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A faster alternative to namedtuple.

Project Description

A faster alternative to namedtuple.

Basic Usage

Creation

import plain_obj
Config = plain_obj.new_type('Config', 'is_debug, skips_dist, run_tests')
config = Config(True, False, True)
if config.is_debug:
    print("This is a verbose debugging message.")

Make a dict

config.as_dict()

Unpacking

is_debug, _, run_tests = config

When to use plain_obj instead of namedtuple?

When faster creation time matters to you.

Comparing plain_obj with namedtuple in Python 2.7:

In [3]: %timeit collections.namedtuple('Point', ['x', 'y', 'z'])
1000 loops, best of 3: 338 µs per loop

In [4]: %timeit plain_obj.new_type('Point', ['x', 'y', 'z'])
10000 loops, best of 3: 97.8 µs per loop

In [5]: Point = collections.namedtuple('Point', ['x', 'y', 'z'])

In [6]: NewPoint = plain_obj.new_type('Point', ['x', 'y', 'z'])

In [7]: %timeit Point(1, 2, 3)
The slowest run took 7.99 times longer than the fastest. This could mean that an intermediate result is being cached.
1000000 loops, best of 3: 507 ns per loop

In [8]: %timeit NewPoint(1, 2, 3)
The slowest run took 6.70 times longer than the fastest. This could mean that an intermediate result is being cached.
1000000 loops, best of 3: 462 ns per loop

In [9]: p = Point(1, 2, 3)

In [10]: new_p = NewPoint(1, 2, 3)

In [11]: %timeit p.x, p.y, p.z
The slowest run took 9.92 times longer than the fastest. This could mean that an intermediate result is being cached.
1000000 loops, best of 3: 408 ns per loop

In [12]: %timeit new_p.x, new_p.y, new_p.z
The slowest run took 11.70 times longer than the fastest. This could mean that an intermediate result is being cached.
10000000 loops, best of 3: 163 ns per loop

Comparing plain_obj with namedtuple in Python 3.6:

In [3]: %timeit collections.namedtuple('Point', ['x', 'y', 'z'])
382 µs ± 3.82 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)

In [4]: %timeit plain_obj.new_type('Point', ['x', 'y', 'z'])
53.5 µs ± 1.2 µs per loop (mean ± std. dev. of 7 runs, 10000 loops each)

In [5]: Point = collections.namedtuple('Point', ['x', 'y', 'z'])

In [6]: NewPoint = plain_obj.new_type('Point', ['x', 'y', 'z'])

In [7]: %timeit Point(1, 2, 3)
521 ns ± 2.5 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each)

In [8]: %timeit NewPoint(1, 2, 3)
438 ns ± 5.53 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each)

In [9]: p = Point(1, 2, 3)

In [10]: new_p = NewPoint(1, 2, 3)

In [11]: %timeit p.x, p.y, p.z
282 ns ± 2.52 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each)

In [12]: %timeit new_p.x, new_p.y, new_p.z
148 ns ± 1.7 ns per loop (mean ± std. dev. of 7 runs, 10000000 loops each)

As you can see, it’s faster in all cases including type creation, object instantiation and attribute access.

Release History

This version
History Node

0.1.2

History Node

0.1.1

History Node

0.1.0

Download Files

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File Name & Hash SHA256 Hash Help Version File Type Upload Date
plain_obj-0.1.2.tar.gz
(2.8 kB) Copy SHA256 Hash SHA256
Source Sep 3, 2017

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