import plotly.graph_objects as go
import pandas as pd
-from datetime import datetime, timedelta
def select_data(data: pd.DataFrame, itm:str) -> pd.DataFrame:
- """
+ """Select the data for graphs from the provided data frame.
+
+ :param data: Data frame with data for graphs.
+ :param itm: Item (in this case job name) which data will be selected from
+ the input data frame.
+ :type data: pandas.DataFrame
+ :type itm: str
+ :returns: A data frame with selected data.
+ :rtype: pandas.DataFrame
"""
df = data.loc[(data["job"] == itm)].sort_values(
by="start_time", ignore_index=True)
+ df = df.dropna(subset=["duration", ])
return df
-def graph_statistics(df: pd.DataFrame, job:str, layout: dict,
- start: datetime=datetime.utcnow()-timedelta(days=180),
- end: datetime=datetime.utcnow()) -> tuple:
- """
+def graph_statistics(df: pd.DataFrame, job:str, layout: dict) -> tuple:
+ """Generate graphs:
+ 1. Passed / failed tests,
+ 2. Job durations
+ with additional information shown in hover.
+
+ :param df: Data frame with input data.
+ :param job: The name of job which data will be presented in the graphs.
+ :param layout: Layout of plot.ly graph.
+ :type df: pandas.DataFrame
+ :type job: str
+ :type layout: dict
+ :returns: Tuple with two generated graphs (pased/failed tests and job
+ duration).
+ :rtype: tuple(plotly.graph_objects.Figure, plotly.graph_objects.Figure)
"""
data = select_data(df, job)
- data = data.dropna(subset=["duration", ])
- if data.empty:
- return None, None
-
- data = data.loc[(
- (data["start_time"] >= start) & (data["start_time"] <= end)
- )]
if data.empty:
return None, None
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"date: {row['start_time'].strftime('%Y-%m-%d %H:%M:%S')}<br>"
f"duration: "
f"{(int(row['duration']) // 3600):02d}:"
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'])}"
)