def ingest_health_log()

in distributed_nhc/export_nhc_result_to_kusto.py [0:0]

• 20 lines of code
• 2 McCabe index (conditional complexity)

def ingest_health_log(health_file, creds, ingest_url, database, health_table_name):
    filename_parts = os.path.basename(health_file).split("-", maxsplit=2)
    ts_str = filename_parts[2].split(".")[0]
    ts = datetime.strptime(ts_str, "%Y-%m-%d_%H-%M-%S")

    job_name = filename_parts[1]

    if job_name == "pssh":
        job_name = f"{job_name}-{ts_str}"

    with open(health_file, 'r') as f:
        lines = f.readlines()
        reader = DictReader(lines, fieldnames = ["Hostname", "RawResult"], delimiter='|', restkey="extra")

        df = pd.DataFrame(reader)
        df['Timestamp'] = ts
        df['JobName'] = job_name
        df['NodeName'] = df.apply(lambda x: x['Hostname'].strip(), axis=1)
        df['RawResult'] = df.apply(lambda x: x['RawResult'].strip(), axis=1)
        df['Healthy'] = df.apply(lambda x: x['RawResult'] == "Healthy", axis=1)
        df = df[['Timestamp', 'JobName', 'Hostname', 'Healthy', 'RawResult']]

        ingest_client = QueuedIngestClient(KustoConnectionStringBuilder.with_azure_token_credential(ingest_url, creds))
        print(f"Ingesting health results from {os.path.basename(health_file)} into {ingest_url} at {database}/{health_table_name}")
        ingest_client.ingest_from_dataframe(df, IngestionProperties(database, health_table_name))