fix(cdash): Rename

Signed-off-by: pmikus <peter.mikus@protonmail.ch>
Change-Id: Ia6dff2674a28b42ebfbe91230587f1e175ae1137

4 files changed, 743 insertions, 0 deletions

diff --git a/csit.infra.dash/app/cdash/news/__init__.py b/csit.infra.dash/app/cdash/news/__init__.py
new file mode 100644
index 0000000000..5692432123
--- /dev/null
+++ b/csit.infra.dash/app/cdash/news/__init__.py
@@ -0,0 +1,12 @@
+# Copyright (c) 2022 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.
diff --git a/csit.infra.dash/app/cdash/news/layout.py b/csit.infra.dash/app/cdash/news/layout.py
new file mode 100644
index 0000000000..dfe6eba67a
--- /dev/null
+++ b/csit.infra.dash/app/cdash/news/layout.py
@@ -0,0 +1,508 @@
+# Copyright (c) 2022 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 logging
+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
+from dash import Input, Output
+from yaml import load, FullLoader, YAMLError
+
+from ..data.data import Data
+from ..utils.constants import Constants as C
+from ..utils.utils import classify_anomalies, show_tooltip, gen_new_url
+from ..utils.url_processing import url_decode
+from ..data.data import Data
+from .tables import table_summary
+
+
+class Layout:
+    """The layout of the dash app and the callbacks.
+    """
+
+    def __init__(self, app: Flask, html_layout_file: str, data_spec_file: str,
+        tooltip_file: str) -> None:
+        """Initialization:
+        - save the input parameters,
+        - read and pre-process the data,
+        - prepare data for the control panel,
+        - read HTML layout file,
+        - read tooltips from the tooltip 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.
+        :param data_spec_file: Path and name of the file specifying the data to
+            be read from parquets for this application.
+        :param tooltip_file: Path and name of the yaml file specifying the
+            tooltips.
+        :type app: Flask
+        :type html_layout_file: str
+        :type data_spec_file: str
+        :type tooltip_file: str
+        """
+
+        # Inputs
+        self._app = app
+        self._html_layout_file = html_layout_file
+        self._data_spec_file = data_spec_file
+        self._tooltip_file = tooltip_file
+
+        # Read the data:
+        data_stats, data_mrr, data_ndrpdr = Data(
+            data_spec_file=self._data_spec_file,
+            debug=True
+        ).read_stats(days=C.NEWS_TIME_PERIOD)
+
+        df_tst_info = pd.concat([data_mrr, data_ndrpdr], ignore_index=True)
+
+        # Prepare information for the control panel:
+        self._jobs = sorted(list(df_tst_info["job"].unique()))
+        d_job_info = {
+            "job": list(),
+            "dut": list(),
+            "ttype": list(),
+            "cadence": list(),
+            "tbed": list()
+        }
+        for job in self._jobs:
+            lst_job = job.split("-")
+            d_job_info["job"].append(job)
+            d_job_info["dut"].append(lst_job[1])
+            d_job_info["ttype"].append(lst_job[3])
+            d_job_info["cadence"].append(lst_job[4])
+            d_job_info["tbed"].append("-".join(lst_job[-2:]))
+        self.job_info = pd.DataFrame.from_dict(d_job_info)
+
+        # Pre-process the data:
+
+        def _create_test_name(test: str) -> str:
+            lst_tst = test.split(".")
