nix: adjacent process monitoring report columns

This commit is contained in:
steve-chavez
2025-06-19 16:36:25 -05:00
parent e1c71c92d6
commit 49de3c1ab8
3 changed files with 20 additions and 3 deletions
+1 -1
View File
@@ -240,7 +240,7 @@ let
echo -e 'If a branch finishes its loadtest in less seconds than another branch, it will have blank cells for the missing seconds.\n'
find loadtest -type f -iname '*.csv' \
| sort -nr \
| sort -m \
| ${mergeMonitorResults}
'';
+17 -1
View File
@@ -3,7 +3,8 @@ import sys
import pandas as pd
KEY = "Elapsed seconds"
BASE_METRICS = ["CPU (%)", "MEM (%)", "Real (MB)"]
branch_order = []
merged = None
paths = [p.strip() for p in sys.stdin.read().split() if p.strip()]
@@ -11,18 +12,33 @@ paths = [p.strip() for p in sys.stdin.read().split() if p.strip()]
for csv_path in paths:
# br is branch (variable shortened to pass linter)
br = os.path.splitext(os.path.basename(csv_path))[0]
branch_order.append(br)
df = pd.read_csv(csv_path)
if KEY not in df.columns:
sys.exit(f"{csv_path} is missing the {KEY} column")
for m in BASE_METRICS:
if m not in df.columns:
sys.exit(f"Error: '{csv_path}' missing required column '{m}'.")
# add branch marker to every metric column
df = df.rename(columns={c: f"{c} [{br}]" for c in df.columns if c != KEY})
# outer join so missing rows appear
merged = df if merged is None else merged.merge(df, on=KEY, how="outer")
# Re-order columns so related metrics are adjacent
ordered_cols = [KEY]
for metric in BASE_METRICS:
for br in branch_order:
col_name = f"{metric} [{br}]"
if col_name in merged.columns:
ordered_cols.append(col_name)
merged = merged[ordered_cols]
# replace nan with empty string
merged = merged.fillna("")
merged.to_markdown(sys.stdout, index=False, tablefmt="github")
+2 -1
View File
@@ -5,6 +5,7 @@ import psutil
import pandas as pd
KEY = "Elapsed seconds"
BASE_METRICS = ["CPU (%)", "MEM (%)", "Real (MB)"]
SAMPLE_INTERVAL_SECS = 1
if len(sys.argv) != 2 or not sys.argv[1].isdigit():
@@ -53,6 +54,6 @@ end = time.time()
total_time = end - start
print(f"Finished {pid} pid monitoring in {total_time:.3f}", file=sys.stderr)
cols = [KEY, "CPU (%)", "MEM (%)", "Real (MB)"]
cols = [KEY] + BASE_METRICS
df = pd.DataFrame(records, columns=cols, dtype=str)
df.to_csv(sys.stdout, index=False)