def output(self, args, begin_ns, end_ns, final=0):
count = 0
limit = args.top
total_ns = end_ns - begin_ns
graph = Pyasciigraph()
values = []
print('%s to %s' % (ns_to_asctime(begin_ns), ns_to_asctime(end_ns)))
for tid in sorted(self.state.tids.values(),
key=operator.attrgetter('cpu_ns'), reverse=True):
if len(args.proc_list) > 0 and tid.comm not in args.proc_list:
continue
pc = float("%0.02f" % ((tid.cpu_ns * 100) / total_ns))
if tid.migrate_count > 0:
migrations = ", %d migrations" % (tid.migrate_count)
else:
migrations = ""
values.append(("%s (%d)%s" % (tid.comm, tid.tid, migrations), pc))
count = count + 1
if limit > 0 and count >= limit:
break
for line in graph.graph("Per-TID CPU Usage", values, unit=" %"):
print(line)
values = []
total_cpu_pc = 0
for cpu in sorted(self.state.cpus.values(),
key=operator.attrgetter('cpu_ns'), reverse=True):
cpu_pc = float("%0.02f" % cpu.cpu_pc)
total_cpu_pc += cpu_pc
values.append(("CPU %d" % cpu.cpu_id, cpu_pc))
for line in graph.graph("Per-CPU Usage", values, unit=" %"):
print(line)
print("\nTotal CPU Usage: %0.02f%%\n" %
(total_cpu_pc / len(self.state.cpus.keys())))
def test_neg_multicolor(self):
test = [('testval0', 600), ('testval1', 400, Red),
('testval2', [(600, Gre), (500, Blu)]),
('testval3', [(200, Yel), (100, )]), ('testval4', -170, Cya),
('testval5', 50, Blu), ('testval6', [(-300, Gre),
(-230, Red)]),
('testval7', [(-100, Gre), (-230, Red), (200, Yel),
(600, Blu)])]
graph = Pyasciigraph()
res = graph.graph('☭test print', test)
expected = [
u'\u262dtest print',
u'###############################################################################',
u' \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588 600 testval0',
u' \x1b[0;31m\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\x1b[0m \x1b[0;31m400\x1b[0m testval1',
u' \x1b[0;34m\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\x1b[0m\x1b[0;32m\u2588\u2588\u2588\u2588\u2588\x1b[0m \x1b[0;32m600\x1b[0m,\x1b[0;34m500\x1b[0m testval2',
u' \u2588\u2588\u2588\u2588\u2588\x1b[0;33m\u2588\u2588\u2588\u2588\u2588\x1b[0m \x1b[0;33m200\x1b[0m,100 testval3',
u' \x1b[0;36m\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\x1b[0m \x1b[0;36m-170\x1b[0m testval4',
u' \x1b[0;34m\u2588\u2588\x1b[0m \x1b[0;34m50\x1b[0m testval5',
u' \x1b[0;32m\u2588\u2588\u2588\x1b[0m\x1b[0;31m\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\x1b[0m \x1b[0;32m-300\x1b[0m,\x1b[0;31m-230\x1b[0m testval6',
u' \x1b[0;31m\u2588\u2588\u2588\u2588\u2588\u2588\u2588\x1b[0m\x1b[0;32m\u2588\u2588\u2588\u2588\u2588\x1b[0m\x1b[0;33m\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\x1b[0m\x1b[0;34m\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\x1b[0m \x1b[0;32m-100\x1b[0m,\x1b[0;31m-230\x1b[0m,\x1b[0;33m200\x1b[0m,\x1b[0;34m600\x1b[0m testval7'
]
gprint(res)
gprint(expected)
assert res == expected
def print_charts(dataset, title, args, weekday=False):
chart = []
keys = sorted(dataset.keys())
mean = numpy.mean(list(dataset.values()))
median = numpy.median(list(dataset.values()))
for key in keys:
if dataset[key] >= median * 1.33:
displayed_key = "%s (\033[92m+\033[0m)" % (int_to_weekday(key) if weekday else key)
elif dataset[key] <= median * 0.66:
displayed_key = "%s (\033[91m-\033[0m)" % (int_to_weekday(key) if weekday else key)
else:
displayed_key = (int_to_weekday(key) if weekday else key)
chart.append((displayed_key, dataset[key]))
thresholds = {
int(mean): Gre, int(mean * 2): Yel, int(mean * 3): Red,
}
data = hcolor(chart, thresholds)
graph = Pyasciigraph(
separator_length=4,
multivalue=False,
human_readable='si',
)
for line in graph.graph(title, data):
if args.no_color:
ansi_escape = re.compile(r'\x1B\[[0-?]*[ -/]*[@-~]')
line = ansi_escape.sub('', line)
print(line)
print("")
def output(self, args, begin_ns, end_ns, final=0):
count = 0
limit = args.top
graph = Pyasciigraph()
values = []
print('%s to %s' % (ns_to_asctime(begin_ns), ns_to_asctime(end_ns)))
for tid in sorted(self.state.tids.values(),
key=operator.attrgetter('allocated_pages'),
reverse=True):
values.append(("%s (%d)" % (tid.comm, tid.tid),
tid.allocated_pages))
count = count + 1
if limit > 0 and count >= limit:
break
for line in graph.graph("Per-TID Memory Allocations", values,
unit=" pages"):
print(line)
values = []
count = 0
for tid in sorted(self.state.tids.values(),
key=operator.attrgetter('freed_pages'),
reverse=True):
values.append(("%s (%d)" % (tid.comm, tid.tid), tid.freed_pages))
count = count + 1
if limit > 0 and count >= limit:
break
for line in graph.graph("Per-TID Memory Deallocation", values,
unit=" pages"):
print(line)
print("\nTotal memory usage:\n- %d pages allocated\n- %d pages freed" %
(self.state.mm["allocated_pages"], self.state.mm["freed_pages"]))
def output(self, args, begin_ns, end_ns, final=0):
count = 0
limit = args.top
total_ns = end_ns - begin_ns
graph = Pyasciigraph()
values = []
print('%s to %s' % (ns_to_asctime(begin_ns), ns_to_asctime(end_ns)))
for tid in sorted(self.tids.values(),
key=operator.attrgetter('cpu_ns'), reverse=True):
if len(args.proc_list) > 0 and tid.comm not in args.proc_list:
continue
pc = float("%0.02f" % ((tid.cpu_ns * 100) / total_ns))
values.append(("%s (%d)" % (tid.comm, tid.tid), pc))
count = count + 1
if limit > 0 and count >= limit:
break
for line in graph.graph("Per-TID CPU Usage", values):
print(line)
values = []
nb_cpu = len(self.cpus.keys())
for cpu in sorted(self.cpus.values(),