+            suite = lst_tst[-2].replace("2n1l-", "").replace("1n1l-", "").\
+                replace("2n-", "")
+            return f"{suite.split('-')[0]}-{lst_tst[-1]}"
+
+        def _get_rindex(array: list, itm: any) -> int:
+            return len(array) - 1 - array[::-1].index(itm)
+
+        tst_info = {
+            "job": list(),
+            "build": list(),
+            "start": list(),
+            "dut_type": list(),
+            "dut_version": list(),
+            "hosts": list(),
+            "failed": list(),
+            "regressions": list(),
+            "progressions": list()
+        }
+        for job in self._jobs:
+            # Create lists of failed tests:
+            df_job = df_tst_info.loc[(df_tst_info["job"] == job)]
+            last_build = str(max(pd.to_numeric(df_job["build"].unique())))
+            df_build = df_job.loc[(df_job["build"] == last_build)]
+            tst_info["job"].append(job)
+            tst_info["build"].append(last_build)
+            tst_info["start"].append(data_stats.loc[
+                (data_stats["job"] == job) &
+                (data_stats["build"] == last_build)
+            ]["start_time"].iloc[-1].strftime('%Y-%m-%d %H:%M'))
+            tst_info["dut_type"].append(df_build["dut_type"].iloc[-1])
+            tst_info["dut_version"].append(df_build["dut_version"].iloc[-1])
+            tst_info["hosts"].append(df_build["hosts"].iloc[-1])
+            failed_tests = df_build.loc[(df_build["passed"] == False)]\
+                ["test_id"].to_list()
+            l_failed = list()
+            try:
+                for tst in failed_tests:
+                    l_failed.append(_create_test_name(tst))
+            except KeyError:
+                l_failed = list()
+            tst_info["failed"].append(sorted(l_failed))
+
+            # Create lists of regressions and progressions:
+            l_reg = list()
+            l_prog = list()
+
+            tests = df_job["test_id"].unique()
+            for test in tests:
+                tst_data = df_job.loc[df_job["test_id"] == test].sort_values(
+                    by="start_time", ignore_index=True)
+                x_axis = tst_data["start_time"].tolist()
+                if "-ndrpdr" in test:
+                    tst_data = tst_data.dropna(
+                        subset=["result_pdr_lower_rate_value", ]
+                    )
+                    if tst_data.empty:
+                        continue
+                    try:
+                        anomalies, _, _ = classify_anomalies({
+                            k: v for k, v in zip(
+                                x_axis,
+                                tst_data["result_ndr_lower_rate_value"].tolist()
+                            )
+                        })
+                    except ValueError:
+                        continue
+                    if "progression" in anomalies:
+                        l_prog.append((
+                            _create_test_name(test).replace("-ndrpdr", "-ndr"),
+                            x_axis[_get_rindex(anomalies, "progression")]
+                        ))
+                    if "regression" in anomalies:
+                        l_reg.append((
+                            _create_test_name(test).replace("-ndrpdr", "-ndr"),
+                            x_axis[_get_rindex(anomalies, "regression")]
+                        ))
+                    try:
+                        anomalies, _, _ = classify_anomalies({
+                            k: v for k, v in zip(
+                                x_axis,
+                                tst_data["result_pdr_lower_rate_value"].tolist()
+                            )
+                        })
+                    except ValueError:
+                        continue
+                    if "progression" in anomalies:
+                        l_prog.append((
+                            _create_test_name(test).replace("-ndrpdr", "-pdr"),
+                            x_axis[_get_rindex(anomalies, "progression")]
+                        ))
+                    if "regression" in anomalies:
+                        l_reg.append((
+                            _create_test_name(test).replace("-ndrpdr", "-pdr"),
+                            x_axis[_get_rindex(anomalies, "regression")]
+                        ))
+                else:  # mrr
+                    tst_data = tst_data.dropna(
+                        subset=["result_receive_rate_rate_avg", ]
+                    )
+                    if tst_data.empty:
+                        continue
+                    try:
+                        anomalies, _, _ = classify_anomalies({
+                            k: v for k, v in zip(
+                                x_axis,
+                                tst_data["result_receive_rate_rate_avg"].\
+                                    tolist()
+                            )
+                        })
+                    except ValueError:
+                        continue
+                    if "progression" in anomalies:
+                        l_prog.append((
+                            _create_test_name(test),
+                            x_axis[_get_rindex(anomalies, "progression")]
+                        ))
+                    if "regression" in anomalies:
+                        l_reg.append((
+                            _create_test_name(test),
+                            x_axis[_get_rindex(anomalies, "regression")]
+                        ))
+
+            tst_info["regressions"].append(
+                sorted(l_reg, key=lambda k: k[1], reverse=True))
+            tst_info["progressions"].append(
+                sorted(l_prog, key=lambda k: k[1], reverse=True))
+
