Repeatedly Appending To A Large List (python 2.6.6)
Solution 1:
One thing you might want to consider is writing your data to a file as it's collected. I don't know (or really care) if it will affect performance, but it will help ensure that you don't lose all your data if power blips. Once you've got all the data, you can suck it out of the file and jam it in a list or an array or a numpy matrix or whatever for processing.
Solution 2:
Appending to a python list has a constant cost. It is not affected by the number of items in the list (in theory). In practice appending to a list will get slower once you run out of memory and the system starts swapping.
http://wiki.python.org/moin/TimeComplexity
It would be helpful to understand why you actually append things into a list. What are you planning to do with the items. If you don't need all of them you could build a ring buffer, if you don't need to do computation you could write the list to a file, etc.
Solution 3:
First of all, 38 two-character sets per second, 1 stop bit, 8 data bits, and no parity, is only 760 baud, not fast at all.
But anyway, my suggestion, if you're worried about having overly large lists/don't want to use one huge list, is just to store store a list on disk once it reaches a certain size and start a new list, repeating until you've gotten all the data, then combining all the lists into one once you're done receiving the data.
Though you may skip the sublists completely and just go with nmichaels' suggestion, writing the data to a file as you get it and using a small circular buffer to hold the received data that has not yet been written.
Solution 4:
It might be faster to use numpy if you know how long the array is going to be and you can convert your hex codes to ints:
import numpy
a = numpy.zeros(3000000, numpy.int32)
for i in range(3000000):
a[i] = int(scanHexFromSerial(),16)
This will leave you with an array of integers (which you could convert back to hex with hex()), but depending on your application maybe that will work just as well for you.
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