What Happened? When you use next(iter(instance_of_Class2)), iter() calls .close() on the inner generator when it (the iterator, not the generator!) goes out of scope (and is deleted), while with Class1, iter() only closes its instance >>> g = (i for i in range(3)) >>> b = Class2(g) >>> i = iter(b) # hold iterator open … Read more
You’re probably looking for Generator Delegation (PEP380) For simple iterators, yield from iterable is essentially just a shortened form of for item in iterable: yield item def generator(iterable): for i in iterable: yield do_something(i) def generate_all(): yield from generator(get_the_list()) It’s pretty concise and also has a number of other advantages, such as being able to … Read more
What exactly do you mean by thread-safe? You certainly shouldn’t change the dictionary while you’re iterating over it, whether in the same thread or not. If the dictionary is being accessed in multiple threads in general, the caller should take out a lock (the same one covering all accesses) so that they can lock for … Read more
The assignment syntax (“yield expression”) allows you to treat the generator as a rudimentary coroutine. First proposed in PEP 342 and documented here: https://docs.python.org/2/reference/expressions.html#yield-expressions The client code that is working with the generator can communicate data back into the generator using its send() method. That data is accessible via the assignment syntax. send() will also … Read more
No the yield return will not cause any locks to be freed / unlocked. The lock statement will expand out to a try / finally block and the iterator will not treat this any differently than an explicit try / finally in the iterator method. The details are a bit more complicated but the basic … Read more
This is a great question. I’ll try to show you how we can use Python’s introspective abilities and open source to get an answer. We can use the dis module to peek behind the curtain and see how the CPython interpreter implements a for loop over an iterator. >>> def for_loop(iterable): … for item in … Read more
One possible solution, as you already mentioned, is to use channels. Here is an example that should work in your case: import { channel } from ‘redux-saga’ import { put, take } from ‘redux-saga/effects’ const downloadFileChannel = channel() export function* loadFile(id) { … const download = RNFS.downloadFile({ … // push `S_PROGRESS` action into channel on … Read more
Why reinvent the wheel when you can use os.walk import os for root, dirs, files in os.walk(path): for name in files: print os.path.join(root, name) os.walk is a generator that yields the file names in a directory tree by walking the tree either top-down or bottom-up
Yes, it is. You can find out a lot more about it in chapter 6 of my book, C# in Depth. Fortunately chapter 6 is available for free from Manning’s web site. I also have two other articles on the book’s web site. Feedback welcome.
It’s a balancing act: do you want to force all the data into memory immediately so you can free up the connection, or do you want to benefit from streaming the data, at the cost of tying up the connection for all that time? The way I look at it, that decision should potentially be … Read more