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			192 lines
		
	
	
		
			6.7 KiB
		
	
	
	
		
			Python
		
	
	
		
			Executable File
		
	
	
	
	
			
		
		
	
	
			192 lines
		
	
	
		
			6.7 KiB
		
	
	
	
		
			Python
		
	
	
		
			Executable File
		
	
	
	
	
#!/usr/bin/env python2
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# Script to parse a logging file, extract the stats, and graph them
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#
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# Copyright (C) 2016-2018  Kevin O'Connor <kevin@koconnor.net>
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#
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# This file may be distributed under the terms of the GNU GPLv3 license.
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import optparse, datetime
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import matplotlib
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matplotlib.use('Agg')
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import matplotlib.pyplot, matplotlib.dates, matplotlib.font_manager
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import matplotlib.ticker
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MAXBANDWIDTH=25000.
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MAXBUFFER=2.
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STATS_INTERVAL=5.
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TASK_MAX=0.0025
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APPLY_PREFIX = ['mcu_awake', 'mcu_task_avg', 'mcu_task_stddev', 'bytes_write',
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                'bytes_read', 'bytes_retransmit', 'freq', 'adj']
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def parse_log(logname, mcu):
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    if mcu is None:
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        mcu = "mcu"
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    mcu_prefix = mcu + ":"
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    apply_prefix = { p: 1 for p in APPLY_PREFIX }
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    f = open(logname, 'rb')
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    out = []
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    for line in f:
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        parts = line.split()
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        if not parts or parts[0] not in ('Stats', 'INFO:root:Stats'):
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            #if parts and parts[0] == 'INFO:root:shutdown:':
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            #    break
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            continue
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        prefix = ""
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        keyparts = {}
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        for p in parts[2:]:
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            if '=' not in p:
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                prefix = p
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                if prefix == mcu_prefix:
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                    prefix = ''
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                continue
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            name, val = p.split('=', 1)
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            if name in apply_prefix:
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                name = prefix + name
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            keyparts[name] = val
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        if keyparts.get('bytes_write', '0') == '0':
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            continue
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        keyparts['#sampletime'] = float(parts[1][:-1])
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        out.append(keyparts)
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    f.close()
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    return out
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def find_print_restarts(data):
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    runoff_samples = {}
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    last_runoff_start = last_buffer_time = last_sampletime = 0.
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    last_print_stall = 0
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    for d in reversed(data):
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        # Check for buffer runoff
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        sampletime = d['#sampletime']
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        buffer_time = float(d.get('buffer_time', 0.))
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        if (last_runoff_start and last_sampletime - sampletime < 5
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            and buffer_time > last_buffer_time):
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            runoff_samples[last_runoff_start][1].append(sampletime)
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        elif buffer_time < 1.:
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            last_runoff_start = sampletime
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            runoff_samples[last_runoff_start] = [False, [sampletime]]
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        else:
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            last_runoff_start = 0.
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        last_buffer_time = buffer_time
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        last_sampletime = sampletime
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        # Check for print stall
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        print_stall = int(d['print_stall'])
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        if print_stall < last_print_stall:
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            if last_runoff_start:
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                runoff_samples[last_runoff_start][0] = True
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        last_print_stall = print_stall
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    sample_resets = {sampletime: 1 for stall, samples in runoff_samples.values()
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                     for sampletime in samples if not stall}
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    return sample_resets
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def plot_mcu(data, maxbw, outname):
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    # Generate data for plot
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    basetime = lasttime = data[0]['#sampletime']
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    lastbw = float(data[0]['bytes_write']) + float(data[0]['bytes_retransmit'])
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    sample_resets = find_print_restarts(data)
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    times = []
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    bwdeltas = []
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    loads = []
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    awake = []
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    hostbuffers = []
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    for d in data:
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        st = d['#sampletime']
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        timedelta = st - lasttime
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        if timedelta <= 0.:
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            continue
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        bw = float(d['bytes_write']) + float(d['bytes_retransmit'])
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        if bw < lastbw:
