Re: xkcd.com/353 ( Flying with Python )
On 30/03/24 7:21 pm, HenHanna wrote: https://xkcd.com/1306/ what does SIGIL mean? I think its' a Perl term, referring to the $/@/# symbols in front of identifiers. -- Greg -- https://mail.python.org/mailman/listinfo/python-list
Re: xkcd.com/353 ( Flying with Python )
> > > https://xkcd.com/1306/ > > what does SIGIL mean? > > I think its' a Perl term, referring to the $/@/# symbols in front of > identifiers. > I had a vague recollection of hearing it elsewhere (*Game of Thrones,* on the armies' battle flags?), but didn't know what it meant. Google tells me: *an inscribed or painted symbol considered to have magical power.* So, they're more than just line noise. They confer power on their users... Perhaps '@' in the context of decorators is the most prominent example in Python, since decorators technically don't allow the programmer to do something they couldn't before, but are now are used everywhere, a key feature of many applications and modules. Magical-ly, y'rs, Skip > -- https://mail.python.org/mailman/listinfo/python-list
Re: xkcd.com/353 ( Flying with Python )
On 2024-03-30 11:25, Skip Montanaro via Python-list wrote: > https://xkcd.com/1306/ > what does SIGIL mean? I think its' a Perl term, referring to the $/@/# symbols in front of identifiers. I had a vague recollection of hearing it elsewhere (*Game of Thrones,* on the armies' battle flags?), but didn't know what it meant. Google tells me: *an inscribed or painted symbol considered to have magical power.* So, they're more than just line noise. They confer power on their users... Perhaps '@' in the context of decorators is the most prominent example in Python, since decorators technically don't allow the programmer to do something they couldn't before, but are now are used everywhere, a key feature of many applications and modules. Magical-ly, y'rs, I wouldn't consider '@' to be a sigil any more than I would a unary minus. In Perl there's the prefixes $ (scalar), @ (array) and % (hash/dictionary), but also & (function), although it's rare because there's also the () afterwards. Variables in PHP have the prefix $ and only $. In old versions of BASIC, string variables had the suffix $, and integer variables the suffix %. Some versions also had the suffix # (for double precision, I think). -- https://mail.python.org/mailman/listinfo/python-list
Re: xkcd.com/353 ( Flying with Python )
On 30/03/2024 07:04, Greg Ewing via Python-list wrote: > On 30/03/24 7:21 pm, HenHanna wrote: >> https://xkcd.com/1306/ >> what does SIGIL mean? > > I think its' a Perl term, referring to the $/@/# symbols in front of > identifiers. There seem to be several derivation sources including a fantasy world city suspended above a very thin, tall steeple Personally, I know SIGIL as an opensource EPUB editor! None of them seem to have any direct connection to the xkcd cartoon. -- Alan G Author of the Learn to Program web site http://www.alan-g.me.uk/ http://www.amazon.com/author/alan_gauld Follow my photo-blog on Flickr at: http://www.flickr.com/photos/alangauldphotos -- https://mail.python.org/mailman/listinfo/python-list
Can you help me with this memoization simple example?
I am creating a memoization example with a function that adds up / averages
the elements of an array and compares it with the cached ones to retrieve
them in case they are already stored.
In addition, I want to store only if the result of the function differs
considerably (passes a threshold e.g. 50 below).
I created an example using a decorator to do so, the results using the
decorator is slightly faster than without the memoization which is OK, but
is the logic of the decorator correct ? anybody can tell me ?
My code is attached below:
import time
def memoize(f):
cache = {}
def g(*args):
if args[1] == "avg":
sum_key_arr = sum(list(args[0])) / len(list(args[0]))
elif args[1] == "sum":
sum_key_arr = sum(list(args[0]))
if sum_key_arr not in cache:
for (
key,
value,
) in (
cache.items()
): # key in dict cannot be an array so I use the sum of the
array as the key
if (
abs(sum_key_arr - key) <= 50
): # threshold is great here so that all values are
approximated!
# print('approximated')
return cache[key]
else:
# print('not approximated')
cache[sum_key_arr] = f(args[0], args[1])
return cache[sum_key_arr]
return g
@memoize
def aggregate(dict_list_arr, operation):
if operation == "avg":
return sum(list(dict_list_arr)) / len(list(dict_list_arr))
if operation == "sum":
return sum(list(dict_list_arr))
return None
t = time.time()
for i in range(200, 15000):
res = aggregate(list(range(i)), "avg")
elapsed = time.time() - t
print(res)
print(elapsed)
--
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Re: Can you help me with this memoization simple example?
On 2024-03-31 00:09, marc nicole via Python-list wrote:
I am creating a memoization example with a function that adds up / averages
the elements of an array and compares it with the cached ones to retrieve
them in case they are already stored.
In addition, I want to store only if the result of the function differs
considerably (passes a threshold e.g. 50 below).
I created an example using a decorator to do so, the results using the
decorator is slightly faster than without the memoization which is OK, but
is the logic of the decorator correct ? anybody can tell me ?
My code is attached below:
import time
def memoize(f):
cache = {}
def g(*args):
if args[1] == "avg":
sum_key_arr = sum(list(args[0])) / len(list(args[0]))
'list' will iterate over args[0] to make a list, and 'sum' will iterate
over that list.
It would be simpler to just let 'sum' iterate over args[0].
elif args[1] == "sum":
sum_key_arr = sum(list(args[0]))
if sum_key_arr not in cache:
for (
key,
value,
) in (
cache.items()
): # key in dict cannot be an array so I use the sum of the
array as the key
You can't use a list as a key, but you can use a tuple as a key,
provided that the elements of the tuple are also immutable.
if (
abs(sum_key_arr - key) <= 50
): # threshold is great here so that all values are
approximated!
# print('approximated')
return cache[key]
else:
# print('not approximated')
cache[sum_key_arr] = f(args[0], args[1])
return cache[sum_key_arr]
return g
@memoize
def aggregate(dict_list_arr, operation):
if operation == "avg":
return sum(list(dict_list_arr)) / len(list(dict_list_arr))
if operation == "sum":
return sum(list(dict_list_arr))
return None
t = time.time()
for i in range(200, 15000):
res = aggregate(list(range(i)), "avg")
elapsed = time.time() - t
print(res)
print(elapsed)
--
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