popo | grid layout tool , the best choice | Grid library

I assume there is a problem with quotes " or ' or both.

In order to debug your script and see the actual commands expansion by the shell I use set -x to start commands echo and set +x to stop command echo.

Suggest to run the following script:

Your code is all over the place.

Should be something like

Because the input for the while; do...done < "$file" code block is handled from the file containing the software names to install; the read -rp "Would you like to install $line? [Y/n]" yn which was not given a specific input handler, just inherits the file input from its outer code block.

Rather than reading user input, it reads (consumes) lines from the software list file.

There need to be distinct input handlers for reading file and reading user input.

Edited with suggestion from John Kugelman

Here it is with a couple other fixes:

Considering popo:basic5542 is a static value, you can try as below expression.

Your C implementation has 64-bit pointers and 32-bit unsigned int, and %x is for unsigned int. With %x, your C implementation is printing only the low 32 bits of the pointers.

Additionally, the behavior of printing a pointer with %x is not defined by the C standard.

To print a pointer properly, convert it to void * and print it with %p:

Yikes, that turns out to be a bit involved. There's no good out-of-the-box way to do it. Here's how I would do it. First, I'd make a way to take some action on each screen:

The error message means that Redis is still loading data, i.e. in your case, the AOF file. You cannot run FLUSHALL until the loading finishes.

If you don't need the data to be loaded, you can delete the AOF file before starting Redis.

If you're using Visual Studio there's a really easy shortcut you can use: Paste XML as Classes:

Which creates for your sample XML:

You can use the <=> equality operator which is null safe as shown here.

I added a schema to the dataframe creation as it seemed that without it the auto schema inference didn't give a type to the columns with only nulls and the join failed.

The resulting dataframe is exactly the one you wanted