python-2.7

问题 I use pip freeze > requirements.txt to gather all packages I installed. But after developing many days, some packages are now unused. How can I find these unused packages and remove them, to make my project more clear? 回答1: Inside Pycharm Go to code > inspect code Select Whole project option and click OK. In inspection results panel locate Package requirements section under Python (note that this section will be showed only if there is any requirements.txt or setup.py file). The section will

问题 I was wondering if i could open any kind of application in Python during runtime? 回答1: Assuming that you are using Windows you would use one of the following commands like this. subprocess.call import subprocess subprocess.call('C:\\myprogram.exe') os.startfile import os os.startfile('C:\\myprogram.exe') 回答2: Using system you can also take advantage of open function (especially if you are using mac os/unix environment. Can be useful when you are facing permission issue. import os path = "

问题 I have two lists, list1 and list2 . Here len(list2) << len(list1) . Now I want to merge both of the lists such that every nth element of final list is from list2 and the others from list1 . For example: list1 = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'] list2 = ['x', 'y'] n = 3 Now the final list should be: ['a', 'b', 'x', 'c', 'd', 'y', 'e', 'f', 'g', 'h'] What is the most Pythonic way to achieve this? I want to add all elements of list2 to the final list, final list should include all

问题 I have started using djangorestframework-jwt package instead of PyJWT , I just could not know how to decode the incoming token (I know there is verify token methode).... All I need to know is how to decode the token and get back info encoded...... 回答1: May be its too late to answer, but we can decode jwt and get our payload back using jwt.decode from jwt module Assume that jwt token you get looks like and your encrypted payload lies in middle of the token { "token":

问题 I'm using a library function several times in my code which tests for a pass/fail condition and executes different code accordingly, but for some reason does not have a return value for the result it finds; I'd like to add this with a decorator so that I can call it in my code. What is the correct way to do this given that I cannot edit the source file? Should I do something like: def test_pass(param1, param2): external_function(param1, param2) if(...): return False else: return True Or is

问题 I'm using a library function several times in my code which tests for a pass/fail condition and executes different code accordingly, but for some reason does not have a return value for the result it finds; I'd like to add this with a decorator so that I can call it in my code. What is the correct way to do this given that I cannot edit the source file? Should I do something like: def test_pass(param1, param2): external_function(param1, param2) if(...): return False else: return True Or is

问题 I have started using djangorestframework-jwt package instead of PyJWT , I just could not know how to decode the incoming token (I know there is verify token methode).... All I need to know is how to decode the token and get back info encoded...... 回答1: May be its too late to answer, but we can decode jwt and get our payload back using jwt.decode from jwt module Assume that jwt token you get looks like and your encrypted payload lies in middle of the token { "token":

问题 I am trying to apply a filter on several columns on an rdd. I want to pass in a list of indices as a parameter to specify which ones to filter on, but pyspark only applies the last filter. I've broken down the code into some simple test cases and tried the non-looped version and they work. test_input = [('0', '00'), ('1', '1'), ('', '22'), ('', '3')] rdd = sc.parallelize(test_input, 1) # Index 0 needs to be longer than length 0 # Index 1 needs to be longer than length 1 for i in [0,1]: rdd =

问题 I am trying to apply a filter on several columns on an rdd. I want to pass in a list of indices as a parameter to specify which ones to filter on, but pyspark only applies the last filter. I've broken down the code into some simple test cases and tried the non-looped version and they work. test_input = [('0', '00'), ('1', '1'), ('', '22'), ('', '3')] rdd = sc.parallelize(test_input, 1) # Index 0 needs to be longer than length 0 # Index 1 needs to be longer than length 1 for i in [0,1]: rdd =

问题 Code: class Fraction(object): def __init__(self, num, denom): self.numerator = num self.denominator = denom def main(): f = Fraction(1, 3) print type(f) if __name__ == "__main__": main() Output: <class '__main__.Fraction'> Question: Why is the type __main__.Fraction instead of just Fraction ? Why is there "." between __main__ and Fraction ? "." implies that Fraction is a sub-class of __main__ . But why? Even if I remove If __name__ == "__main__" from the code, I still get the same output: