On 2019-02-03 22:58, David Mertz wrote:
>>> len(v) # Number of elements in the Vector `v`
Agreed, this should definitely be the behavior. So how do we get a
vector of lengths of each element?
>>> # Compute the length of each element of the Vector `v`
>>> v.apply(len)
>>> v @ len
Also possible is:
v.len()
We couldn't do that for every possible function, but this one is special
inasmuch as we expect the items each to have a .__len__() but don't want
to spell the dunders. Likewise for just a handful of other
methods/functions.
The key different though is that *I* would want to a way to use both
methods already attached to the objects/items. in a vector and also a
generic user-provided function that operates on the items. I guess you
disagree about "method pass-through" but it reads more elegantly to me:
>>> # Replace all "a" by "b"
>>> v.apply(lambda s: s.replace("a", "b"))
>>> v @ (lambda s: s.replace("a", "b"))
Compare these with:
v.replace("a", "b")
Since we already know v is a Vector, we kinda expect methods to be
vectorized. This feels like the "least surprise" and also the least
extra code. Moreover, spelling chained methods with many .appy() calls
(even if spelled '@') feels very cumbersome:
Do they need multiple uses of apply and @?
(A) v.apply(lambda s: s.replace("a", "b")).apply(str.upper).apply(lambda
s: s.count("B"))
>
v.apply(lambda s: s.replace("a", "b").upper().count("B"))
(B) v @ lambda s: s.replace("a", "b") @ str.upper @ lambda s: s.count("B")
v @ lambda s: s.replace("a", "b").upper().count("B")
(C) v.replace("a","b").upper().count("B")
Between these, (C) feels a heck of a lot more intuitive and readable to me.
[snip]
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