3 ms·
The difficulty here is combining multiple libraries each using its own abstractions. For example, since the standard library does not have a Matrix class suita
by nimrody 7y ago
The difficulty here is combining multiple libraries each using its own abstractions.
For example, since the standard library does not have a Matrix class suitable for numerical applications (or maybe it does today...) using multiple libraries each with its own Matrix class is difficult. Multiple libraries are needed since one library may not contain all numerical algorithms one may require for a given app.
This is not a problem for Google where I assume everyone is using internally written code -- but is a problem for most of us.
- jcelerier 7y ago> For example, since the standard library does not have a Matrix class suitable for numerical applications (or maybe it does today...) using multiple libraries each with its own Matrix class is difficult. well, Python comes with a builtin "matrix-like" array type and yet it's not the one which is the most used in scientific computation.
- RayDonnelly 7y ago.. because it's (relatively speaking) brand new?
- aldanor 7y agoPython provides the buffer interface, however (which `array` module implements), which links Python's buffers and memoryviews to numpy arrays to multiple other 3rd-party array-like and table-like types and structures.