Swap memory in Python ? - three questions

[Terry Reedy]

Robert LaMarca wrote:
> Hi, 
> 
> I am using numpy and wish to create very large arrays.   My system is AMD 64 x 2 Ubuntu 8.04.  Ubuntu should be 64 bit. I have 3gb RAM and a 15 GB swap drive.  
> 
> The command I have been trying to use is; 
> g=numpy.ones([1000,1000,1000],numpy.int32)
> 
> This returns a memory error.  
> A smaller array ([500,500,500]) worked fine.. 
> Two smaller arrays again crashed the system.
> 
> So... I did the math.  a 1000x1000x1000 array at 32 bits should be around 4gb RAM... Obviously larger than RAM, but much smaller than the swap drive.
> 
> 1. So... does Numpy have a really lot of overhead? Or is my system just not somehow getting to make use of the 15gb swap area. 
> 2. Is there a way I can access the swap area, or direct numpy to do so? Or do I have to write out my own numpy cache system... 
> 3. How difficult is it to use data compression internally on numpy arrays? 

I do not know what numpy does, but constant arrays only need to store 
the dimensions and the constant value and have a getitem method that 
returns that constant value for any valid index.  This is at most a few 
hundred bytes regardless of the dimensions.