yield

How does 'yield' work in this permutation generator?

血红的双手。 提交于 2019-12-06 04:07:38
问题 def perm_generator(lst): if len(lst) == 1: yield lst else: for i in range(len(lst)): for perm in perm_generator(lst[:i] + lst[i+1:]): yield [lst[i]] + perm This code has been bugging me, since I don't understand how the yield s connect to each other. My understanding was that yield acts like a return , but it stops temporarily until it is called again. How do these yield s work? 回答1: It might help seeing a version that doesn't use generators: def perm_generator(lst): res = [] if len(lst) == 1

13.生成器,列表推到式

你离开我真会死。 提交于 2019-12-06 03:05:24
12. 前 方 高能 - 生成器器和 生成器器表达式 本节主要内容: 生成器和 生成器函数 列列表推导式 一. 生成器什什么是 生成器. 生成器实质就是迭代器. 在python中有三种 方式来获取 生成器: 通过 生成器函数 通过各种推导式来实现 生成器 通过数据的转换也可以获取 生成器 首先, 我们先看 一个很简单的函数: def func(): print("111") return 222 ret = func() print(ret) 结果: 111 222 将函数中的return换成yield就是 生成器 def func(): print("111") yield 222 ret = func() print(ret) 结果: <generator object func at 0x10567ff68> 运 行行的结果和上 面不 一样. 为什什么呢. 由于函数中存在了了yield. 那么这个函数就是 一个 生成器函数. 这个时候. 我们再执 行行这个函数的时候. 就不再是函数的执 行行了了. 而是获取这个 生成器.如何使 用呢? 想想迭代器. 生成器的本质是迭代器. 所以. 我们可以直接执 行行__next__()来执 行行 以下 生成器. def func(): print("111") yield 222 gener = func() # 这个时候函数不不会执 行行

19.yield和send的区别

泪湿孤枕 提交于 2019-12-05 22:42:12
转载: https://www.cnblogs.com/xhcdream/p/8304953.html     https://www.cnblogs.com/wushuaishuai/p/9212812.html send方法和next方法唯一的区别是在执行send方法会首先把上一次挂起的yield语句的返回值通过参数设定,从而实现与生成器方法的交互。 但是需要注意,在一个生成器对象没有执行next方法之前,由于没有yield语句被挂起,所以执行send方法会报错。 因为当send方法的参数为None时,它与next方法完全等价。但是注意,虽然这样的代码可以接受,但是不规范。所以,在调用send方法之前,还是先调用一次next方法为好。 #生成器的send用法 generator.send(value) def test(): i = 1 while i < 5: temp = yield i**2 print(temp) i += 1 t = test() #第一次运行只能使用next或者send(None) print(t.__next__()) #send的作用相当于使生成器继续运行,并且传递的参数为yield的返回值(程序中即temp的值) print(t.send("Hello World")) print(t.__next__())#相当于send(None)

python generator of generators?

流过昼夜 提交于 2019-12-05 22:31:05
问题 I wrote a class that reads a txt file. The file is composed of blocks of non-empty lines (let's call them "sections"), separated by an empty line: line1.1 line1.2 line1.3 line2.1 line2.2 My first implementation was to read the whole file and return a list of lists, that is a list of sections, where each section is a list of lines. This was obviously terrible memory-wise. So I re-implemented it as a generator of lists, that is at every cycle my class reads a whole section in memory as a list

Multiple content_for on the same page

前提是你 提交于 2019-12-05 22:13:10
问题 I have large block of HTML in my application that I would like to move into a shared template and then use content_for with yields to insert the necessary content. However, if I use it more than once in the same layout file the content_for just appends to the previous making that idea not work so well. Is there a solution to this? <div class="block side"> <div class="block_head"> <div class="bheadl"></div> <div class="bheadr"></div> <h2><%= yield :block_head %></h2> </div> <div class="block

