[issue33593] Support heapq on typed arrays?

[Raymond Hettinger]

Raymond Hettinger  added the comment:

As noted by Serhiy, the interaction with the Array type would incur significant 
overhead.  Your fastest approach will be to follow his suggest to first convert 
to a list and then perform heap manipulations.

Marking this as closed.  Thank you for the suggestion.

--
resolution:  -> rejected
stage:  -> resolved
status: open -> closed

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[issue33593] Support heapq on typed arrays?

[Serhiy Storchaka]

Serhiy Storchaka  added the comment:

Workaround:

alist = list(a)
heapq.heapify(alist)
a[:] = alist

And it should be not much slower than using heapq.heapify() directly if it 
could support general sequences. Using it with array.array would add 
significant overhead due to boxing.

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nosy: +serhiy.storchaka

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[issue33593] Support heapq on typed arrays?

[Diego Argueta]

Diego Argueta  added the comment:

However I do see your point about the speed.

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[issue33593] Support heapq on typed arrays?

[Diego Argueta]

Diego Argueta  added the comment:

I was referring to the C arrays in the Python standard library: 
https://docs.python.org/3/library/array.html

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[issue33593] Support heapq on typed arrays?

[Raymond Hettinger]

Raymond Hettinger  added the comment:

I don't think we should go down this path.  The efficiency of the C 
implementation depends on it being tightly coupled to lists.  This tool is used 
in the schedulers of various async tools (such as Tornando), used for merge(), 
nsmallest(), and nlargest() all of which depend on this foundational tool being 
very fast.

Also, I question whether it makes sense at all to be heapifying numpy arrays 
using standard library tooling.  It numpy arrays actually needed this and 
needed for it to be efficient, it would need to be implemented natively in 
numpy.

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nosy: +rhettinger
versions: +Python 3.8 -Python 2.7, Python 3.6

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[issue33593] Support heapq on typed arrays?

[Diego Argueta]

New submission from Diego Argueta :

It'd be really great if we could have support for using the `heapq` module on 
typed arrays from `array`. For example:


```
import array
import heapq
import random

a = array.array('I', (random.randrange(10) for _ in range(10)))
heapq.heapify(a)
```

Right now this code throws a TypeError:

TypeError: heap argument must be a list


I suppose I could use `bisect` to insert items one by one but I imagine a 
single call to heapify() would be more efficient, especially if I'm loading the 
array from a byte string.

>From what I can tell the problem lies in the C implementation, since removing 
>the _heapq imports at the end of the heapq module (in 3.6) makes it work.

--
components: Library (Lib)
messages: 317250
nosy: da
priority: normal
severity: normal
status: open
title: Support heapq on typed arrays?
type: enhancement
versions: Python 2.7, Python 3.6

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