PYTHON ADVANCED GUIDE Your Advanced Python Tutorial in 7 Days. A Step-by-Step Guide from Intermediate to Advanced. (2022 Crash Course) Alec Dennis PYTHON ADVANCED GUIDE Chapter 1: 5 Object-oriented programming Polymorphism 7 Encapsulation 1O Chapter two 12 Essential programming tools bash script RegEx in Python 14 Python Package Manager 16 SourceControl 16 Bringing It All Together 17 Chapter three 19 Working with files Creating new files 20 What exactly are binary files? 22 Opening Your File Up 23 Chapter four 26 Exception handling Handling the Zero Division Error Exception 27 Reading an Exception Error Trace Back 31 Using exceptions to prevent crashes 32 The Else Block 34 Failing Silently 37 How to Handle the File Not Found Exception Error 38 Checking to See if a File Exists 38 Try and Except 39 Practice Exercise 40 CONCLUSION 41 CHAPTER ONE OBJECT-ORIENTED PROGRAMMING We'll now look at the four object-oriented programming concepts and how they apply to Python. Inheritance The first major notion is referred to as "inheritance." This refers to the ability of one object to derive from another.
Take, for example, sports automobiles. Vehicles are all sports cars, but not all vehicles are sports cars. Furthermore, all sedans are vehicles, but not all vehicles are sedans, and sedans are most emphatically not sports cars, despite the fact that they are both vehicles. Basically, this Object-Oriented programming principle states that objects can and should be split up into as little and precise notions as feasible.
This is accomplished in Python by deriving classes. Assume we've created a new class called SportsCar. Now, construct a new class called SportsCar, but instead of deriving from object, we'll derivate from Vehicle. We don't need the honk function here; only the constructor function is required.
Declare a sporty car now. I'm going to stick with the Ferrari. Now test this by calling After that, save and run. Everything should go off without a hitch.
Why is this the case? This is due to the concept of inheritance, which states that a child class inherits functions and class variables from a parent class. It's a simple enough concept to grasp. The next one is a little more difficult. Polymorphism The concept of polymorphism is that the same process can be carried out in various ways depending on the circumstances.
In Python, this can be accomplished in two ways: method overloading and method overriding. Overloading a method means defining the same function twice with different arguments. For example, we might provide our Vehicle class with two distinct initializer procedures. It currently assumes a car has four doors.
If we wanted to specify the number of doors on a car, we could add a new initializer function below our present one with a doors parameter, as shown below (the newer one is at the bottom): Someone can now select whether or not to define the number of doors when creating an instance of the Vehicle class. If they do not, it is believed that the number of doors is four. Method overriding occurs when a child class uses its code to override a parent class's method. As an example, make a new class called Moped that extends Vehicle.
Set the doors to zero, which is ludicrous, and the air conditioning to fake. The only arguments that matter are the make/model and the year of manufacture. This is how it should look: Abstraction Abstraction is the next key topic in object- oriented programming. This is the idea that the programmer and user should be kept away from the computer's inner workings.
This has two advantages. The first is that it reduces the inherent security concerns and the danger of catastrophic system malfunctions, whether caused by humans or not. By isolating the programmer from the inner workings of the computer, such as memory and the CPU, and, in some cases, even the operating system, there is a low risk of irreparable damage. The second benefit of abstraction is that it naturally makes the language easier to grasp, read, and learn.
Though it reduces the language's strength by removing some of the user's control over the complete computer architecture, this is exchanged for the ability to write fast and effectively in the language, without wasting time dealing with trivialities like memory addresses or the like. These are applicable in Python because, well, it's quite simple. You can't get into the computer's nitty-gritty, or do anything with memory allocation, or even precisely allot an array size, but this is a tradeoff for incredible readability, a highly safe language in a very secure environment, and ease of use with programming. Compare the following C code snippet: to the Python code for doing the same: Abstraction is generally a net advantage for a vast majority of programs produced today, which is why Python and other object- oriented programming languages are so popular.
Encapsulation Encapsulation is the final important notion in object-oriented programming. This is the simplest to explain. This is the idea that common data should be combined and programs should be modular. I'm not going to go into detail because it's a very simple concept.
Classes are as succinct an example of encapsulation as you can get: common traits and methods are bound together under one coherent structure, making it very easy to make objects of the type without having to generate a ton of super-specific variables for each instance. So there you have it. We had finally reached the end of our Python trip. First and foremost, I'd want to thank you for reading all the way through Python for Beginners: The Ultimate Guide to Python Programming.
