UnicodeEncodeError: ‘ascii’ codec can’t encode character u’xa0′ in position 20: ordinal not in range(128)
I’m having problems dealing with unicode characters from text fetched from different web pages (on different sites). I am using BeautifulSoup.
I’m having problems dealing with unicode characters from text fetched from different web pages (on different sites). I am using BeautifulSoup.
I sometimes need to iterate a list in Python looking at the “current” element and the “next” element. I have, till now, done so with code like:
I have the following code:
So this is embarrassing. I’ve got an application that I threw together in Flask and for now it is just serving up a single static HTML page with some links to CSS and JS. And I can’t find where in the documentation Flask describes returning static files. Yes, I could use render_template but I know the data is not templatized. I’d have thought send_file or url_for was the right thing, but I could not get those to work. In the meantime, I am opening the files, reading content, and rigging up a Response with appropriate mimetype:
I’m trying to create a few Buttons (with a for loop) like so: def a(self, name): print(name) users = {"Test": "127.0.0.0", "Test2": "128.0.0.0"} row = 1 for name in users: user_button = Tkinter.Button(self.root, text=name, command=lambda: self.a(name)) user_button.grid(row=row, column=0) row += 1 and for the buttons to each get their own parameter (Test getting “Test” and … Read more
How can I do case insensitive string comparison in Python?
I’m writing a Python application that takes a command as an argument, for example:
I am making a game in which the player has to use a bowl to catch falling items. I have some images of items in a list and an image of a bowl that is used to catch the items. The items keep on falling and reset to the top of the screen if they reach the boundary (bottom edge). I got this logic done which allows the items to fall but I do not know how to detect when there is a collision between the bowl and item.
I have seen many answers posted to questions on Stack Overflow involving the use of the Pandas method apply. I have also seen users commenting under them saying that “apply is slow, and should be avoided”.
Consider below example: