Handle no job list gracefully

src/__init__.py

@@ -92,28 +92,30 @@ def export_jobs_to_dataframe():
     logger = logging.getLogger(__name__)
     logger.info("Exporting jobs to DataFrame. All jobs are appended to one frame")
     jobs = parse_job_pickle()
-    number_of_jobs = len(jobs)
-    if jobs is not None and number_of_jobs > 0:
-        logger.info(f"Found {number_of_jobs} jobs")
-        df = pd.DataFrame()
-        count = 1
-        for job in jobs:
-            count += 1
-            logger.info(f"Working on job {count}/{number_of_jobs}")
-            job_df = pd.DataFrame()
-            for item in job.items.list:
-                job_df = job_df.append(pd.DataFrame(data=[dict(
-                    qid=item.id,
-                    label=item.label,
-                    description=item.description
-                )]))
-            df = df.append(job_df)
-            logger.debug(f"Added {len(job.items.list)} items to the dataframe")
-        logger.debug(f"Exporting {len(df)} rows to pickle")
-        pickle_filename = "dataframe.pkl.gz"
-        df.to_pickle(pickle_filename)
-        console.print(f"Wrote to {pickle_filename} in the current directory")
-
+    if jobs is not None:
+        number_of_jobs = len(jobs)
+        if jobs is not None and number_of_jobs > 0:
+            logger.info(f"Found {number_of_jobs} jobs")
+            df = pd.DataFrame()
+            count = 1
+            for job in jobs:
+                count += 1
+                logger.info(f"Working on job {count}/{number_of_jobs}")
+                job_df = pd.DataFrame()
+                for item in job.items.list:
+                    job_df = job_df.append(pd.DataFrame(data=[dict(
+                        qid=item.id,
+                        label=item.label,
+                        description=item.description
+                    )]))
+                df = df.append(job_df)
+                logger.debug(f"Added {len(job.items.list)} items to the dataframe")
+            logger.debug(f"Exporting {len(df)} rows to pickle")
+            pickle_filename = "dataframe.pkl.gz"
+            df.to_pickle(pickle_filename)
+            console.print(f"Wrote to {pickle_filename} in the current directory")
+    else:
+        console.print("No jobs found. Create a job list first by using '--prepare-jobs'")
 
 def export_jobs_to_quickstatements():
     logger = logging.getLogger(__name__)