Let us hope it was informative and provided you with all of the tools you need to reach your objectives, whatever they may be. The next step is to put this knowledge to use. You just made one of the best decisions of your life by learning the foundations of Python, whether as a hobby or a career move, and your objective now should be finding ways to use it in your day-to-day life to make life easier or to do tasks you've wanted to complete for a long time. CHAPTER TWO ESSENTIAL PROGRAMMING TOOLS BASH SCRIPT A Bash script is a data file that comprises a series of commands that you can generally code but that will save you time if you don't.
Take notice that in programming, any code that would typically be put on the command line can be placed on the script and executed exactly as is. Similarly, any code that might be included in a script can usually be performed exactly as is. There may be several processes manifesting one program running in memory at the same time. You can, for example, use two terminals and run the command prompt at the same time.
In such a circumstance, the system will have two command prompt processes running at the same time. When they have finished their execution, the system can terminate them, and there will be no more processes representing the command prompt. You can use the terminal to run the Bash script, which will provide you with a shell. When you start a script, it will not execute in current process, but will instead start a new process that will be executed inside.
However, as a beginner in programming, you don't need to be concerned about the mechanism of this script because running Bash might be extremely simple. You may also come across some tutorials on script execution, which is essentially the same thing. Before running the script, make sure it has permission, as the software will return an error message if you don't. Below is a sample Bash script: You can use the 755 shorthand to alter the script and ensure that it can be shared with others to execute.
RegEx in Python RegEx is a regular expression that specifies a text string and allows you to construct patterns for managing, matching, and locating text. Python is an example of a programming language that makes use of regex. Regex can also be used to search for text within a file in text editors and from the command line. When you first see regex, you may believe it is a new programming language.
However, if you work with text or need to parse massive volumes of data, knowing regex could save you countless hours. In Python, the RE module provides full regex functionality. If there is a mistake while using or compiling a regex, it additionally raises the exception re. When using regex in Python, you must be familiar with two fundamental functions.
But first, you should grasp that distinct characters have different meanings when employed in a regular expression. So that you are not perplexed when working with regex, we will use the term r'expression' to refer to Raw Strings. The search and match functions are the most crucial in Python regex. The search function looks for the first occurrence of a RE pattern within a string that includes optional flags.
The search function contains the following parameters (the syntax is below): String - will be searched to match the pattern within the string Pattern - regex to be matched Flags - modifiers that can be specified using bitwise If successful, the re.search function will return an object match; otherwise, it will return object none. To discover a matched expression, utilize the groups() or groups(num) function of object match. Here's an example of code that makes use of the search function: The output will be: Meanwhile, the match function will attempt to match the RE pattern to string with appropriate flags. The syntax for the match function is as follows: The following parameters are available for the match function: String - this will be searched to match the pattern at the start of the string Pattern - this is the regex to be matched Flags - modifiers that can be specified using bitwise Python Package Manager Package managers are tools used in programming to automate the process of installing, configuring, upgrading, and uninstalling programs for a certain language system in an organized manner.
It is also known as a package management system because it deals with the distribution and archiving of data files that include the name of the software, version, number, purpose, and a list of dependencies required for the language to operate properly. When you use a package management, the metadata is normally preserved in the local database to prevent code incompatibilities and missing permissions. A utility in Python can be used to locate, install, upgrade, and remove Python packages. It can also determine the most recent version of a package installed on the system and upgrade the existing package from a distant or local server.
Python Package Manager is not free, and it can only be accessed via ActivePython. It also makes use of repositories, which are collections of pre-installed packages that contain various types of modules. SourceControl A source control (also known as version control or revision control) in programming manages changes to the codes, which are recognized by a letter or number code referred to as the revision number or simply revision. For example, revision 1 refers to the initial set of code, whereas revision 2 refers to the first alteration.
Every edit will be accompanied with a timestamp as well as the identity of the person who made the modification. Revisions are necessary so that the code may be restored or compared. When working with a group, source control is essential. You can combine your code changes with other code changes made by a developer using different views that reveal detailed changes, and then merge the correct code into the primary code branch.
Source control is essential for coding projects, whether you're using Python or another language. Keep in mind that each coding project should begin with the use of a source control system such as Mercurial or Git. Since the dawn of programming, various source control techniques have emerged.