134
How Python Compares Floats and Ints: When Equals Isn’t Really Equal
(blog.codingconfessions.com)
this post was submitted on 27 May 2024
134 points (94.1% liked)
Technology
59149 readers
2298 users here now
This is a most excellent place for technology news and articles.
Our Rules
- Follow the lemmy.world rules.
- Only tech related content.
- Be excellent to each another!
- Mod approved content bots can post up to 10 articles per day.
- Threads asking for personal tech support may be deleted.
- Politics threads may be removed.
- No memes allowed as posts, OK to post as comments.
- Only approved bots from the list below, to ask if your bot can be added please contact us.
- Check for duplicates before posting, duplicates may be removed
Approved Bots
founded 1 year ago
MODERATORS
you are viewing a single comment's thread
view the rest of the comments
view the rest of the comments
Even in python you can have control of what types of numbers are used under the hood with numpy arrays (and chances are if you are using floats in any quantity you want to be using numpy). I would be very surprised if
array([1,2,3], dtype=uint8) == array([1,2,3], dtype=int16)gave[False, False, False]. In general I think==for numbers should give mathematical equivalence, with the understanding that comparing floats is highly likely to give false negatives unless you are extremely careful with what you are comparing.Numpys more or less a math wrapper for c isnt it?
More Fortran than C, but its the same for any language doing those sorts of array mathematics, they will be calling compiled versions of blas and lapack. Numpy builds up low level highly optimised compiled functions into a coherant python ecosystem. A numpy array is a C array with some metadata sure, but a python list is also just a C array of pointers to pyobjects.