On 2019-12-16 08:56:26 +0100, dieter wrote:
> Note also that Python memeory management is quite elaborate:
> not every memory block is immediately obtained from and released
> to the operating system: Python has its own memory management
> data structures (to fill the gap between the fine grained
Would you try the pull request in this issue?
https://bugs.python.org/issue36694
I'm not sure this issue is relating to you because I don't know about your data.
Regards,
On Sun, Dec 1, 2019 at 10:14 AM José María Mateos wrote:
>
> Hi,
>
> I just asked this question on the IRC channel but
José María Mateos writes:
> I just asked this question on the IRC channel but didn't manage to get
> a response, though some people replied with suggestions that expanded
> this question a bit.
>
> I have a program that has to read some pickle files, perform some
> operations on them, and then
On Sun, Dec 01, 2019 at 12:26:15PM +1100, Chris Angelico wrote:
I can't answer your question authoritatively, but I can suggest a
place to look. Python's memory allocator doesn't always return memory
to the system when the objects are freed up, for various reasons
including the way that memory
On 11/30/19 5:05 PM, José María Mateos wrote:
> Hi,
>
> I just asked this question on the IRC channel but didn't manage to get
> a response, though some people replied with suggestions that expanded
> this question a bit.
>
> I have a program that has to read some pickle files, perform some
>
On Sun, Dec 1, 2019 at 12:15 PM José María Mateos wrote:
> print("Memory usage:", psutil.Process(os.getpid()).memory_info().rss)
>
> Notice that memory usage increases noticeably specially on files 4 and
> 5, the biggest ones, and doesn't come down as I would expect it to. But
> the
Hi,
I just asked this question on the IRC channel but didn't manage to get a
response, though some people replied with suggestions that expanded this
question a bit.
I have a program that has to read some pickle files, perform some
operations on them, and then return. The pickle objects I
