I have a problem to parse 1000’s of text files(around 3000 lines in each file of ~400KB size ) in a folder. I did read them using readlines,
Is there any way of keeping a result variable in memory so I don’t have to recalculate it each time I run the beginning of my script?
I am doing a long (5-10 sec) series of the exact operations on a data set (which I am reading from disk) every time I run my script.
This wouldn’t be too much of a problem since I’m pretty good at using the interactive editor to debug my code in between runs; however sometimes the interactive capabilities just don’t cut it.
tl;dr
Does Python reuse ids? How likely it is that two objects with non overlapping lifetime will get the same id?
I sometimes write Python programs which are very difficult to determine how much memory it will use before execution. As such, I sometimes invoke a Python program that tries to allocate massive amounts of RAM causing the kernel to heavily swap and degrade the performance of other running processes.
I’m looking for simple but recommended way in Django to store a variable in memory only. When Apache restarts or the Django development server restarts, the variable is reset back to 0. More specifically, I want to count how many times a particular action takes place on each model instance (database record), but for performance reasons, I don’t want to store these counts in the database. I don’t care if the counts disappear after a server restart. But as long as the server is up, I want these counts to be consistent between the Django shell and the web interface, and I want to be able to return how many times the action has taken place on each model instance.
Is there a limit to memory for python? I’ve been using a python script to calculate the average values from a file which is a minimum of 150mb big.
I am using jupyter notebook with Python3 on windows 10. My computer has 8GB RAM and at least 4GB of my RAM is free.
How can I get the total physical memory within Python in a distribution agnostic fashion? I don’t need used memory, just the total physical memory.
Is there a Python library that allows manipulation of zip archives in memory, without having to use actual disk files?