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They amount to the same, but the explicit loop was much easier for me to understand (and I’m still not sure if one applies a function to a value or a value to a function, so I never remember if the function or the values go first in an apply filter call)
Someone else has mentioned it, but I would have gone with: sum(1 for age in ages if age > 17) with the other method you're treating a boolean as an int. Weak typing.
sum(int(age > 17) for age in ages)
I feel like this kind of operation on a list feels more naturally expressed by filtering the list and taking the length of the filtered list. Like this line of JS feels so much easier to read than that line of python: ages.filter(age => age > 17).length Directly translating this approach to python: len(list(filter(lambda age: (age > 17), ages))) Although a better way to write this in python I guess would be using lis…
np.sum(age>17)
(Assumes age is a np.array)
Someone else has mentioned it, but I would have gone with: sum(1 for age in ages if age > 17) with the other method you're treating a boolean as an int. Weak typing.
[1]: https://docs.python.org/3/library/functions.html?highlight=s...
[2]: https://docs.python.org/3/library/stdtypes.html#boolean-valu...
I feel like this kind of operation on a list feels more naturally expressed by filtering the list and taking the length of the filtered list. Like this line of JS feels so much easier to read than that line of python: ages.filter(age => age > 17).length Directly translating this approach to python: len(list(filter(lambda age: (age > 17), ages))) Although a better way to write this in python I guess would be using lis…
Someone else has mentioned it, but I would have gone with: sum(1 for age in ages if age > 17) with the other method you're treating a boolean as an int. Weak typing.
“I don’t know the type hierarchy used in language X” is not the same thing as “language X is weakly typed”.
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(AMD64)] on win32
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>>> isinstance(True, int)
True
>>> isinstance(False, int)
True
>>> issubclass(bool, int)
TrueEarlier quoted context omitted.
It is a poor functional language. List comprehensions (from Haskell) are nice, but the rest is garbage. Crippled lambdas, no currying, "match" is a clumsy statement, weird name spaces and a rigid whitespace syntax. No real immutability.
IIRC, Haskell’s list comprehensions are lifted from Erlang.
[0]:https://en.wikipedia.org/wiki/Miranda_(programming_language)...
APL makes a lot of sense in the era of 110 baud teletypes in which it was invented. Brevity was of extreme importance in that era.
You're saying that brevity for typing on 110 baud teletypes was the primary reason for the density of APL operators, but that's not historically true. For one thing Iverson and pretty much everyone else high profile in the APL community has said that the conciseness was itself a major part of the power of APL. Further proof of that: APL began as a mathematical notation on chalkboards, and only later was it decided to…
Someone else has mentioned it, but I would have gone with: sum(1 for age in ages if age > 17) with the other method you're treating a boolean as an int. Weak typing.
I agree with the improvement in readability but still like the bool/int equivalence: sum(int(age > 17) for age in ages) Every nanosecond is vital!
python -m timeit 'sum(1 for age in range(100000) if age > 17)'
50 loops, best of 5: 5.08 msec per loop
python -m timeit 'sum(int(age > 17) for age in range(100000))'
50 loops, best of 5: 7.96 msec per loop
python -m timeit 'sum(age > 17 for age in range(100000))'
50 loops, best of 5: 4.78 msec per loopI feel like this kind of operation on a list feels more naturally expressed by filtering the list and taking the length of the filtered list. Like this line of JS feels so much easier to read than that line of python: ages.filter(age => age > 17).length Directly translating this approach to python: len(list(filter(lambda age: (age > 17), ages))) Although a better way to write this in python I guess would be using lis…
I feel like the numpy version is most concise, most readable, and most array-ish: np.sum(age>17) (Assumes age is a np.array)
OP here; maybe I'll add a comment to the article to make the comparison between NumPy and APL for this expression. Thanks!