生成器

淺唱寂寞╮ 提交于 2019-12-05 19:47:35
生成器: 生成器的本质就是迭代器 生成器函数 —— 本质上就是我们自己写得函数 生成器的表现形式 生成器函数 生成器表达式生成器函数: 含有yield关键字的函数就是生成器函数yield不能和return共用且需要写在函数内 特点: 调用函数的之后函数不执行,返回一个生成器 每次调用next方法的时候会取到一个值 直到取完最后一个,在执行next会报错 #生成器函数 : 执行之后会得到一个生成器作为返回值 ret = generator() print(ret) print(ret.__next__()) def generator(): print(1) yield 'a' print(2) yield 'b' yield 'c' g = generator() for i in g: print(i) ret = g.__next__() print(ret) ret = g.__next__() print(ret) ret = g.__next__() print(ret) send send 获取下一个值的效果和next基本一致只是在获取下一个值的时候,给上一yield的位置传递一个数据使用send的注意事项 第一次使用生成器的时候 是用next获取下一个值 最后一个yield不能接受外部的值 def generator(): print('abc') php =

Partial, Layout, Template rendering problems

拈花ヽ惹草 提交于 2019-12-05 18:21:38
The Situation So when I visit a page, I want to be able to apply a layout to a partial (I have three partials that I want with the same layout). Right now, I am trying to do it with this command: <%= render :partial => "shared/services/essay", :layout => "layouts/services/tab_pane", :locals => { :service => "essay" } %> where shared/services/essay goes something like: <% content_for :intro do %> <p> blah. </p> <% end %> <% content_for :workflow do %> <div> blah. </div> <% end %> <% content_for :value_prop do %> <p> blah. </p> <% end %> and `layouts/services/tab_pane' goes like: <div class="tab

初识函数--生成器

流过昼夜 提交于 2019-12-05 18:03:40
生成器本质就是迭代器,所以取值方式和迭代器一样,只不过迭代器是python自带的,生成器是自己写的 生成器的生成方式:a--通过生成器函数;b--推导式;c--python内置函数或模块(a,c本质一样,都是通过生成器函数,3是自带的,1是自己写) return和yield: 都是返回值,都可以返回多个,只是return是一次性返回多个 return还会终止函数的执行,函数体内return后面的代码不执行 yield会记录当前的执行位置: 一个yield对应一个next yield和yield from的区别(例3.3 例3.4): yield:将可迭代对象一次性返回 yield from:将可迭代对象一个一个地返回 例 3.1 def func(): print(1) yield 2 func() # 函数的调用就是生成生成器,什么都不输出..如果只print(func())是生成器的内存地址 print(func().__next__()) # 因为生成器的本质就是迭代器,所以取值和迭代器是一样的 例 3.2 def func(): print(1) yield 11 print(2) yield 22 func() print(func()) print(func().__next__()) print(func().__next__()) 例 3.3 def func():

C#: How to translate the Yield Keyword

邮差的信 提交于 2019-12-05 16:49:53
What would the MSDN sample look like without the yield keyword? You may use any example if you perfer. I would just like to understand what is going on under the hood. Is the yield operator eagerly or lazily evaluated? Sample: using System; using System.Collections; public class List { public static IEnumerable Power(int number, int exponent) { int counter = 0; int result = 1; while (counter++ < exponent) { result = result * number; yield return result; } } static void Main() { // Display powers of 2 up to the exponent 8: foreach (int i in Power(2, 8)) { Console.Write("{0} ", i); } } } MSDN -

Workaround for python 2.4's yield not allowed in try block with finally clause

混江龙づ霸主 提交于 2019-12-05 11:53:57
I'm stuck on python2.4, so I can't use a finally clause with generators or yield . Is there any way to work around this? I can't find any mentions of how to work around this limitation in python 2.4, and I'm not a big fan of the workarounds I've thought of (mainly involving __del__ and trying to make sure it runs within a reasonable time) aren't very appealing. You can duplicate code to avoid the finally block: try: yield 42 finally: do_something() Becomes: try: yield 42 except: # bare except, catches *anything* do_something() raise # re-raise same exception do_something() (I've not tried this