+        self._data = pd.DataFrame.from_dict(tst_info)
+
+        # Read from files:
+        self._html_layout = str()
+        self._tooltips = dict()
+
+        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}"
+            )
+
+        try:
+            with open(self._tooltip_file, "r") as file_read:
+                self._tooltips = load(file_read, Loader=FullLoader)
+        except IOError as err:
+            logging.warning(
+                f"Not possible to open the file {self._tooltip_file}\n{err}"
+            )
+        except YAMLError as err:
+            logging.warning(
+                f"An error occurred while parsing the specification file "
+                f"{self._tooltip_file}\n{err}"
+            )
+
+        self._default_period = C.NEWS_SHORT
+        self._default_active = (False, True, False)
+        self._default_table = \
+            table_summary(self._data, self._jobs, self._default_period)
+
+        # Callbacks:
+        if self._app is not None and hasattr(self, 'callbacks'):
+            self.callbacks(self._app)
+
+    @property
+    def html_layout(self) -> dict:
+        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:
+            return html.Div(
+                id="div-main",
+                className="small",
+                children=[
+                    dcc.Location(id="url", refresh=False),
+                    dbc.Row(
+                        id="row-navbar",
+                        class_name="g-0",
+                        children=[
+                            self._add_navbar(),
+                        ]
+                    ),
+                    dbc.Row(
+                        id="row-main",
+                        class_name="g-0",
+                        children=[
+                            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.NEWS_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 control panel. 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 tables. It is placed on the right side.
+
+        :returns: Column with tables.
+        :rtype: dbc.Col
+        """
+
+        return dbc.Col(
+            id="col-plotting-area",
+            children=[
+                dcc.Loading(
+                    children=[
+                        dbc.Row(  # Failed tests
+                            id="row-table",
+                            class_name="g-0 p-2",
+                            children=self._default_table
+                        ),
+                        dbc.Row(
+                            class_name="g-0 p-2",
+                            align="center",
+                            justify="start",
+                            children=[
+                                dbc.InputGroup(
+                                    class_name="me-1",
+                                    children=[
+                                        dbc.InputGroupText(
+                                            style=C.URL_STYLE,
+                                            children=show_tooltip(
+                                                self._tooltips,
+                                                "help-url", "URL",
+                                                "input-url"
+                                            )
+                                        ),
+                                        dbc.Input(
+                                            id="input-url",
+                                            readonly=True,
+                                            type="url",
+                                            style=C.URL_STYLE,
+                                            value=""
+                                        )
+                                    ]
+                                )
+                            ]
+                        )
+                    ]
+                )
+            ],
+            width=9,
+        )
+
+    def _add_ctrl_panel(self) -> dbc.Row:
+        """Add control panel.
+
+        :returns: Control panel.
+        :rtype: dbc.Row
+        """
+        return [
+            dbc.Label(
+                class_name="g-0 p-1",
+                children=show_tooltip(self._tooltips,
+                    "help-summary-period", "Window")
+            ),
+            dbc.Row(
+                class_name="g-0 p-1",
+                children=[
+                    dbc.ButtonGroup(
+                        id="bg-time-period",
+                        children=[
+                            dbc.Button(
+                                id="period-last",
+                                children="Last Run",
+                                className="me-1",
+                                outline=True,
+                                color="info"
+                            ),
+                            dbc.Button(
+                                id="period-short",
+                                children=f"Last {C.NEWS_SHORT} Runs",
+                                className="me-1",
+                                outline=True,
+                                active=True,
+                                color="info"
+                            ),
+                            dbc.Button(
+                                id="period-long",
+                                children="All Runs",
+                                className="me-1",
+                                outline=True,
+                                color="info"
+                            )
+                        ]
+                    )
+                ]
+            )
+        ]
+
+    def callbacks(self, app):
+        """Callbacks for the whole application.
+
+        :param app: The application.