key=operator.attrgetter('cpu_ns'), reverse=True):
cpu_total_ns = cpu.cpu_ns
cpu_pc = float("%0.02f" % cpu.cpu_pc)
values.append(("CPU %d" % cpu.cpu_id, cpu_pc))
for line in graph.graph("Per-CPU Usage", values):
print(line)
def irq_list_to_freq(self, irq, _min, _max, res, name, nr):
step = (_max - _min) / res
if step == 0:
return
buckets = []
values = []
graph = Pyasciigraph()
for i in range(res):
buckets.append(i * step)
values.append(0)
for i in irq["list"]:
v = (i.stop_ts - i.start_ts) / 1000
b = min(int((v - _min) / step), res - 1)
values[b] += 1
g = []
i = 0
for v in values:
g.append(("%0.03f" % (i * step + _min), v))
i += 1
for line in graph.graph('Handler duration frequency distribution %s '
'(%s) (usec)' % (name, nr),
g,
info_before=True,
count=True):
print(line)
print("")
def __init__(self):
self._cur_oxygen = 0
self._cur_systolic = 0
self._cur_diastolic = 0
self._cur_pulse = 0
self._graph_lock = threading.Lock()
self._graph = Pyasciigraph()
def output_file_read(self, args):
count = 0
limit = args.top
graph = Pyasciigraph()
values = []
files = {}
for tid in self.tids.values():
for fd in tid.fds.values():
if not fd.filename in files.keys():
files[fd.filename] = {}
files[fd.filename]["read"] = fd.read
files[fd.filename]["write"] = fd.write
if fd.filename.startswith("pipe") or \
fd.filename.startswith("socket") or \
fd.filename.startswith("anon_inode"):
files[fd.filename]["name"] = "%s (%s)" % (fd.filename, tid.comm)
else:
files[fd.filename]["name"] = fd.filename
files[fd.filename]["other"] = "(%d %d)" % (fd.fd, tid.tid)
else:
files[fd.filename]["read"] += fd.read
files[fd.filename]["write"] += fd.write
for f in files.values():
if f["read"] == 0:
continue
values.append(("%s %s %s" % (f["name"],
convert_size(f["read"]), f["other"]), f["read"]))
count = count + 1
if limit > 0 and count >= limit:
break
for line in graph.graph('Files Read', values, sort=2):
print(line)
def calculate_text_coverage(self):
"""
Prints CLI stats about percentage of matched dbpedia facts in wiki raw text.
"""
matched_count = self.count_matches()
total_count = {}
for entity, relation_types in self.dbpedia.iteritems():
for relation, values in relation_types.iteritems():
target_resources = values.get('resources', [])
total_count.setdefault(relation, 0)
total_count[relation] += len(target_resources)
occurrence_count = {}
for relation in total_count:
occurrence_count[relation] = {
'total':
total_count[relation],
'matched':
min(total_count[relation],
matched_count.setdefault(relation, 0))
} # there might be more occurrences of a fact in an article, thus, resulting in a coverage above 100%
# print bar chart
data = [
('% ' + str(vals['matched']) + '/' + str(vals['total']) + ' ' +
rel.split('/')[-1], vals['matched'] / vals['total'] * 100)
for rel, vals in occurrence_count.iteritems()
]
graph = Pyasciigraph()
for line in graph.graph('occurred facts in percentage', data):
print(line)
def output(self, args, begin_ns, end_ns, final=0):
count = 0
limit = args.top
graph = Pyasciigraph()
values = []
print('%s to %s' % (ns_to_asctime(begin_ns), ns_to_asctime(end_ns)))
for tid in sorted(self.state.tids.values(),
key=operator.attrgetter('allocated_pages'),
reverse=True):
values.append(
("%s (%d)" % (tid.comm, tid.tid), tid.allocated_pages))
count = count + 1
if limit > 0 and count >= limit:
break
for line in graph.graph("Per-TID Memory Allocations",
values,
unit=" pages"):
print(line)
values = []
count = 0
for tid in sorted(self.state.tids.values(),
key=operator.attrgetter('freed_pages'),
reverse=True):
values.append(("%s (%d)" % (tid.comm, tid.tid), tid.freed_pages))
count = count + 1
if limit > 0 and count >= limit:
break
for line in graph.graph("Per-TID Memory Deallocation",
values,
unit=" pages"):
print(line)
print("\nTotal memory usage:\n- %d pages allocated\n- %d pages freed" %
(self.state.mm["allocated_pages"], self.state.mm["freed_pages"]))
def print_charts(dataset, title, weekday=False):
""" Prints nice charts based on a dict {(key, value), ...} """
chart = []
keys = sorted(dataset.keys())
mean = numpy.mean(list(dataset.values()))
median = numpy.median(list(dataset.values()))
for key in keys:
if (dataset[key] >= median * 1.33):
displayed_key = "%s (\033[92m+\033[0m)" % (int_to_weekday(key) if weekday else key)
elif (dataset[key] <= median * 0.66):
displayed_key = "%s (\033[91m-\033[0m)" % (int_to_weekday(key) if weekday else key)
else:
displayed_key = (int_to_weekday(key) if weekday else key)
chart.append((displayed_key, dataset[key]))
thresholds = {
int(mean): Gre, int(mean * 2): Yel, int(mean * 3): Red,
}
data = hcolor(chart, thresholds)
graph = Pyasciigraph(
separator_length=4,
multivalue=False,
human_readable='si',
)
for line in graph.graph(title, data):
print(line)
print("")
def show_index(self):
graphArray = []
for coin in IndexedCoinModel.select():
graphArray.append((coin.Ticker, coin.DesiredPercentage))
pyGraph = Pyasciigraph(line_length=50,
min_graph_length=50,
separator_length=4,
multivalue=False,
human_readable='si',
graphsymbol='*',
float_format='{0:,.2f}')
thresholds = {
15: Gre,
30: Blu,
50: Yel,
60: Red,
}
data = hcolor(graphArray, thresholds)
sys.stdout.write("\n")
for line in pyGraph.graph('Index Distribution', data=data):
sys.stdout.write(line + "\n")
sys.stdout.write("\n")
def iotop_output_print_file_write(self, files):
# Compute files read
count = 0
limit = self._arg_limit
