tahoe-lafs/src/allmydata/web/reliability.py

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from nevow import rend, inevow, tags as T
reliability = None # might not be usable
try:
from allmydata import reliability # requires Numeric and PIL
except ImportError:
pass
from allmydata.web.common import getxmlfile, get_arg
DAY=24*60*60
MONTH=31*DAY
YEAR=365*DAY
def is_available():
if reliability:
return True
return False
def yandm(seconds):
return "%dy.%dm" % (int(seconds/YEAR), int( (seconds%YEAR)/MONTH))
class ReliabilityTool(rend.Page):
addSlash = True
docFactory = getxmlfile("reliability.xhtml")
DEFAULT_PARAMETERS = [
("drive_lifetime", "8Y", "time"),
("k", 3, "int"),
("R", 7, "int"),
("N", 10, "int"),
("delta", "1M", "time"),
("check_period", "1M", "time"),
("report_period", "3M", "time"),
("report_span", "5Y", "time"),
]
def parse_time(self, s):
if s.endswith("M"):
return int(s[:-1]) * MONTH
if s.endswith("Y"):
return int(s[:-1]) * YEAR
return int(s)
def format_time(self, s):
if s%YEAR == 0:
return "%dY" % (s/YEAR)
if s%MONTH == 0:
return "%dM" % (s/MONTH)
return "%d" % s
def get_parameters(self, ctx):
req = inevow.IRequest(ctx)
parameters = {}
for name,default,argtype in self.DEFAULT_PARAMETERS:
v = get_arg(ctx, name, default)
if argtype == "time":
value = self.parse_time(v)
else:
value = int(v)
parameters[name] = value
return parameters
def renderHTTP(self, ctx):
self.parameters = self.get_parameters(ctx)
self.results = reliability.ReliabilityModel.run(**self.parameters)
return rend.Page.renderHTTP(self, ctx)
def make_input(self, name, old_value):
return T.input(name=name, type="text",
value=self.format_time(old_value))
def render_forms(self, ctx, data):
f = T.form(action=".", method="get")
table = []
for name, default_value, argtype in self.DEFAULT_PARAMETERS:
old_value = self.parameters[name]
i = self.make_input(name, old_value)
table.append(T.tr[T.td[name+":"], T.td[i]])
go = T.input(type="submit", value="Recompute")
return [T.h2["Simulation Parameters:"],
f[T.table[table], go],
]
def data_simulation_table(self, ctx, data):
for row in self.results.samples:
yield row
def render_simulation_row(self, ctx, 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) = row
ctx.fillSlots("t", yandm(when))
ctx.fillSlots("P_repair", "%.6f" % P_repaired_last_check_period)
ctx.fillSlots("P_dead_unmaintained", "%.6g" % P_dead_unmaintained)
ctx.fillSlots("P_dead_maintained", "%.6g" % P_dead_maintained)
return ctx.tag
def render_report_span(self, ctx, 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) = self.results.samples[-1]
return ctx.tag[yandm(when)]
def render_P_loss_unmaintained(self, ctx, 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) = self.results.samples[-1]
return ctx.tag["%.6g (%1.8f%%)" % (P_dead_unmaintained,
100*P_dead_unmaintained)]
def render_P_loss_maintained(self, ctx, 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) = self.results.samples[-1]
return ctx.tag["%.6g (%1.8f%%)" % (P_dead_maintained,
100*P_dead_maintained)]
def render_P_repair_rate(self, ctx, 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) = self.results.samples[-1]
freq = when / cumulative_number_of_repairs
return ctx.tag["%.6g" % freq]
def render_P_repair_shares(self, ctx, 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) = self.results.samples[-1]
generated_shares = cumulative_number_of_new_shares / cumulative_number_of_repairs
return ctx.tag["%1.2f" % generated_shares]