def graph(metric, agent, tag, resolution, period):
"""graphs things"""
try:
if not agent and not tag:
click.echo('Specify an agent or tag to get the metrics')
sys.exit(1)
if agent:
agent_id = None
agent_details = agents_api.get_agents(**context.settings)
for a in agent_details:
if a['name'] == agent:
agent_id = a['id']
for s in series_api.get_agent_series(agent_id=agent_id,
metric=metric,
resolution=resolution,
period=period,
**context.settings):
points = []
for point in s['points']:
if point['type'] == 'boolean':
if point['all']:
points.append(0)
else:
points.append(2)
else:
points.append(point['avg'])
print "Min: %d Max: %d Avg: %d %s " % (
min(points), max(points), sum(points) / len(points),
sparkline.sparkify(points).encode('utf-8'))
if tag:
for s in series_api.get_tag_series(tag=tag,
metric=metric,
resolution=resolution,
period=period,
**context.settings):
points = []
click.echo(click.style(s['source']['name'], fg='green'))
for point in s['points']:
if point['type'] == 'boolean':
if point['all']:
points.append(0)
else:
points.append(2)
else:
points.append(point['avg'])
print "Min: %d Max: %d Avg: %d %s " % (
min(points), max(points), sum(points) / len(points),
sparkline.sparkify(points).encode('utf-8'))
except Exception, e:
print 'Graph failed. %s' % e
sys.exit(1)
def _print_conn_metrics(
conn, metrics, height=1, prefix="", auto_yaxis=True, file=sys.stdout
):
colors = [Fore.RED, Fore.CYAN, Fore.CYAN]
for name, get_values in metrics.items():
values = [value for timestamp, value in get_values()]
if name == "ConnectionState":
max_yaxis = 1
elif auto_yaxis:
max_yaxis = None
else:
max_yaxis = bps(conn["bandwidth"])
if height == 1:
chart = sparkify(values, minimum=0, maximum=max_yaxis)
print(prefix, end=" ", file=file)
elif height > 1:
opts = {
"minimum": 0,
"height": height,
"format": "{:14,.0f} ",
}
# The asciichartpy module is a bit wonky and not really idiomatic
# python as they just pass a giant dictionary of options (typical of
# javascript land). Do not provide a "maximum" key with a value of
# None. If use wants auto-scaling, don't provide the key at all.
if max_yaxis is not None:
opts["maximum"] = max_yaxis
chart = plot(values, opts)
print(_format_metric(name, chart, color=colors.pop()), file=file)
print(file=file)
def refresh(self, data):
self.win.border(0)
self.win.addstr(1, 1, 'FR {:<8.2f} []'.format(data[0]))
self.win.addstr(2, 1, 'FF {:<8.2f} []'.format(data[1]))
self.win.addstr(3, 1, 'FF {:<8.2f} []'.format(data[2]))
# self.win.addstr(4, 1, 'FL {:<8.2f} []'.format(data[3]))
self.win.addstr(4, 1, 'Battery {}'.format(sparkify([1.0, 2.0, 3.0, 2.5, 0.2, 1.0, 2.0, 3.0, 2.5, 0.2]).encode('utf-8')))
self.win.refresh()
def vmStates_update(self):
#this method performs the API call 'listVirtualMachines'
# Delete all current content
self.vmStatesText.delete(1.0, END)
request = {}
checkTime = datetime.datetime.utcnow(
) # get the current time (UTC = GMT)
try:
result = self.api.listVirtualMachines(request)
testdict = result['virtualmachine'][
0] #this should throw exception if dictionary lookup fails
except:
# something wrong with the API connection, show error message and exit
self.vmStatesText.insert(
'end', "*** Error: VM data not returned by API ***")
return
# Only data for Running VM will be added to cpuData
timenow = datetime.datetime.now()
self.cpuData.append([[vm['name'], [timenow,
self.get_cpuused(vm)]]
for vm in result['virtualmachine']
if vm['state'] == 'Running'])
vm_names = map(lambda x: x[0],
self.cpuData[0]) #create a list of VM names
data = sum(self.cpuData,
[]) # flattens data by removing some of the list brackets
self.vmStatesText.insert(
'end', "%d VMs in the account '%s'\nchecked at %s" %
(result['count'], result['virtualmachine'][1]['account'],
checkTime.strftime("%Y-%m-%d %H:%M:%S UTC")))
vmcounter = 0
for vm in result['virtualmachine']:
vmcounter = vmcounter + 1
if vm['state'] == 'Running':
data_per_vm = [d[1] for d in data if d[0] == vm['name']]
self.vmStatesText.insert(
'end', "\n [%2d] %s |%s|" %
(vmcounter, vm['name'],
sparkline.sparkify([d[1] for d in data_per_vm])),
