_PDR"] = \
+ df.apply(lambda row: row["result_pdr_lower_rate_value"] / 1e6, axis=1)
+ cov["Throughput_PDR_Mbps"] = df.apply(
+ lambda row: row["result_pdr_lower_bandwidth_value"] /1e9, axis=1
+ )
+ cov["Latency Forward [us]_10% PDR_P50"] = df.apply(
+ lambda row: _latency(row["result_latency_forward_pdr_10_hdrh"], 50.0),
+ axis=1
+ )
+ cov["Latency Forward [us]_10% PDR_P90"] = df.apply(
+ lambda row: _latency(row["result_latency_forward_pdr_10_hdrh"], 90.0),
+ axis=1
+ )
+ cov["Latency Forward [us]_10% PDR_P99"] = df.apply(
+ lambda row: _latency(row["result_latency_forward_pdr_10_hdrh"], 99.0),
+ axis=1
+ )
+ cov["Latency Forward [us]_50% PDR_P50"] = df.apply(
+ lambda row: _latency(row["result_latency_forward_pdr_50_hdrh"], 50.0),
+ axis=1
+ )
+ cov["Latency Forward [us]_50% PDR_P90"] = df.apply(
+ lambda row: _latency(row["result_latency_forward_pdr_50_hdrh"], 90.0),
+ axis=1
+ )
+ cov["Latency Forward [us]_50% PDR_P99"] = df.apply(
+ lambda row: _latency(row["result_latency_forward_pdr_50_hdrh"], 99.0),
+ axis=1
+ )
+ cov["Latency Forward [us]_90% PDR_P50"] = df.apply(
+ lambda row: _latency(row["result_latency_forward_pdr_90_hdrh"], 50.0),
+ axis=1
+ )
+ cov["Latency Forward [us]_90% PDR_P90"] = df.apply(
+ lambda row: _latency(row["result_latency_forward_pdr_90_hdrh"], 90.0),
+ axis=1
+ )
+ cov["Latency Forward [us]_90% PDR_P99"] = df.apply(
+ lambda row: _latency(row["result_latency_forward_pdr_90_hdrh"], 99.0),
+ axis=1
+ )
+ cov["Latency Reverse [us]_10% PDR_P50"] = df.apply(
+ lambda row: _latency(row["result_latency_reverse_pdr_10_hdrh"], 50.0),
+ axis=1
+ )
+ cov["Latency Reverse [us]_10% PDR_P90"] = df.apply(
+ lambda row: _latency(row["result_latency_reverse_pdr_10_hdrh"], 90.0),
+ axis=1
+ )
+ cov["Latency Reverse [us]_10% PDR_P99"] = df.apply(
+ lambda row: _latency(row["result_latency_reverse_pdr_10_hdrh"], 99.0),
+ axis=1
+ )
+ cov["Latency Reverse [us]_50% PDR_P50"] = df.apply(
+ lambda row: _latency(row["result_latency_reverse_pdr_50_hdrh"], 50.0),
+ axis=1
+ )
+ cov["Latency Reverse [us]_50% PDR_P90"] = df.apply(
+ lambda row: _latency(row["result_latency_reverse_pdr_50_hdrh"], 90.0),
+ axis=1
+ )
+ cov["Latency Reverse [us]_50% PDR_P99"] = df.apply(
+ lambda row: _latency(row["result_latency_reverse_pdr_50_hdrh"], 99.0),
+ axis=1
+ )
+ cov["Latency Reverse [us]_90% PDR_P50"] = df.apply(
+ lambda row: _latency(row["result_latency_reverse_pdr_90_hdrh"], 50.0),
+ axis=1
+ )
+ cov["Latency Reverse [us]_90% PDR_P90"] = df.apply(
+ lambda row: _latency(row["result_latency_reverse_pdr_90_hdrh"], 90.0),
+ axis=1
+ )
+ cov["Latency Reverse [us]_90% PDR_P99"] = df.apply(
+ lambda row: _latency(row["result_latency_reverse_pdr_90_hdrh"], 99.0),
+ axis=1
+ )
+
+ if csv:
+ return cov
+
+ # Split data into tabels depending on the test suite.
+ for suite in cov["suite"].unique().tolist():
+ df_suite = pd.DataFrame(cov.loc[(cov["suite"] == suite)])
+ unit = df_suite["Throughput_Unit"].tolist()[0]
+ df_suite.rename(
+ columns={
+ "Throughput_NDR": f"Throughput_NDR_M{unit}",
+ "Throughput_PDR": f"Throughput_PDR_M{unit}"
+ },
+ inplace=True
+ )
+ df_suite.drop(["suite", "Throughput_Unit"], axis=1, inplace=True)
+ l_data.append((suite, df_suite, ))
+ return l_data
+
+
+def coverage_tables(data: pd.DataFrame, selected: dict) -> list:
+ """Generate an accordion with coverage tables.
