If your intention is to some other scope, iterate over it, do some other stuff, then be able to iterate over it again later on in that same scope. Then the only thing you shouldn’t try doing is passing the iterator, instead pass the generator: var generator = function*() { yield 1; yield 2; yield … Read more
Just use the .union() method. >>> l = [set([1,2,3]), set([4,5,6]), set([1,4,9])] >>> frozenset().union(*l) frozenset([1, 2, 3, 4, 5, 6, 9]) This works for any iterable of iterables.
As pointed in the comments, you could do it in a new thread, using Queue. The drawback is that you’d still need some way to access the final result (what fmin returns at the end). My example below uses an optional callback to do something with it (another option would be to just yield it … Read more
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. >>> my_list = [1, 3, 5, 9, 2, 6] >>> filtered_list = [item … Read more
An iterator traverses a collection one at a time. A generator generates a sequence, one item at a time. You might for example, iterate over the result of a generator…
Yes, increasing the buffer size might drastically increase the execution speed of your program, because it will reduce the number of context switches. Goroutines aren’t garbage-collected, but channels are. In your example, the fibonacci goroutine will run forever (waiting for another goroutine to read from the channel c), and the channel c will never be … Read more
Something like http://jscc.phorward-software.com/, maybe? JS/CC is the first available parser development system for JavaScript and ECMAScript-derivates. It has been developed, both, with the intention of building a productive compiler development system and with the intention of creating an easy-to-use academic environment for people interested in how parse table generation is done general in bottom-up parsing. … Read more
Those methods are roughly the same. It is correct to subclass Sequence when your dataset doesn’t fit in memory. But you shouldn’t run any preprocessing in any of the class’ methods because that will be reexecuted once per epoch wasting lots of computing resources. It is probably also easier to shuffle the samples rather than … Read more
Try this: an_iterator = iter(a_list) … docs here. Is that what you want?
You can return a tuple of record and exception in the parsefunc and let the consumer function decide what to do with the exception: import random def get_record(line): num = random.randint(0, 3) if num == 3: raise Exception(“3 means danger”) return line def parsefunc(stream): for line in stream: try: rec = get_record(line) except Exception as … Read more