Why is if True slower than if 1 in Python? Shouldn't if True be faster than if 1 ? I was trying to learn the timeit module. Starting with the basics, I tried these: >>> def test1(): ... if True: ... return 1 ... else: ... return 0 >>> print timeit("test1()", setup = "from __main__ import test1") 0.193144083023 >>> def test2(): ...
为什么if True比Python中的if 1更慢呢？ if True比if 1更快呢？ 我正在尝试学习timeit模块。 从基础开始，我尝试了这些： >>> def test1(): ... if True: ... return 1 ... else: ... return 0 >>> print timeit("test1()", setup = "from __main__ import test1") 0.193144083023 >>> def test2(): ... if 1: ... return 1 ... else: ... r
When comparing floats to integers, some pairs of values take much longer to be evaluated than other values of a similar magnitude. For example: >>> import timeit >>> timeit.timeit("562949953420000.7 < 562949953421000") # run 1 million times 0.5387085462592742 But if the float or integer is made smaller or larger by a certain amount, the comparison runs much more quickly:
将浮点数与整数进行比较时，某些值对需要比其他类似值的值更长的时间来评估。 例如： >>> import timeit >>> timeit.timeit("562949953420000.7 < 562949953421000") # run 1 million times 0.5387085462592742 但是如果浮点数或整数的数值变小或变大一些，则比较运行得更快： >>> timeit.timeit("562949953420000.7 < 562949953422000") # integer increased by 1000 0.1481498428446173
I am currently trying to teach myself c++, and I am working on file IO. I have read through the cplusplus.com tutorial, and am using the basic file IO techniques I learned there: std::ifstream \using this to open a read-only file std::ofstream \using this to create an output file std::getline \using this to read each line of the file outputfile << linecontents \using this to write to t
我目前正在尝试自学c ++，并且正在处理文件IO。 我已经阅读了cplusplus.com教程，并且使用了我在那里学到的基本文件IO技术： std::ifstream \using this to open a read-only file std::ofstream \using this to create an output file std::getline \using this to read each line of the file outputfile << linecontents \using this to write to the output file 我有一个大约10MB的文本文件，其中包含第一百万
I want to iterate over each line of an entire file. One way to do this is by reading the entire file, saving it to a list, then going over the line of interest. This method uses a lot of memory, so I am looking for an alternative. My code so far: for each_line in fileinput.input(input_file): do_something(each_line) for each_line_again in fileinput.input(input_file): do_somet
我想遍历整个文件的每一行。 一种方法是读取整个文件，将其保存到列表中，然后转到感兴趣的行。 这种方法使用了大量的内存，所以我正在寻找替代方案。 我的代码到目前为止： for each_line in fileinput.input(input_file): do_something(each_line) for each_line_again in fileinput.input(input_file): do_something(each_line_again) 执行此代码会给出错误消息： device active 。 有什么建议么？
I'm trying to do some of the code golf challenges, but they all require the input to be taken from stdin . How do I get that in Python? You could use the fileinput module: import fileinput for line in fileinput.input(): pass fileinput will loop through all the lines in the input specified as file names given in command-line arguments, or the standard input if no arguments are provid
我试图做一些代码高尔夫的挑战，但他们都需要输入来自stdin 。 我如何在Python中获取？ 你可以使用fileinput模块： import fileinput for line in fileinput.input(): pass fileinput将遍历输入中指定为命令行参数中给定的文件名的所有行，或者在未提供参数的情况下循环输入标准输入。 有几种方法可以做到这一点。 sys.stdin是一个类似文件的对象，如果您想要读取所有内容或想要读取所有内容并自动将其拆分为新行
from pandas.io.parsers import read_csv import numpy as np df = read_csv("WHO.csv") country_col = df['Country'] print("df signs:n", np.sign(df)) Traceback（最近调用最后一次）：print（“df signs： n”，np.sign（df））中的文件“/home/yuyuyu/Documents/pythonData/pandas/series2.py”，第20行TypeError：无法编译类型：str（）<int（）
from pandas.io.parsers import read_csv import numpy as np df = read_csv("WHO.csv") country_col = df['Country'] print("df signs:n", np.sign(df)) Traceback（最近调用最后一次）：print（“df signs： n”，np.sign（df））中的文件“/home/yuyuyu/Documents/pythonData/pandas/series2.py”，第20行TypeError：无法编译类型：str（）<int（）
I'm used to doing print >>f, "hi there" However, it seems that print >> is getting deprecated. What is the recommended way to do the line above? Update: Regarding all those answers with "n" ...is this universal or Unix-specific? IE, should I be doing "rn" on Windows? This should be as simple as: with open('somefile.txt', 'a') as the_file:
我习惯于print >>f, "hi there" 但是，似乎print >>已被弃用。 建议的方式是做什么？ 更新：关于所有那些带有"n"答案......这是通用还是Unix特有的？ IE，我应该在Windows上做"rn"吗？ 这应该如下简单： with open('somefile.txt', 'a') as the_file: the_file.write('Hellon') 从文档： 在编写以文本模式打开的文件时（默认），不要使用os.linesep作为行终止符; 在
Is there a simple way to determine if a variable is a list, dictionary, or something else? I am getting an object back that may be either type and I need to be able to tell the difference. To get the type of an object, you can use the built-in type() function. Passing an object as the only parameter will return the type object of that object: >>> type([]) is list True >>> t
有没有简单的方法来确定一个变量是一个列表，字典或其他东西？ 我得到一个可能是任何类型的对象，我需要能够区分它们。 要获取对象的类型，可以使用内置的type()函数。 传递一个对象作为唯一的参数将返回该对象的类型对象： >>> type([]) is list True >>> type({}) is dict True >>> type('') is str True >>> type(0) is int True >>> type({}) <type 'dict'> >>
What is the best way to check whether a given object is of a given type? How about checking whether the object inherits from a given type? Let's say I have an object o . How do I check whether it's a str ? To check if o is an instance of str or any subclass of str , use isinstance (this would be the "canonical" way): if isinstance(o, str): To check if the type of o is ex
检查给定对象是否为给定类型的最佳方法是什么？ 如何检查对象是否从给定类型继承？ 假设我有一个对象o 。 我如何检查它是否是一个str ？ 要检查是否o是的实例str或的任何子类str ，使用isinstance（这将是“规范”的方式）： if isinstance(o, str): 要检查o的类型是否完全是str ： if type(o) is str: 以下内容也适用，在某些情况下可能有用： if issubclass(type(o), str): if type(o) in ([str] + str.__subclasses_
I like the Python list comprehension syntax. Can it be used to create dictionaries too? For example, by iterating over pairs of keys and values: mydict = {(k,v) for (k,v) in blah blah blah} # doesn't work In Python 2.6 and earlier, the dict constructor can receive an iterable of key/value pairs: d = dict((key, value) for (key, value) in iterable) From Python 2.7 and 3 onwards, you can jus
我喜欢Python列表理解语法。 它也可以用来创建词典吗？ 例如，通过迭代键和值对： mydict = {(k,v) for (k,v) in blah blah blah} # doesn't work 在Python 2.6及更早版本中，dict构造函数可以接收可迭代的键/值对： d = dict((key, value) for (key, value) in iterable) 从Python 2.7和3开始，您可以直接使用dict comprehension语法： d = {key: value for (key, value) in iterable} 当然，只要每个元素都是两个元