yield

Python爬虫从入门到放弃（十九）之 Scrapy爬取所有知乎用户信息(下)

由 别说谁变了你拦得住时间么 提交于 2020-01-03 04:40:32
在上一篇文章中主要写了关于爬虫过程的分析，下面是代码的实现，完整代码在： https://github.com/pythonsite/spider items中的代码主要是我们要爬取的字段的定义 class UserItem(scrapy.Item): id = Field() name = Field() account_status = Field() allow_message= Field() answer_count = Field() articles_count = Field() avatar_hue = Field() avatar_url = Field() avatar_url_template = Field() badge = Field() business = Field() employments = Field() columns_count = Field() commercial_question_count = Field() cover_url = Field() description = Field() educations = Field() favorite_count = Field() favorited_count = Field() follower_count = Field() following_columns

pytest文档6-fixture之yield实现teardown

由 一个人想着一个人 提交于 2020-01-03 02:07:37
前言 上一篇讲到fixture通过scope参数控制setup级别，既然有setup作为用例之前前的操作，用例执行完之后那肯定也有teardown操作。 这里用到fixture的teardown操作并不是独立的函数，用yield关键字呼唤teardown操作 scope="module" 1.fixture参数scope="module"，module作用是整个.py文件都会生效，用例调用时，参数写上函数名称就行 # 新建一个文件test_f1.py # coding:utf-8 import pytest ''' ** 作者：上海-悠悠 QQ交流群：588402570** ''' @pytest.fixture(scope="module") def open(): print("打开浏览器，并且打开百度首页") def test_s1(open): print("用例1：搜索python-1") def test_s2(open): print("用例2：搜索python-2") def test_s3(open): print("用例3：搜索python-3") if __name__ == "__main__": pytest.main(["-s", "test_f1.py"]) 运行结果： ============================= test

ES6的学习（3）

由 我们两清 提交于 2020-01-01 20:47:12
Iterator遍历器 工作原理： - 创建一个指针对象，指向数据结构的起始位置。 - 第一次调用next方法，指针自动指向数据结构的第一个成员 - 接下来不断调用next方法，指针会一直往后移动，直到指向最后一个成员 - 每调用next方法返回的是一个包含value和done的对象，{value: 当前成员的值,done: 布尔值} * value表示当前成员的值，done对应的布尔值表示当前的数据的结构是否遍历结束。 * 当遍历结束的时候返回的value值是undefined，done值为false //原理 function mockIterator ( arr ) { let nextIndex = 0 ; return { next : function ( ) { return nextIndex < arr . length ? { value : arr [ nextIndex ++ ] , done : false } : { value : undefined , done : true } } } } Generator函数 特点： 1 、 function 与函数名之间有一个星号 2 、内部用 yield 表达式来定义不同的状态 例如： function * generatorExample ( ) { let result = yield 'hello'

In there something similar to Java's Thread.yield() in Python? Does that even make sense?

由 半腔热情 提交于 2020-01-01 09:06:12
问题 I want to tell my Python threads to yield, and so avoid hogging the CPU unnecessarily. In Java, you could do that using the Thread.yield() function. I don't think there is something similar in Python, so I have been using time.sleep(t) where t = 0.00001 . For t=0 there seems to be no effect. I think that maybe there is something I am not understanding correctly about Python's threading model, and hence the reason for the missing thread.yield() . Can someone clarify this to me? Thanks! PS:

what does yield without value do in context manager

由 不问归期 提交于 2020-01-01 04:13:27
问题 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? 回答1: yield expression returns control to the whatever is using the generator. The generator pauses at this point, which means that the

Multithreading, when to yield versus sleep

由 ≡放荡痞女 提交于 2019-12-31 09:04:48
问题 To clarify terminology, yield is when thread gives up its time slice. My platform of interest is POSIX threads, but I think the question is general. Suppose I have consumer/producer pattern. If I want to throttle either consumer or producer, which is better to use, sleep or yield? I am mostly interested in efficiency of using either function. 回答1: The "right" way to code a producer / consumer is to have the consumer wait for the producer's data. You can achieve this by using a synchronization

Can I yield from an inner function?

由 ▼魔方 西西 提交于 2019-12-31 08:58:52
问题 With ES6 generators, I see code like this: var trivialGenerator = function *(array) { var i,item; for(var i=0; i < array.length; i++){ item = array[i]; yield item; }; }; Is it possible to write something more like the code below instead? var trivialGenerator = function *(array) { array.forEach(function *(item){ yield item; }); }; I'm asking because the classic for loop is an abomination. 回答1: No, you can't use yield inside of the inner function. But in your case you don't need it. You can

lines of code are not executed after calling method containing yield

由 老子叫甜甜 提交于 2019-12-31 04:00:13
问题 Consider the following method: IEnumerable<DateTime> GetTimes(int count) { for (int i = 0; i < count; i++) yield return DateTime.Now; yield break; } Now, I want to call it: var times = GetTimes(2); Console.WriteLine("First element:" + times.Take(1).Single().ToString()); Console.WriteLine("Second element:" + times.Skip(1).Take(1).Single().ToString()); Console.WriteLine("Third element:" + times.Skip(2).Take(1).Single().ToString()); Console.WriteLine("Finished..."); But the last line of code

[技术博客] 如何避免在代码中多重render

由 試著忘記壹切 提交于 2019-12-31 03:57:23
目录 问题发现 方案1 extracted_method and return(父函数and return法) 方案2 子函数yield,父函数调用后{return} 方案3 extracted_method; return if performed? 作者： 马振亚 问题发现 在实际写rails的controller时,一般在controller的最后总是会render一个json供不同的前端使用,当我们一个controller的逻辑在一个方法中写完时,总是能比较轻松的保证一个controller里面有一次render. 但是大多数情况下我们controller需要对用户进行比较多的验证,验证是否具有某种特殊的权限,如果验证失败返回统一的错误json信息(比如没有社长权限等),这种情况下一般会采用单独将验证的代码放置到前置的验证函数中去. 在这个过程中我发现了一个比较棘手的问题,就是在验证失败的时候前面的验证函数会render失败信息,但是返回到主函数之后代码段会继续执行下去,在执行的过程中很容易出现异常或者是再次render一个新的json造成多重render错误. 希望找到一种方法在第一次render之后就能退出避免相关的异常和错误的发生. 方案1 extracted_method and return(父函数and return法) class Controller def

using filter and generator to generator endless prime number in python

由 我们两清 提交于 2019-12-30 07:41:44
问题 Below is a python program I found to find prime numbers using Sieve of Eratosthenes. It uses filter and generator. I'm not able to understand it. def _odd_iter(): n = 1 while True: n = n + 2 yield n def _not_divisible(n): return lambda x: x % n > 0 def primes(): yield 2 it = _odd_iter() while True: n = next(it) yield n it = filter(_not_divisible(n), it) for n in primes(): if n < 1000: print(n) else: break What I don't understand is it = filter(_not_divisible(n), it) . For example for number
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