+        :type app: Flask
+        """
+
+        @app.callback(
+            Output("row-table", "children"),
+            Output("input-url", "value"),
+            Output("period-last", "active"),
+            Output("period-short", "active"),
+            Output("period-long", "active"),
+            Input("period-last", "n_clicks"),
+            Input("period-short", "n_clicks"),
+            Input("period-long", "n_clicks"),
+            Input("url", "href")
+        )
+        def _update_application(btn_last: int, btn_short: int, btn_long: int,
+            href: str) -> tuple:
+            """Update the application when the event is detected.
+
+            :returns: New values for web page elements.
+            :rtype: tuple
+            """
+
+            _, _, _ = btn_last, btn_short, btn_long
+
+            periods = {
+                "period-last": C.NEWS_LAST,
+                "period-short": C.NEWS_SHORT,
+                "period-long": C.NEWS_LONG
+            }
+            actives = {
+                "period-last": (True, False, False),
+                "period-short": (False, True, False),
+                "period-long": (False, False, True)
+            }
+
+            # Parse the url:
+            parsed_url = url_decode(href)
+            if parsed_url:
+                url_params = parsed_url["params"]
+            else:
+                url_params = None
+
+            trigger_id = callback_context.triggered[0]["prop_id"].split(".")[0]
+            if trigger_id == "url" and url_params:
+                trigger_id = url_params.get("period", list())[0]
+
+            period = periods.get(trigger_id, self._default_period)
+            active = actives.get(trigger_id, self._default_active)
+
+            ret_val = [
+                table_summary(self._data, self._jobs, period),
+                gen_new_url(parsed_url, {"period": trigger_id})
+            ]
+            ret_val.extend(active)
+            return ret_val
diff --git a/csit.infra.dash/app/cdash/news/news.py b/csit.infra.dash/app/cdash/news/news.py
new file mode 100644
index 0000000000..362ee13052
--- /dev/null
+++ b/csit.infra.dash/app/cdash/news/news.py
@@ -0,0 +1,47 @@
+# Copyright (c) 2022 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 News Dash application.
+"""
+import dash
+
+from ..utils.constants import Constants as C
+from .layout import Layout
+
+
+def init_news(server):
+    """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.NEWS_ROUTES_PATHNAME_PREFIX,
+        external_stylesheets=C.EXTERNAL_STYLESHEETS,
+        title=C.NEWS_TITLE
+    )
+
+    layout = Layout(
+        app=dash_app,
+        html_layout_file=C.HTML_LAYOUT_FILE,
+        data_spec_file=C.DATA_SPEC_FILE,
+        tooltip_file=C.TOOLTIP_FILE,
+    )
+    dash_app.index_string = layout.html_layout
+    dash_app.layout = layout.add_content()
+
+    return dash_app.server
diff --git a/csit.infra.dash/app/cdash/news/tables.py b/csit.infra.dash/app/cdash/news/tables.py
new file mode 100644
index 0000000000..7c0cc66eda
--- /dev/null
+++ b/csit.infra.dash/app/cdash/news/tables.py
@@ -0,0 +1,176 @@
+# Copyright (c) 2022 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 tables with news.
+"""
+
+import pandas as pd
+import dash_bootstrap_components as dbc
+
+from datetime import datetime, timedelta
+
+
+def _table_info(job_data: pd.DataFrame) -> dbc.Table:
+    """Generates table with info about the job.
+
+    :param job_data: Dataframe with information about the job.
+    :type job_data: pandas.DataFrame
+    :returns: Table with job info.
+    :rtype: dbc.Table
+    """
+    return dbc.Table.from_dataframe(
+        pd.DataFrame.from_dict(
+            {
+                "Job": job_data["job"],
+                "Last Build": job_data["build"],
+                "Date": job_data["start"],
+                "DUT": job_data["dut_type"],
+                "DUT Version": job_data["dut_version"],
+                "Hosts": ", ".join(job_data["hosts"].to_list()[0])
+            }
+        ),
+        bordered=True,
+        striped=True,
+        hover=True,
+        size="sm",
+        color="info"
+    )
+
+
+def _table_failed(job_data: pd.DataFrame, failed: list) -> dbc.Table:
+    """Generates table with failed tests from the last run of the job.
