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:
I need a queue which multiple threads can put stuff into, and multiple threads may read from.
I have two GPUs and would like to run two different networks via ipynb simultaneously, however the first notebook always allocates both GPUs.
Using Django ORM, can one do something like queryset.objects.annotate(Count('queryset_objects', gte=VALUE)). Catch my drift?