graph = Pyasciigraph()
values = []
sorted_f = sorted(files.items(),
key=lambda files: files[1]['write'],
reverse=True)
for f in sorted_f:
if f[1]["write"] == 0:
continue
info_fmt = "{:>10}".format(
common.convert_size(f[1]["write"], padding_after=True))
values.append(("%s %s %s" %
(info_fmt, f[1]["name"], str(f[1]["other"])[1:-1]),
f[1]["write"]))
count = count + 1
if limit > 0 and count >= limit:
break
for line in graph.graph('Files Write',
values,
sort=2,
with_value=False):
print(line)
def plot_testsuite_time(json_data, top_k=TOP_K, ascii_graph=False, report_file=None):
suite_time = {}
overall_time = 0.0
for suite in json_data:
name = suite['testsuite']['@name'].rsplit(".",1)[-1]
time = float(suite['testsuite']['@time'].replace(',',''))
overall_time += time
if name in suite_time:
total_time = suite_time[name]
suite_time[name] = total_time + time
else:
suite_time[name] = time
d_descending = OrderedDict(sorted(suite_time.items(),
key=lambda kv: kv[1], reverse=True))
gdata = []
for k,v in take(d_descending.iteritems(), top_k):
gdata.append((k, v))
print '\nTop ' + str(top_k) + ' testsuite in terms of execution time (in seconds).. [Total time: ' + str(overall_time) + ' seconds]'
if ascii_graph:
graph = Pyasciigraph()
for line in graph.graph('', gdata):
print line
else:
for line in gdata:
print line[0] + "\t" + str(line[1])
if report_file != None:
with open(report_file, "w") as f:
f.write('Top ' + str(top_k) + ' testsuite in terms of execution time (in seconds).. [Total time: ' + str(overall_time) + ' seconds]\n')
for line in gdata:
f.write(line[0] + "\t" + str(line[1]) + "\n")
def graph_intervals(tl_videos, interval=timedelta(hours=1)):
"""
Plot ascii frequency of photos per bin
"""
bins = {}
for video in tl_videos:
# round bin start
start = prev_mark(interval, video.start)
end = next_mark(interval, video.end)
# generate a list of marks
video_extents = list(
rrule(SECONDLY,
dtstart=start,
until=end,
interval=int(interval.total_seconds())))
for bin_start in video_extents:
images_in_slice = [
im for im in video.images
if bin_start <= im.taken < bin_start + interval
]
bins[bin_start] = len(images_in_slice)
graphable = []
for h in sorted(bins):
# print("{}:{}".format(h,freq[h]))
graphable.append(tuple((h.isoformat(), bins[h])))
# print (graphable)
graph = Pyasciigraph()
for line in graph.graph('Frequency per {}'.format(interval), graphable):
print(line)
def graph_thresholds(test_data):
# H color test
# Multicolor on one line
print('\nMultiColor example:')
# Color lines according to Thresholds
thresholds = {
51: Gre,
100: Blu,
350: Yel,
500: Red,
}
data = hcolor(test_data, thresholds)
# graph with colors, power of 1000, different graph symbol,
# float formatting and a few tweaks
graph = Pyasciigraph(
line_length=120,
min_graph_length=50,
separator_length=4,
multivalue=True,
human_readable='si',
graphsymbol='*', # comment out if you want to use solid bars
float_format='{0:,.2f}',
force_max_value=2000,
)
for line in graph.graph(label='With Thresholds', data=data):
print(line)
return graph, data
def twitterstat(account, tweetid):
d = webdriver.Remote(command_executor="http://127.6.138.129:15002", desired_capabilities=webdriver.DesiredCapabilities.PHANTOMJS)
L = "https://twitter.com/"+account+"/status/"+tweetid
d.get(L)
soup = BeautifulSoup(d.page_source)
try:
tweet = soup.find('p', {'class':'TweetTextSize TweetTextSize--26px js-tweet-text tweet-text'}).text
retweets = soup.find('ul', {'class':'stats'}).find('li', {'class':'js-stat-count js-stat-retweets stat-count'}).find('a').find('strong').text
likes = soup.find('ul', {'class':'stats'}).find('li', {'class':'js-stat-count js-stat-favorites stat-count'}).find('a').find('strong').text
if "," in retweets:
retweets = retweets.replace(',', '')
if "," in likes:
likes = likes.replace(',', '')
chart = [('retweets', int(retweets)), ('likes', int(likes))]
gr = Pyasciigraph()
show = gr.graph(tweet,chart)
return "\033[1;31m%s\n\033[1;34m%s\n%s\033[m\n" %(show[0], show[2], show[3])
except:
try:
tweet = soup.find('p', {'class':'TweetTextSize TweetTextSize--26px js-tweet-text tweet-text'}).text
return "\033[1;31m%s\033[m\n" %tweet
except:
return "\033[1;31mCould not find tweet\033[m\n"
def print_graph(dataset, title):
graph = Pyasciigraph(
separator_length=4,
multivalue=False,
human_readable='si',
)
chart = []
keys = sorted(dataset.keys())
mean = np.mean(list(dataset.values()))
# median = np.median(list(dataset.values()))
for key in keys:
chart.append((key, dataset[key]))
if (not args.no_color):
thresholds = {
int(mean): Gre,
int(mean * 2): Yel,
int(mean * 3): Red,
}
data = hcolor(chart, thresholds)
else:
data = chart
for line in graph.graph(title, data):
print(line)
def test_human_readable_si(self):
test = [('long_labe☭', 1234), ('sl', 1231234), ('line3', 1231231234),
('line4', 1231231231234), ('line5', 1231231231231234),
('line6', 1231231231231231234),
('line7', 1231231231231231231234),
('line8', 1231231231231231231231234),
('line9', 123231231231231231231231234)]
graph = Pyasciigraph(human_readable='si')
res = graph.graph('☭test print', test)
expected = [
'☭test print',
'###############################################################################',
' 1K long_labe☭',
' 1M sl ',
' 1G line3 ',
' 1T line4 ',
' 1P line5 ',
' 1E line6 ',
' 1Z line7 ',
' 1Y line8 ',
'█████████████████████████████████████████████████████████████ 123Y line9 ',
