3 Unique Python Features You NEED To Know

Python is definitely an interesting language that has many unique features. However, many of these features are never actually used out in the wild because people simply don't know they exist. So in this video, I'm going to go over some more modern and relatively new Python features that I rarely see used that I think are interesting and that you should definitely know about. They're not all in the most recent version of Python, but they're things that are in modern Python that I think are worth knowing. But that's it. Let's dive in. Now, the first feature I have on my list here is called the match Statement. Now it's also referred to as structural pattern matching, has a few different names. And it was released in Python version 3.10. Now, you've likely seen this before, but I doubt that you've actually used it in your code. And when I review Python code, many people don't actually seem to use this. Okay, so what is the match statement? Well, the match statement when you simply works exactly like a switch statement in various other programing languages. For example, let's just move this down here. You can have a look at this code right here. You see we have some inner function. This function has a match statement inside of it. And all we're doing is we're trying to match the status to one of these various cases that we have. So we have a case for success. That simply means if status is equal to success, go ahead and do this. We have a case for error means same thing. If it's error you know go ahead and do this pending do this. And then we have a default case a default case is kind of like an L statement or default. If you're familiar with a switch statement where if the status doesn't match any of these, will go ahead into this default case. default case isn't required. We don't have to have it. But in this case we do, where we just put the default case to handle anything else. Okay. So if we were to run this function here, you can see that we can kind of go through this match statement and we can process all of these different values that we have in our list. And then we will get the output, you know, operation completed, an error occurred still in progress, etc., so that alone is pretty useful. It can allow us to prevent writing, you know, a ton of nested if statements. And we can just write it like this match statement where we're trying to match a particular value. However, where this gets more interesting is when we get into a more complex pattern matching scenario. So in this match statement doesn't just work to match strings or numbers or, you know, particular value, you can actually match patterns. So have a look at this second example down here. we're able to do is we have a case for simply the value zero right. So just like before we can match if data is equal to zero we also can use this pipe operator. And we can check for multiple values. So we can check if it's one or if it's two or if it's three. And all of that will be handled by this case. Then we can also check for the structure, which is why a lot of times people refer to this as structural pattern matching of the object, which is data. So in this case we can say case first and second. Now what this is saying is we're looking for any kind of data where we have an array or sorry, a list I should say in Python of two values. So for example, if you look down here we have apple and banana that would match with this pattern right here. And then we would be able to extract the values. So apple and banana were the first and second item by using the variables first and second. know it looks a little bit weird. It looks kind of like magic, but that's how this works. Now same thing with a dictionary or an object in Python, whatever you want to refer to it as, right. What we're able to do is we have name. So the key name, some value name the key age some value h. In this case we're matching with anything that is a dictionary that contains exactly these two keys. And then we can strip out what the values are and print them or process them however we want. Now we also can just check if something is a string. This is kind of interesting right? We could just use the string function. And now we're saying okay I want to match anything that is a string. Then if we go down here this is the default case. I'm going to run the code for you. So you can quickly see that this does indeed work. And notice that we get all of the match statements here up above. Right. And then same thing. We have all of the match statements here. Now what's important to note you use the match statement that it's going to attempt to match in the order in which you write these cases. So for example, if we change this to zero, right, and we had some string zero, it would actually match with this first statement here. Not with this statement down here okay. Because it's going to go into the first case that it sees, especially because we have the return and there's a lot of other information. Sorry about the match statement. You could do some really interesting complex stuff here I definitely would suggest checking it out. leave a link to the documentation in the description down below. This is a feature that I rarely see used, which can be extremely powerful, especially when you have a variety of different type of data and you want to process that in some kind of format, right? So we can look for the exact type of pattern really simplifies and cleans up our code. And then we can handle all of these different cases as we see fit. Now the next feature on my list is actually relatively old compared to the other ones on this list. However, it is still something that's definitely worth knowing about and that I see few Python developers, especially beginners or intermediates using. Now that's called data classes, and in order for us to see the value of this, we need to actually look at how you would typically write a class before data classes exist. So in Python, if you want to have a class that represents data, so represents