I have a Python program that reads lines of files and analyzes them. The program intentionally reads many lines into the RAM.
The program started getting MemoryError while appending a line (as str) to list. When I check in the task manager (the program runs on Windows 10), I see that the memory of the program is on 1635MB (stable) and the total memory use of the machine is below 50%.
I read that Python does not limit the memory, so what could be the reason?
Technical details:
I use Python 3.6.5 on Windows 10, 64-bit 16GB RAM machine. I run the program from the PowerShell terminal and not through the IDE.
I see that the memory of the program is on 1635MB
Windows EXEs compiled as 32-bit have, by default, a 2GB memory limit even when on 64-bit OS SKUs where plenty more memory is available. You're at 1.6 GB, so you're probably bumping up against this limit.
Make sure you are running the 64-bit version of Python.exe. Python.org's download page defaults to 32-bit for unknown reasons. But if you browse to the bottom of their download page for a given release, you can find the x86-64 version for 64-bit architecture.
I have a new Surface Book 2 with Windows Build 18.09 on it. The processor is an i7 8.th generation (8 cores) and it has 16 GB of RAM.
When I run any type of Python Code, the performance is unbearibly slow. I really do not think it is normal Python performance on this Laptop due to the following reasons:
the resource monitor shows 5% processor usage for any python code I run. Considering 8 cores being 100%, the python process should definitely use 12,5%.
I have another Windows 2-1 tablet (Miix 520) that has an i7 7th generation processor and that is normally throattling a lot. Still this tablet runs the same python code with the same python interpreter around 60% faster - not to speak of my Linux laptop with i7 7th generation running the code around 4-5 times faster.
I have no clue what I can do to get appropriate python performance. One comment I found elsewhere was the explanation that Windows Defender is slowing down python processes. I can not deactivate it because it is a working computer that is partially managed by IT. However, I can blacklist folders and files which I did for the whole Anaconda folder - I use Anaconda in order to manage python environments on Windows - and for python.exe. Unfortunately, this did not bring any improvements.
Does anyone has any experiences / explanations for such low performance of python on Windows (or the Surface Book 2 in particular)? Does any one have suggestions what could be done in order to get "normal" python performance?
It turned out that Windows Defender is slowing down the execution of of python processes.
Blacklisting python.exe and the folder from where I execute my script in Windows Defender leads to a significant performance boost.
Another reason, I found out about, is that Windows seems to have lower disc access rates than Linux. This was significant in my case because I processed 50.000 images.
So I packaged a few Python files into an .exe for windows. The machine I did it on was a school computer using windows 8. Everything worked well. I uploaded it to my cloud storage and downloaded it on my personal PC (Windows 10).
The program runs, but one of the features (loading a video) does not work. I get an error in the python.
Any ideas?
The problem is that the video isn't opening.
Here is some more info:
My Python code initially had the same exact errors when running from source. The problem was that I had imported an incompatible opencv. I switched from 3.0.0 to 3.2.0 which fix the source problem. From there I decided to continue with packaging the files into an .exe (using PyInstaller). On the Windows 8 Machine, it worked flawlessly. I decided to share that same exe file on my windows 10 machine and it didn't work. I got errors like I initially did with the wrong opencv. So I decided to package files on my windows 10 machine. I made sure I had the correct packages (PyQt4, opencv etc.) but the same errors were reproduced.
I then tested the .exe file around other Win 8 / Win 7 machines in my lab (School). None worked. It only works on one computer which I initially built and packaged it on.
I am not sure why this is happening. All machines were 64 bit. Or could it be something with my environment variables?
Any suggestions?
Thank you very much!
More(Unnecessary) Info:
This software isn't mine, but rather my mentor's. I am simply helping her debug the issues. It will then be uploaded online so other people can use it. This is why I want to make sure it works on every machine
- CS Student, Rising Junior Undergrad
I apologize for such a long post and Thanks again!
I was trying to probe the Python 32bit memory limit. So I wrote the little program
a=[]
while 1:
a.append(chr(65))
and watched the Windows task manager for the memory consumption of python.exe.
Firstly, I was surprised that it is occationally reduced (almost halved sometimes). Second, the amount only goes up to about 500MB (I believe on another 64bit machine it rose endlessly).
