[Python-ideas] Delayed Execution via Keyword

Thu Mar 2 18:53:51 EST 2017

Other things that scrutinize an expression are iteration or branching (with
the current evaluation model). If `xs` is a thunk, then `for x in xs` must
scrutinize `xs`. At first this doesn't seem required; however, in general
`next` imposes a data dependency on the next call to `next`. For example:

x0 = next(xs)
x1 = next(xs)

print(x1)
print(x0)

If `next` doesn't force computation then evaluating `x1` before `x0` will
bind `x1` to `xs[0]` which is not what the eager version of the code does.

To preserve the current semantics of the language you cannot defer
arbitrary expressions because they may have observable side-effects.
Automatically translating would require knowing ahead of time if a function
can have observable side effects, but that is not possible in Python.
Because it is impossible to tell in the general case, we must rely on the
user to tell us when it is safe to defer an expression.

On Thu, Mar 2, 2017 at 6:42 PM, Abe Dillon <abedillon at gmail.com> wrote:

> I'm going to repeat here what I posted in the thread on lazy imports.
> If it's possible for the interpreter to determine when it needs to force
> evaluation of a lazy expression or statement, then why not use them
> everywhere? If that's the case, then why not make everything lazy by
> default? Why not make it a service of the language to lazify your code
> (analogous to garbage collection) so a human doesn't have to worry about
> screwing it up?
>
> There are, AFAIK, three things that *must* force evaluation of lazy
> expressions or statements:
>
> 1) Before the GIL is released, all pending lazy code must be evaluated
> since the current thread can't know what variables another thread will try
> to access (unless there's a way to explicitly label variables as "shared",
> then it will only force evaluation of those).
>
> 2) Branching statements force evaluation of anything required to evaluate
> the conditional clause.
>
> 3) I/O forces evaluation of any involved lazy expressions.
>
>
> On Mon, Feb 20, 2017 at 7:07 PM, Joshua Morton <joshua.morton13 at gmail.com>
> wrote:
>
>> This comes from a bit of a misunderstanding of how an interpreter figures
>> out what needs to be compiled. Most (all?) JIT compilers run code in an
>> interpreted manner, and then compile subsections down to efficient machine
>> code when they notice that the same code path is taken repeatedly, so in
>> pypy something like
>>
>>     x = 0
>>     for i in range(100000):
>>         x += 1
>>
>> would, get, after 10-20 runs through the loop, turned into assembly that
>> looked like what you'd write in pure C, instead of the very indirection and
>> pointer heavy code that such a loop would be if you could take it and
>> convert it to cpython actually executes, for example. So the "hot" code is
>> still run.
>>
>> All that said, this is a bit of an off topic discussion and probably
>> shouldn't be on list.
>>
>> What you really do want is functional purity, which is a different
>> concept and one that python as a language can't easily provide no matter
>> what.
>>
>> --Josh
>>
>> On Mon, Feb 20, 2017 at 7:53 PM Abe Dillon <abedillon at gmail.com> wrote:
>>
>>> On Fri, Feb 17, 2017, Steven D'Aprano wrote:
>>>
>>> JIT compilation delays *compiling* the code to run-time. This is a
>>> proposal for delaying *running* the code until such time as some other
>>> piece of code actually needs the result.
>>>
>>>
>>> My thought was that if a compiler is capable of determining what needs
>>> to be compiled just in time, then an interpreter might be able to determine
>>> what expressions need to be evaluated just when their results are actually
>>> used.
>>>
>>> So if you had code that looked like:
>>>
>>> >>> log.debug("data: %s", expensive())
>>>
>>> The interpreter could skip evaluating the expensive function if the
>>> result is never used. It would only evaluate it "just in time". This would
>>> almost certainly require just in time compilation as well, otherwise the
>>> byte code that calls the "log.debug" function would be unaware of the byte
>>> code that implements the function.
>>>
>>> This is probably a pipe-dream, though; because the interpreter would
>>> have to be aware of side effects.
>>>
>>>
>>>
>>> On Mon, Feb 20, 2017 at 5:18 AM, <tritium-list at sdamon.com> wrote:
>>>
>>>
>>>
>>> > -----Original Message-----
>>> > From: Python-ideas [mailto:python-ideas-bounces+tritium-
>>> > list=sdamon.com at python.org] On Behalf Of Michel Desmoulin
>>> > Sent: Monday, February 20, 2017 3:30 AM
>>> > To: python-ideas at python.org
>>> > Subject: Re: [Python-ideas] Delayed Execution via Keyword
>>> >
>>> > I wrote a blog post about this, and someone asked me if it meant
>>> > allowing lazy imports to make optional imports easier.
>>> >
>>> > Someting like:
>>> >
>>> > lazy import foo
>>> > lazy from foo import bar
>>> >
>>> > So now if I don't use the imports, the module is not loaded, which
>>> could
>>> > also significantly speed up applications starting time with a lot of
>>> > imports.
>>>
>>> Would that not also make a failure to import an error at the time of
>>> executing the imported piece of code rather than at the place of import?
>>> And how would optional imports work if they are not loaded until use?
>>> Right
>>> now, optional imports are done by wrapping the import statement in a
>>> try/except, would you not need to do that handling everywhere the
>>> imported
>>> object is used instead?
>>>
>>> (I haven't been following the entire thread, and I don't know if this is
>>> a
>>> forest/tress argument)
>>>
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>>
>>
>
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