Why is :memory: in sqlite so slow? I’ve been trying to see if there are any performance improvements gained by using in-memory sqlite vs. disk based sqlite. Basically I’d like to trade startup time and memory to get extremely rapid queries which do not hit disk during the course of the application. However, the following … Read more
I have 5 lists, all of the same length, and I’d like to write them to 5 columns in a CSV. So far, I can only write one to a column with this code:
How do you calculate program run time in python? Answers: Thank you for visiting the Q&A section on Magenaut. Please note that all the answers may not help you solve the issue immediately. So please treat them as advisements. If you found the post helpful (or not), leave a comment & I’ll get back to … Read more
I’ve written a simple script to parse XML chat logs using the BeautifulSoup module. The standard soup.prettify() works ok except chat logs have a lot of fluff in them. You can see both the script code and some of the XML input file I’m working with below:
I have a simple problem in Python that is very very strange.
I want to find out what the maximum amount of RAM allocated during the call to a function is (in Python). There are other questions on SO related to tracking RAM usage:
Problem:
The code compiles fine but when ever i call the read_db_config function i get “Exception: mysql not found in the mysql_config.ini file”
I’m trying to run example from Celery documentation.
I’m wondering about the way that python’s Multiprocessing.Pool class works with map, imap, and map_async. My particular problem is that I want to map on an iterator that creates memory-heavy objects, and don’t want all these objects to be generated into memory at the same time. I wanted to see if the various map() functions would wring my iterator dry, or intelligently call the next() function only as child processes slowly advanced, so I hacked up some tests as such: