milkisklim

He has a Masters degree in communication. I remember him talking about taking classes for it way back in the day.

This reminds me of one of the fake cover stories they made up for the Manhattan project wherein they stated they were trying to make a sub that could submerge in the Rio Grande.

I'm not apologizing for keeping y'all in my delusions.

-1/12

Wesley figured it out?! Wesley. Wow, this is a new low.

Please state the nature of your medical emergency.

This sounds like the peasant rail gun with extra steps.

Here's the Wikipedia page

Basically he is an old man/ software engineer who's famous for his philosophy of coding.

I know I sound like a corporate shill, but check out Cleveland Kitchen brand sauerkraut. It's not as good as homemade, but it's worlds better than that nuclear waste found in the questionable meat aisle of the grocery store or the cans.

Disclaimer: I would only call my skill level as intermediate and would yield to any more senior developer here.

It's not a hard and fast rule, but you can usually write it without the else and in fewer lines.

So take for a very contrived example a function that needs to return a non boolean value for a boolean test. A use case could be if you need to figure out a string argument for another function, such as you need to determine if you need to keep the "first" or "last" duplicate in a dataframe (I'm thinking about pandas's df.drop_dupliactes method).

Continuing with the drop_duplicate thing let's say we have a dataframe we need to de-duplicate but for some reason if the overall length of the dataframe is even, we need to keep the first duplicate and if the dataframe length is odd we keep the last. I don't know why we would, but that was a very particular request from the customer and we need the money to buy more Warhammer figurines.

import pandas as pd

# With else statement
def foo(x: int) -> str:
    if x%2>0:
        return "last"
    else:
        return "first"

# No else statement, shorter.
def foo(x: int) -> str:
    if x%2>0:
        return "last"
    return "first"


#import dataframe, deduplicate
df = pd.read_csv("c:\\path\\to\\data.csv")
dedup = df.drop_duplicates(keep=foo(len(df))

Here's an essay that goes into more detail

For following good practices, I highly recommend using a linter like ruff. I've learned a lot from it's explanations on why my code is bad.

Also I have tried to avoid using else statements.