Transcription
Hello everyone!
Today we have a video covering everything about Python for some period of time. I don't know yet how long it will be, as I haven't started editing, but that's not the point. We will look at everything we have. Naturally, Python has a multitude of functions, capabilities, and more.
To learn everything in an advanced format, with plenty of examples and tips on how to pass interviews, solve problems, and generally live with it, head over to my Telegram channel. The link is in the description. Just scroll down, and you'll find it. Subscribe and keep an eye on it. Also, make sure to subscribe to my YouTube channel.
Let's start with the fact that we have our Python. To work with it, you need to install it. I won't dwell on this. Just go to the downloads, install the current version of Python, and get to work.
What else should we mention? Python and programming languages, in general, are divided into interpreted and compiled languages. Python is an interpreted language. The essence of an interpreted language is that it has an interpreter that executes the code line by line. Compilation, on the other hand, happens in compiled languages, where we have a bunch of code that we compile into a bundle, and then we run that. Some languages are a combination of both interpretation and compilation, like Java.
Python also has a feature that I will show you now. There are certain extensions, .pyc files, which are essentially a form of compilation of our Python for faster execution. This feature appeared in newer versions to optimize performance.
It's important to understand that interpretation is the foundation in Python. The combined approach can help you stand out a bit in interviews.
Now that we have installed Python, what else do we need to know? Most programming languages have package managers, and Python is no exception. We have a package manager called pip. What is it? Through pip, we can install various dependencies. Python itself is a language where we write something, but for it to work according to our needs, we need dependencies.
For example, if we want to make requests to a server, we look for our library, requests, and see the documentation. We find out how to install it with the next command. It's not crucial to understand everything about the package manager right now, but it's good to know it exists.
Now let's move on to our Python. I've divided it into certain sections, and we will go through these sections. Naturally, there are many different aspects and more. Everything in an advanced format is available in my Telegram channel, so go ahead and subscribe.
Let's start with variables. In general, variables... Let's open up and consider tabular values, dictionaries, lists, numbers, sets, strings, and tuples.
Let's start with integers. Okay, we have our regular numbers, including negative numbers and floating-point numbers. Floating-point numbers can be negative or positive. Then we have complex numbers, which are more of a discrete mathematical concept. Not everyone will find them useful, but at least that option exists.
Next, we have strings. Regular strings are just created by opening parentheses and writing "Hello, world!" and closing them. We can also use double quotes.
Lists, or arrays, are a collection of values. For example, if we have 5 items, we can combine them into a list: [1, 2, 3, 4, 5]. The numbering starts from zero. The same goes for lists; you can include any data types in a list.
Now, tuples. The essence of tuples is that they are fixed. When we create a tuple, we cannot change its length. For example, if we create a tuple with two values, we cannot add more values to it. Tuples are created much faster than lists. If you need a fixed value that won't change, tuples are your best bet.
Next, we have dictionaries. The principle here is that we have a key and a value. It's also important to understand that lists, tuples, and dictionaries work based on certain principles.
Sets are an unordered collection of unique values. Boolean values can be either True or False, or NaN when there is no value.
Now, when we talk about variables, we need to understand references. When we assign a value, like 5 or "Hello, world!", we allocate a memory cell for that value. If we change the value, the original memory cell loses its reference, and the garbage collector will remove it.
In Python, the garbage collector works automatically. If we have a value and we reference it, we won't clean it up. Once we stop referencing it, it gets cleaned up, which improves performance.
When we work with lists, we can mutate them. For example, if we have a list of numbers and we add a new number, the reference remains the same. However, with tuples, we cannot mutate them.
It's crucial to understand that when we copy a list, we can end up with two variables pointing to the same memory location. If we change one, the other will also change. To avoid this, we need to make a copy.
There are two types of copying: shallow copy and deep copy. A shallow copy copies the top level, while a deep copy copies all levels.
Now, let's move on to methods for our data types. We have numbers, strings, lists, dictionaries, and sets.
Starting with numbers, we have addition, subtraction, multiplication, division, and integer division. We can also raise numbers to a power and find the remainder.
There are many mathematical methods available, and it's essential to understand that we can work with modules like math.
When working with strings, we can convert them to upper case, lower case, or title case. We can also strip whitespace, replace words, and split strings into lists.
We can check if a string starts or ends with a specific word, find the index of a word, and get the length of a string.
In Python, we also have f-strings, which allow us to embed expressions inside string literals.
Now, let's talk about boolean values. They can be either True or False. We can convert values to boolean, where 0 is always False, and an empty string is also False.
Next, we have lists. Lists can contain different data types, and we can access elements by their index. We can add elements, remove elements, and sort lists.
Slicing is an interesting feature that works not only with lists but also with strings. We can extract elements from a list or string using slicing.
Dictionaries are key-value pairs. We can add, modify, and delete elements by their keys.
Sets are collections of unique elements. We can add and remove elements, check for existence, and perform set operations like union and intersection.
Now, let's move on to classes. Classes are a fundamental part of object-oriented programming. We define classes using the class keyword, and we can create instances of those classes.
In Python, we can use inheritance to create subclasses. We can also use encapsulation to protect attributes and methods.
Decorators are another important concept. They allow us to modify the behavior of functions or methods.
Finally, we have error handling with try and except blocks. We can catch and handle exceptions to prevent our program from crashing.
That's a brief overview of Python. If you found this interesting, please subscribe, like, and share with your friends. Stay in touch!