('stateRunning'))
elif vm['state'] == 'Stopped':
self.vmStatesText.insert(
'end', "\n [%2d] %s (%s)" %
(vmcounter, vm['name'], vm['state']), ('stateStopped'))
else:
self.vmStatesText.insert(
'end', "\n [%2d] %s (%s)" %
(vmcounter, vm['name'], vm['state']), ('stateOther'))
#set callback to this method after plot_interval seconds
self.vmStatesText.after(self.plot_interval * 1000,
self.vmStates_update)
def print_results():
try:
highest_mem_usage = next(s for s in sorted(mem_usage, key=lambda x: x['mem_usage'], reverse=True))
except StopIteration:
highest_mem_usage = {"pid": os.getpid(), "timestamp": 0, "mem_usage": 0}
graph = sparkline.sparkify([m['mem_usage'] for m in mem_usage]).encode("utf-8")
print("PID: {pid} Highest memory usage: {mem_usage}MB. Usage over time: {sparkline}".format(sparkline=graph, **highest_mem_usage))
def print_results():
try:
highest_mem_usage = next(s for s in sorted(mem_usage, key=lambda x: x['mem_usage'], reverse=True))
except StopIteration:
highest_mem_usage = {"pid": os.getpid(), "timestamp": 0, "mem_usage": 0}
graph = sparkline.sparkify([m['mem_usage'] for m in mem_usage]).encode("utf-8")
print("PID: {pid} Highest memory usage: {mem_usage}MB. Usage over time: {sparkline}".format(sparkline=graph, **highest_mem_usage))
def print_sparkline(r, g, b):
# prints a sparkline, a small graph which shows the color levels of R, G, and B
spark = sparkline.sparkify([r, g, b])#.encode('utf-8')
r = round(r/(255/5.))
g = round(g/(255/5.))
b = round(b/(255/5.))
color_code = 16 + (r * 36) + (g * 6) + b
shape = u'\u25CF'
print colored(spark[0], 'red'), \
colored(spark[1], 'green'), \
colored(spark[2], 'blue'), \
'\x1b[38;5;%dm' % color_code, shape
help="text | json (default: text)",
default="text")
opts, args = opt_parser.parse_args()
profiler = Profiler({"extended": True, "blocks": ["all"]})
profiler.gettweets(opts, args)
data = profiler.report()
if (opts.output == "json"):
print data
else:
print "Count: " + "{:>9}".format(str(data["count"]))
print "Users: " + "{:>9}".format(str(data["usercount"]))
print "User percentiles: " + sparkline.sparkify(data["userspercentiles"])
print " " + str(data["userspercentiles"])
print "Has hashtag: " + "{:>9}".format(str(
data["hashtagcount"])) + " (" + str("%.2f" % (
float(data["hashtagcount"]) / float(data["count"]) * 100.0)) + "%)"
print "Hashtags: " + "{:>9}".format(str(data["hashtags"]))
print "Hashtags percentiles: " + sparkline.sparkify(
data["hashtagspercentiles"])
print " " + str(data["hashtagspercentiles"])
print "Has URL: " + "{:>9}".format(str(
data["urlcount"])) + " (" + str(
"%.2f" %
(float(data["urlcount"]) / float(data["count"]) * 100.0)) + "%)"
print "URLs: " + "{:>9}".format(str(data["urls"]))
print "URLs percentiles: " + sparkline.sparkify(data["urlspercentiles"])
print " " + str(data["urlspercentiles"])
def sparkify(difficulty):
return sparkline.sparkify(difficulty)
def graph(metric, agent, tag, resolution, period):
"""graphs things"""
try:
if not agent and not tag:
click.echo('Specify an agent or tag to get the metrics')
sys.exit(1)
if agent:
agent_id = None
agent_details = agents_api.get_agents(**context.settings)
for a in agent_details:
if a['name'] == agent:
agent_id = a['id']
for s in series_api.get_agent_series(agent_id=agent_id, metric=metric, resolution=resolution, period=period, **context.settings):
points = []
for point in s['points']:
if point['type'] == 'boolean':
if point['all']:
points.append(0)
else:
points.append(2)
else:
points.append(point['avg'])
print "Min: %d Max: %d Avg: %d %s " % (min(points), max(points), sum(points)/len(points), sparkline.sparkify(points).encode('utf-8'))
if tag:
for s in series_api.get_tag_series(tag=tag, metric=metric, resolution=resolution, period=period, **context.settings):
points = []
click.echo(click.style(s['source']['name'], fg='green'))
for point in s['points']:
if point['type'] == 'boolean':
if point['all']:
points.append(0)
else:
points.append(2)
else:
points.append(point['avg'])
print "Min: %d Max: %d Avg: %d %s " % (min(points), max(points), sum(points)/len(points), sparkline.sparkify(points).encode('utf-8'))