The computer has 4GB memory, windows boot>3GB is supposingly active and I patched the python.exe with imagecfg.exe -l. No other relevant processes are running and total memory does not exceed 40%. I believe the very same procedure worked on another computer though.
Any suggestions how I can check if my python can go up to 3GB now?
Is Python generally slower on Windows vs. a *nix machine? Python seems to blaze on my Mac OS X machine whereas it seems to run slower on my Window's Vista machine. The machines are similar in processing power and the vista machine has 1GBs more memory.
I particularly notice this in Mercurial but I figure this may simply be how Mercurial is packaged on windows.
I wanted to follow up on this and I found something that I believe is 'my answer'. It appears that Windows (vista, which is what I notice this on) is not as fast in handling files. This was mentioned by tony-p-lee.
I found this comparisons of Ubuntu vs Vista vs Win7. Their results are interesting and like they say, you need to take the results with a grain of salt. But I think the results lead me to the cause. Python, which I feel was indirectly tested, is about equivalent if not a tad-bit faster on Windows.. See the section "Richards benchmark".
Here is their graph for file transfers:
(source: tuxradar.com)
I think this specifically help address the question because Hg is really just a series of file reads, copies and overall handling. Its likely this is causing the delay.
http://www.tuxradar.com/content/benchmarked-ubuntu-vs-vista-vs-windows-7
No real numbers here but it certainly feels like the start up time is slower on Windows platforms. I regularly switch between Ubuntu at home and Windows 7 at work and it's an order of magnitude faster starting up on Ubuntu, despite my work machine being at least 4x the speed.
As for runtime performance, it feels about the same for "quiet" applications. If there are any GUI operations using Tk on Windows, they are definitely slower. Any console applications on windows are slower, but this is most likely due to the Windows cmd rendering being slow more than python running slowly.
Maybe the python has more depend on a lot of files open (import different modules).
Windows doesn't handle file open as efficiently as Linux.
Or maybe Linux probably have more utilities depend on python and python scripts/modules are more likely to be buffered in the system cache.
I run Python locally on Windows XP and 7 as well as OSX on my Macbook. I've seen no noticable performance differences in the command line interpreter, wx widget apps run the same, and Django apps also perform virtually identically.
One thing I noticed at work was that the Kaspersky virus scanner tended to slow the python interpreter WAY down. It would take 3-5 seconds for the python prompt to properly appear and 7-10 seconds for Django's test server to fully load. Properly disabling its active scanning brought the start up times back to 0 seconds.
With the OS and network libraries, I can confirm slower performance on Windows, at least for versions =< 2.6.
I wrote a CLI podcast-fetcher script which ran great on Ubuntu, but then wouldn't download anything faster than about 80 kB/s (where ~1.6 MB/s is my usual max) on either XP or 7.
I could partially correct this by tweaking the buffer size for download streams, but there was definitely a major bottleneck on Windows, either over the network or IO, that simply wasn't a problem on Linux.
Based on this, it seems that system and OS-interfacing tasks are better optimized for *nixes than they are for Windows.
Interestingly I ran a direct comparison of a popular Python app on a Windows 10 x64 Machine (low powered admittedly) and a Ubuntu 14.04 VM running on the same machine.
I have not tested load speeds etc, but am just looking at processor usage between the two. To make the test fair, both were fresh installs and I duplicated a part of my media library and applied the same config in both scenarios. Each test was run independently.
On Windows Python was using 20% of my processor power and it triggered System Compressed Memory to run up at 40% (this is an old machine with 6GB or RAM).
With the VM on Ubuntu (linked to my windows file system) the processor usage is about 5% with compressed memory down to about 20%.
This is a huge difference. My trigger for running this test was that the app using python was running my CPU up to 100% and failing to operate. I have now been running it in the VM for 2 weeks and my processor usage is down to 65-70% on average. So both on a long and short term test, and taking into account the overhead of running a VM and second operating system, this Python app is significantly faster on Linux. I can also confirm that the Python app responds better, as does everything else on my machine.
Now this could be very application specific, but it is at minimum interesting.
The PC is an old AMD II X2 X265 Processor, 6GB of RAM, SSD HD (which Python ran from but the VM used a regular 5200rpm HD which gets used for a ton of other stuff including recording of 2 CCTV cameras).