Here's how I would do it:
phrase = "I am in a box"
words = phrase.split(' ')
longest = max(words, key=len)
width = len(longest)
pretty = "\n".join(["*"*(width+4),*[f"* {w[::-1].center(width)[::-1]} *" for w in words],"*"*(width+4)])
print(pretty)
*******
* I *
* am *
* in *
* a *
* box *
*******
Now let's break it down!
First we do what you did, splitting the phrase into words and extracting other helpful data:
phrase = "I am in a box"
words = phrase.split(' ')
longest = max(words, key=len)
width = len(longest)
Then comes the real algorithm. Let's make a list of one string per line. Clearly the first and last lines are going to be the length of the longest plus 4 (i.e. (wall + padding)*2
).
So at the start and end of the list we put:
"*"*(width+4)
Then we need to fill in the actual meat of the box. We're going to use a list iteration to make as many string as there are lines, and join each line with \n
:
[line_contents for w in words]
But we need to actually have line_contents
be something for each line. So let's replace that with an f-string.
At the start and end of each line there is the padding (ignoring the extra padding the small words have) and an asterisk. So our f-string is currently f"* {padded_word} *"
.
To actually make the padded words, we can use str.center(width)
. This gives the whole f-string as f"* {w.center(width)} *"
.
Now putting everything together we get:
"\n".join(["*"*(width+4),*[f"* {w.center(width)} *" for w in words],"*"*(width+4)]
NOTE: I used the *
operator to unpack the list iteration into the larger list.
If we run the program we get:
*******
* I *
* am *
* in *
* a *
* box *
*******
Looks good! But wait one moment - it seems like str.center
is making the off-center words go to the right! This is contrary to your example.
However, there's an easy solution: reverse the word, pad it, then reverse it back. This will make the off-center words go left instead. To reverse any indexable object, you can use slice notation: [start, stop, step]
--> [beginning, end, -1]
--> [::-1]
.
Now if we add this into what we have so far, we get what I presented initially.