Merge pull request #65 from galaxyproject/dev

Final 1.x release

README.md

@@ -1,4 +1,4 @@
-# Benchmarking Scripts
+# Automated Benchmarking
 An opinionated Python Bioblend script for automating benchmarking tasks in Galaxy.
 
 
@@ -7,8 +7,8 @@ An opinionated Python Bioblend script for automating benchmarking tasks in Galax
 
 1. Clone this repository.
    ```bash
-   git clone https://github.com/ksuderman/bioblend-scripts.git
-   cd bioblend-scripts
+   git clone https://github.com/galaxyproject/gxabm.git
+   cd gxabm
    ```
 1. Create a virtual env and install the required libraries
    ```bash

abm.py

@@ -18,9 +18,9 @@
 from lib import job, dataset, workflow, history, library, folder, benchmark, helm, kubectl, config
 
 log = logging.getLogger('abm')
-log.setLevel(logging.ERROR)
+log.setLevel(logging.INFO)
 
-VERSION = '1.4.0'
+VERSION = '1.4.1'
 
 BOLD = '\033[1m'
 CLEAR = '\033[0m'
@@ -118,7 +118,7 @@ def alias(shortcut, fullname):
 
 def parse_menu():
     log.debug('parse_menu')
-    menu_config = f'{os.path.dirname(__file__)}/lib/menu.yml'
+    menu_config = f'{os.path.dirname(os.path.abspath(__file__))}/lib/menu.yml'
     if not os.path.exists(menu_config):
         print(f"ERROR: Unable to load the menu configuration from {menu_config}")
         sys.exit(1)

config/dna2.yml

@@ -0,0 +1,30 @@
+- workflow_id: d8beac5a0d816eee
+  output_history_base_name: DNA 29C 116G-MEM
+  runs:
+    - history_name: HG00171
+      inputs:
+      - name: FASTQ Dataset
+        dataset_id: 3ef6e7918b01e665
+    - history_name: HG00152
+      inputs:
+      - name: FASTQ Dataset
+        dataset_id: daf58ed87714bfc3
+    - history_name: HG00599
+      inputs:
+      - name: FASTQ Dataset
+        dataset_id: 1c8ebd93f5710bc6
+    - history_name: HG01167
+      inputs:
+      - name: FASTQ Dataset
+        dataset_id: c49cc12509f57ec1
+    - history_name: HG003
+      inputs:
+      - name: FASTQ Dataset
+        dataset_id: 845199e085d0abbe
+- workflow_id: b94314cb9cb46380
+  output_history_base_name: PairedDNA 29C 116G-MEM
+  runs:
+    - history_name: SRS9540951
+      inputs:
+      - name: FASTQ Dataset
+        dataset_id: 4b0ef3aaf341f57b

lib/benchmark.py

@@ -38,27 +38,49 @@ def run(args: list):
 
     profiles = load_profiles()
     num_runs = config['runs']
-    for n in range(num_runs):
+    for cloud in config['cloud']:
+        if cloud not in profiles:
+            print(f"WARNING: No profile found for {cloud}")
+            continue
+        if not set_active_profile(cloud):
+            print(f"ERROR: Unable to set the profile for {cloud}")
+            continue
+        if lib.KUBECONFIG is None:
+            print(f"ERROR: No kubeconfig set for {cloud}")
+            continue
         print("------------------------")
-        print(f"Benchmarking run #{n+1}")
-        for cloud in config['cloud']:
-            if cloud not in profiles:
-                print(f"WARNING: no profile for instance {cloud}")
+        print(f"Benchmarking: {cloud}")
+        for conf in config['job_configs']:
+            job_conf_path = f"rules/{conf}.yml"
+            if not helm.update([job_conf_path]):
+                print(f"WARNING: job conf not found {conf}")
                 continue
-            if not set_active_profile(cloud):
-                print(f"WARNING: unable to set {cloud} as the active profile")
-            if lib.KUBECONFIG is None:
-                print(f"WARNGING: no kubeconfig for instance {cloud}")
-                continue
-            for job_conf in config['job_configs']:
-                job_conf_path = f"rules/{job_conf}.yml"
-                if not helm.update([job_conf_path]):
-                    print(f"WARNING: job conf not found {job_conf}")
-                    continue
-                history_name_prefix = f"Run {n} {job_conf}"
+            for n in range(num_runs):
+                history_name_prefix = f"{n} {cloud} {conf}"
                 for workflow_conf in config['workflow_conf']:
                     workflow.run([workflow_conf, history_name_prefix])
 
