def handle(self, *args, **options):
verbose = int(options.get('verbosity'))
interval = options.get('interval')
nstreams = options.get('nstreams')
types = options.get('types')
flush = options.get('flush')
demo = options.get('demo')
span = options.get('span')
norealtime = options.get('norealtime')
if nstreams is None and types is None and not demo and flush:
datastream.delete_streams()
return
elif flush:
raise base.CommandError(
"Do you really want to remove all datastream data from the database? Use only '--flush' parameter."
)
if nstreams is None and types is None and not flush and demo:
types = DEMO_TYPE
if span == '':
span = DEMO_SPAN
elif demo:
raise base.CommandError("In demo mode other parameters are fixed.")
if nstreams is None and types is None:
nstreams = DEFAULT_NSTREAMS
if types and check_types.match(types):
types = split_types.findall(types)
if nstreams is not None and len(types) != nstreams:
raise base.CommandError(
"Number of stream types does not mach number of streams.")
nstreams = len(types)
elif types:
raise base.CommandError(
"Invalid stream types string. Must be a comma separated list of <int|float|enum>[(start,end)|(enum values)]."
)
streams = []
for i in range(nstreams):
if types is not None:
typ = types[i]
else:
typ = ('int', '')
if typ[0] == 'enum':
value_type = 'nominal'
downsamplers = ['count']
elif typ[0] == 'graph':
value_type = 'graph'
downsamplers = ['count']
else:
value_type = 'numeric'
downsamplers = datastream.backend.value_downsamplers
visualization_value_downsamplers = []
for downsampler in ['mean', 'min', 'max']:
if downsampler in downsamplers:
visualization_value_downsamplers.append(downsampler)
type_constructor, random_function, default_domain = TYPES[typ[0]]
domain = typ[1] or default_domain
domain_range = [type_constructor(d) for d in domain.split(',')]
stream_id = datastream.ensure_stream(
{'title': 'Stream %d' % i},
{
'description': lorem_ipsum.paragraph(),
'unit_description': 'random, domain: %s' % domain,
'stream_number': i,
'visualization': {
'type':
'state' if typ is 'enum' else 'line',
'hidden':
True if typ is 'graph' else False,
'value_downsamplers':
visualization_value_downsamplers,
'time_downsamplers': ['mean'],
'minimum':
domain_range[0] if value_type == 'numeric' else None,
'maximum':
domain_range[1] if value_type == 'numeric' else None,
},
},
downsamplers,
datastream.Granularity.Seconds,
value_type=value_type,
)
streams.append((stream_id, typ))
span = span.split(' ')
if len(span) == 1 and span[0]:
span = span[0]
for val, key in (('days', 'd'), ('hours', 'h'), ('minutes', 'm'),
('seconds', 's')):
if span[-1] == key:
try:
s = int(span[:-1])
except ValueError:
raise base.CommandError(
"Time span value must be an integer.")
span_to = datetime.datetime.now(pytz.utc)
last_timestamp = self.last_timestamp(streams)
span_from = max(
span_to - datetime.timedelta(**{val: s}),
last_timestamp + datetime.timedelta(seconds=interval))
break
else:
raise base.CommandError("Unknown time span unit '%s'." %
span[-1])
elif len(span) == 2:
try:
# TODO: Support also timezone in the datetime format
span_from, span_to = [
datetime.datetime.strptime(x, '%Y-%m-%dT%H:%M:%S')
for x in span
]
except ValueError:
raise base.CommandError(
"Use time format 'yyyy-mm-ddThh:mm:ss' (i.e. '2007-03-04T21:08:12')."
)
else:
raise base.CommandError(
"Invalid time span parameter. It should be one or two space-delimited values."