except Exception, e:
print 'Graph failed. %s' % e
sys.exit(1)
except ImportError:
print('install https://github.com/RedKrieg/pysparklines')
def display_sentence(sentence):
words = sentence.split()
if len(words) <= 20:
return sentence
fmt = '{} […] {}'
return fmt.format(' '.join(words[:10]), ' '.join(words[-10:]))
if __name__ == '__main__':
# pylint: disable=C0103
data = []
for line in fileinput.input():
sentence = line.strip()
data.append((sentence, len(sentence.split())))
data.sort(key=itemgetter(1), reverse=True)
separated = False
for s, l in data:
if l < 25 and not separated:
print(78*'-')
separated = True
print('{}{}'.format(str(l).ljust(5), display_sentence(s)))
lengths = [_[1] for _ in data]
if sparkline:
print(sparkline.sparkify(lengths))
import numpy as np
print('average: {:.1f}, std: {:.1f}'.format(np.mean(lengths),
np.std(lengths)))
def printInfo(self):
sensors = self.sensors['create']
imu = self.sensors['imu']
if sensors is None or imu is None:
print('No valid sensor info')
return
a, m, g = imu
now = time.time()
dt = self.last_time - now
beta = 0.5
q = self.ahrs.updateAGM(a, m, g, beta, dt)
r, p, y = quat2euler(q)
# self.data['r'].push(r)
# self.data['p'].push(p)
self.data['y'].push(y)
self.last_time = now
ir = []
for i in [36, 37, 38, 39, 40, 41]:
ir.append(sensors[i])
cliff = []
for i in [20, 21, 22, 23]:
cliff.append(sensors[i])
po = [
'--------------------------------------------------------',
' Light Bumper: {:6} {:6} {:6} L| {:6} |R {:6} {:6} {:6}'.format(
sensors.light_bumper_left,
sensors.light_bumper_front_left,
sensors.light_bumper_center_left,
sparkline.sparkify(ir).encode('utf-8'),
# '',
sensors.light_bumper_center_right,
sensors.light_bumper_front_right,
sensors.light_bumper_right),
' Cliff: {:6} {:6} L| {:4} |R {:6} {:6}'.format(
sensors.cliff_left_signal,
sensors.cliff_front_left_signal,
sparkline.sparkify(cliff).encode('utf-8'),
# '',
sensors.cliff_front_right_signal,
sensors.cliff_right_signal),
' Encoders: {:7} L|R {:7}'.format(sensors.encoder_counts_left,
sensors.encoder_counts_right),
' Distance Delta: {:8} mm Total: {:10.1f} m'.format(
sensors.distance, self.distance),
# ' Yaw: {:8.1f} {:30} degrees'.format(self.data['y'].get_last(), self.data['y'].spark()),
'--------------------------------------------------------',
' Power: {:6} mAhr [{:3} %]'.format(
sensors.battery_charge,
int(100.0 * sensors.battery_charge /
sensors.battery_capacity)),
' Voltage: {:7.1f} V Current: {:7.1f} A'.format(
sensors.voltage / 1000, sensors.current / 1000)
]
for s in po:
print(s)
def spark(self):
data = self.get_all()
return sparkline.sparkify(data).encode('utf-8')
if self.index > 0:
ret = self._data[self.index:self.size] + self._data[0:self.index]
else:
ret = self._data
return ret
def get_last(self):
return self._data[self.index - 1]
def get_first(self):
return self._data[self.index]
def spark(self):
data = self.get_all()
return sparkline.sparkify(data).encode('utf-8')
if __name__ == "__main__":
cb = CircularBuffer(60)
for i in range(200):
cb.push(i)
print(cb.get_all())
print('get cb[7]', cb[7])
print('get cb[0]', cb[0])
print('get last', cb.get_last())
print('ine', cb.get_last(),
sparkline.sparkify(cb.get_all()).encode('utf-8'))
print(cb.get_first(), cb.spark(), cb.get_last())
print("install https://github.com/RedKrieg/pysparklines")
def display_sentence(sentence):
words = sentence.split()
if len(words) <= 20:
return sentence
fmt = "{} […] {}"
return fmt.format(" ".join(words[:10]), " ".join(words[-10:]))
if __name__ == "__main__":
# pylint: disable=C0103
data = []
for line in fileinput.input():
sentence = line.strip()
data.append((sentence, len(sentence.split())))
data.sort(key=itemgetter(1), reverse=True)
separated = False
for s, l in data:
if l < 25 and not separated:
print(78 * "-")
separated = True
print("{}{}".format(str(l).ljust(5), display_sentence(s)))
lengths = [_[1] for _ in data]
if sparkline:
print(sparkline.sparkify(lengths))
import numpy as np
print("average: {:.1f}, std: {:.1f}".format(np.mean(lengths), np.std(lengths)))