]
gprint(res)
gprint(expected)
assert res == expected
def iotop_output_write(self):
count = 0
limit = self._arg_limit
graph = Pyasciigraph()
values = []
for tid in sorted(self.state.tids.values(),
key=operator.attrgetter('write'), reverse=True):
if not self.filter_process(tid):
continue
info_fmt = "{:>10} {:<25} {:>9} file {:>9} net {:>9} unknown "
values.append((info_fmt.format(
common.convert_size(tid.write, padding_after=True),
"%s (%d)" % (tid.comm, tid.pid),
common.convert_size(tid.disk_write,
padding_after=True),
common.convert_size(tid.net_write,
padding_after=True),
common.convert_size(tid.unk_write,
padding_after=True)),
tid.write))
count = count + 1
if limit > 0 and count >= limit:
break
for line in graph.graph('Per-process I/O Write', values,
with_value=False):
print(line)
def plot(self):
graph = Pyasciigraph()
print()
for line in graph.graph(self.name, list(self.data.items())):
print(line)
print()
print("-" * 80)
def getPorts():
print "Distinct ports attacked: " + executeQuery("db.session.distinct('destination_port').length")
if verbose or veryVerbose:
portList = executeQuery("db.session.aggregate({\$group:{_id:'\$destination_port','count':{\$sum:1}}},{\$sort:{count:-1}}).forEach(function(x){printjson(x)})").split('\n')
for pair in portList:
match = re.search(r'"_id" : (\d+), "count" : (\d+) }',pair)
if match:
countByPort[match.group(1)] = int(match.group(2))
print figlet_format('Ports', font='small')
graph = Pyasciigraph()
for line in graph.graph('', sorted(countByPort.items(), key=operator.itemgetter(1), reverse=True)):
print(line)
print
else:
portList = executeQuery("db.session.aggregate({\$group:{_id:'\$destination_port','count':{\$sum:1}}},{\$sort:{count:-1}},{\$limit:10}).forEach(function(x){printjson(x)})").split('\n')
for pair in portList:
match = re.search(r'"_id" : (\d+), "count" : (\d+) }',pair)
if match:
countByPort[match.group(1)] = int(match.group(2))
print figlet_format('Ports ( Top 10 )', font='small')
graph = Pyasciigraph()
for line in graph.graph('', sorted(countByPort.items(), key=operator.itemgetter(1), reverse=True)):
print(line)
print
def _print_results(self, begin_ns, end_ns, final=0):
count = 0
limit = self._arg_limit
graph = Pyasciigraph()
values = []
self.state = self._automaton.state
alloc = 0
freed = 0
print('Timerange: [%s, %s]' %
(common.ns_to_hour_nsec(
begin_ns, gmt=self._arg_gmt, multi_day=True),
common.ns_to_hour_nsec(
end_ns, gmt=self._arg_gmt, multi_day=True)))
for tid in sorted(self.state.tids.values(),
key=operator.attrgetter('allocated_pages'),
reverse=True):
if not self.filter_process(tid):
continue
values.append(
("%s (%d)" % (tid.comm, tid.tid), tid.allocated_pages))
count = count + 1
if limit > 0 and count >= limit:
break
for line in graph.graph("Per-TID Memory Allocations",
values,
unit=" pages"):
print(line)
values = []
count = 0
for tid in sorted(self.state.tids.values(),
key=operator.attrgetter('freed_pages'),
reverse=True):
if not self.filter_process(tid):
continue
values.append(("%s (%d)" % (tid.comm, tid.tid), tid.freed_pages))
count = count + 1
freed += tid.freed_pages
if limit > 0 and count >= limit:
break
for line in graph.graph("Per-TID Memory Deallocation",
values,
unit=" pages"):
print(line)
for tid in sorted(self.state.tids.values(),
key=operator.attrgetter('allocated_pages'),
reverse=True):
if not self.filter_process(tid):
continue
alloc += tid.allocated_pages
for tid in sorted(self.state.tids.values(),
key=operator.attrgetter('freed_pages'),
reverse=True):
if not self.filter_process(tid):
continue
freed += tid.freed_pages
print("\nTotal memory usage:\n- %d pages allocated\n- %d pages freed" %
(alloc, freed))
def synthesize_trials(block: Block) -> List[dict]:
# TODO: Do this in separate thread, and output some kind of progress indicator.
json_data = __generate_json_request(block)
solutions = cast(List[dict], [])
# Make sure the local image is up-to-date.
update_docker_image("sweetpea/server")
# 1. Start a container for the sweetpea server, making sure to use -d and -p to map the port.
container = start_docker_container("sweetpea/server", 8080)
# 2. POST to /experiments/generate using the backend request json as the body.
# TOOD: Do this in separate thread, and output some kind of progress indicator.
print("Sending formula to backend... ", end='', flush=True)
t_start = datetime.now()
try:
__check_server_health()
experiments_request = requests.post(
'http://localhost:8080/experiments/generate', data=json_data)
if experiments_request.status_code != 200 or not experiments_request.json(
)['ok']:
tmp_filename = ""
with tempfile.NamedTemporaryFile(delete=False) as f:
f.write(str.encode(json_data))
tmp_filename = f.name
raise RuntimeError(
"Received non-200 response from experiment generation! LowLevelRequest body saved to temp file '"
+ tmp_filename + "' status_code=" +
str(experiments_request.status_code) + " response_body=" +
str(experiments_request.text))
solutions = experiments_request.json()['solutions']
t_end = datetime.now()
print(str((t_end - t_start).seconds) + "s")
# 3. Stop and then remove the docker container.
finally:
stop_docker_container(container)
# 4. Decode the results
result = list(map(lambda s: __decode(block, s['assignment']), solutions))
# Dump histogram of frequency distribution, just to make sure it's somewhat even.
print()
print("Found " + str(len(solutions)) + " distinct solutions.")