)
if span_from is not None and span_to is not None and span_from <= span_to:
if verbose > 1:
td = span_to - span_from
self.stdout.write(
"Appending %d values from %s to %s.\n" %
(((td.seconds + td.days * 24 * 3600) // interval *
len(streams)), span_from, span_to))
while span_from <= span_to:
for stream_id, (typ, domain) in streams:
type_constructor, random_function, default_domain = TYPES[
typ]
value = random_function(*[
type_constructor(d)
for d in (domain or default_domain).split(',')
])
datastream.append(stream_id, value, span_from)
span_from += datetime.timedelta(seconds=interval)
if verbose > 1:
self.stdout.write("Done. Downsampling.\n")
datastream.downsample_streams(until=span_to)
if norealtime:
return
if verbose > 1:
self.stdout.write(
"Appending real-time value(s) to stream(s) every %s seconds.\n"
% interval)
while True:
for stream_id, (typ, domain) in streams:
type_constructor, random_function, default_domain = TYPES[typ]
value = random_function(*[
type_constructor(d)
for d in (domain or default_domain).split(',')
])
if verbose > 1:
self.stdout.write(
"Appending value '%s' to stream '%s'.\n" %
(value, stream_id))
datastream.append(stream_id, value)
datastream.downsample_streams()
time.sleep(interval)
def handle(self, *args, **options):
verbose = int(options.get('verbosity'))
interval = options.get('interval')
nstreams = options.get('nstreams')
types = options.get('types')
flush = options.get('flush')
demo = options.get('demo')
span = options.get('span')
if nstreams is None and types is None and not demo and flush:
datastream.delete_streams()
return
elif flush:
raise base.CommandError("Do you really want to remove all datastream data from the database? Use only '--flush' parameter.")
if nstreams is None and types is None and not flush and demo:
types = DEMO_TYPE
if span == '':
span = DEMO_SPAN
elif demo:
raise base.CommandError("In demo mode other parameters are fixed.")
if nstreams is None and types is None:
nstreams = DEFAULT_NSTREAMS
if types and check_types.match(types):
types = split_types.findall(types)
if nstreams is not None and len(types) != nstreams:
raise base.CommandError("Number of stream types does not mach number of streams.")
nstreams = len(types)
elif types:
raise base.CommandError("Invalid stream types string. Must be a comma separated list of <int|float|enum>[(start,end)|(enum values)].")
streams = []
for i in range(nstreams):
if types is None or types[i][0] != 'enum':
downsamplers = datastream.backend.value_downsamplers
else:
downsamplers = []
stream_id = datastream.ensure_stream(
({'name': 'stream_%d' % i},),
(
'foobar',
{'stream_number': i},
{'description': lorem_ipsum.paragraph()},
),
downsamplers,
datastream.Granularity.Seconds,
)
if types is not None:
streams.append((stream_id, types[i]))
else:
streams.append((stream_id, ('int', '')))
span = span.split(' ')
if len(span) == 1:
span = span[0]
for val, key in (('days', 'd'), ('hours', 'h')):
if span[-1] == key:
try:
s = int(span[:-1])
except ValueError:
raise base.CommandError("Time span value must be an integer.")
span_to = datetime.datetime.now(pytz.utc)
last_timestamp = self.last_timestamp(streams)
span_from = max(
span_to - datetime.timedelta(**{val: s}),
last_timestamp + datetime.timedelta(seconds=interval)
)
break
else:
raise base.CommandError("Unknown time span unit '%s'." % span[-1])
elif len(span) == 2:
try:
# TODO: Support also timezone in the datetime format
span_from, span_to = map(lambda x: datetime.datetime.strptime(x, '%Y-%m-%dT%H:%M:%S'), span)
except ValueError:
raise base.CommandError("Use time format 'yyyy-mm-ddThh:mm:ss' (i.e. '2007-03-04T21:08:12').")
else:
raise base.CommandError("Invalid time span parameter. It should be one or two space-delimited values.")
if span_from is not None and span_to is not None:
if verbose > 1:
td = span_to - span_from
self.stdout.write("Appending %d values from %s to %s.\n" % (((td.seconds + td.days * 24 * 3600) // interval * len(streams)), span_from, span_to))
while span_from <= span_to:
for stream_id, (type, domain) in streams:
type_constructor, random_function, default_domain = TYPES[type]
value = random_function(*map(type_constructor, (domain or default_domain).split(',')))
datastream.append(stream_id, value, span_from)
span_from += datetime.timedelta(seconds=interval)
if verbose > 1:
self.stdout.write("Downsampling.\n")
datastream.downsample_streams(until=span_to)
if verbose > 1:
self.stdout.write("Appending real-time value(s) to stream(s) every %s seconds.\n" % interval)
while True:
for stream_id, (type, domain) in streams:
type_constructor, random_function, default_domain = TYPES[type]
value = random_function(*map(type_constructor, (domain or default_domain).split(',')))
if verbose > 1:
self.stdout.write("Appending value '%s' to stream '%s'.\n" % (value, stream_id))
datastream.append(stream_id, value)
datastream.downsample_streams()
time.sleep(interval)
def handle(self, *args, **options):
verbose = int(options.get('verbosity'))
interval = options.get('interval')
nstreams = options.get('nstreams')
types = options.get('types')
flush = options.get('flush')
demo = options.get('demo')
span = options.get('span')
norealtime = options.get('norealtime')
if nstreams is None and types is None and not demo and flush:
datastream.delete_streams()
return
elif flush:
raise base.CommandError("Do you really want to remove all datastream data from the database? Use only '--flush' parameter.")
