tahoe-lafs/misc/operations_helpers/provisioning/test_provisioning.py

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import unittest
from allmydata import provisioning
ReliabilityModel = None
try:
from allmydata.reliability import ReliabilityModel
except ImportError:
pass # might not be importable, since it needs NumPy
from nevow import inevow
from zope.interface import implements
2019-05-15 06:17:44 +00:00
class MyRequest(object):
implements(inevow.IRequest)
pass
class Provisioning(unittest.TestCase):
def getarg(self, name, astype=int):
if name in self.fields:
return astype(self.fields[name])
return None
def test_load(self):
pt = provisioning.ProvisioningTool()
self.fields = {}
#r = MyRequest()
#r.fields = self.fields
#ctx = RequestContext()
#unfilled = pt.renderSynchronously(ctx)
lots_of_stan = pt.do_forms(self.getarg)
self.failUnless(lots_of_stan is not None)
self.fields = {'filled': True,
"num_users": 50e3,
"files_per_user": 1000,
"space_per_user": 1e9,
"sharing_ratio": 1.0,
"encoding_parameters": "3-of-10-5",
"num_servers": 30,
"ownership_mode": "A",
"download_rate": 100,
"upload_rate": 10,
"delete_rate": 10,
"lease_timer": 7,
}
#filled = pt.renderSynchronously(ctx)
more_stan = pt.do_forms(self.getarg)
self.failUnless(more_stan is not None)
# trigger the wraparound configuration
self.fields["num_servers"] = 5
#filled = pt.renderSynchronously(ctx)
more_stan = pt.do_forms(self.getarg)
# and other ownership modes
self.fields["ownership_mode"] = "B"
more_stan = pt.do_forms(self.getarg)
self.fields["ownership_mode"] = "E"
more_stan = pt.do_forms(self.getarg)
def test_provisioning_math(self):
self.failUnlessEqual(provisioning.binomial(10, 0), 1)
self.failUnlessEqual(provisioning.binomial(10, 1), 10)
self.failUnlessEqual(provisioning.binomial(10, 2), 45)
self.failUnlessEqual(provisioning.binomial(10, 9), 10)
self.failUnlessEqual(provisioning.binomial(10, 10), 1)
DAY=24*60*60
MONTH=31*DAY
YEAR=365*DAY
class Reliability(unittest.TestCase):
def test_basic(self):
if ReliabilityModel is None:
raise unittest.SkipTest("reliability model requires NumPy")
# test that numpy math works the way I think it does
import numpy
decay = numpy.matrix([[1,0,0],
[.1,.9,0],
[.01,.09,.9],
])
start = numpy.array([0,0,1])
g2 = (start * decay).A[0]
self.failUnlessEqual(repr(g2), repr(numpy.array([.01,.09,.9])))
g3 = (g2 * decay).A[0]
self.failUnlessEqual(repr(g3), repr(numpy.array([.028,.162,.81])))
# and the dot product
recoverable = numpy.array([0,1,1])
P_recoverable_g2 = numpy.dot(g2, recoverable)
self.failUnlessAlmostEqual(P_recoverable_g2, .9 + .09)
P_recoverable_g3 = numpy.dot(g3, recoverable)
self.failUnlessAlmostEqual(P_recoverable_g3, .81 + .162)
r = ReliabilityModel.run(delta=100000,
report_period=3*MONTH,
report_span=5*YEAR)
self.failUnlessEqual(len(r.samples), 20)
last_row = r.samples[-1]
#print last_row
(when, unmaintained_shareprobs, maintained_shareprobs,
P_repaired_last_check_period,
cumulative_number_of_repairs,
cumulative_number_of_new_shares,
P_dead_unmaintained, P_dead_maintained) = last_row
self.failUnless(isinstance(P_repaired_last_check_period, float))
self.failUnless(isinstance(P_dead_unmaintained, float))
self.failUnless(isinstance(P_dead_maintained, float))
self.failUnlessAlmostEqual(P_dead_unmaintained, 0.033591004555395272)
self.failUnlessAlmostEqual(P_dead_maintained, 3.2983995819177542e-08)
if __name__=='__main__':
unittest.main()