How to extract a substring of a string when “unhashable type: 'slice'” from html parsed data
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Set on_delete=SET_DEFAULT if you know your default policy will not be deleted (you could override the delete method on Policy to avoid These are your options from a technical perspective: Set on_delete=CASCADE if you want the Item to be deleted when the Policy is deleted Set on_delete=PROTECT if you don't want to allow any Policy to be deleted if there's still any Item pointing to it, In Set on_delete=SET_DEFAULT if you know ,USB: usb_device_handle_win
It depends on your business requirements.Should every Item always point to a valid Policy ? And what 's the requirement from business point-of-view when a Policy gets deleted? Should the Items pointing to it also be deleted? We don' t know your requirements, so it 's difficult to answer your question. These are your options from a technical perspective: Set on_delete = CASCADE if you want the Item to be deleted when the Policy is deleted Set on_delete = PROTECT if you don 't want to allow any Policy to be deleted if there' s still any Item pointing to it.In that case you 'll have to try: policy.delete(); except ProtectedError: ... in your code to handle that situation. Set on_delete = SET_DEFAULT if you know your default policy will not be deleted(you could override the delete method on Policy to avoid deleting the default policy). Set on_delete = SET_NULL if an Item can have no Policy.That may be valid in certain business scenarios.But in this case you must also have null = True.
# Importing the libraries import numpy as np import matplotlib.pyplot as plt import pandas as pd # Importing the dataset # dataset = pd.read_csv('50_Startups.csv') dataset = pd.DataFrame(np.random.rand(10, 10)) y = dataset.iloc[: , 4] X = dataset.iloc[: , 0: 4] # Encoding categorical data from sklearn.preprocessing import LabelEncoder, OneHotEncoder labelencoder_X = LabelEncoder() # I changed this line X.values[: , 3] = labelencoder_X.fit_transform(X.values[: , 3])
I would like to retrieve the message:, Questions , Interesting proof of the time-independent Schrödinger equation ,WordPress Development
from bs4 import BeautifulSoup import requests url = "http://rss.cnn.com/rss/edition_us.rss" content = requests.get(url) #retrieve the html code as a string print(content.status_code) soup = BeautifulSoup(content.text, 'html.parser') print(soup.prettify()) tag = soup.find_all('description') print(tag)
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