diff options
Diffstat (limited to 'csit.infra.dash/app/cdash/news')
| -rw-r--r-- | csit.infra.dash/app/cdash/news/__init__.py | 12 | ||||
| -rw-r--r-- | csit.infra.dash/app/cdash/news/layout.py | 508 | ||||
| -rw-r--r-- | csit.infra.dash/app/cdash/news/news.py | 47 | ||||
| -rw-r--r-- | csit.infra.dash/app/cdash/news/tables.py | 176 |
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 + ) + ] |