Instead, we have another library that we can use inside of Python called the decimal library and that's what we're going to go through in this guide. I'm going to show you the key differences between float's and decimals and then we can talk a little bit about when you'd want to use one over the other. And this is also going to give us a nice introduction on how we can import outside libraries.

Even though decimal is inside a python we're going to have to explicitly call it because we can't simply use it the same way that we've used other functions leading up to this point. So before we get into anything let's come up with a few example variables. So I'm going to say product cost and let's set this equal to some type of floating-point number like 88.40 and I'm only keeping this zero here so it's easier to visualize it as a cost. Technically it's going to look like 88.4 from the Python interpreter because it ignores trailing zeros.

Next, we're going to figure out a commission rate. So for the commission rate let's say that this commission is going to be 0.08 for the sake of argument which is the equivalent of 8 percent. So we're using this to build a commission management tool for this program and then for product quantities and I'm going to create a variable here called quantity. We'll say there are 450 of these items that are sold.

So now if I want to perform this calculation I can say product cost I can use our assignment operator which we recently learned about. And I can take the commission rate and multiply that by the product cost. And now if I want to print it I can say print the product costs multiplied by the quantity. So what that is going to do is it's going to take each one of these values and it's going to multiply the commission rate by the product cost. And that's going to give us our commission value. It's going to add that onto the product cost. So essentially this is a system that is trying to see how much money a salesperson should make every time a product gets sold. And that's what this will do. It's going to say This product may have cost 88.40 but we also have to pay the salesperson 8 percent. So we want the total product cost including the commission. So that's what that will equal and then we're going to multiply that by how many units were sold which in this case is 450. So I'm going to run that and the value that we get right here is 42962.4

And let's save this as a comment an inline comment right here. Just so you can see this is the value when we're working with a float because all of these even though they may look like decimals they're technically floating-point numbers. Now I'm going to comment this out so that we don't get it confused.

Now let's talk about how we can work with decimals, we're going to have to come up to the very top and we're going to import this from Python and the way you can import a library is by saying from decimal and this is obviously for the decimal library import decimal.

Now if that makes no sense to you do not worry what we're doing here is we have access in Python to the decimal library and inside of the decimal library. There are all kinds of classes and functions and different elements like that that we have access to and we're saying that we want to take the decimal class and that everything that's included in that all the functions and everything like that from the decimal library and we want to use it in this file. Now this is like I said in the beginning this is just an introduction to working with outside libraries. We're going to have an entire section dedicated to that later on when we get into more advanced topics. For right now just know that we're pulling in the decimal library and the specific function of a decimal and this is what we're going to use. So now that we have all of this let's actually comment copy the come in and out just so you can see both of them side by side.

Now the way that you can create a decimal is to copy decimal it has to be all like this with it titled with the capital D and decimal spelled out and then because it's a function we're going to call decimal. And what this is going to do is it is going to override this so it's no longer going to be a floating-point number. Now it's going to be a decimal and I'm going to do the same thing here. And this is going to give us what we're looking at looking for. So we have a product cost. We have a commission rate which are now decimals they are no longer floating-point numbers. We're keeping our quantity the same. And now let's run this process again. So I'm going to come up to product cost and lets comment everything else out. We don't have to call decimal again because all of these elements now are decimals. And if I run this you can see we get a much larger number

I'm going to copy this and add it to the comment so you have it for the show notes. Now, this may seem kind of odd because right here when we're working with floats we simply ended the calculation right at point four and that seems pretty accurate. However, what decimals do is they give you a much higher level of precision. You can see that technically our commission and the total for the product was not 42962.4. But instead, it was 42962.4 and then a crazy long decimal here. That may not seem like a big deal but imagine that you're building this for a large company like Wal-Mart or some type of company like that and you're going to be running these types of calculations all day every day on millions and billions of dollars in transactions then these little numbers that don't seem like a big deal are going to add up and they are going to cause errors from your financial reporting and your calculations that definitely can be an issue.

Now that is on if you're building some type of finance application and you want to make sure that your financial calculations when you're adding and multiplying and dividing you want to make sure that those numbers are accurate.

Now, where this also comes into play is when it comes to scientific calculations there have been instances, in fact, NASA had a very bad instance where they were using floating-point arithmetic instead of these high precision types of decimals and they actually had a crash of a space shuttle because of that. And so it's very critical to make sure for any type of system that requires a high-level precision that you're picking the right tool for the right job. There are many times when a floating-point number works perfectly fine. And then you can just use it exactly like this. However when it comes to anything that is finance-related or scientific or where the level of precision is incredibly important then it's a good idea to bring in the decimal class just like we did right here so that you can get what the actual value is.

Code

from decimal import Decimal

product_cost = 88.40
commission_rate = 0.08
qty = 450

product_cost += (commission_rate * product_cost)
print(product_cost * qty) # 42962.4

product_cost = Decimal(88.40)
commission_rate = Decimal(0.08)
qty = 450

product_cost += (commission_rate * product_cost)
print(product_cost * qty) # 42962.40000000000282883716451