fix doc

README.org

@@ -489,6 +489,65 @@ In [2]: # gk is your entry point
    site.vlans[vlanid].submit({"nodes": nodes})
    #+END_SRC
 
+** Metrics API
+*** Get some timeseries (and plot them)
+    For this example you'll need ~matplotlib~, ~seaborn~ and ~pandas~.
+
+    #+BEGIN_SRC python :exports code :tangle examples/timeseries.py
+    import logging
+    import os
+
+    from grid5000 import Grid5000
+
+    import pandas as pd
+    import matplotlib.pyplot as plt
+    import seaborn as sns
+    import time
+
+    logging.basicConfig(level=logging.DEBUG)
+
+    conf_file = os.path.join(os.environ.get("HOME"), ".python-grid5000.yaml")
+    gk = Grid5000.from_yaml(conf_file)
+
+    metrics = gk.sites["lyon"].metrics
+    print("--- available metrics")
+    print(metrics.list())
+
+    print("---- power metric")
+    print(metrics["power"])
+
+    print("----- a timeserie")
+    now = time.time()
+    kwargs = {
+        "only": "nova-1,nova-2,nova-3",
+        "resolution": 1,
+        "from": int(now - 600),
+        "to": int(now)
+    }
+    timeseries = metrics["power"].timeseries.list(**kwargs)
+
+    # let's visualize this
+    df = pd.DataFrame()
+    for timeserie in timeseries:
+        print(timeserie)
+        timestamp = timeserie.timestamps
+        value = timeserie.values
+        measurement = timeserie.uid
+        df = pd.concat([df, pd.DataFrame({
+            "timestamp": timestamp,
+            "value": value,
+            "measurement": [measurement]*len(timestamp)
+        })])
+
+    sns.relplot(data=df,
+                x="timestamp",
+                y="value",
+                hue="measurement",
+                kind="line")
+    plt.show()
+    #+END_SRC
+
+
 ** More snippets
 *** Site of a cluster
 

README.rst

@@ -505,10 +505,72 @@ Before starting, the file ``$HOME/.python-grid5000.yaml`` will be loaded.
       # set in vlan
       site.vlans[vlanid].submit({"nodes": nodes})
 
-4.8 More snippets
+4.8 Metrics API
+~~~~~~~~~~~~~~~
+
+4.8.1 Get some timeseries (and plot them)
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+For this example you’ll need ``matplotlib``, ``seaborn`` and ``pandas``.
+
+.. code:: python
+
+    import logging
+    import os
+
+    from grid5000 import Grid5000
+
+    import pandas as pd
+    import matplotlib.pyplot as plt
+    import seaborn as sns
+    import time
+
+    logging.basicConfig(level=logging.DEBUG)
+
+    conf_file = os.path.join(os.environ.get("HOME"), ".python-grid5000.yaml")
+    gk = Grid5000.from_yaml(conf_file)
+
+    metrics = gk.sites["lyon"].metrics
+    print("--- available metrics")
+    print(metrics.list())
+
+    print("---- power metric")
+    print(metrics["power"])
+
+    print("----- a timeserie")
+    now = time.time()
+    kwargs = {
+        "only": "nova-1,nova-2,nova-3",
+        "resolution": 1,
+        "from": int(now - 600),
+        "to": int(now)
+    }
+    timeseries = metrics["power"].timeseries.list(**kwargs)
+
+    # let's visualize this
+    df = pd.DataFrame()
+    for timeserie in timeseries:
+        print(timeserie)
+        timestamp = timeserie.timestamps
+        value = timeserie.values
+        measurement = timeserie.uid
+        df = pd.concat([df, pd.DataFrame({
+            "timestamp": timestamp,
+            "value": value,
+            "measurement": [measurement]*len(timestamp)
+        })])
+
+    sns.relplot(data=df,
+                x="timestamp",
+                y="value",
+                hue="measurement",
+                kind="line")
+    plt.show()
+
+4.9 More snippets
 ~~~~~~~~~~~~~~~~~
 
-4.8.1 Site of a cluster
+4.9.1 Site of a cluster
 ^^^^^^^^^^^^^^^^^^^^^^^
 
 .. code:: python
@@ -536,7 +598,7 @@ Before starting, the file ``$HOME/.python-grid5000.yaml`` will be loaded.
             clusters.remove(matching[0])
     print("We found the following matches %s" % matches)
 
-4.8.2 Get all job with a given name on all the sites
+4.9.2 Get all job with a given name on all the sites
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
 .. code:: python
@@ -577,7 +639,7 @@ Before starting, the file ``$HOME/.python-grid5000.yaml`` will be loaded.
     for job in jobs:
         job.delete()
 
-4.8.3 Caching API responses
+4.9.3 Caching API responses
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
 The Grid’5000 reference API is static. In this situation to speed up the

examples/timeseries.py

@@ -28,9 +28,9 @@ kwargs = {
     "from": int(now - 600),
     "to": int(now)
 }
+timeseries = metrics["power"].timeseries.list(**kwargs)
 
 # let's visualize this
-timeseries = metrics["power"].timeseries.list(**kwargs)
 df = pd.DataFrame()
 for timeserie in timeseries:
     print(timeserie)
@@ -48,4 +48,4 @@ sns.relplot(data=df,
             y="value",
             hue="measurement",
             kind="line")
-plt.show()
\ No newline at end of file
+plt.show()

examples/vlan_set_2.py

@@ -11,7 +11,7 @@ logging.basicConfig(level=logging.DEBUG)
 def _to_network_address(host, interface):
     """Translate a host to a network address
     e.g:
-    paravance-20.rennes.grid5000.fr -> paravance-20-eth2.rennes.grid5000.fr
+    paranoia-20.rennes.grid5000.fr -> paranoia-20-eth2.rennes.grid5000.fr
     """
     splitted = host.split('.')
     splitted[0] = splitted[0] + "-" + interface
@@ -26,7 +26,7 @@ site = gk.sites["rennes"]
 
 job = site.jobs.create({"name": "pyg5k",
                         "command": "sleep 3600",
-                        "resources": "{type='kavlan'}/vlan=1+{cluster='paravance'}nodes=1",
+                        "resources": "{type='kavlan'}/vlan=1+{cluster='paranoia'}nodes=1",
                         "types": ["deploy"]
 })