+
+ :param data: Coverage data.
+ :param selected: Dictionary with user selection.
+ :type data: pandas.DataFrame
+ :type selected: dict
+ :returns: Accordion with suite names (titles) and tables.
+ :rtype: dash_bootstrap_components.Accordion
+ """
+
+ accordion_items = list()
+ for suite, cov_data in select_coverage_data(data, selected):
+ cols = list()
+ for idx, col in enumerate(cov_data.columns):
+ if idx == 0:
+ cols.append({
+ "name": ["", "", col],
+ "id": col,
+ "deletable": False,
+ "selectable": False,
+ "type": "text"
+ })
+ elif idx < 5:
+ cols.append({
+ "name": col.split("_"),
+ "id": col,
+ "deletable": False,
+ "selectable": False,
+ "type": "numeric",
+ "format": Format(precision=2, scheme=Scheme.fixed)
+ })
+ else:
+ cols.append({
+ "name": col.split("_"),
+ "id": col,
+ "deletable": False,
+ "selectable": False,
+ "type": "numeric",
+ "format": Format(precision=0, scheme=Scheme.fixed)
+ })
+
+ accordion_items.append(
+ dbc.AccordionItem(
+ title=suite,
+ children=dash_table.DataTable(
+ columns=cols,
+ data=cov_data.to_dict("records"),
+ merge_duplicate_headers=True,
+ editable=True,
+ filter_action="none",
+ sort_action="native",
+ sort_mode="multi",
+ selected_columns=[],
+ selected_rows=[],
+ page_action="none",
+ style_cell={"textAlign": "right"},
+ style_cell_conditional=[{
+ "if": {"column_id": "Test Name"},
+ "textAlign": "left"
+ }]
+ )
+ )
+ )
+
+ return dbc.Accordion(
+ children=accordion_items,
+ class_name="gy-2 p-0",
+ start_collapsed=True,
+ always_open=True
+ )
self._data_spec = list()
# Data frame to keep the data:
- self._data = pd.DataFrame()
+ self._data = {
+ "statistics": pd.DataFrame(),
+ "trending": pd.DataFrame(),
+ "iterative": pd.DataFrame(),
+ "coverage": pd.DataFrame()
+ }
# Read from files:
try:
def data(self):
return self._data
- def _get_list_of_files(self,
- path,
- last_modified_begin=None,
- last_modified_end=None,
- days=None) -> list:
+ @staticmethod
+ def _get_list_of_files(
+ path,
+ last_modified_begin=None,
+ last_modified_end=None,
+ days=None
+ ) -> list:
"""Get list of interested files stored in S3 compatible storage and
returns it.
return file_list
+ @staticmethod
def _create_dataframe_from_parquet(
- self,
path, partition_filter=None,
columns=None,
- categories=list(),
+ categories=None,
validate_schema=False,
last_modified_begin=None,
last_modified_end=None,
:returns: Pandas DataFrame or None if DataFrame cannot be fetched.
:rtype: DataFrame
"""
- df = None
+ df = pd.DataFrame()
start = time()
if days:
last_modified_begin = datetime.now(tz=UTC) - timedelta(days=days)
use_threads=True,
dataset=True,
columns=columns,
- # categories=categories,
+ categories=categories,
partition_filter=partition_filter,
last_modified_begin=last_modified_begin,
last_modified_end=last_modified_end
f"\nCreation of dataframe {path} took: {time() - start}\n"
)
except NoFilesFound as err:
- logging.error(f"No parquets found.\n{err}")
+ logging.error(
+ f"No parquets found in specified time period.\n"
+ f"Nr of days: {days}\n"
+ f"last_modified_begin: {last_modified_begin}\n"
+ f"{err}"
+ )
except EmptyDataFrame as err:
- logging.error(f"No data.\n{err}")
+ logging.error(
+ f"No data in parquets in specified time period.\n"
+ f"Nr of days: {days}\n"
+ f"last_modified_begin: {last_modified_begin}\n"
+ f"{err}"
+ )
return df
:rtype: dict(str: pandas.DataFrame)
"""
- self._data = dict()
- self._data["trending"] = pd.DataFrame()
- self._data["iterative"] = pd.DataFrame()
lst_trending = list()
lst_iterative = list()
+ lst_coverage = list()
for data_set in self._data_spec:
logging.info(
partition_filter = lambda part: True \
if part[data_set["partition"]] == data_set["partition_name"] \
else False
-
- data = self._create_dataframe_from_parquet(
+ if data_set["data_type"] in ("trending", "statistics"):
+ time_period = days
+ else:
+ time_period = None
+ data = Data._create_dataframe_from_parquet(
path=data_set["path"],
partition_filter=partition_filter,
- columns=data_set.get("columns", list()),
- categories=data_set.get("categories", list()),
- days=None if data_set["data_type"] == "iterative" else days
+ columns=data_set.get("columns", None),
+ categories=data_set.get("categories", None),
+ days=time_period
)
if data_set["data_type"] == "statistics":
data["release"] = data_set["release"]
data["release"] = data["release"].astype("category")
lst_iterative.append(data)
+ elif data_set["data_type"] == "coverage":
+ data["release"] = data_set["release"]
+ data["release"] = data["release"].astype("category")
+ lst_coverage.append(data)
else:
raise NotImplementedError(
f"The data type {data_set['data_type']} is not implemented."