print()
hist_data = [("Solution #" + str(idx + 1), sol['frequency'])
for idx, sol in enumerate(solutions)]
hist_data.sort(key=lambda tup: tup[1], reverse=True)
graph = Pyasciigraph()
for line in graph.graph('Most Frequently Sampled Solutions',
hist_data[:15]):
print(line)
return result
def makeGraph(fList):
docs = 0
vids = 0
songs = 0
images = 0
others = 0
compressed = 0
codess = 0
ll = len(fList)
if (oss == 1):
print("Total no of files in system: ", ll)
else:
print("Total no of files in user home: ", ll)
for file in fList:
if file.name.lower().endswith('.pdf') or file.name.lower().endswith(
'.docx') or file.name.lower().endswith(
'.doc') or file.name.lower().endswith('.txt'):
docs += 1
if file.name.lower().endswith('.mp4') or file.name.endswith(
'.mkv') or file.name.endswith('.avi'):
vids += 1
if file.name.lower().endswith('.jpeg') or file.name.endswith(
'.png') or file.name.endswith('.jpg') or file.name.endswith(
'.gif'):
images += 1
if file.name.lower().endswith('.mp3') or file.name.endswith(
'.ogg') or file.name.endswith('.wav'):
songs += 1
if file.name.endswith('.apk') or file.name.endswith(
'.jar') or file.name.endswith('.exe') or file.name.endswith(
'.iso') or file.name.endswith(
'.dmg') or file.name.endswith(
'.csv') or file.name.endswith(
'.log') or file.name.endswith('.db'):
others += 1
if file.name.lower().endswith('.zip') or file.name.endswith(
'.7z') or file.name.endswith('.deb') or file.name.endswith(
'.tar.gz') or file.name.endswith('.rpm'):
compressed += 1
if file.name.endswith('.c') or file.name.endswith(
'.py') or file.name.endswith('.java') or file.name.endswith(
'.cpp'):
codess += 1
data = [('docs', docs), ('songs', songs), ('videos', vids),
('images', images), ('codes', codess), ("compressed", compressed),
('others', others)]
pattern = [Gre, Yel, Red]
data = vcolor(data, pattern)
graph = Pyasciigraph()
for line in graph.graph('Files on PC', data):
print(line)
def histogram(data, name):
name = 'count of %s response time by week' % name
g = Pyasciigraph()
buckets = defaultdict(int)
for item in data:
buckets[int(item // (86400 * 7))] += 1
for line in g.graph(name, ((k, v) for k, v in buckets.iteritems())):
print line
def print_distribution_graph(data, title):
y = np.bincount(data)
ii = np.nonzero(y)[0]
dist = [(str(x[0]), x[1]) for x in zip(ii, y[ii])]
graph = Pyasciigraph(human_readable='si')
for line in graph.graph(title, dist):
print line
print ""
def print_distribution_graph(data, title):
y = np.bincount(data)
ii = np.nonzero(y)[0]
dist = [(str(x[0]), x[1]) for x in zip(ii,y[ii])]
graph = Pyasciigraph(human_readable='si')
for line in graph.graph(title, dist):
print line
print ""
def histogram(data, name):
name = 'count of %s response time by week' % name
g = Pyasciigraph()
buckets = defaultdict(int)
for item in data:
buckets[int(item // (86400 * 7))] += 1
for line in g.graph(name, ((k, v) for k, v in buckets.iteritems())):
print line
def output_latencies(self, args):
graph = Pyasciigraph()
for proc in self.latency_hist.keys():
values = []
for v in self.latency_hist[proc]:
values.append(("%s" % (v[0]), v[1]))
for line in graph.graph('%s requests latency (ms)' % proc, values,
unit=" ms"):
print(line)
def validate(pred, min_period, max_period):
graph = Pyasciigraph()
num_count = 0
hit_count = 0
spend_count = 0
earned_count = 0
earned_cash = 0
earned_set = list()
graph_data = defaultdict(int)
for target_period in xrange(min_period, max_period + 1):
dataset_begin = min_period
dataset_end = target_period - 1
if dataset_begin > dataset_end:
continue
result = p.predict(target_period=target_period, dataset_begin=dataset_begin, dataset_end=dataset_end)
actual_numbers = set(all_data[target_period]['numbers'])
predicted_numbers = set(result['numbers'])
hit_numbers = actual_numbers & predicted_numbers
m_count = len(predicted_numbers)
h_count = len(hit_numbers)
num_count += m_count
hit_count += h_count
if m_count > 0 and m_count <= 10:
spend_count += 1
if (h_count, m_count) in reward_table:
earned_count += 1
earned_cash += reward_table[(h_count, m_count)]
earned_set.append((h_count, m_count))
hour = '%s:00' % all_data[target_period]['time'].split(':')[0]
graph_data[hour] += 1
print 'predictor: %s' % p.get_name()
for line in graph.graph('', graph_data.items(), sort=2):
print line.encode('UTF-8')
if num_count == 0:
print 'hit rate: N/A'
else:
print 'hit rate: %.6f (%d / %d)' % ((float(hit_count) / num_count), hit_count, num_count)
if spend_count == 0:
print 'C/P: N/A'
else:
print 'C/P: %.6f (%d / %d)' % ((float(earned_count) / spend_count), earned_count, spend_count)
print 'earned set: %s' % earned_set
print 'spend: %d NTD' % (spend_count * 25)
print 'earned cash: %d NTD' % earned_cash
print
def output_latencies(self, args):
graph = Pyasciigraph()
for proc in self.latency_hist.keys():
values = []
for v in self.latency_hist[proc]:
values.append(("%s" % (v[0]), v[1]))
for line in graph.graph('%s requests latency (ms)' % proc,
values,
unit=" ms"):
print(line)
def print_stats_diagram(self, total_entries):
data = []
graph = Pyasciigraph(separator_length=4)
for resolver_name in sorted(self.resolver_names):
item = (resolver_name, self.statistics[resolver_name])
data.append(item)
item = ('TOTAL', total_entries)
data.append(item)
for line in graph.graph('Blocking Statistics:', data):
print(line)
def iotop_output_nr_sector(self, args):
graph = Pyasciigraph()
values = []