like a user or a book or some kind of entity, you would typically write it something like this where you have this init method. Maybe you take in an ID, some name, maybe some roles for this particular user, and then you're almost always going to be defining a few methods on these objects to make them more usable in your code. For example, you use this magic method wrapper which gives you a string representation of the object so you can actually see what it looks like. If you're debugging the code, for example, and you write something like this, we have user name and then the roles. Then you have something like equals for example, where you're going to check the equivalence of two objects. You might have the string method, you might have a few other ones as well. Right. But a lot of times when you're just trying to represent data, you're almost always just writing the same kind of boilerplate code. You're always writing the same equal method, you're always writing the same wrapper method. And there isn't really good reason to do that, other than the fact that there's no better way. So what I'm going to show you now is what's called the data class, which avoids you having to do all of this. So I'm going to open up this example here. And notice that we have this class right here, which is a data class. And this is exactly the same as the class that you just saw. It's equivalently pretty much the exact same. There's a few very, very minor differences. And it's written in significantly less code. There was no init method. There's no equal method. There's no wrapper method. Right. We didn't have to do any of that. But this actually functions the exact same way on this data class. I can use the double equal sign right between two user objects, and it will test for equivalence in the exact same way as our other class. I can try to print it note and when I print it out I'm going to get that wrapper where it's going to show me exactly what this looks like in that debugging format. And by default, if I don't pass a roll, it's automatically going to be an empty list. Because of this field that I brought in here from the data classes Now I have a whole video on data classes which I will link on screen, which you can watch if you want the really in-depth explanation. But the point is these are very, very useful. Now one thing to note here is that I did enable frozen on this because I decorated it with the data class decorator, and when I do that, it means that you cannot change the values inside of this user object. You can freeze it, right? You can make it immutable, which is also an interesting component of data classes. So in order to make something a data class, you use the data class decorator. You define the different fields that you want. You can use standard Python types or you can use from the typing module. For example, if you want something like a list. And then if you want some kind of default value, you can do that with this field. So default factory means create a new list. It's important you do like this and not define a list. Due to how Python kind of interprets that list object. And then if we come down here another example, we have a product for example. Right. We have a price we have in stock ID name. In this case it's mutable. And if we look down here, these are the operations you can perform on these data classes that are automatically implemented that you don't need to write yourself. So I can create an instance of user. And I didn't need to write a. Net. I can have the ID, I can have the name, I can have the rules. I don't need to pass the rules. Same thing with the product. You know I can pass the values. I didn't need to write the init method. Then I can print these out. When I do that it's automatically going to use a wrapper method for me, which I'm going to show you in one second. And then you can check for the equivalence of these values. Right. And an equal method is automatically implemented for you. Same thing with the immutability which will be enforced which I'll show you. And then this works really nicely with the match statement. So what I can actually do is I can now use these objects with the match statement, and I can check if a product has the price of zero. Right. I can check if the product has a price that's greater than 1000 or something, right? Where I can check if it's a regular product. So it's kind of a cool thing you can do with match. If I run this code here, scroll down and notice that we get the user right. So this is automatically implemented for us. We get product automatically implemented. We get the equal method automatically implemented. Same thing here. You know user cannot modify the field name because immutable. And then it's a fine. So one of our products was expensive because we made it $1,200 okay. So the data class is super super useful. Again I'll put that video on screen and just consider right this versus this. Which one would you rather write? Of course you would rather use the data class. Now the next feature that I have for you is something called the positional or keyword only parameters. Now, parameters in Python are notoriously a little bit confusing because of all of the different combinations of ways that you can call them. So I want to quickly go into a bit of a primer about parameters and then show you this relatively new feature. All right. So let's have a look at this function here. Right. We have some function. We have some values now a b c d right. These are our parameters. Now when I call the function I can call it using what's known as positional parameters. So I can say you know my function. And I can pass 123, four or something. Right. And when I do that I'm now assigning the value a to one, b to two, c to three, d to four. So I can do that. That's totally fine. But I also could do something like b equals to a equals one okay. And then I can say c equals three d equals whatever. And I can pass these in like kind of a random order. Whatever order that I want. And I can kind of pick and choose if I want to pass