Python Interpreters Benchmarks
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 performance measurements

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

 N  CPU secs Elapsed secs Memory KB Code B ≈ CPU Load
1,0001.621.64121,232344  24% 19% 99% 23% 24% 24% 26% 19%

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

Read  benchmark to see what this program should do.

 notes

  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(forceobj=True)
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

 Wed, 12 Jan 2022 12:00:34 GMT

COMMAND LINE:
 /usr/bin/python3 templates.numba 1000

PROGRAM OUTPUT:

<ul>

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

</ul>

Revised BSD license

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