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chore: update to python3 #2

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4 changes: 2 additions & 2 deletions README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -42,12 +42,12 @@ to maintain precision when dealing with tiny numbers, and prints out the results
for a given set of assumptions:

```
$ python durability.py
$ python3 durability.py
usage: durability.py [-h]
data_shards parity_shards annual_shard_failure_rate
shard_replacement_days
durability.py: error: too few arguments
$ python durability.py 4 2 0.10 1python durability.py 17 3 0.00405 6.5
$ python3 durability.py 17 3 0.00405 6.5

#
# total shards: 20
Expand Down
60 changes: 30 additions & 30 deletions durability.py
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Original file line number Diff line number Diff line change
@@ -1,4 +1,4 @@
#!/usr/bin/env python2
#!/usr/bin/env python3
######################################################################
#
# File: durability.py
Expand Down Expand Up @@ -82,12 +82,12 @@ def pad(self, s, width):


def print_markdown_table(data, column_names):
print
print ' | '.join(column_names)
print ' | '.join(['---'] * len(column_names))
print()
print(' | '.join(column_names))
print(' | '.join(['---'] * len(column_names)))
for item in data:
print ' | '.join(item[cn] for cn in column_names)
print
print(' | '.join(item[cn] for cn in column_names))
print()


def factorial(n):
Expand All @@ -108,8 +108,8 @@ def choose(n, r):
assert n >= 0
assert 0 <= r <= n

c = 1L
for num, denom in zip(xrange(n, n-r, -1), xrange(1, r+1, 1)):
c = 1
for num, denom in zip(range(n, n-r, -1), range(1, r+1, 1)):
c = (c * num) // denom
return c

Expand Down Expand Up @@ -175,7 +175,7 @@ def probability_of_failure_in_any_period(p, n):
n_int = int(n)
result = 0.0
sign = 1
for i in xrange(1, n_int + 1):
for i in range(1, n_int + 1):
p_exp_i = p ** i
if p_exp_i != 0:
result += sign * choose(n_int, i) * (p ** i)
Expand Down Expand Up @@ -270,18 +270,18 @@ def do_scenario(total_shards, min_shards, annual_shard_failure_rate, shard_repla
num_periods = 365.0 / shard_replacement_days
failure_rate_per_period = annual_shard_failure_rate / num_periods

print
print '#'
print '# total shards:', total_shards
print '# replacement period (days): %6.4f' % (shard_replacement_days)
print '# annual shard failure rate: %6.4f' % (annual_shard_failure_rate)
print '#'
print
print()
print('#')
print('# total shards:', total_shards)
print('# replacement period (days): %6.4f' % (shard_replacement_days))
print('# annual shard failure rate: %6.4f' % (annual_shard_failure_rate))
print('#')
print()

failure_probability_per_period = 1.0 - math.exp(-failure_rate_per_period)
data = []
period_cumulative_prob = 0.0
for failed_shards in xrange(total_shards, -1, -1):
for failed_shards in range(total_shards, -1, -1):
period_failure_prob = binomial_probability(failed_shards, total_shards, failure_probability_per_period)
period_cumulative_prob += period_failure_prob
annual_loss_prob = probability_of_failure_in_any_period(period_cumulative_prob, num_periods)
Expand All @@ -299,15 +299,15 @@ def do_scenario(total_shards, min_shards, annual_shard_failure_rate, shard_repla
'nines' : nines
})

print Table(data, ['failure_threshold',
print(Table(data, ['failure_threshold',
'individual_prob',
'cumulative_prob',
'annual_loss_rate',
'annual_odds',
'durability',
'nines'
])
print
]))
print()

return dict(
(item['failure_threshold'], item)
Expand All @@ -323,18 +323,18 @@ def example():
p = 2.0
data = [
{ 'k': str(k), 'p': '%6.4f' % (math.exp(-p) * p**k / factorial(k),) }
for k in xrange(7)
for k in range(7)
]
print_markdown_table(data, ['k', 'p'])

print 'Probability of n Failing'
print('Probability of n Failing')
annual_rate = 0.25
p_one_failing = probability_of_failure_for_failure_rate(annual_rate)
print 'probability of one failing: %6.4f' % p_one_failing
print 'probability of none failing: %6.4f' % (1 - p_one_failing)
print 'probability of three not failing: %6.4f' % (1 - p_one_failing) ** 3
print 'probability of two or more failing: %6.4f' % (binomial_probability(2, 3, p_one_failing) + binomial_probability(3, 3, p_one_failing))
print
print('probability of one failing: %6.4f' % p_one_failing)
print('probability of none failing: %6.4f' % (1 - p_one_failing))
print('probability of three not failing: %6.4f' % (1 - p_one_failing) ** 3)
print('probability of two or more failing: %6.4f' % (binomial_probability(2, 3, p_one_failing) + binomial_probability(3, 3, p_one_failing)))
print()
probs = {'ok': (1 - p_one_failing), 'FAIL': p_one_failing}
data = []
total_prob = 0.0
Expand All @@ -352,12 +352,12 @@ def example():
})
total_prob += probs[a] * probs[b] * probs[c]
print_markdown_table(data, ['A', 'A prob', 'B', 'B prob', 'C', 'C prob', 'Probability'])
print 'sum of probabilities: %6.4f' % total_prob
print
print('sum of probabilities: %6.4f' % total_prob)
print()

data = [
{'Number of Failures': str(k), 'Probability': '%6.4f' % binomial_probability(k, 3, p_one_failing)}
for k in xrange(4)
for k in range(4)
]
print_markdown_table(data, ['Number of Failures', 'Probability'])

Expand Down