Issue/85 (#86)

* fixes edgecase where all run tasks have been cached

* update dependencies

* adds tests for timeline functions

omics/cli/run_analyzer/timeline.py

@@ -25,23 +25,25 @@ def _parse_time_str(time_str):
 def _get_task_timings_data(tasks, time_units="min"):
     time_scale_factor = TIME_SCALE_FACTORS[time_units]
 
-    # remove tasks that don't have a creationTime
-    filtered_tasks = [task for task in tasks if task.get("creationTime")]
+    # retain only tasks that have creationTime, stopTime and startTime
+    filtered_tasks = [
+        task
+        for task in tasks
+        if task.get("creationTime") and task.get("stopTime") and task.get("startTime")
+    ]
     if not filtered_tasks:
-        print("No tasks found with timing data, a plot cannot be created", file=sys.stderr)
+        print(
+            "No tasks found with timing data, possibly all tasks were cached, a plot cannot be created",
+            file=sys.stderr,
+        )
         return pd.DataFrame()
 
     tare = min([_parse_time_str(task["creationTime"]) for task in filtered_tasks])
 
-    for i, task in enumerate(tasks):
-        if "creationTime" not in task:
-            task["creationTime"] = tare
-            task["startTime"] = task["creationTime"]
-            task["stopTime"] = task["creationTime"]
-        else:
-            task["creationTime"] = _parse_time_str(task["creationTime"])
-            task["startTime"] = _parse_time_str(task["startTime"])
-            task["stopTime"] = _parse_time_str(task["stopTime"])
+    for i, task in enumerate(filtered_tasks):
+        task["creationTime"] = _parse_time_str(task["creationTime"])
+        task["startTime"] = _parse_time_str(task["startTime"])
+        task["stopTime"] = _parse_time_str(task["stopTime"])
         task["cpus"] = task.get("cpus", 0)
         task["gpus"] = task.get("gpus", 0)
         task["memory"] = task.get("memory", 0)
@@ -61,17 +63,18 @@ def _get_task_timings_data(tasks, time_units="min"):
         task["label"] = f"({task['arn']}) {task['name']}"
         task["text_x"] = (task["stopTime"] - tare).total_seconds() + 30 * time_scale_factor
 
-        tasks[i] = task
+        filtered_tasks[i] = task
         task["estimatedUSD"] = task.get("metrics", {}).get("estimatedUSD", 0.0)
 
-    return pd.DataFrame.from_records(tasks).sort_values("creationTime")
+    return pd.DataFrame.from_records(filtered_tasks).sort_values("creationTime")
 
 
 def plot_timeline(tasks, title="", time_units="min", max_duration_hrs=5, show_plot=True):
     """Plot a time line figure for supplied tasks"""
     time_scale_factor = TIME_SCALE_FACTORS[time_units]
     data = _get_task_timings_data(tasks, time_units=time_units)
-
+    if data.empty:
+        return None
     source = ColumnDataSource(data)
 
     tooltips = [