ignore_index=True,
copy=False
)
+ self._data["coverage"] = pd.concat(
+ lst_coverage,
+ ignore_index=True,
+ copy=False
+ )
for key in self._data.keys():
logging.info(
- passed
- telemetry
- test_id
- - test_type
- version
categories:
- job
- passed
- telemetry
- test_id
- - test_type
- version
categories:
- job
- build
- dut_type
- dut_version
+ - tg_type
+ - version
+- data_type: coverage
+ partition: test_type
+ partition_name: ndrpdr
+ release: rls2302
+ path: s3://fdio-docs-s3-cloudfront-index/csit/parquet/coverage_rls2302
+ columns:
+ - job
+ - build
+ - dut_type
+ - dut_version
+ - tg_type
+ - hosts
+ - start_time
+ - passed
+ - test_id
- version
+ - result_pdr_lower_rate_unit
+ - result_pdr_lower_rate_value
+ - result_ndr_lower_rate_value
+ - result_pdr_lower_bandwidth_value
+ - result_ndr_lower_bandwidth_value
+ - result_latency_reverse_pdr_90_hdrh
+ - result_latency_reverse_pdr_50_hdrh
+ - result_latency_reverse_pdr_10_hdrh
+ - result_latency_forward_pdr_90_hdrh
+ - result_latency_forward_pdr_50_hdrh
+ - result_latency_forward_pdr_10_hdrh
categories:
- job
- build
- dut_version
- tg_type
- version
+# - data_type: coverage
+# partition: test_type
+# partition_name: device
+# release: rls2302
+# path: s3://fdio-docs-s3-cloudfront-index/csit/parquet/coverage_rls2302
+# columns:
+# - job
+# - build
+# - dut_type
+# - dut_version
+# - start_time
+# - passed
+# - test_id
+# - version
+# categories:
+# - job
+# - build
+# - dut_type
+# - dut_version
+# - version
report_title=C.REPORT_TITLE,
comp_title=C.COMP_TITLE,
stats_title=C.STATS_TITLE,
- news_title=C.NEWS_TITLE
+ news_title=C.NEWS_TITLE,
+ cov_title=C.COVERAGE_TITLE
)
{{ comp_title }}
</a>
</p>
+ <p>
+ <p>
+ <a href="/coverage/" class="btn btn-primary fw-bold w-25">
+ {{ cov_title }}
+ </a>
+ </p>
<p>
<a href="/stats/" class="btn btn-primary fw-bold w-25">
{{ stats_title }}
"container_memif": "LXC/DRC Container Memif",
"crypto": "IPSec IPv4 Routing",
"ip4": "IPv4 Routing",
- "ip6": "IPv6 Routing",
"ip4_tunnels": "IPv4 Tunnels",
+ "ip6": "IPv6 Routing",
+ "ip6_tunnels": "IPv6 Tunnels",
"l2": "L2 Ethernet Switching",
+ "lb": "Load Balancer",
"srv6": "SRv6 Routing",
"vm_vhost": "VMs vhost-user",
"nfv_density-dcr_memif-chain_ipsec": "CNF Service Chains Routing IPSec",
# Default name of downloaded file with selected data.
TREND_DOWNLOAD_FILE_NAME = "trending_data.csv"
+
+ ############################################################################
+ # Coverage data.
+
+ # The title.
+ COVERAGE_TITLE = "Per Release Coverage Data"
+
+ # The pathname prefix for the application.
+ COVERAGE_ROUTES_PATHNAME_PREFIX = "/coverage/"
+
+ # Default name of downloaded file with selected data.
+ COVERAGE_DOWNLOAD_FILE_NAME = "coverage_data.csv"
+
+ ############################################################################
\ No newline at end of file
Code Review / csit.git / commitdiff