yield

In Python most examples of yield from explain it with saying that yield from foo() is similar to for x in foo(): yield x On the other hand it doesn't seem to be exactly the same and there's some magic thrown in. I feel a bit uneasy about using a function that does magic that I don't understand. What do I have to know about the magic of yield from to avoid getting into a situation where the magic does something I don't expect? What advantages does the magic provide, that I should be aware of? When foo() returns a regular iterable, the two are equivalent. The 'magic' comes into play when foo()

1.1 迭代器 1、 可迭代对象： str,list,tuple,set,dict, 迭代器： f( 文件 ) ， range() 可迭代对象和迭代器都可以 for 循环 可迭代对象不会计数， 迭代器会计数，上面操作到第 3 个，则下面的程序继续使用第 4 个 以上数据类型中都有一个函数 __iter__() 所有包含了函数 __iter__() 的数据类型都是可迭代对象 Iterable 2、 获取迭代器 .__iter__ 迭代器往外拿元素 .__next__ lis = [1,2,3,4] it = lis.__iter__() #it 是迭代器 print(it.__next__()) # 打印第一个元素 print(it.__next__()) # 打印第二个元素 3、Iterable: 可迭代对象 内部包含 __iter__() Iterator: 迭代器 内部包含 __iter__() 和 __next__ from collections import Iterable # 可迭代的 from collections import Iterator # 迭代器 lis = [1,2,3,4] isinstence( 对象，类型 ) # 判断对象是否是这个类型 isinstence(lis,Iterable) # 判断是否是可迭代对象 isinstence(lis

import contextlib import time @contextlib.contextmanager def time_print(task_name): t = time.time() try: yield finally: print task_name, "took", time.time() - t, "seconds." def doproc(): x=1+1 with time_print("processes"): [doproc() for _ in range(500)] # processes took 15.236166954 seconds. when does doproc get executed when using this decorator? yield expression returns control to the whatever is using the generator. The generator pauses at this point, which means that the @contextmanager decorator knows that the code is done with the setup part. In other words, everything you want to do in

Can you help me in understanding of yield keyword in asp .NET(C#) . kemiller2002 Yield return automatically creates an enumerator for you. http://msdn.microsoft.com/en-us/library/9k7k7cf0.aspx So you can do something like //pseudo code: while(get_next_record_from_database) { yield return your_next_record; } It allows you to quickly create an object collection (an Enumerator) that you can loop through and retrieve records. The yield return statement handles all the of the code needed to create an enumerator for you. The big part of the yield return statement is that you don't have to load all

I was wondering if there is any concurrency (now or future), or performance benefit to using yield return over returning a list. See the following examples Processing Method void Page_Load() { foreach(var item in GetPostedItems()) Process(item); } using yield return IEnumerable<string> GetPostedItems() { yield return Item1.Text; yield return Item2.Text; yield return Item3.Text; } returning a list IEnumerable<string> GetPostedItems() { var list = new List<string>(); list.Add(Item1.Text); list.Add(Item2.Text); list.Add(Item3.Text); return list; } In the yield return example, the result is

I used node.js(0.11.13) with --harmony flag and used function *() and yield keywords. I tried to simplify my development on node.js with help of coffeescript, so far it works great but I went into troubles with yield and declaring a generator - it complains about 'reserved keyword yield' . Any ideas? Another way to open the gate to the black dimension is: co = require 'co' sleep = require 'co-sleep' co(`function*(){1` console.log 'hi!' `yield sleep(1000)` console.log 'bye!' `1}`)() It's seems to be perfectly valid coffee-script, though, webstorm cofeescript plugin cries about errors, but it

可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效，请关闭广告屏蔽插件后再试): 问题: I want to use generator yield and async functions. I read this topic , and wrote next code: import asyncio async def createGenerator(): mylist = range(3) for i in mylist: await asyncio.sleep(1) yield i*i async def start(): mygenerator = await createGenerator() for i in mygenerator: print(i) loop = asyncio.get_event_loop() try: loop.run_until_complete(start()) except KeyboardInterrupt: loop.stop() pass But i got the error: SyntaxError: 'yield' inside async function How to use yield generator in async function? 回答1: Upd: Starting with Python 3