performance measurements

Each table row shows performance measurements for this Numba program with a particular command-line input value N.

 N  CPU secs Elapsed secs Memory KB Code B ≈ CPU Load
1,0001.481.5077,492335  88% 11% 1% 2%
1,0001.461.4677,500335  1% 5% 0% 95%
1,0001.461.4677,320335  1% 0% 0% 99%

Read the ↓ make, command line, and program output logs to see how this program was run.

Read templates benchmark to see what this program should do.

 notes

 templates Numba program source code

import sys

from jinja2 import Template
from numba import jit

templ = """

"""


class User(object):
    __slots__ = ('user_id', 'username')

    def __init__(self, user_id, username):
        self.user_id = user_id
        self.username = username


@jit
def render_template(user_id):
    users = [
        User(user_id, 'SomeUsername')
    ]

    template = Template(templ)
    return template.render(users=users)


def main():
    n = int(sys.argv[1])

    for i in range(n):
        res = render_template(i)

    print(res)

main()

 make, command-line, and program output logs

Fri, 10 Nov 2017 20:21:49 GMT

COMMAND LINE:
/opt/anaconda/bin/python templates.numba 1000

PROGRAM OUTPUT:

<ul>

  <li><a href="/user/999">SomeUsername</a></li>

</ul>

Revised BSD license

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