4 ms·

Adding `array` [0] to the list. It's generally slower than a list, but massively more memory-efficient. You're limited to a heterogeneous type, of course, but t

Adding `array` [0] to the list. It's generally slower than a list, but massively more memory-efficient. You're limited to a heterogeneous type, of course, but they can be quite useful for some operations. [0]: https://docs.python.org/3/library/array.html https://docs.python.org/3/library/array.html

cgopalan 2y ago
You mean homogenous instead of heterogenous, right?
- tomjakubowski 2y ago
  To add to this, arrays are also restricted to primitive C types. A Python array object is simply a heap allocated `unsigned long *` or what have you. https://docs.python.org/3/library/array.html https://docs.python.org/3/library/array.html https://github.com/python/cpython/blob/main/Modules/arraymodule.c https://github.com/python/cpython/blob/main/Modules/arraymod... And you can use struct for heterogenous data =) It has a neat DSL for packing/unpacking the data, reminiscent of the "little languages" from classic book The Practice of Programming. Python is actually pretty nice working with binary data. https://docs.python.org/3/library/struct.html https://docs.python.org/3/library/struct.html
  - sgarland 2y ago
    > Python is actually pretty nice working with binary data. It really is! I’ve been working on a project to generate large amounts of synthetic data, and it calls out to C for various shared libraries to do the heavy lifting *. Instead of encoding and decoding back and forth, I can just ship bytes around, and then directly write them out to a file. Saves a lot of time. *: yes, I should just rewrite it into a faster language entirely. I intend to, but for the time being it’s been “how fast can I make Python without anything but stdlib,” as long as you accept ctypes as being included in that definition.
- sgarland 2y ago
  Ugh… yes. Thank you.
- banannaise 2y ago
  It would be very funny to have an iterable type where the items are required to contain incompatible types.
  - Sohcahtoa82 2y ago
    Somewhere out there, I'm sure someone could come up with a use case.
lang4d 2y ago
Why is it slower compared to a normal list?
- sgarland 2y ago
  The simplistic answer is that lists have been heavily optimized over the years, arrays haven’t been touched much. I’m not positive on why lists are faster to create than lists, though. Retrieval makes sense (lists already store the Python object, arrays have to cast it back), but creation I’m unsure about. I’ll check dis.dis. EDIT: from a sibling comment above [0], maybe because array reallocs are done much more granularly than lists, so as it grows, it’ll have to do so more frequently compared to lists? [0]: https://github.com/python/cpython/blob/main/Modules/arraymodule.c#L162 https://github.com/python/cpython/blob/main/Modules/arraymod...

cgopalan 2y ago

You mean homogenous instead of heterogenous, right?

tomjakubowski 2y ago
To add to this, arrays are also restricted to primitive C types. A Python array object is simply a heap allocated `unsigned long *` or what have you. https://docs.python.org/3/library/array.html https://docs.python.org/3/library/array.html https://github.com/python/cpython/blob/main/Modules/arraymodule.c https://github.com/python/cpython/blob/main/Modules/arraymod... And you can use struct for heterogenous data =) It has a neat DSL for packing/unpacking the data, reminiscent of the "little languages" from classic book The Practice of Programming. Python is actually pretty nice working with binary data. https://docs.python.org/3/library/struct.html https://docs.python.org/3/library/struct.html
- sgarland 2y ago
  > Python is actually pretty nice working with binary data. It really is! I’ve been working on a project to generate large amounts of synthetic data, and it calls out to C for various shared libraries to do the heavy lifting *. Instead of encoding and decoding back and forth, I can just ship bytes around, and then directly write them out to a file. Saves a lot of time. *: yes, I should just rewrite it into a faster language entirely. I intend to, but for the time being it’s been “how fast can I make Python without anything but stdlib,” as long as you accept ctypes as being included in that definition.
sgarland 2y ago
Ugh… yes. Thank you.
banannaise 2y ago
It would be very funny to have an iterable type where the items are required to contain incompatible types.
- Sohcahtoa82 2y ago
  Somewhere out there, I'm sure someone could come up with a use case.

lang4d 2y ago

Why is it slower compared to a normal list?

sgarland 2y ago
The simplistic answer is that lists have been heavily optimized over the years, arrays haven’t been touched much. I’m not positive on why lists are faster to create than lists, though. Retrieval makes sense (lists already store the Python object, arrays have to cast it back), but creation I’m unsure about. I’ll check dis.dis. EDIT: from a sibling comment above [0], maybe because array reallocs are done much more granularly than lists, so as it grows, it’ll have to do so more frequently compared to lists? [0]: https://github.com/python/cpython/blob/main/Modules/arraymodule.c#L162 https://github.com/python/cpython/blob/main/Modules/arraymod...