Efficiently reading structured binary files using numpy's fromfile method

nev_packet = pylab.dtype([
    ('nstx', 'h'),
    ('npkt_id', 'h'),
    ('npkt_data_size', 'h'),
    ('timestamp', 'Q'),
    ('eventid', 'h'),
    ('nttl', 'H'),
    ('ncrc', 'h'),
    ('ndummy1', 'h'),
    ('ndummy2', 'h'),
    ('dnExtra', '8i'),
    ('eventstring', '128c')
])
data = pylab.fromfile(fin, dtype=nev_packet, count=-1)

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A note on Python's exit() and errors

Python's context managers are a very neat way of handling code that needs a teardown once you are done. Python objects have do have a destructor method ( __del__ ) called right before the last instance of the object is about to be destroyed. You can do a teardown there. However there is a lot of fine print to the __del__ method. A cleaner way of doing tear-downs is through Python's context manager , manifested as the with keyword. class CrushMe: def __init__(self): self.f = open('test.txt', 'w') def foo(self, a, b): self.f.write(str(a - b)) def __enter__(self): return self def __exit__(self, exc_type, exc_val, exc_tb): self.f.close() return True with CrushMe() as c: c.foo(2, 3) One thing that is important, and that got me just now, is error handling. I made the mistake of ignoring all those 'junk' arguments ( exc_type, exc_val, exc_tb ). I just skimmed the docs and what popped out is that you need to return True or...

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Store numpy arrays in sqlite

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