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            lastbw = bw
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            continue
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        load = float(d['mcu_task_avg']) + 3*float(d['mcu_task_stddev'])
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        if st - basetime < 15.:
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            load = 0.
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        pt = float(d['print_time'])
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        hb = float(d['buffer_time'])
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        if hb >= MAXBUFFER or st in sample_resets:
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            hb = 0.
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        else:
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            hb = 100. * (MAXBUFFER - hb) / MAXBUFFER
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        hostbuffers.append(hb)
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        times.append(datetime.datetime.utcfromtimestamp(st))
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        bwdeltas.append(100. * (bw - lastbw) / (maxbw * timedelta))
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        loads.append(100. * load / TASK_MAX)
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        awake.append(100. * float(d.get('mcu_awake', 0.)) / STATS_INTERVAL)
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        lasttime = st
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        lastbw = bw
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    # Build plot
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    fig, ax1 = matplotlib.pyplot.subplots()
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    ax1.set_title("MCU bandwidth and load utilization")
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    ax1.set_xlabel('Time')
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    ax1.set_ylabel('Usage (%)')
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    ax1.plot_date(times, bwdeltas, 'g', label='Bandwidth', alpha=0.8)
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    ax1.plot_date(times, loads, 'r', label='MCU load', alpha=0.8)
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    ax1.plot_date(times, hostbuffers, 'c', label='Host buffer', alpha=0.8)
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    ax1.plot_date(times, awake, 'y', label='Awake time', alpha=0.6)
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    fontP = matplotlib.font_manager.FontProperties()
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    fontP.set_size('x-small')
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    ax1.legend(loc='best', prop=fontP)
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    ax1.xaxis.set_major_formatter(matplotlib.dates.DateFormatter('%H:%M'))
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    ax1.grid(True)
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    fig.set_size_inches(8, 6)
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    fig.savefig(outname)
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def plot_frequency(data, outname, mcu):
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    all_keys = {}
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    for d in data:
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        all_keys.update(d)
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    one_mcu = mcu is not None
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    graph_keys = { key: ([], []) for key in all_keys
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                   if (key in ("freq", "adj") or (not one_mcu and (
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                           key.endswith(":freq") or key.endswith(":adj")))) }
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    basetime = lasttime = data[0]['#sampletime']
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    for d in data:
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        st = datetime.datetime.utcfromtimestamp(d['#sampletime'])
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        for key, (times, values) in graph_keys.items():
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            val = d.get(key)
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            if val not in (None, '0', '1'):
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                times.append(st)
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                values.append(float(val))
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    # Build plot
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    fig, ax1 = matplotlib.pyplot.subplots()
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    if one_mcu:
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        ax1.set_title("MCU '%s' frequency" % (mcu,))
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    else:
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        ax1.set_title("MCU frequency")
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    ax1.set_xlabel('Time')
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    ax1.set_ylabel('Frequency')
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    for key in sorted(graph_keys):
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        times, values = graph_keys[key]
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        ax1.plot_date(times, values, '.', label=key)
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    fontP = matplotlib.font_manager.FontProperties()
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    fontP.set_size('x-small')
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    ax1.legend(loc='best', prop=fontP)
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    ax1.xaxis.set_major_formatter(matplotlib.dates.DateFormatter('%H:%M'))
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    ax1.yaxis.set_major_formatter(matplotlib.ticker.FormatStrFormatter('%d'))
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    ax1.grid(True)
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    fig.set_size_inches(8, 6)
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    fig.savefig(outname)
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def main():
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    usage = "%prog [options] <logfile> <outname>"
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    opts = optparse.OptionParser(usage)
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    opts.add_option("-f", "--frequency", action="store_true",
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                    help="graph mcu frequency")
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    opts.add_option("-m", "--mcu", type="string", dest="mcu", default=None,
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                    help="limit stats to the given mcu")
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    options, args = opts.parse_args()
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    if len(args) != 2:
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        opts.error("Incorrect number of arguments")
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    logname, outname = args
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    data = parse_log(logname, options.mcu)
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    if not data:
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        return
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    if options.frequency:
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        plot_frequency(data, outname, options.mcu)
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        return
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    plot_mcu(data, MAXBANDWIDTH, outname)
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if __name__ == '__main__':
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    main()
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