For a): from selenium.common.exceptions import NoSuchElementException def check_exists_by_xpath(xpath): try: webdriver.find_element_by_xpath(xpath) except NoSuchElementException: return False return True For b): Moreover, you can take the XPath expression as a standard throughout all your scripts and create functions as above mentions for universal use. I recommend to use CSS selectors. I recommend not to mix/use “by id”, “by … Read more
Use the abc module to create abstract classes. Use the abstractmethod decorator to declare a method abstract, and declare a class abstract using one of three ways, depending upon your Python version. In Python 3.4 and above, you can inherit from ABC. In earlier versions of Python, you need to specify your class’s metaclass as … Read more
Widgets are not thread safe, see Threads and QObjects: Although QObject is reentrant, the GUI classes, notably QWidget and all its subclasses, are not reentrant. They can only be used from the main thread. And see more definitions here: Reentrancy and Thread-Safety You should only use widgets in the main thread, and use signal and … Read more
Do this: from threading import Thread def func1(): print(‘Working’) def func2(): print(“Working”) if __name__ == ‘__main__’: Thread(target = func1).start() Thread(target = func2).start()
one way to do this would be to use indexing with .loc. Example In the absence of an example dataframe, I’ll make one up here: import numpy as np import pandas as pd df = pd.DataFrame({‘c1’: list(‘abcdefg’)}) df.loc[5, ‘c1’] = ‘Value’ >>> df c1 0 a 1 b 2 c 3 d 4 e 5 … Read more
Here is my implementation, and it works for me with some fixes. It enhances the alignment of the key and secret phrase with 32 bytes and IV to 16 bytes: import base64 import hashlib from Crypto import Random from Crypto.Cipher import AES class AESCipher(object): def __init__(self, key): self.bs = AES.block_size self.key = hashlib.sha256(key.encode()).digest() def encrypt(self, … Read more
By using drop_duplicates pd.concat([df1,df2]).drop_duplicates(keep=False) Update : The above method only works for those data frames that don’t already have duplicates themselves. For example: df1=pd.DataFrame({‘A’:[1,2,3,3],’B’:[2,3,4,4]}) df2=pd.DataFrame({‘A’:[1],’B’:[2]}) It will output like below , which is wrong Wrong Output : pd.concat([df1, df2]).drop_duplicates(keep=False) Out[655]: A B 1 2 3 Correct Output Out[656]: A B 1 2 3 2 3 … Read more
There are built-in functions called getattr and setattr getattr(object, attrname) setattr(object, attrname, value) In this case x = getattr(t, ‘attr1’) setattr(t, ‘attr1’, 21)
You can create a big subplot that covers the two subplots and then set the common labels. import random import matplotlib.pyplot as plt x = range(1, 101) y1 = [random.randint(1, 100) for _ in range(len(x))] y2 = [random.randint(1, 100) for _ in range(len(x))] fig = plt.figure() ax = fig.add_subplot(111) # The big subplot ax1 = … Read more
You could try: dict((k, bigdict[k]) for k in (‘l’, ‘m’, ‘n’)) … or in Python 3 Python versions 2.7 or later (thanks to Fábio Diniz for pointing that out that it works in 2.7 too): {k: bigdict[k] for k in (‘l’, ‘m’, ‘n’)} Update: As Håvard S points out, I’m assuming that you know the … Read more