for disk in sorted(self.state.disks.values(),
key=operator.attrgetter('nr_sector'), reverse=True):
if disk.nr_sector == 0:
continue
values.append((disk.prettyname, disk.nr_sector))
for line in graph.graph('Disk nr_sector', values, unit=" sectors"):
print(line)
def test_type_output(self):
test = [('long_labe☭', 423), ('sl', 1234), ('line3', 531), ('line4', 200), ('line5', 834)]
graph = Pyasciigraph()
res = graph.graph('test print', test)
if sys.version < '3':
expected = unicode
else:
expected = str
for line in res:
assert type(line) == expected
def print_graph(header, data, is_bytes=False):
graph = Pyasciigraph(float_format='{:,.1f}',
min_graph_length=20,
separator_length=1,
line_length=shutil.get_terminal_size(
(DEFAULT_TERMINAL_WIDTH, 20)).columns,
human_readable='cs' if is_bytes else None)
for line in graph.graph(header, data):
print(line)
print()
def iotop_output_nr_sector(self):
graph = Pyasciigraph()
values = []
for disk in sorted(self.state.disks.values(),
key=operator.attrgetter('nr_sector'), reverse=True):
if disk.nr_sector == 0:
continue
values.append((disk.prettyname, disk.nr_sector))
for line in graph.graph('Disk nr_sector', values, unit=" sectors"):
print(line)
def output_net_sent_bytes(self, args):
count = 0
graph = Pyasciigraph()
values = []
for iface in sorted(self.ifaces.values(),
key=operator.attrgetter('send_bytes'), reverse=True):
values.append(("%s %s" % (convert_size(iface.send_bytes), iface.name),
iface.send_bytes))
for line in graph.graph('Network sent_bytes', values):
print(line)
def test_type_output(self):
test = [('long_labe☭', 423), ('sl', 1234), ('line3', 531), ('line4', 200), ('line5', 834)]
graph = Pyasciigraph()
res = graph.graph('test print', test)
if sys.version < '3':
expected = unicode
else:
expected = str
for line in res:
assert type(line) == expected
def print_histogram(data, label=''):
# Work around a bug in ascii_graph.
# https://github.com/kakwa/py-ascii-graph/issues/3
histogram = [(str(key), value) \
for (key, value) \
in data]
graph = Pyasciigraph()
for line in graph.graph(label, histogram):
# Encode explicitly to get around this bug:
# https://github.com/kakwa/py-ascii-graph/issues/4
print line.encode('utf-8')
def output_nr_requests(self, args):
count = 0
graph = Pyasciigraph()
values = []
for disk in sorted(self.disks.values(),
key=operator.attrgetter('nr_requests'), reverse=True):
if disk.nr_sector == 0:
continue
values.append((disk.prettyname, disk.nr_requests))
for line in graph.graph('Disk nr_requests', values):
print(line)
def hist(data, label):
data, outliers = reject_outliers(data)
outlier_msg = "{} outliers rejected: {}"
outlier_str = ["{:.3f}".format(x) for x in sorted(list(outliers))]
# print(outlier_msg.format(len(outliers), outlier_str))
count, division = np.histogram(data, bins=8)
hist_data = [(str(d), c) for d, c in zip(division, count)]
graph = Pyasciigraph()
for line in graph.graph(label, hist_data):
print(line)
print()
def print_histogram(data, label=''):
# Work around a bug in ascii_graph.
# https://github.com/kakwa/py-ascii-graph/issues/3
histogram = [(str(key), value) \
for (key, value) \
in data]
graph = Pyasciigraph()
for line in graph.graph(label, histogram):
# Encode explicitly to get around this bug:
# https://github.com/kakwa/py-ascii-graph/issues/4
print line.encode('utf-8')
def getHoneypots():
honeypotList = executeQuery("db.session.aggregate({\$group:{_id:'\$honeypot','count':{\$sum:1}}},{\$sort:{count:-1}}).forEach(function(x){printjson(x)})").split('\n')
for pair in honeypotList:
match = re.search(r'"_id" : "(.*)", "count" : (\d+) }',pair)
if match:
attacksByHoneypot[match.group(1)] = int(match.group(2))
print figlet_format('Honeypots', font='small')
graph = Pyasciigraph()
for line in graph.graph('', sorted(attacksByHoneypot.items(), key=operator.itemgetter(1), reverse=True)):
print(line)
print
def __repr__(self):
self.days, self.workdays = Utils.get_days(self.year, self.month)
today = date.today()
now = datetime.now()
start_of_month = datetime(self.year, self.month, 1, 0, 0, 0)
seconds_of_month_passed = (now - start_of_month).total_seconds()
total_seconds_of_month = len(self.days) * 24 * 60 * 60
percentage_of_month_gone = seconds_of_month_passed / total_seconds_of_month
total_workdays = len(self.workdays)
current_hours = self.report.get_durations_by_day(self.report.facts)[1]
total_needed_hours = Utils.calculate_needed_hours(
self.year, self.month)
if current_hours == 0:
percentage_of_workhours_done = 0
else:
percentage_of_workhours_done = current_hours / total_needed_hours
status_relative = (percentage_of_workhours_done -
percentage_of_month_gone)
status_absolute = status_relative * 100 * (total_needed_hours / 100)
status_absolute = "{:.1f} h {}".format(
abs(status_absolute),
"ahead" if status_absolute >= 0 else "behind")
graph = Pyasciigraph(float_format='{0:.1%}',
graphsymbol='֍',
line_length=20)
graph = "\n ".join(
graph.graph(None, [("Passed", percentage_of_month_gone),
("Fulfilled", percentage_of_workhours_done)]))
data = dict(
month=today.strftime("%B %Y"),
total_workdays=total_workdays,
current_hours=current_hours,
total_needed_hours=total_needed_hours,
needed_hours_left=total_needed_hours - current_hours,
percentage_of_workhours_done=percentage_of_workhours_done,
percentage_of_month_gone=percentage_of_month_gone,
graph=graph,
status_absolute=status_absolute,
status_relative=status_relative,
)
return """
{month}:
