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-rw-r--r--csit.infra.dash/app/cdash/utils/telemetry_data.py45
1 files changed, 32 insertions, 13 deletions
diff --git a/csit.infra.dash/app/cdash/utils/telemetry_data.py b/csit.infra.dash/app/cdash/utils/telemetry_data.py
index e88b8eed06..9c2e45f9a1 100644
--- 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
@@ -43,7 +45,8 @@ class TelemetryData:
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:
@@ -86,18 +89,34 @@ class TelemetryData:
"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