graph-vmtop.py

#!/usr/bin/python3

import argparse
import os
import csv
import datetime
import pandas as pd
import matplotlib

matplotlib.use("Agg")
import matplotlib.pyplot as plt
from matplotlib.pyplot import figure

parser = argparse.ArgumentParser(description="Graph from vmtop")

parser.add_argument(
    "-p",
    "--path",
    type=str,
    required=True,
    help="folder containing the CSV files produced by vmtop",
)
parser.add_argument("-t", "--title", type=str, help="Title of the graph")
parser.add_argument(
    "-f", "--filename", type=str, required=True, help="csv list of input files to graph"
)
parser.add_argument(
    "-m", "--metric", type=str, required=True, help="csv list of metrics to graph"
)
parser.add_argument(
    "-u",
    "--units",
    type=str,
    required=True,
    help="csv list of units (same order as the metrics)",
)
parser.add_argument(
    "-n", "--name", type=str, required=True, help="Prefix of output file"
)
parser.add_argument(
    "-s", "--separate", action="store_true", help="Make 1 chart per metric"
)
parser.add_argument(
    "-b", "--begin", type=str, help="Begin timestamp (%Y-%m-%d %H:%M:%S)"
)
parser.add_argument("-e", "--end", type=str, help="Begin timestamp (%Y-%m-%d %H:%M:%S)")

args = parser.parse_args()

if args.begin:
    args.begin = datetime.datetime.strptime(args.begin, "%Y-%m-%d %H:%M:%S")
if args.end:
    args.end = datetime.datetime.strptime(args.end, "%Y-%m-%d %H:%M:%S")

metrics = ["timestamp"]
i = 0
units = {}
for m in args.metric.split(","):
    metrics.append(m)
    units[m] = args.units.split(",")[i]
    i += 1

files = {}
for v in args.filename.split(","):
    files[v] = {}
    for m in metrics:
        files[v][m] = []


for f in files.keys():
    fpath = os.path.join(args.path, "%s.csv" % f)

    reader = csv.DictReader(open(fpath, "r"))
    for row in reader:
        dt = datetime.datetime.strptime(row["timestamp"], "%Y-%m-%d %H:%M:%S")
        if args.begin is not None and dt < args.begin:
            continue
        if args.end is not None and dt > args.end:
            break
        files[f]["timestamp"].append(dt)
        for m in metrics:
            if m == "timestamp":
                continue
            files[f][m].append(float(row[m]))

# If we have more than 1 metric, generate 1 image with multiple graphs
if len(metrics) > 2 and not args.separate:
    fig, axs = plt.subplots(len(metrics) - 1, sharex=True)
    if args.title:
        fig.suptitle(args.title)
    h = 4.0 * (len(metrics) - 1)
    fig.set_figwidth(h * (16.0 / 9.0))
    fig.set_figheight(h)

    i = 0
    for m in metrics:
        if m == "timestamp":
            continue

        axs[i].set(xlabel="Time", ylabel="%s %s" % (m, units[m]))
        for f in files.keys():
            axs[i].plot(files[f]["timestamp"], files[f][m], label=f)

        i += 1
    plt.gcf().autofmt_xdate()
    plt.legend()
    if args.name is not None:
        out_file = os.path.join(args.path, "%s.png" % args.name)
    else:
        out_file = os.path.join(args.path, "multi.png")
    fig.savefig(out_file)
    plt.close()
    print("Generated %s" % out_file)
else:
    for m in metrics:
        if m == "timestamp":
            continue
        fig = plt.figure(figsize=(16, 9))
        if args.title:
            fig.suptitle(args.title)
        plt.xlabel("Time")
        plt.ylabel("%s %s" % (m, units[m]))
        for f in files.keys():
            plt.plot(files[f]["timestamp"], files[f][m], label=f)
        plt.gcf().autofmt_xdate()
        plt.legend()

        if args.name is not None:
            out_file = os.path.join(args.path, "%s-%s.png" % (args.name, m))
        else:
            out_file = os.path.join(args.path, "%s.png" % m)
        fig.savefig(out_file)
        plt.close()
        print("Generated %s" % out_file)