if nstreams is None and types is None and not flush and demo:
types = DEMO_TYPE
if span == '':
span = DEMO_SPAN
elif demo:
raise base.CommandError("In demo mode other parameters are fixed.")
if nstreams is None and types is None:
nstreams = DEFAULT_NSTREAMS
if types and check_types.match(types):
types = split_types.findall(types)
if nstreams is not None and len(types) != nstreams:
raise base.CommandError("Number of stream types does not mach number of streams.")
nstreams = len(types)
elif types:
raise base.CommandError("Invalid stream types string. Must be a comma separated list of <int|float|enum>[(start,end)|(enum values)].")
streams = []
for i in range(nstreams):
if types is not None:
typ = types[i]
else:
typ = ('int', '')
if typ[0] == 'enum':
value_type = 'nominal'
downsamplers = ['count']
elif typ[0] == 'graph':
value_type = 'graph'
downsamplers = ['count']
else:
value_type = 'numeric'
downsamplers = datastream.backend.value_downsamplers
visualization_value_downsamplers = []
for downsampler in ['mean', 'min', 'max']:
if downsampler in downsamplers:
visualization_value_downsamplers.append(downsampler)
type_constructor, random_function, default_domain = TYPES[typ[0]]
domain = typ[1] or default_domain
domain_range = [type_constructor(d) for d in domain.split(',')]
stream_id = datastream.ensure_stream(
{'title': 'Stream %d' % i},
{
'description': lorem_ipsum.paragraph(),
'unit_description': 'random, domain: %s' % domain,
'stream_number': i,
'visualization': {
'type': 'state' if typ is 'enum' else 'line',
'hidden': True if typ is 'graph' else False,
'value_downsamplers': visualization_value_downsamplers,
'time_downsamplers': ['mean'],
'minimum': domain_range[0] if value_type == 'numeric' else None,
'maximum': domain_range[1] if value_type == 'numeric' else None,
},
},
downsamplers,
datastream.Granularity.Seconds,
value_type=value_type,
)
streams.append((stream_id, typ))
span = span.split(' ')
if len(span) == 1 and span[0]:
span = span[0]
for val, key in (('days', 'd'), ('hours', 'h'), ('minutes', 'm'), ('seconds', 's')):
if span[-1] == key:
try:
s = int(span[:-1])
except ValueError:
raise base.CommandError("Time span value must be an integer.")
span_to = datetime.datetime.now(pytz.utc)
last_timestamp = self.last_timestamp(streams)
span_from = max(
span_to - datetime.timedelta(**{val: s}),
last_timestamp + datetime.timedelta(seconds=interval)
)
break
else:
raise base.CommandError("Unknown time span unit '%s'." % span[-1])
elif len(span) == 2:
try:
# TODO: Support also timezone in the datetime format
span_from, span_to = [datetime.datetime.strptime(x, '%Y-%m-%dT%H:%M:%S') for x in span]
except ValueError:
raise base.CommandError("Use time format 'yyyy-mm-ddThh:mm:ss' (i.e. '2007-03-04T21:08:12').")
else:
raise base.CommandError("Invalid time span parameter. It should be one or two space-delimited values.")