-----------------------------------------------------
Workdays: {total_workdays:3}
Hours: {current_hours:.1f} / {total_needed_hours} ({needed_hours_left:.1f} left)
Status: {status_absolute} | {status_relative:+.1%}
{graph}
""".format(**data)
def iotop_output_net_recv_bytes(self, args):
graph = Pyasciigraph()
values = []
for iface in sorted(self.state.ifaces.values(),
key=operator.attrgetter('recv_bytes'),
reverse=True):
values.append(("%s %s" % (convert_size(iface.recv_bytes),
iface.name),
iface.recv_bytes))
for line in graph.graph('Network recv_bytes', values,
with_value=False):
print(line)
def test_mulivalue_color_graphs(self):
test = [('testval0', 600),
('testval1', 400, Red),
('testval2', [(300, Gre),(500, Blu)]),
('testval3', [(200, Yel),(100,)]),
('testval4', 100, Cya),
('testval5', 50, Blu),
('testval6', [(100, Gre), (150, Red), (200, Yel), (600, Blu)]) ]
graph = Pyasciigraph(separator_length=4)
res = graph.graph('test graph', test)
expected = ['test graph', '#################################################################################', '\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588 600 testval0', '\x1b[0;31m\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588 \x1b[0m \x1b[0;31m400\x1b[0m testval1', '\x1b[0;32m\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\x1b[0m\x1b[0;34m\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588 \x1b[0m \x1b[0;32m300\x1b[0m,\x1b[0;34m500\x1b[0m testval2', '\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\x1b[0;33m\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588 \x1b[0m \x1b[0;33m200\x1b[0m,100 testval3', '\x1b[0;36m\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588 \x1b[0m \x1b[0;36m100\x1b[0m testval4', '\x1b[0;34m\u2588\u2588\u2588\u2588 \x1b[0m \x1b[0;34m50\x1b[0m testval5', '\x1b[0;32m\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\x1b[0m\x1b[0;31m\u2588\u2588\u2588\u2588\x1b[0m\x1b[0;33m\u2588\u2588\u2588\u2588\x1b[0m\x1b[0;34m\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588 \x1b[0m\x1b[0;32m100\x1b[0m,\x1b[0;31m150\x1b[0m,\x1b[0;33m200\x1b[0m,\x1b[0;34m600\x1b[0m testval6']
assert res == expected
def iotop_output_net_sent_bytes(self):
graph = Pyasciigraph()
values = []
for iface in sorted(self.state.ifaces.values(),
key=operator.attrgetter('send_bytes'),
reverse=True):
values.append(("%s %s" % (common.convert_size(iface.send_bytes),
iface.name),
iface.send_bytes))
for line in graph.graph('Network sent_bytes', values,
with_value=False):
print(line)
def output_dev_latency(self, args):
count = 0
graph = Pyasciigraph()
values = []
for disk in self.disks.values():
if disk.completed_requests == 0:
continue
total = (disk.request_time / disk.completed_requests) / MSEC_PER_NSEC
total = float("%0.03f" % total)
values.append(("ms %s" % disk.prettyname, total))
for line in graph.graph('Disk request time/sector', values, sort=2):
print(line)
def test_no_label(self):
test = [(1, 423), (2, 1234), (3, 531), ('line4', 200), ('line5', 834)]
graph = Pyasciigraph()
res = graph.graph(data=test)
expected = [
'██████████████████████ 423 1 ',
'██████████████████████████████████████████████████████████████████ 1234 2 ',
'████████████████████████████ 531 3 ',
'██████████ 200 line4',
'████████████████████████████████████████████ 834 line5',
]
assert res == expected
def print_histogram(data, label=''):
# Fill in percentages of the total.
for key, datapoint in enumerate(data):
name, value = datapoint
percentage = (float(value) / stats['count']) * 100 if stats['count'] else 0
name = '(%6.2f%%) %s' % (percentage, name)
data[key] = (name, value)
graph = Pyasciigraph()
for line in graph.graph(label, data):
# Encode explicitly to get around this bug:
# https://github.com/kakwa/py-ascii-graph/issues/4
print line.encode('utf-8')
def test_color_graphs(self):
test = [('testval0', 142),
('testval1', 204, BPur),
('testval2', 501, URed),
('testval3', 103, IRed),
('testval4', 29, BIGre),
('testval5', 19, UYel),
('testval6', 99, ICya),
('testval7', 404, BBlu)]
graph = Pyasciigraph()
res = graph.graph('test graph', test)
expected = ['test graph', '###############################################################################', '\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588 142 testval0', '\x1b[1;35m\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588 \x1b[0m\x1b[1;35m204\x1b[0m testval1', '\x1b[4;31m\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588 \x1b[0m\x1b[4;31m501\x1b[0m testval2', '\x1b[0;91m\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588 \x1b[0m\x1b[0;91m103\x1b[0m testval3', '\x1b[1;92m\u2588\u2588\u2588 \x1b[0m \x1b[1;92m29\x1b[0m testval4', '\x1b[4;33m\u2588\u2588 \x1b[0m \x1b[4;33m19\x1b[0m testval5', '\x1b[0;96m\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588 \x1b[0m \x1b[0;96m99\x1b[0m testval6', '\x1b[1;34m\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588 \x1b[0m\x1b[1;34m404\x1b[0m testval7']
assert res == expected
def twitteruser(account):
d = webdriver.Remote(command_executor="http://127.6.138.129:15002", desired_capabilities=webdriver.DesiredCapabilities.PHANTOMJS)
L = "https://twitter.com/"+account
d.get(L)
soup = BeautifulSoup(d.page_source, "html.parser")
try:
try:
name = soup.find('a', {'class': 'ProfileHeaderCard-nameLink u-textInheritColor js-nav'}).text
#print 'name'
if soup.find('span', {'class': 'js-display-url'}):
desc = soup.find('span', {'class': 'js-display-url'}).text
