"""Plotly Dash HTML layout override.
"""
-import logging
import pandas as pd
import dash_bootstrap_components as dbc
from dash import html
from dash import callback_context
from dash import Input, Output, State
-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.utils import gen_new_url
+from ..utils.anomalies import classify_anomalies
from ..utils.url_processing import url_decode
-from ..data.data import Data
from .tables import table_summary
"""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:
+ def __init__(
+ self,
+ app: Flask,
+ data_stats: pd.DataFrame,
+ data_trending: pd.DataFrame,
+ html_layout_file: str
+ ) -> None:
"""Initialization:
- save the input parameters,
- read and pre-process the data,
- read tooltips from the tooltip file.
:param app: Flask application running the dash application.
+ :param data_stats: Pandas dataframe with staistical data.
+ :param data_trending: Pandas dataframe with trending data.
: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 data_stats: pandas.DataFrame
+ :type data_trending: pandas.DataFrame
: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,
- copy=False
- )
# Prepare information for the control panel:
- self._jobs = sorted(list(df_tst_info["job"].unique()))
+ self._jobs = sorted(list(data_trending["job"].unique()))
d_job_info = {
"job": list(),
"dut": list(),
}
for job in self._jobs:
# Create lists of failed tests:
- df_job = df_tst_info.loc[(df_tst_info["job"] == job)]
+ df_job = data_trending.loc[(data_trending["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)
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()
+ tst_data = df_job.loc[(
+ (df_job["test_id"] == test) &
+ (df_job["passed"] == True)
+ )].sort_values(by="start_time", ignore_index=True)
if "-ndrpdr" in test:
tst_data = tst_data.dropna(
subset=["result_pdr_lower_rate_value", ]
)
if tst_data.empty:
continue
+ x_axis = tst_data["start_time"].tolist()
try:
anomalies, _, _ = classify_anomalies({
k: v for k, v in zip(
)
if tst_data.empty:
continue
+ x_axis = tst_data["start_time"].tolist()
try:
anomalies, _, _ = classify_anomalies({
k: v for k, v in zip(
# Read from files:
self._html_layout = str()
- self._tooltips = dict()
try:
with open(self._html_layout_file, "r") as file_read:
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._add_ctrl_col(),
self._add_plotting_col()
]
+ ),
+ dbc.Offcanvas(
+ class_name="w-75",
+ id="offcanvas-documentation",
+ title="Documentation",
+ placement="end",
+ is_open=False,
+ children=html.Iframe(
+ src=C.URL_DOC_TRENDING,
+ width="100%",
+ height="100%"
+ )
)
]
)
return dbc.NavbarSimple(
id="navbarsimple-main",
children=[
- dbc.NavItem(
- dbc.NavLink(
- C.NEWS_TITLE,
- disabled=True,
- external_link=True,
- href="#"
- )
- )
+ dbc.NavItem(dbc.NavLink(
+ C.TREND_TITLE,
+ external_link=True,
+ href="/trending"
+ )),
+ dbc.NavItem(dbc.NavLink(
+ C.NEWS_TITLE,
+ active=True,
+ external_link=True,
+ href="/news"
+ )),
+ dbc.NavItem(dbc.NavLink(
+ C.STATS_TITLE,
+ external_link=True,
+ href="/stats"
+ )),
+ dbc.NavItem(dbc.NavLink(
+ "Documentation",
+ id="btn-documentation",
+ ))
],
brand=C.BRAND,
brand_href="/",
if n:
return not is_open
return is_open
+
+ @app.callback(
+ Output("offcanvas-documentation", "is_open"),
+ Input("btn-documentation", "n_clicks"),
+ State("offcanvas-documentation", "is_open")
+ )
+ def toggle_offcanvas_documentation(n_clicks, is_open):
+ if n_clicks:
+ return not is_open
+ return is_open
Code Review / csit.git / blobdiff