, 1 min read
Time to move from Numerical Python to SciPy Core
If you are a Python user, and you do Numerical Analysis, it might be time to move from Numerical Python to SciPy Core. I complained earlier about SciPy Core, but it seems that most of the problems I pointed out (missing inline documentation and broken functions) have either been fixed, or I wrongly pointed a finger.
I still have a few issues with the new package though:
- The naming convention for the LinearAlgebra package is awful. I don’t want to have to work with a package called “scipy.basic.linalg”: if you want to save space, don’t abbreviate LinearAlgebra to linalg and add three subpackages to it. Call the package scipy.LinearAlgebra, for example.- There are glitches in the documentation. Both “help(scipy.basic.linalg)” or “help(scipy.linalg)” return a page describing “scipy.basic.linalg” as the “Lite version of scipy.linalg” and a list of 3 supported functions (Heigenvectors, eigenvectors, singular_value_decomposition). There are more than only 3 functions in this package!
On the positive side of things, you can now simply do “import scipy” to get the basic functions (like the scipy.array class). So, time to switch!