fix(cdash): Rename

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

4 files changed, 0 insertions, 743 deletions

diff --git a/csit.infra.dash/app/pal/news/__init__.py b/csit.infra.dash/app/pal/news/__init__.py
deleted file mode 100644
index 5692432123..0000000000
--- a/csit.infra.dash/app/pal/news/__init__.py
+++ /dev/null
@@ -1,12 +0,0 @@
-# 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/pal/news/layout.py b/csit.infra.dash/app/pal/news/layout.py
deleted file mode 100644
index dfe6eba67a..0000000000
--- a/csit.infra.dash/app/pal/news/layout.py
+++ /dev/null
@@ -1,508 +0,0 @@
-# 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/pal/news/news.py b/csit.infra.dash/app/pal/news/news.py
deleted file mode 100644
index aa8cd5fbdc..0000000000
--- a/csit.infra.dash/app/pal/news/news.py
+++ /dev/null
@@ -1,47 +0,0 @@
-# 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.NEWS_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/pal/news/tables.py b/csit.infra.dash/app/pal/news/tables.py
deleted file mode 100644
index 7c0cc66eda..0000000000
--- a/csit.infra.dash/app/pal/news/tables.py
+++ /dev/null
@@ -1,176 +0,0 @@
-# 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
-        )
-    ]