import pandas as pd
import dash_bootstrap_components as dbc
+from datetime import datetime, timedelta
+from dash import html
+
from ..utils.constants import Constants as C
-def table_news(data: pd.DataFrame, job: str) -> list:
+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
: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]
- regressions = {"Test Name": list(), "Last Regression": list()}
+ 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]:
- regressions["Test Name"].append(itm[0])
- regressions["Last Regression"].append(itm[1].strftime('%Y-%m-%d %H:%M'))
- progressions = {"Test Name": list(), "Last Progression": list()}
+ 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]:
- progressions["Test Name"].append(itm[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 [
- 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="light"),
- 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="light"),
- dbc.Label(
- class_name="p-0",
- size="lg",
- children=(
- f"Regressions during the last {C.NEWS_TIME_PERIOD} days "
- f"({len(regressions['Test Name'])})"
- )
- ),
- dbc.Table.from_dataframe(
- pd.DataFrame.from_dict(regressions),
- bordered=True, striped=True, hover=True, size="sm", color="light"),
- dbc.Label(
- class_name="p-0",
- size="lg",
- children=(
- f"Progressions during the last {C.NEWS_TIME_PERIOD} days "
- f"({len(progressions['Test Name'])})"
- )
- ),
- dbc.Table.from_dataframe(
- pd.DataFrame.from_dict(progressions),
- bordered=True, striped=True, hover=True, size="sm", color="light")
- ]
+ return r_list
+
+
+def table_summary(data: pd.DataFrame, jobs: list) -> 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.
+ :type data: pandas.DataFrame
+ :type job: str
+ :returns: List of tables.
+ :rtype: list
+ """
+
+ r_list = list()
+ for job in jobs:
+ r_list.extend(table_news(data, job, C.NEWS_SUMMARY_PERIOD))
+ r_list.append(html.Div(html.P(" ")))
+
+ return r_list
Code Review / csit.git / blobdiff