hover = list()
for _, row in data.iterrows():
+ d_type = "trex" if row["dut_type"] == "none" else row["dut_type"]
hover_itm = (
f"date: {row['start_time'].strftime('%d-%m-%Y %H:%M:%S')}<br>"
f"duration: "
f"{((int(row['duration']) % 3600) // 60):02d}<br>"
f"passed: {row['passed']}<br>"
f"failed: {row['failed']}<br>"
- f"{row['dut_type']}-ref: {row['dut_version']}<br>"
+ f"{d_type}-ref: {row['dut_version']}<br>"
f"csit-ref: {row['job']}/{row['build']}<br>"
f"hosts: {', '.join(row['hosts'])}"
)
"dut_version": list(),
"hosts": list(),
"passed": list(),
- "failed": list()
+ "failed": list(),
+ "lst_failed": list()
}
for job in jobs:
- # TODO: Add list of failed tests for each build
df_job = df_tst_info.loc[(df_tst_info["job"] == job)]
builds = df_job["build"].unique()
for build in builds:
tst_info["dut_version"].append(df_build["dut_version"].iloc[-1])
tst_info["hosts"].append(df_build["hosts"].iloc[-1])
try:
- passed = df_build.value_counts(subset='passed')[True]
+ passed = df_build.value_counts(subset="passed")[True]
except KeyError:
passed = 0
try:
- failed = df_build.value_counts(subset='passed')[False]
+ failed = df_build.value_counts(subset="passed")[False]
+ failed_tests = df_build.loc[(df_build["passed"] == False)]\
+ ["test_id"].to_list()
+ l_failed = list()
+ for tst in failed_tests:
+ lst_tst = tst.split(".")
+ suite = lst_tst[-2].replace("2n1l-", "").\
+ replace("1n1l-", "").replace("2n-", "")
+ l_failed.append(f"{suite.split('-')[0]}-{lst_tst[-1]}")
except KeyError:
failed = 0
+ l_failed = list()
tst_info["passed"].append(passed)
tst_info["failed"].append(failed)
+ tst_info["lst_failed"].append(sorted(l_failed))
self._data = data_stats.merge(pd.DataFrame.from_dict(tst_info))
),
dcc.Loading(
dbc.Offcanvas(
- class_name="w-25",
+ class_name="w-50",
id="offcanvas-metadata",
title="Detailed Information",
placement="end",
elif trigger_id == "graph-duration":
graph_data = duration_data["points"][0].get("text", "")
if graph_data:
+ lst_graph_data = graph_data.split("<br>")
+
+ # Prepare list of failed tests:
+ job = str()
+ build = str()
+ for itm in lst_graph_data:
+ if "csit-ref:" in itm:
+ job, build = itm.split(" ")[-1].split("/")
+ break
+ if job and build:
+ fail_tests = self.data.loc[
+ (self.data["job"] == job) &
+ (self.data["build"] == build)
+ ]["lst_failed"].values[0]
+ if not fail_tests:
+ fail_tests = None
+ else:
+ fail_tests = None
+
+ # Create the content of the offcanvas:
metadata = [
dbc.Card(
class_name="gy-2 p-0",
),
x.split(": ")[1]
]
- ) for x in graph_data.split("<br>")
+ ) for x in lst_graph_data
],
flush=True),
]
]
)
]
+
+ if fail_tests is not None:
+ metadata.append(
+ dbc.Card(
+ class_name="gy-2 p-0",
+ children=[
+ dbc.CardHeader(
+ f"List of Failed Tests ({len(fail_tests)})"
+ ),
+ dbc.CardBody(
+ id="failed-tests",
+ class_name="p-0",
+ children=[dbc.ListGroup(
+ children=[
+ dbc.ListGroupItem(x) \
+ for x in fail_tests
+ ],
+ flush=True),
+ ]
+ )
+ ]
+ )
+ )
+
open_canvas = True
return metadata, open_canvas
import plotly.graph_objects as go
import pandas as pd
-import re
import hdrh.histogram
import hdrh.codec
hover = list()
customdata = list()
for _, row in df.iterrows():
+ d_type = "trex" if row["dut_type"] == "none" else row["dut_type"]
hover_itm = (
f"date: {row['start_time'].strftime('%d-%m-%Y %H:%M:%S')}<br>"
f"<prop> [{row[_UNIT[ttype]]}]: {row[_VALUE[ttype]]}<br>"
f"<stdev>"
- f"{row['dut_type']}-ref: {row['dut_version']}<br>"
+ f"{d_type}-ref: {row['dut_version']}<br>"
f"csit-ref: {row['job']}/{row['build']}<br>"
f"hosts: {', '.join(row['hosts'])}"
)
hover_trend = list()
for avg, stdev, (_, row) in zip(trend_avg, trend_stdev, df.iterrows()):
+ d_type = "trex" if row["dut_type"] == "none" else row["dut_type"]
hover_itm = (
f"date: {row['start_time'].strftime('%d-%m-%Y %H:%M:%S')}<br>"
f"trend [pps]: {avg}<br>"
f"stdev [pps]: {stdev}<br>"
- f"{row['dut_type']}-ref: {row['dut_version']}<br>"
+ f"{d_type}-ref: {row['dut_version']}<br>"
f"csit-ref: {row['job']}/{row['build']}<br>"
f"hosts: {', '.join(row['hosts'])}"
)