#print 'desc'
else:
desc = 'Too lazy to write'
if soup.find('span', {'class':'ProfileHeaderCard-locationText u-dir'}):
location = soup.find('span', {'class':'ProfileHeaderCard-locationText u-dir'}).text
#print 'location'
else:
location = 'Probably in Mars'
if soup.find('span', {'class':'ProfileHeaderCard-joinDateText js-tooltip u-dir'}):
joined = soup.find('span', {'class':'ProfileHeaderCard-joinDateText js-tooltip u-dir'}).text
#print 'joined'
else:
joined = 'The beginning of time'
tweets = soup.find('li', {'class': 'ProfileNav-item--tweets'}).find('span', {"class":"ProfileNav-value"}).text
following = soup.find('li', {'class':'ProfileNav-item--following'}).find('span', {"class":"ProfileNav-value"}).text
followers = soup.find('li', {'class':'ProfileNav-item--followers'}).find('span', {"class":"ProfileNav-value"}).text
likes = soup.find('li', {'class':'ProfileNav-item--favorites'}).find('span', {"class":"ProfileNav-value"}).text
except:
return 'This is new, note the account and send it to me @m4d_d3v'
if ',' in tweets.split()[0] or following.split()[0] or followers.split()[0] or likes.split()[0]:
tweets = tweets.replace(',', '')
following = following.replace(',', '')
followers = followers.replace(',', '')
likes = likes.replace(',', '')
table = [['Name', name], ['Description', desc], ['Location', location], ['Joined', joined]]
chart = [('tweets', int(tweets.split()[0])), ('following', int(following.split()[0])), ('followers', int(followers.split()[0])), ('likes', int(likes.split()[0]))]
gr = Pyasciigraph()
show = gr.graph('Stats',chart)
return "\033[1;34m%s\n\n%s\n%s\n%s\n%s\n%s\n\033[m\n" %(tabulate(table), show[0], show[2], show[3], show[4], show[5])
except:
return "\033[1;31mCould not find user\033[m\n"
def ascii_funnel(info, funnel_data):
"""Return ascii graph by funnel data.
Parameters
----------
info: string
funnel_data: list of tuple
Returns list of ascii string.
-------
"""
graph = Pyasciigraph()
return graph.graph(info, funnel_data)
def test_alternate_graphsymbol(self):
test = [('long_labe☭', 423), ('sl', 1234), ('line3', 531), ('line4', 200), ('line5', 834)]
graph = Pyasciigraph(graphsymbol='*')
res = graph.graph('☭test print', test)
expected = [
'☭test print',
'###############################################################################',
'******************** 423 long_labe☭',
'************************************************************* 1234 sl ',
'************************** 531 line3 ',
'********* 200 line4 ',
'***************************************** 834 line5 ',
]
assert res == expected
def test_unsorted_default_params(self):
test = [('long_labe☭', 423), ('sl', 1234), ('line3', 531), ('line4', 200), ('line5', 834)]
graph = Pyasciigraph()
res = graph.graph('☭test print', test)
expected = [
'☭test print',
'###############################################################################',
'████████████████████ 423 long_labe☭',
'█████████████████████████████████████████████████████████████ 1234 sl ',
'██████████████████████████ 531 line3 ',
'█████████ 200 line4 ',
'█████████████████████████████████████████ 834 line5 ',
]
assert res == expected
def test_float_format(self):
test = [('long_labe☭', 423.197), ('sl', 1234.12341), ('line3', 531.11), ('line4', 200), ('line5', 834)]
graph = Pyasciigraph(float_format='{0:,.2f}')
res = graph.graph('☭test print', test)
expected = [
'☭test print',
'###############################################################################',
'███████████████████ 423.20 long_labe☭',
'█████████████████████████████████████████████████████████ 1,234.12 sl ',
'████████████████████████ 531.11 line3 ',
'█████████ 200.00 line4 ',
'██████████████████████████████████████ 834.00 line5 ',
]
assert res == expected
def test_zeros(self):
test = [('long_labe☭', 0), ('sl', 0), ('line3', 0), ('line4', 0), ('line5', 0)]
graph = Pyasciigraph()
res = graph.graph('☭test print', test)
expected = [
'☭test print',
'###############################################################################',
' 0 long_labe☭',
' 0 sl ',
' 0 line3 ',
' 0 line4 ',
' 0 line5 ',
]
assert res == expected
def getPasswords():
print "Unique passwords: " + executeQuery("db.session.distinct('auth_attempts.password').length")
if verbose or veryVerbose:
passwordList = executeQuery("db.session.aggregate([{\$unwind:'\$auth_attempts'},{\$group:{_id:'\$auth_attempts.password','count':{\$sum:1}}},{\$sort:{count:-1}}]).forEach(function(x){printjson(x)})").split('\n')
for pair in passwordList:
match = re.search(r'"_id" : "(.*)", "count" : (\d+) }',pair)
if match:
countByPassword[match.group(1)] = int(match.group(2))
print figlet_format('Passwords', font='small')
graph = Pyasciigraph()
for line in graph.graph('', sorted(countByPassword.items(), key=operator.itemgetter(1), reverse=True)):
print(line)
print
else:
passwordList = executeQuery("db.session.aggregate([{\$unwind:'\$auth_attempts'},{\$group:{_id:'\$auth_attempts.password','count':{\$sum:1}}},{\$sort:{count:-1}},{\$limit:10}]).forEach(function(x){printjson(x)})").split('\n')
for pair in passwordList:
match = re.search(r'"_id" : "(.*)", "count" : (\d+) }',pair)
if match:
countByPassword[match.group(1)] = int(match.group(2))
print figlet_format('Passwords ( Top 10 )', font='small')
graph = Pyasciigraph()
for line in graph.graph('', sorted(countByPassword.items(), key=operator.itemgetter(1), reverse=True)):
print(line)
print
