principles | potential outline for tidymodels/principles | Machine Learning library

I have gone back to Qt/C++ programming recently after coding a lot with plain C++.

When browsing StackOverflow, I often catch up on posts like "Why use pointers?" where in most cases the gist of the answers is "if you can avoid it, don't use them".

When coding in C++, I now mostly try using stack variables which are passed by (const) reference or, if necessary, std::shared_ptr resp. std::unique_ptr where needed.

Getting back to Qt, I found all those "principles" to be completely ignored apparently.

I know that Qt uses its own memory management to take care of raw pointers, but here's my question:

Why don't they at least use shared_ptr or unique_ptr, particularly since they even have an own implementation QSharedPointer?

There is one project challenge on freecodecamp about building a calculator and I just managed to pass all the tests but when looking back on my code, the section dealing with the operations are barely readable. I've read some articles online regarding how to reduce the complexity of conditionals and the principles to keep in mind for more easy-to-understand logic.

However, figuring out the achievable logics for this task in javascript is quite challenging to me now. I was trying to meet two conditions with this section of code as follows:

User Story #13: If 2 or more operators are entered consecutively, the operation performed should be the last operator entered (excluding the negative (-) sign). For example, if 5 + * 7 = is entered, the result should be 35 (i.e. 5 * 7); if 5 * - 5 = is entered, the result should be -25 (i.e. 5 * (-5)).

User Story #14: Pressing an operator immediately following = should start a new calculation that operates on the result of the previous evaluation.

Here is the link to the page for this particular challenge and this is the link to the code I wrote by far.

Is there any tips and advice on refining the code or other approaches for coping with this part?

I have a text like this:

I'm trying to set up a react website using CICD principles. I can run it locally, use 'npm run build' to get a build folder, and the website works fine when I manually push the files to S3. However, when I try to run the build and deployment through github actions, the upload-artifacts step gives the following warning: 'Warning: No files were found with the provided path: build. No artifacts will be uploaded.' Obviously the deploy job then fails since it can't find any artifacts to download. Why exactly is this happening? The build folder is definitely being created since running ls after the build lists it as one of the folders in the current working directory.

I want to find a better way to update local compoent state after executing mutation. I'm using svelte-apollo but my question is about basic principles. I have watchQuery which get list of items and returns ObservableQuery in component.

I am using tabula-py to read my class timetable PDF file in python and the return value 'data' has a lot of 'nan' values that I cannot seem to clean. Can someone suggest a solution? Should I be using something instead of tabula-py? I've attached a link to the picture of the PDF. I have redacted some info from the PDF for privacy.1

My code is as follows:

I need these methods to retrieve/update/delete records created by authenticated user only. I'm clearly violating one of the key principles of web/software development. How can i refactor this viewset?

I am trying to build an application with tkinter. The layout works without OO principles, but I am struggling to understand how I should move it to OO.

The layout is as shown in the pic below. (1280x720px)

I have the following:

• banner on top with username/welcome message, and logo rh corner, columnspan=8
• menu bar with buttons on the left, split into 2 rows (row1: rowspan 6, row2: rowspan=4)
• working area (white block) that has a Frame, which I'll add a notebook to, each menu button opening a different notebook page.

What is the best way to make this OO? (I am still learning, so very new to OO)

I have just started working on a data analysis that requires analyzing high volume data using Azure Databricks. While planning to use Databricks notebook to analyze, I have come across different storage options to load the data a) DBFS - default file system from Databricks b) Azure Data Lake (ADLS) and c) Azure Blob Storage. Looks like the items (b) and (c) can be mounted into the workspace to retrieve the data for our analysis.

With the above understanding, may I get the following questions clarified please?

1. What's the difference between these storage options while using them in the context of Databricks? Do DBFS and ADLS incorporate HDFS' file management principles under the hood like breaking files into chunks, name node, data node etc?
2. If I mount Azure Blob Storage container to analyze the data, would I still get the same performance as other storage options? Given the fact that blob storage is an object based store, does it still break the files into blocks and load those chunks as RDD partitions into Spark executor nodes?