C-Dash: Add processing of compressed telemetry data

Signed-off-by: Tibor Frank <tifrank@cisco.com>
Change-Id: Iedb67abcc5218d573890d6065e0f5c8acbaf67f6

diff --git a/csit.infra.dash/app/cdash/utils/telemetry_data.py b/csit.infra.dash/app/cdash/utils/telemetry_data.py
index e88b8ee..9c2e45f 100644 (file)
--- a/csit.infra.dash/app/cdash/utils/telemetry_data.py
+++ b/csit.infra.dash/app/cdash/utils/telemetry_data.py
@@ -16,6 +16,8 @@ operations with it.
 """
 
 
 """
 
 

+import binascii
+import zlib

 import pandas as pd
 
 from ..trending.graphs import select_trending_data
 import pandas as pd
 
 from ..trending.graphs import select_trending_data


@@ -43,7 +45,8 @@ class TelemetryData:
     def from_dataframe(self, in_data: pd.DataFrame=pd.DataFrame()) -> None:
         """Read the input from pandas DataFrame.
 
     def from_dataframe(self, in_data: pd.DataFrame=pd.DataFrame()) -> None:
         """Read the input from pandas DataFrame.
 

-        This method must be call at the begining to create all data structures.
+        This method must be called at the beginning to create all data
+        structures.

         """
 
         if in_data.empty:
         """
 
         if in_data.empty:


@@ -86,18 +89,34 @@ class TelemetryData:
                 "value": list(),
                 "timestamp": list()
             }
                 "value": list(),
                 "timestamp": list()
             }

-            if row["telemetry"] is not None and \
-                    not isinstance(row["telemetry"], float):
-                for itm in row["telemetry"]:
-                    itm_lst = itm.replace("'", "").rsplit(" ", maxsplit=2)
-                    metric, labels = itm_lst[0].split("{")
-                    d_telemetry["metric"].append(metric)
-                    d_telemetry["labels"].append(
-                        [tuple(x.split("=")) for x in labels[:-1].split(",")]
-                    )
-                    d_telemetry["value"].append(itm_lst[1])
-                    d_telemetry["timestamp"].append(itm_lst[2])
-                metrics.update(d_telemetry["metric"])
+            
+            # If there is no telemetry data, use empty dictionary
+            if row["telemetry"] is None or isinstance(row["telemetry"], float):
+                lst_telemetry.append(pd.DataFrame(data=d_telemetry))
+                continue
+
+            # Read telemetry data
+            # - list of uncompressed strings List[str, ...], or
+            # - list with only one compressed string List[str]
+            try:
+                tm_data = zlib.decompress(
+                    binascii.a2b_base64(row["telemetry"][0].encode())
+                ).decode().split("\n")
+            except (binascii.Error, zlib.error, AttributeError, IndexError):
+                tm_data = row["telemetry"]
+
+            # Pre-process telemetry data
+            for itm in tm_data:
+                itm_lst = itm.replace("'", "").rsplit(" ", maxsplit=2)
+                metric, labels = itm_lst[0].split("{")
+                d_telemetry["metric"].append(metric)
+                d_telemetry["labels"].append(
+                    [tuple(x.split("=")) for x in labels[:-1].split(",")]
+                )
+                d_telemetry["value"].append(itm_lst[1])
+                d_telemetry["timestamp"].append(itm_lst[2])
+
+            metrics.update(d_telemetry["metric"])

             lst_telemetry.append(pd.DataFrame(data=d_telemetry))
         df["telemetry"] = lst_telemetry
 
             lst_telemetry.append(pd.DataFrame(data=d_telemetry))
         df["telemetry"] = lst_telemetry