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Date: Mon, 27 Apr 2015 20:35:18 +0000 (UTC)
From: Albert-Jan Roskam <fomcl@yahoo.com>
Reply-To: Albert-Jan Roskam <fomcl@yahoo.com>
To: Peter Otten <__peter__@web.de>, "python-list@python.org" <python-list@python.org>
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References: <87h9s1zoap.fsf@Equus.decebal.nl> <mhlh2f$plv$2@ger.gmane.org>
Subject: Re: Wrote a memoize function: I do not mind feedback
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----- Original Message -----
> From: Peter Otten <__peter__@web.de>
> To: python-list@python.org
> Cc:=20
> Sent: Monday, April 27, 2015 4:28 PM
> Subject: Re: Wrote a memoize function: I do not mind feedback
>=20
> Cecil Westerhof wrote:
>=20
>>  I started again with Python. In Clojure you have memoize. I thought it
>>  nice to have this in Python also. So I wrote it. With a Fibonacci
>>  function to show the usefulness.
>>  You can find it here:
>>     https://github.com/CecilWesterhof/PythonLibrary
>>=20
>>  I love to hear what you think of it.
>>=20
>>  And ideas for other functionalities are welcome also. =C3=9Cbung macht =
den
>>  Meister.
>=20
> See also:=20
>=20
> https://docs.python.org/dev/library/functools.html#functools.lru_cache
>=20
> A bit hard to find unless you already know it's there.

If you Google for memoization decorator, you will easily find many more imp=
lementations. Not 100 percent sure, but I think the LRU cache decorator was=
 not exactly light weight. I also like this one from Martelli's Python Cook=
book, where he uses a mutable default argument {a dictionary} to implement =
memoization. I believe I went like this:


def some_func(arg, _memoize=3D{}):
    try:
        return _memoize[arg]
    except KeyError:
        result =3D some_expensive_operation(arg)
        _memoize[arg] =3D result
        return result