add lturping snippet

README.org

@@ -490,6 +490,47 @@ In [2]: # gk is your entry point
    #+END_SRC
 
 ** Metrics API
+*** Get the timeseries corresponding to a job
+    Credits to ~lturpin~.
+    #+BEGIN_SRC python :exports code :tangle examples/job_timeseries.py
+import logging
+import os
+
+from grid5000 import Grid5000
+
+
+logging.basicConfig(level=logging.DEBUG)
+
+
+def get_job_consumption(job_id, gk, site):
+    metrics = gk.sites[site].metrics
+    job = gk.sites[site].jobs[job_id]
+    # nodes as list : "cluster-number.site.grid5000.fr"
+    nodes_dom = job.assigned_nodes
+    # nodes as list : "cluster-number"
+    nodes = map(lambda node_dom: node_dom.split('.')[0], nodes_dom)
+    # nodes as string : "cluster-number,cluster-number,..."
+    nodes_str = ','.join(nodes)
+
+    start = job.started_at
+    end = job.stopped_at
+    kwargs = {
+        "only": nodes_str,
+        "resolution": 1,
+        "from": start,
+        "to": end
+    }
+    timeseries = metrics["power"].timeseries.list(**kwargs)
+    return timeseries
+
+
+conf_file = os.path.join(os.environ.get("HOME"), ".python-grid5000.yaml")
+gk = Grid5000.from_yaml(conf_file)
+
+timeseries = get_job_consumption("1092446", gk, "lyon")
+print(timeseries)
+    #+END_SRC
+
 *** Get some timeseries (and plot them)
     For this example you'll need ~matplotlib~, ~seaborn~ and ~pandas~.
 
@@ -548,6 +589,7 @@ In [2]: # gk is your entry point
     #+END_SRC
 
 
+
 ** More snippets
 *** Site of a cluster
 

README.rst

@@ -508,7 +508,51 @@ Before starting, the file ``$HOME/.python-grid5000.yaml`` will be loaded.
 4.8 Metrics API
 ~~~~~~~~~~~~~~~
 
-4.8.1 Get some timeseries (and plot them)
+4.8.1 Get the timeseries corresponding to a job
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+Credits to ``lturpin``.
+
+.. code:: python
+
+    import logging
+    import os
+
+    from grid5000 import Grid5000
+
+
+    logging.basicConfig(level=logging.DEBUG)
+
+
+    def get_job_consumption(job_id, gk, site):
+        metrics = gk.sites[site].metrics
+        job = gk.sites[site].jobs[job_id]
+        # nodes as list : "cluster-number.site.grid5000.fr"
+        nodes_dom = job.assigned_nodes
+        # nodes as list : "cluster-number"
+        nodes = map(lambda node_dom: node_dom.split('.')[0], nodes_dom)
+        # nodes as string : "cluster-number,cluster-number,..."
+        nodes_str = ','.join(nodes)
+
+        start = job.started_at
+        end = job.stopped_at
+        kwargs = {
+            "only": nodes_str,
+            "resolution": 1,
+            "from": start,
+            "to": end
+        }
+        timeseries = metrics["power"].timeseries.list(**kwargs)
+        return timeseries
+
+
+    conf_file = os.path.join(os.environ.get("HOME"), ".python-grid5000.yaml")
+    gk = Grid5000.from_yaml(conf_file)
+
+    timeseries = get_job_consumption("1092446", gk, "lyon")
+    print(timeseries)
+
+4.8.2 Get some timeseries (and plot them)
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
 For this example you’ll need ``matplotlib``, ``seaborn`` and ``pandas``.