+    # for n in range(num_runs):
+    #     print("------------------------")
+    #     print(f"Benchmarking run #{n+1}")
+    #     for cloud in config['cloud']:
+    #         if cloud not in profiles:
+    #             print(f"WARNING: no profile for instance {cloud}")
+    #             continue
+    #         if not set_active_profile(cloud):
+    #             print(f"WARNING: unable to set {cloud} as the active profile")
+    #         if lib.KUBECONFIG is None:
+    #             print(f"WARNGING: no kubeconfig for instance {cloud}")
+    #             continue
+    #         for job_conf in config['job_configs']:
+    #             job_conf_path = f"rules/{job_conf}.yml"
+    #             if not helm.update([job_conf_path]):
+    #                 print(f"WARNING: job conf not found {job_conf}")
+    #                 continue
+    #             history_name_prefix = f"Run {n} {job_conf}"
+    #             for workflow_conf in config['workflow_conf']:
+    #                 workflow.run([workflow_conf, history_name_prefix])
+
 
 def test(args: list):
     print(common.GALAXY_SERVER)
@@ -73,15 +95,19 @@ def summarize(args: list):
     :return: None
     """
     row = [''] * 12
+    print("Workflow,History,Server,Tool ID,State,Slots,Memory,Runtime,CPU,Memory Limit,Memory Max usage,Memory Soft Limit")
     for file in os.listdir(METRICS_DIR):
         input_path = os.path.join(METRICS_DIR, file)
         with open(input_path, 'r') as f:
             data = json.load(f)
-        row[0] = data['workflow_id']
-        row[1] = data['history_id']
-        row[2] = data['server'] if data['server'] is not None else 'https://iu1.usegvl.org/galaxy'
-        row[3] = data['metrics']['tool_id']
-        row[4] = data['metrics']['state']
+        row[0] = data['run']
+        row[1] = data['cloud']
+        row[2] = data['conf']
+        row[3] = data['workflow_id']
+        row[4] = data['history_id']
+        row[5] = data['server'] if data['server'] is not None else 'https://iu1.usegvl.org/galaxy'
+        row[6] = data['metrics']['tool_id']
+        row[7] = data['metrics']['state']
         add_metrics_to_row(data['metrics']['job_metrics'], row)
         print(','.join(row))
 
@@ -91,7 +117,8 @@ def add_metrics_to_row(metrics_list: list, row: list):
     for job_metrics in metrics_list:
         if job_metrics['name'] in accept_metrics:
             index = accept_metrics.index(job_metrics['name'])
-            row[index + 5] = job_metrics['raw_value']
+            row[index + 8] = job_metrics['raw_value']
+            # row.append(job_metrics['raw_value'])
 
 
 

lib/common.py

@@ -41,9 +41,8 @@ def connect():
 
 
 def set_active_profile(profile_name: str):
-    print(f"Parsing profile for {profile_name}")
+    # print(f"Parsing profile for {profile_name}")
     lib.GALAXY_SERVER, lib.API_KEY, lib.KUBECONFIG = parse_profile(profile_name)
-    print(lib.KUBECONFIG)
     return lib.GALAXY_SERVER != None
 
 

lib/workflow.py

@@ -230,6 +230,11 @@ def run(args: list):
                 print(f"Wrote invocation data to {output_path}")
             invocations = gi.invocations.wait_for_invocation(id, 86400, 10, False)
             print("Waiting for jobs")
+            if len(args) > 1:
+                for parts in args[1].split():
+                    invocations['run'] = parts[0]
+                    invocations['cloud'] = parts[1]
+                    invocations['job_conf'] = parts[2]
             wait_for_jobs(gi, invocations)
     print("Benchmarking run complete")
     return True
@@ -387,20 +392,30 @@ def wait_for_jobs(gi: GalaxyInstance, invocations: dict):
     """
     wfid = invocations['workflow_id']
     hid = invocations['history_id']
+    run = invocations['run']
+    cloud = invocations['cloud']
+    conf = invocations['job_conf']
     for step in invocations['steps']:
         job_id = step['job_id']
         if job_id is not None:
             print(f"Waiting for job {job_id} on {lib.GALAXY_SERVER}")
-            status = gi.jobs.wait_for_job(job_id, 86400, 10, False)
-            data = gi.jobs.show_job(job_id, full_details=True)
-            metrics = {
-                'workflow_id': wfid,
-                'history_id': hid,
-                'metrics': data,
-                'status': status,
-                'server': lib.GALAXY_SERVER
-            }
-            output_path = os.path.join(METRICS_DIR, f"{job_id}.json")
-            with open(output_path, "w") as f:
-                json.dump(metrics, f, indent=4)
-                print(f"Wrote metrics to {output_path}")
+            try:
+                # TDOD Should retry if anything throws an exception.
+                status = gi.jobs.wait_for_job(job_id, 86400, 10, False)
+                data = gi.jobs.show_job(job_id, full_details=True)
+                metrics = {
+                    'run': run,
+                    'cloud': cloud,
+                    'job_conf': conf,
+                    'workflow_id': wfid,
+                    'history_id': hid,
+                    'metrics': data,
+                    'status': status,
+                    'server': lib.GALAXY_SERVER
+                }
+                output_path = os.path.join(METRICS_DIR, f"{job_id}.json")
+                with open(output_path, "w") as f:
+                    json.dump(metrics, f, indent=4)
+                    print(f"Wrote metrics to {output_path}")
+            except Exception as e:
+                print(f"ERROR: {e}")