them positionally or if I want to pass them using a keyword argument, which is what I'm doing right here. And there's all kinds of other combinations of ways that I could call this function. And it can be a little bit confusing. Now it's fine, right. That's just by default how functions are written. But in Python there's actually a way to enforce the way in which your functions are called. And that is by using this fancy operator right here, which is the slash. Now this slash forces arguments to be passed positionally only. I know it seems a bit weird. Why would you do this? We'll talk about that a little bit later. But by me implementing this slash now inside of these function parameters, which is something you may see in larger libraries, it now doesn't allow me to pass name using a keyword argument. And again we'll talk about why that's important in a second. So you can look here and you can see I can call it in this way. Right. I can call it with Alice, I can call with Bob and high, I can call it with, you know, Charlie. And the greeting is equal to hey, because name is passed positionally where I'm not manually defining, you know, name is equal like this to Alice. However, if I go down here and I try to call this, I say, you know, greet name is equal to David, you'll see that we actually get a type error. And it will tell us that this is a positional only argument or parameter, and that I can not call it by specifying the name. So let me just call this function and show you what that looks like. Okay. And you can see all three of these function calls are worked properly. And then when I did try to call it here you can see the result. For it said this was a positional only argument. Right. So it got some positional on the arguments passed. There's a keyword argument name. So you are able to do this enforcement okay. Now let me quickly talk about why that's actually important. The reason why this is interesting actually applies more to APIs. And if you're creating libraries that other people are going to be using, and that's because this allows you to make significantly more robust functions and just APIs in general, so that you can control the way in which they're used and make sure they stay backwards compatible. So, for example, if callers can't use a name, right, if I'm not able to use, you know, name is equal to whatever and pass the parameter or, you know, values equal to whatever or max is equal to two. If I can't use that right as a keyword argument, then it means that I can rename this parameter later on. And I'm not going to break any user's code. So this is especially important when you're writing something that you know is going to change in the future. If you make sure that something is only passed positionally, then the name of the positional argument doesn't actually matter, and you can change it to anything you want in the future or implement a new, for example, keyword argument that has the same name. So it's just allows flexibility to you as someone who's writing these functions. Now, again, imagine the code you're writing is used by someone else, and maybe millions of people are using it. And then all of a sudden you change the name of one of your parameters. If it could have been called by keyword and you now change it, you're going to break a bunch of people's code, right? So that's kind of one of the main reasons. Now another one is semantics, right. So some of the parameters don't have meaningful names. For example x y ab you know, one two or whatever. Right. So when you force the use of positional arguments, you signal to the user that this is more used internally in the function and to pass it positionally rather than trying to name the keywords. Now same thing. As I said before, Rim for future keyword updates, right? So you can keep the names available to use them later on. And it's also more consistent with built in functions where a lot of the built in functions, work like this already, where you can only pass values positionally. Right? You can't pass them with keyword arguments. So hopefully that makes a little bit of sense. Now to kind of continue this, you also can force arguments to be only keyword. So not be pass positional and be pass keyword only. And that's by using this asterix. So the way this works is anything that I want to be positional only I put before this forward slash. If I do that anything before this. So you know pause only to write. All of these can only be passed by position. Then anything after this can be passed freely as normally, so it can be passed by position or by keyword. Okay, so regular I can pass this with a keyword argument or I can pass normally. Then if I put an asterix, anything to the right of this can only be passed by a keyword. So now I cannot pass this value positionally, I can only pass it by a keyword, and similar reasons for doing that apply to as why you would only pass a positionally. I know this is kind of advanced, you know, niche Python code, but that's the point of this video is to show you guys some new stuff that you probably never seen before. And I know I didn't see this until I started looking deeper into Let's actually run the code here. And you can see now that this works, right. It says, you know, makes parameters positional only one regular two keyword only three. I just quickly change this example back so it would work with the way that it was being called. Anyways, that is pretty much going to wrap this up. Now. If you've made it to this point in the video, then I can tell you definitely value learning you like more of those advanced topics. And I mean, you're spending your time watching a video like this. And if that's the case, then I think you would definitely benefit from the sponsor of today's video, which is brilliant. Brilliant is where you learn by doing with thousands of interactive lessons in math, data analysis, programing and AI. They adopt a first principles approach, ensuring you understand the why behind each concept. 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