Conclusion
This lesson provides a brief summary of what we have covered so far in this chapter.
As explained on the NumPy website, NumPy is the fundamental package for
scientific computing with Python. However, as illustrated in this chapter, the usage of NumPy strengths goes far beyond a mere multi-dimensional container of
generic data. Using ndarray as a private property in one case (TypedList) or
directly subclassing the ndarray class (GPUData) to keep track of memory in
another case, we’ve seen how it is possible to extend NumPy’s capabilities to
suit very specific needs. The limit is only your imagination and your experience.
The next chapter will give a brief overview of some other useful libraries that can be used in Python.