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authorpmikus <peter.mikus@protonmail.ch>2022-09-19 08:49:01 +0200
committerPeter Mikus <peter.mikus@protonmail.ch>2022-09-19 06:54:43 +0000
commitd6a60b5043c6f7c3dfc45853feb68d0aca5a4a5f (patch)
tree022343584d4e00a0da8ef12eb4e713d67344fc95 /csit.infra.dash/app/pal/news/tables.py
parentd2ef7bc01df66f6a27f25d061db064cf4a463267 (diff)
feat(uti): Move directory
Signed-off-by: pmikus <peter.mikus@protonmail.ch> Change-Id: I7300ecfe756baaf3fbeedb020070f882cfaca445
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+# 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
+ )
+ ]