1518.sagews

Adapting a useful trick, we attempt to set up analogues of IPython's "magic" %timeit function for notebook cells.  See timeit for documentation on the underlying Python library module.

First, we wrap an existing Sage library function:

class timeit1:
    def __init__(self, number=0, repeat=3, precision=3, preparse=False):
        self.number = number
        self.repeat = repeat
        self.precision = precision
        self.preparse = preparse
    def eval(self, s, globals, locals):
        return sage.misc.sage_timeit.sage_timeit(s, globals, number=self.number, repeat=self.repeat, precision=self.precision, preparse=self.preparse)

%timeit1()
c = (1 + 1j) / 3
z = 0
for i in xrange(100):
    z = z**2 + c

625 loops, best of 3: 16.9 µs per loop

import time

%timeit1(number=1)
print 'Sleeping...'
time.sleep(1)
print 'Awake!'

1 loops, best of 3: 996 ms per loop

Here's an alternative, with sample statistics computed for repeat iterations:

class timeit2:
    def __init__(self, repeat=1, precision=3, preparse=True):
        import time
        self.time = time.time
        self.repeat = repeat
        self.precision = int(precision)
        self.preparse = preparse
    def eval(self, s, globals, locals):
        if self.preparse:
            s = preparse(s)
        results = []
        for r in xrange(self.repeat):
            start_time = self.time()
            ans = python.eval(s,  globals, locals)
            results.append(self.time() - start_time)
        v = vector(RDF, results)
        print 'r = %d, mean = %.*g, std. dev. = %.*g' % (self.repeat, self.precision, v.mean(), self.precision, v.standard_deviation(population=True))
        return ans

def iterate(f, n, x):
    ans = x
    for i in xrange(n):
        ans = f(ans)
    return ans

%timeit2(repeat=10)
big = iterate(lambda x: x ^ x, 2, 8)

r = 10, mean = 0.108, std. dev. = 0.0175

%timeit2(repeat=3, precision=5)
print 'Sleeping...'
time.sleep(1)
print 'Awake!'

Sleeping... Awake! Sleeping... Awake! Sleeping... Awake! r = 3, mean = 0.99736, std. dev. = 0.0049723