Make sure you code is as portable as possible.

Key Takeaways

portability. How can I make sure the code that I'm writing is as portable as possible and is going to work in as many situations as it possibly can? All right, so let's look at a bad file handler. Notice that we have this data processor and then inside of here, we hardcode some input and output directories. Now, immediately by us hard- coding these directories, what we've done is just ensure that this code will never work on any machine other than ours. The reason for that is that I would need to manually change this, which is obviously not good for the code. That doesn't make it portable. And this is a Windows file path. Which means even if we did have these exact uh directory structures on Mac or Linux for example, this would simply not work because of the fact that we've hard-coded the Windows style path rather than using a dynamic path which you can do in Python. So if we go to a good example here, you can see that what I do right away is I import OS and I create this environment variable file. Inside of here, I put all of the dynamic values that I may need to change depending on the environment in which I'm running this code. I have my API information. I have the current environment I'm in. I have the file path directory which works crossplatform. And now if I go here, I rely on environment variables rather than relying on hard-coded values. Same thing for my file paths. I use the path variable from the path lib which makes this dynamic and works crossplatform.