Stats
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relikd
46
src/analyze_stats.py
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46
src/analyze_stats.py
Executable file
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#!/usr/bin/env python3
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import lib_common as mylib
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pp = ['flurry.com', 'facebook.com', 'admob.com', 'apple.com', 'tapjoyads.com',
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'crashlytics.com', 'ioam.de', 'amazonaws.com', 'chartboost.com',
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'googleadservices.com',
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'app-measurement.com', 'doubleclick.net', 'adjust.com', 'appsflyer.com'
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]
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study = ["com.amazon.AmazonDE", "com.innersloth.amongus", "ca.gc.hcsc.canada.covid19", "com.instructure.icanvas", "mobi.gameguru.fruitsurgeon", "com.google.GoogleMobile", "com.google.chrome.ios", "com.google.Classroom", "com.burbn.instagram", "com.mcdonalds.mobileapp", "com.microsoft.skype.teams", "com.netflix.Netflix", "com.yourcompany.PPClient", "com.randonautica.app", "com.toyopagroup.picaboo", "com.casual.stairwaytoheaven", "com.tmobile.nameid", "com.burbn.threads", "com.zhiliaoapp.musically", "com.triller.projectx", "com.atebits.Tweetie2", "com.ubercab.UberEats", "net.whatsapp.WhatsApp", "com.google.ios.youtube", "com.zello.client.main",
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"com.apm2studio.runawaychallenge", "com.adidas.app", "com.booking.BookingApp", "com.braindom", "es.aeat.pin24h", "de.rki.coronawarnapp", "com.Atinon.PassOver", "com.greeneking.orderandpay", "com.ingka.ikea.app", "it.ministerodellasalute.immuni", "it.pagopa.app.io", "fr.izly.izlyiphone", "lagamerie.mmv", "au.com.menulog.m", "com.apalonapps.radarfree", "it.poste.postebuy2", "com.neocortext.doublicatapp", "com.Celltop.SpiralRoll", "com.spotify.client", "com.qsdhbdft.stackblocks", "com.redforcegames.stack.colors", "ph.telegra.Telegraph", "com.eightsec.TriviaIO", "com.watched.play", "it.wind.mywind",
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"com.alipay.iphoneclient", "jp.go.mhlw.covid19radar", "au.gov.health.covidsafe", "com.AnkaStudios.DriveThru3D", "ru.mail.mail", "com.phone.lock", "com.magictouch.xfollowers", "video.like", "jp.naver.line", "com.cg.moneybuster", "com.tencent.mqq", "zzkko.com.ZZKKO", "com.viber", "com.vk.vkclient", "com.waze.iphone", "com.tencent.xin", "icacacat.wobble.man.upstairs", "ru.avito.app", "ru.city-mobil.taxi", "com.yueyou.cyreader", "cn.gov.tax.its", "jp.jmty.Jmty", "com.siwuai.duapp", "com.huaxiaozhu.rider", "com.autonavi.amap"]
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ret = {x: 0 for x in pp}
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app_count = 0
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log_count = 0
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rec_count = [0, 0]
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rec_total = [0, 0]
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for bid in mylib.appids_in_out(['*']):
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app_count += 1
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for fname, json in mylib.enum_jsons(bid):
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# if json['duration'] > 40:
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i = 0 if bid in study else 1
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rec_count[i] += 1
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rec_total[i] += json['duration']
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for dom, logs in json['logs'].items():
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par = mylib.parent_domain(dom)
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l = len(logs)
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if par in pp:
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ret[par] += l
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log_count += l
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print('Domain: Percent of requests')
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for k, x in ret.items():
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def in_pct(u):
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return round(u * 10000) / 100
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print(f' {k}: {in_pct(x / log_count)}%')
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print('')
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print('Avg rec time')
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print(f' study {rec_total[0] / rec_count[0]} sec')
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print(f' not study {rec_total[1] / rec_count[1]} sec')
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print('')
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print(f'Apps: {app_count}, Recordings: {sum(rec_count)}, Logs: {log_count}')
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print('')
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99
src/analyze_timeit.py
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99
src/analyze_timeit.py
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#!/usr/bin/env python3
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import os
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import sys
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import timeit
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import matplotlib
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import matplotlib.pyplot as plt
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matplotlib.use('Agg') # disable interactive mode
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def split_arr(arr):
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arr.sort(key=lambda x: -x[1])
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ret = []
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while len(arr) > 0:
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ret.append(arr[0])
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del(arr[0])
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if len(arr) > 0:
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ret.append(arr[-1])
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del(arr[-1])
