from datetime import datetime, timedelta
-def select_data(data: pd.DataFrame, itm:str) -> pd.DataFrame:
+def select_data(data: pd.DataFrame, itm:str, start: datetime,
+ end: datetime) -> pd.DataFrame:
"""
"""
- df = data.loc[(data["job"] == itm)].sort_values(
- by="start_time", ignore_index=True)
+ df = data.loc[
+ (data["job"] == itm) &
+ (data["start_time"] >= start) & (data["start_time"] <= end)
+ ].sort_values(by="start_time", ignore_index=True)
+ df = df.dropna(subset=["duration", ])
return df
"""
"""
- 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)
- )]
+ data = select_data(df, job, start, 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'])}"
)