AI engineering glossary · NumPy pandas visualization
What is memory-mapped array?
Memory-mapped array (also called np.memmap, memmap): An array whose data stays in a file on disk while NumPy reads pieces of it into memory only when they are accessed. It lets you work with datasets larger than the available RAM and share data between processes, at the cost of slower disk access.
Memory-mapped array: an example
np.load('big.npy', mmap_mode='r') lets you slice a 30 GB array on a 16 GB laptop, loading only the parts you touch.
Related terms
More NumPy pandas visualization terms
Where you learn it
Memory-mapped array is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.