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copied!<p>Do you understand list comprehensions? If so, a generator expression is like a list comprehension, but instead of finding all the items you're interested and packing them into list, it waits, and yields each item out of the expression, one by one.</p> <p>python2 version:</p> <pre><code>>>> my_list = [1, 3, 5, 9, 2, 6] >>> filtered_list = [item for item in my_list if item > 3] >>> print filtered_list [5, 9, 6] >>> len(filtered_list) 3 >>> # compare to generator expression ... >>> filtered_gen = (item for item in my_list if item > 3) >>> print filtered_gen # notice it's a generator object <generator object at 0xb7d5e02c> >>> len(filtered_gen) # So technically, it has no length Traceback (most recent call last): File "<stdin>", line 1, in <module> TypeError: object of type 'generator' has no len() >>> # We extract each item out individually. We'll do it manually first. ... >>> filtered_gen.next() 5 >>> filtered_gen.next() 9 >>> filtered_gen.next() 6 >>> filtered_gen.next() # Should be all out of items and give an error Traceback (most recent call last): File "<stdin>", line 1, in <module> StopIteration >>> # Yup, the generator is spent. No values for you! ... >>> # Let's prove it gives the same results as our list comprehension ... >>> filtered_gen = (item for item in my_list if item > 3) >>> gen_to_list = list(filtered_gen) >>> print gen_to_list [5, 9, 6] >>> filtered_list == gen_to_list True >>> </code></pre> <p>python3 version:</p> <p>change <code>next()</code> to <code>__next__()</code></p> <p>Because a generator expression only has to yield one item at a time, it can lead to big savings in memory usage. Generator expressions make the most sense in scenarios where you need to take one item at a time, do a lot of calculations based on that item, and then move on to the next item. If you need more than one value, you can also use a generator expression and grab a few at a time. If you need all the values before your program proceeds, use a list comprehension instead.</p>

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