generator

问题 I have a vector of size = N where each element i can have values from 0 to possible_values[i]-1. I want to do a function that iterates me through all those values. I was able to do that in Python using a recursive generator: def all_values(size,values,pos=0): if pos == size: yield [] else: for v in xrange(values[pos]): for v2 in all_values(size,values,pos+1): v2.insert(0,v) yield v2 possible_values=[3,2,2] for v in all_values(3,possible_values): print v Example output: [0, 0, 0] [0, 0, 1] [0,

问题 I have a generator called generateNumbers in JavaScript and another generator generateLargerNumbers which takes each value generated by generateNumbers and applies a function addOne to it, as such: function addOne(value) { return value + 1 } function* generateNumbers() { yield 1 yield 2 yield 3 } function* generateLargerNumbers() { for (const number of generateNumbers()) { yield addOne(number) } } Is there any terser way to do this without building an array out of the generated values? I'm

问题 The same notorious error npm ERR! peerinvalid The package generator-karma does not satisfy its siblings' peerDependencies requirements! npm ERR! peerinvalid Peer generator-angular@0.7.1 wants generator-karma@~0.6.0 npm ERR! peerinvalid Peer generator-angular-ui-router@0.5.3 wants generator-karma@~0.5.0 npm ERR! System Darwin 12.5.0 npm ERR! command "node" "/usr/local/bin/npm" "install" "-g" "generator-angular" npm ERR! cwd /Users/dmitrizaitsev/Dropbox/Priv/APP/my-yo-project npm ERR! node -v

问题 I wanted to create a redis cache in python, and as any self respecting scientist I made a bench mark to test the performance. Interestingly, redis did not fare so well. Either Python is doing something magic (storing the file) or my version of redis is stupendously slow. I don't know if this is because of the way my code is structured, or what, but I was expecting redis to do better than it did. To make a redis cache, I set my binary data (in this case, an HTML page) to a key derived from the

问题 According to answer to this question, yield break in C# is equivalent to return in Python. In the normal case, return indeed stops a generator. But if your function does nothing but return , you will get a None not an empty iterator, which is returned by yield break in C# def generate_nothing(): return for i in generate_nothing(): print i You will get a TypeError: 'NoneType' object is not iterable , but if I add and never run yield before return , this function returns what I expect. def

问题 Would anybody help me to solve the following problem. I have tried it on my own and I have attached the solution also. I have used 2-d list, but I want a different solution without 2-d list, which should be more pythonic. pl suggest me any of you have any other way of doing this. Q) Consider Share prices for a N number of companies given for each month since year 1990 in a CSV file. Format of the file is as below with first line as header. Year,Month,Company A, Company B,Company C, ..........

问题 Would anybody help me to solve the following problem. I have tried it on my own and I have attached the solution also. I have used 2-d list, but I want a different solution without 2-d list, which should be more pythonic. pl suggest me any of you have any other way of doing this. Q) Consider Share prices for a N number of companies given for each month since year 1990 in a CSV file. Format of the file is as below with first line as header. Year,Month,Company A, Company B,Company C, ..........

问题 Consider these two functions: def foo(): x = 0 while True: yield x x += 1 def wrap_foo(limit=10, gen=True): fg = foo() count = 0 if gen: while count < limit: yield next(fg) count += 1 else: return [next(fg) for _ in range(limit)]= foo() is a generator, and wrap_foo() just puts a limit on how much data gets generated. I was experimenting with having the wrapper behave as a generator with gen=True , or as a regular function that puts all generated data into memory directly with the kwarg gen

问题 I have something, when run as a list comprehension , runs fine. It looks like, [myClass().Function(things) for things in biggerThing] Function is a method, and it builds a list. The method itself doesn't return anything, but lists get manipulated within. Now when I change it to a generator , (myClass().Function(things) for things in biggerThing) It doesn't manipulate the data like I would expect it to. In fact, it doesn't seem to manipulate it at all. What is the functional difference between

问题 I'm playing around with generators and generator expressions and I'm not completely sure that I understand how they work (some reference material): >>> a = (x for x in range(10)) >>> next(a) 0 >>> next(a) 1 >>> a.send(-1) 2 >>> next(a) 3 So it looks like generator.send was ignored. That makes sense (I guess) because there is no explicit yield expression to catch the sent information ... However, >>> a = ((yield x) for x in range(10)) >>> next(a) 0 >>> print next(a) None >>> print next(a) 1 >>