def compute_state(self, disk):
cur_time = time()
counters = None
if len(disk) == 0:
counters = psutil.disk_io_counters()
else:
counters = psutil.disk_io_counters(perdisk=True)
if self.prev_counters is None:
self.prev_counters = counters
self.prev_time = cur_time
return None
data = {}
if len(disk) == 0:
data["read_speed"] = humanize_bytes(
(counters.read_bytes - self.prev_counters.read_bytes) /
(cur_time - self.prev_time))
data["write_speed"] = humanize_bytes(
(counters.write_bytes - self.prev_counters.write_bytes) /
(cur_time - self.prev_time))
else:
if disk in counters.keys() and disk in self.prev_counters.keys():
data["read_speed"] = humanize_bytes(
(counters[disk].read_bytes -
self.prev_counters[disk].read_bytes) /
(cur_time - self.prev_time))
data["write_speed"] = humanize_bytes(
(counters[disk].write_bytes -
self.prev_counters[disk].write_bytes) /
(cur_time - self.prev_time))
self.prev_counters = counters
self.prev_time = cur_time
return data
def test_humanize_bytes(self): self.assertEqual(humanize_bytes(0), '0 B') self.assertEqual(humanize_bytes(1), '1 B') self.assertEqual(humanize_bytes(1, suffix='bit'), '1 bit') self.assertEqual(humanize_bytes(1000, si_prefix=True), '1 kB') self.assertEqual(humanize_bytes(1024, si_prefix=True), '1 kB') self.assertEqual(humanize_bytes(1000000000, si_prefix=True), '1.00 GB') self.assertEqual(humanize_bytes(1000000000, si_prefix=False), '953.7 MiB')
def test_humanize_bytes(self): self.assertEqual(humanize_bytes(0), '0 B') self.assertEqual(humanize_bytes(1), '1 B') self.assertEqual(humanize_bytes(1, suffix='bit'), '1 bit') self.assertEqual(humanize_bytes(1000, si_prefix=True), '1 kB') self.assertEqual(humanize_bytes(1024, si_prefix=True), '1 kB') self.assertEqual(humanize_bytes(1000000000, si_prefix=True), '1.00 GB') self.assertEqual(humanize_bytes(1000000000, si_prefix=False), '953.7 MiB')
def test_humanize_bytes(self):
self.assertEqual(humanize_bytes(0), "0 B")
self.assertEqual(humanize_bytes(1), "1 B")
self.assertEqual(humanize_bytes(1, suffix="bit"), "1 bit")
self.assertEqual(humanize_bytes(1000, si_prefix=True), "1 kB")
self.assertEqual(humanize_bytes(1024, si_prefix=True), "1 kB")
self.assertEqual(humanize_bytes(1000000000, si_prefix=True), "1.00 GB")
self.assertEqual(humanize_bytes(1000000000, si_prefix=False), "953.7 MiB")
def file_size(pl, suffix='B', si_prefix=False): '''Return file size in &encoding. :param str suffix: string appended to the file size :param bool si_prefix: use SI prefix, e.g. MB instead of MiB :return: file size or None if the file isn't saved or if the size is too big to fit in a number ''' # Note: returns file size in &encoding, not in &fileencoding. But returned # size is updated immediately; and it is valid for any buffer file_size = vim_funcs['line2byte'](len(vim.current.buffer) + 1) - 1 return humanize_bytes(file_size, suffix, si_prefix)
def file_size(pl, suffix='B', si_prefix=False):
'''Return file size in &encoding.
:param str suffix:
string appended to the file size
:param bool si_prefix:
use SI prefix, e.g. MB instead of MiB
:return: file size or None if the file isn't saved or if the size is too big to fit in a number
'''
# Note: returns file size in &encoding, not in &fileencoding. But returned
# size is updated immediately; and it is valid for any buffer
file_size = vim_funcs['line2byte'](len(vim.current.buffer) + 1) - 1
return humanize_bytes(file_size, suffix, si_prefix)
def render_one(self,
idata,
recv_format='⬇ {value:>8}',
sent_format='⬆ {value:>8}',
suffix='B/s',
si_prefix=False,
**kwargs):
if not idata or 'prev' not in idata:
return None
t1, b1 = idata['prev']
t2, b2 = idata['last']
measure_interval = t2 - t1
if None in (b1, b2):
return None
r = []
for i, key in zip((0, 1), ('recv', 'sent')):
format = locals()[key + '_format']
try:
value = (b2[i] - b1[i]) / measure_interval
except ZeroDivisionError:
self.warn('Measure interval zero.')
value = 0
max_key = key + '_max'
is_gradient = max_key in kwargs
hl_groups = ['network_load_' + key, 'network_load']
if is_gradient:
hl_groups[:0] = (group + '_gradient' for group in hl_groups)
r.append({
'contents':
format.format(value=humanize_bytes(value, suffix, si_prefix)),
'divider_highlight_group':
'background:divider',
'highlight_group':
hl_groups,
})
if is_gradient:
max = kwargs[max_key]
if value >= max:
r[-1]['gradient_level'] = 100
else:
r[-1]['gradient_level'] = value * 100.0 / max
return r
def render_one(
self, idata, recv_format="⬇ {value:>8}", sent_format="⬆ {value:>8}", suffix="B/s", si_prefix=False, **kwargs
):
if not idata or "prev" not in idata:
return None
t1, b1 = idata["prev"]
t2, b2 = idata["last"]
measure_interval = t2 - t1
if None in (b1, b2):
return None
r = []
for i, key in zip((0, 1), ("recv", "sent")):
format = locals()[key + "_format"]
try:
value = (b2[i] - b1[i]) / measure_interval
except ZeroDivisionError:
self.warn("Measure interval zero.")
value = 0
max_key = key + "_max"
is_gradient = max_key in kwargs
hl_groups = ["network_load_" + key, "network_load"]
if is_gradient:
hl_groups[:0] = (group + "_gradient" for group in hl_groups)
r.append(
{
"contents": format.format(value=humanize_bytes(value, suffix, si_prefix)),
"divider_highlight_group": "background:divider",
"highlight_group": hl_groups,
}
)
if is_gradient:
max = kwargs[max_key]
if value >= max:
r[-1]["gradient_level"] = 100
else:
r[-1]["gradient_level"] = value * 100.0 / max
return r
def render_one(self, idata, recv_format='⬇ {value:>8}', sent_format='⬆ {value:>8}', suffix='B/s', si_prefix=False, **kwargs):
if not idata or 'prev' not in idata:
return None
t1, b1 = idata['prev']
t2, b2 = idata['last']
measure_interval = t2 - t1
if None in (b1, b2):
return None
r = []
for i, key in zip((0, 1), ('recv', 'sent')):
format = locals()[key + '_format']
try:
value = (b2[i] - b1[i]) / measure_interval
except ZeroDivisionError:
self.warn('Measure interval zero.')
value = 0
max_key = key + '_max'
is_gradient = max_key in kwargs
hl_groups = ['network_load_' + key, 'network_load']
if is_gradient:
hl_groups[:0] = (group + '_gradient' for group in hl_groups)
r.append({
'contents': format.format(value=humanize_bytes(value, suffix, si_prefix)),
'divider_highlight_group': 'background:divider',
'highlight_group': hl_groups,
})
if is_gradient:
max = kwargs[max_key]
if value >= max:
r[-1]['gradient_level'] = 100
else:
r[-1]['gradient_level'] = value * 100.0 / max
return r
