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Tag: python-3.x

Discord.py get uses and author from an invite

I would like to get all the invites from a discord server. I get all the invite but I want to get the author and the uses from it. Everything works just fine except the guild.uses. Tried to embed the things from the discord API. “””From discord api https://discordpy.readthedocs.io/en/latest/api.html Attribute & Method max_age abc.GuildChannel.invites(), Guild.invites() max_uses abc.GuildChannel.invites(), Guild.invites() created_at abc.GuildChannel.invites(),

STR going into terminal instead of GUI text box

I am trying to learn how to make a GUI so I decided to practice making a calculator. I have all of the number buttons and the ‘+’, ‘-‘, ‘*’, ‘/’ buttons working. I got stuck at the decimal button. When ever I press the button in the GUI it goes into my terminal instead of the text box. Here

instance variable difference (Python)

I have 2 questions about the solutions below. Below is my answer (Solution 1) for this question of leetcode: https://leetcode.com/problems/distribute-coins-in-binary-tree/ Quesion1 I was wondering why below does not work. What is the difference between the variable ans of Solution 1 and Solution 2? Because changes on grid variable below (Solution 3) is accumulated and affects all each recursions, I thought

Exponential of SparseTensor with mapping

I want to take the exp of each element in the sparse matrix. Here is a simple example: But this gives the followig error: Can you please help me to sort this out without converting this to dense matrix? Answer If you have Tensorflow 2.4, you can use tf.sparse.map_values: Here is the magic: Note that tf.sparse.to_dense is only there so

Partition string in python and get all the value before colon

I have to get all the values before the last colon(:) i.e. client:user:username:type from the following string: Input: client:user:username:type:1234567 Output: client:user:username:type I know I can split by : and then iterate and append all the tokens before :. But is there a better pythonic way to achieve this? Answer just find the index of last : and then extract the

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