+
+    :param job_data: Dataframe with information about the job.
+    :param failed: List of failed tests.
+    :type job_data: pandas.DataFrame
+    :type failed: list
+    :returns: Table with fialed tests.
+    :rtype: dbc.Table
+    """
+    return dbc.Table.from_dataframe(
+        pd.DataFrame.from_dict(
+            {
+                (
+                    f"Last Failed Tests on "
+                    f"{job_data['start'].values[0]} ({len(failed)})"
+                ): failed
+            }
+        ),
+        bordered=True,
+        striped=True,
+        hover=True,
+        size="sm",
+        color="danger"
+    )
+
+
+def _table_gressions(itms: dict, color: str) -> dbc.Table:
+    """Generates table with regressions.
+
+    :param itms: Dictionary with items (regressions or progressions) and their
+        last occurence.
+    :param color: Color of the table.
+    :type regressions: dict
+    :type color: str
+    :returns: The table with regressions.
+    :rtype: dbc.Table
+    """
+    return dbc.Table.from_dataframe(
+        pd.DataFrame.from_dict(itms),
+        bordered=True,
+        striped=True,
+        hover=True,
+        size="sm",
+        color=color
+    )
+
+
+def table_news(data: pd.DataFrame, job: str, period: int) -> list:
+    """Generates the tables with news:
+    1. Falied tests from the last run
+    2. Regressions and progressions calculated from the last C.NEWS_TIME_PERIOD
+       days.
+
+    :param data: Trending data with calculated annomalies to be displayed in the
+        tables.
+    :param job: The job name.
+    :param period: The time period (nr of days from now) taken into account.
+    :type data: pandas.DataFrame
+    :type job: str
+    :type period: int
+    :returns: List of tables.
+    :rtype: list
+    """
+
+    last_day = datetime.utcnow() - timedelta(days=period)
+    r_list = list()
+    job_data = data.loc[(data["job"] == job)]
+    r_list.append(_table_info(job_data))
+
+    failed = job_data["failed"].to_list()[0]
+    if failed:
+        r_list.append(_table_failed(job_data, failed))
+
+    title = f"Regressions in the last {period} days"
+    regressions = {title: list(), "Last Regression": list()}
+    for itm in job_data["regressions"].to_list()[0]:
+        if itm[1] < last_day:
+            break
+        regressions[title].append(itm[0])
+        regressions["Last Regression"].append(
+            itm[1].strftime('%Y-%m-%d %H:%M'))
+    if regressions["Last Regression"]:
+        r_list.append(_table_gressions(regressions, "warning"))
+
+    title = f"Progressions in the last {period} days"
+    progressions = {title: list(), "Last Progression": list()}
+    for itm in job_data["progressions"].to_list()[0]:
+        if itm[1] < last_day:
+            break
+        progressions[title].append(itm[0])
+        progressions["Last Progression"].append(
+            itm[1].strftime('%Y-%m-%d %H:%M'))
+    if progressions["Last Progression"]:
+        r_list.append(_table_gressions(progressions, "success"))
+
+    return r_list
+
+
+def table_summary(data: pd.DataFrame, jobs: list, period: int) -> list:
+    """Generates summary (failed tests, regressions and progressions) from the
+    last week.
+
+    :param data: Trending data with calculated annomalies to be displayed in the
+        tables.
+    :param jobs: List of jobs.
+    :params period: The time period for the summary table.
+    :type data: pandas.DataFrame
+    :type job: str
+    :type period: int
+    :returns: List of tables.
+    :rtype: list
+    """
+
+    return [
+        dbc.Accordion(
+            children=[
+                dbc.AccordionItem(
+                    title=job,
+                    children=table_news(data, job, period)
+                ) for job in jobs
+            ],
+            class_name="gy-2 p-0",
+            start_collapsed=True,
+            always_open=True
+        )
+    ]