if span_from is not None and span_to is not None and span_from <= span_to:
if verbose > 1:
td = span_to - span_from
self.stdout.write("Appending %d values from %s to %s.\n" % (((td.seconds + td.days * 24 * 3600) // interval * len(streams)), span_from, span_to))
while span_from <= span_to:
for stream_id, (typ, domain) in streams:
type_constructor, random_function, default_domain = TYPES[typ]
value = random_function(*[type_constructor(d) for d in (domain or default_domain).split(',')])
datastream.append(stream_id, value, span_from)
span_from += datetime.timedelta(seconds=interval)
if verbose > 1:
self.stdout.write("Done. Downsampling.\n")
datastream.downsample_streams(until=span_to)
if norealtime:
return
if verbose > 1:
self.stdout.write("Appending real-time value(s) to stream(s) every %s seconds.\n" % interval)
while True:
for stream_id, (typ, domain) in streams:
type_constructor, random_function, default_domain = TYPES[typ]
value = random_function(*[type_constructor(d) for d in (domain or default_domain).split(',')])
if verbose > 1:
self.stdout.write("Appending value '%s' to stream '%s'.\n" % (value, stream_id))
datastream.append(stream_id, value)
datastream.downsample_streams()
time.sleep(interval)
def handle(self, *args, **options):
verbose = int(options.get('verbosity'))
interval = options.get('interval')
nstreams = options.get('nstreams')
types = options.get('types')
flush = options.get('flush')
demo = options.get('demo')
span = options.get('span')
if nstreams is None and types is None and not demo and flush:
datastream.delete_streams()
return
elif flush:
raise base.CommandError(
"Do you really want to remove all datastream data from the database? Use only '--flush' parameter."
)
if nstreams is None and types is None and not flush and demo:
types = DEMO_TYPE
if span == '':
span = DEMO_SPAN
elif demo:
raise base.CommandError("In demo mode other parameters are fixed.")
if nstreams is None and types is None:
nstreams = DEFAULT_NSTREAMS
if types and check_types.match(types):
types = split_types.findall(types)
if nstreams is not None and len(types) != nstreams:
raise base.CommandError(
"Number of stream types does not mach number of streams.")
nstreams = len(types)
elif types:
raise base.CommandError(
"Invalid stream types string. Must be a comma separated list of <int|float|enum>[(start,end)|(enum values)]."
)
streams = []
for i in range(nstreams):
if types is None or types[i][0] != 'enum':
downsamplers = datastream.backend.value_downsamplers
else:
downsamplers = []
stream_id = datastream.ensure_stream(
({
'name': 'stream_%d' % i
}, ),
(
'foobar',
{
'stream_number': i
},
{
'description': lorem_ipsum.paragraph()
},
),
downsamplers,
datastream.Granularity.Seconds,
)
if types is not None:
streams.append((stream_id, types[i]))
else:
streams.append((stream_id, ('int', '')))
span = span.split(' ')
if len(span) == 1:
span = span[0]
for val, key in (('days', 'd'), ('hours', 'h')):
if span[-1] == key:
try:
s = int(span[:-1])
except ValueError:
raise base.CommandError(
"Time span value must be an integer.")
span_to = datetime.datetime.now(pytz.utc)
last_timestamp = self.last_timestamp(streams)
span_from = max(
span_to - datetime.timedelta(**{val: s}),
last_timestamp + datetime.timedelta(seconds=interval))
break
else:
raise base.CommandError("Unknown time span unit '%s'." %
span[-1])
elif len(span) == 2:
try:
# TODO: Support also timezone in the datetime format
span_from, span_to = map(
lambda x: datetime.datetime.strptime(
x, '%Y-%m-%dT%H:%M:%S'), span)
except ValueError:
raise base.CommandError(
"Use time format 'yyyy-mm-ddThh:mm:ss' (i.e. '2007-03-04T21:08:12')."
)
else:
raise base.CommandError(
"Invalid time span parameter. It should be one or two space-delimited values."
)
if span_from is not None and span_to is not None:
if verbose > 1:
td = span_to - span_from
self.stdout.write(
"Appending %d values from %s to %s.\n" %
(((td.seconds + td.days * 24 * 3600) // interval *
len(streams)), span_from, span_to))
while span_from <= span_to:
for stream_id, (type, domain) in streams:
type_constructor, random_function, default_domain = TYPES[
type]
value = random_function(*map(type_constructor, (
domain or default_domain).split(',')))
datastream.append(stream_id, value, span_from)
span_from += datetime.timedelta(seconds=interval)
if verbose > 1:
self.stdout.write("Downsampling.\n")
datastream.downsample_streams(until=span_to)
if verbose > 1:
self.stdout.write(
"Appending real-time value(s) to stream(s) every %s seconds.\n"
% interval)
while True:
for stream_id, (type, domain) in streams:
type_constructor, random_function, default_domain = TYPES[type]
value = random_function(*map(type_constructor, (
domain or default_domain).split(',')))
if verbose > 1:
self.stdout.write(
"Appending value '%s' to stream '%s'.\n" %
(value, stream_id))
datastream.append(stream_id, value)
datastream.downsample_streams()
time.sleep(interval)