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return [x[0] for x in ret], [x[1] for x in ret]
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def gen_graph(arr, outfile):
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keys, vals = split_arr(arr)
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pie1, _ = plt.pie(vals, labels=keys, colors=['#AAA', '#444'], normalize=True)
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plt.setp(pie1, width=0.5)
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plt.subplots_adjust(left=0, right=1, top=0.7, bottom=0.3)
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plt.savefig(outfile, bbox_inches='tight', pad_inches=0, transparent=True)
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plt.close()
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def test(times, value):
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ret = []
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for x, y in [
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('index_app_names', f"['{value}']"),
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('index_categories', f"['{value}']"),
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('bundle_combine', f"['{value}']"),
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('index_rank', f"['{value}']"),
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('index_domains', f"['{value}']"),
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('html_bundle', f"['{value}']"),
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('html_categories', ''),
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('html_index_apps', ''),
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('html_ranking', ''),
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('html_group_compare', ''),
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('html_index_domains', ''),
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('html_root', '1, 1, inclStatic=True')
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]:
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sys.stdout = open(os.devnull, 'w')
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t = timeit.timeit(f'process({y})',
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setup=f'from {x} import process',
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number=times) / times
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sys.stdout = sys.__stdout__
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print(f"('{x}', {t}),")
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ret.append((x, t))
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return ret
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pre_calc = [ # 1.7468616582500003
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('index_app_names', 0.05087930704999999),
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('index_categories', 0.03988175075),
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('bundle_combine', 0.89672237075),
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('index_rank', 0.09671105084999994),
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('index_domains', 0.08596107025000013),
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('html_bundle', 0.23503021030000007),
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('html_categories', 0.10772542440000006),
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('html_index_apps', 0.014855155450000091),
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('html_ranking', 0.04087204415000016),
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('html_group_compare', 0.004021174899999735),
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('html_index_domains', 0.04882671115000008),
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('html_root', 0.12537538825),
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]
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post_calc = [ # 0.5836890604499999
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('index_app_names', 0.0006852585000000022),
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('index_categories', 0.0008334453500000005),
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('bundle_combine', 0.0136475935),
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('index_rank', 0.0012115025499999988),
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('index_domains', 0.0800649297),
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('html_bundle', 0.002384871350000006),
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('html_categories', 0.15204053159999997),
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('html_index_apps', 0.020598785899999993),
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('html_ranking', 0.059948232549999994),
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('html_group_compare', 0.004277908699999999),
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('html_index_domains', 0.06897567679999997),
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('html_root', 0.17902032395000003),
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]
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# gen_graph(pre_calc, 'times.svg')
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# result = pre_calc
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result = test(20, '*')
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# result = test(20, 'com.amazon.AmazonDE')
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print('pre_calc', sum([x for _, x in pre_calc]))
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print('measure ', sum([x for _, x in result]))
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gen_graph(result, 'times.svg')
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# result1 = test(10, '*')
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# result2 = test(10, 'com.amazon.AmazonDE')
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# a = sum([x for _, x in result1])
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# b = sum([x for _, x in result2])
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# result2.append((' ', a - b))
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# gen_graph(result1, 'times1.svg')
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# gen_graph(result2, 'times2.svg')
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