Begin to code with python ebook free download

If you are setting up a new project or architecture, this would come as handy and help you adhere to all the best practices. A Whirlwind Tour of Python is a fast-paced introduction to essential features of the Python language, aimed at researchers and developers who are already familiar with programming in another language. The material is specifically designed for those who wish to use Python for data science and scientific programming.

Your email address will not be published. Save my name, email, and website in this browser for the next time I comment. Home Python. List of Free Python Books 1. Facebook 1. Python is an object oriented, interpreted,flexible language that is becoming increasingly popular for scientific computing. Snake Wrangling for Kids. Python for Kids is a lighthearted introduction to the Python language and to programming in general, complete with illustrations and kid-friendly examples.

We begin with the basics of how to install Python and write simple commands. In bite-sized chapters, you'll discover the essentials of Python, including how to use Python's extensive standard li Python for You and Me. This is a simple open book to learn Python programming language, it is for the programmers who are new to Python. They are all covered here. In the introduction, Mr. Shaw makes a big deal about how if you, the reader, feel like he is insulting your intelligence, then you are not in the intended audience for this book.

I assume he is attempting to be funny, but he comes across as snarky, at best. Regardless of whether you enjoy that type of writing, the core content is pretty good. I think beginners will benefit from the book. Think Python free PDF download. Before we do that though, allow me to speak a few words about the console.

In this era of GUIs and touchscreen devices, it seems a little ridiculous to have to resort to a tool such as the console, when everything is just about one click away.

But the truth is every time you remove your right hand from the keyboard or the left one, if you're a lefty to grab your mouse and move the cursor over to the spot you want to click on, you're losing time.

Getting things done with the console, counter-intuitive as it may be, results in higher productivity and speed. I know, you have to trust me on this. Speed and productivity are important and, personally, I have nothing against the mouse, but there is another very good reason for which you may want to get well-acquainted with the console: when you develop code that ends up on some server, the console might be the only available tool.

If you make friends with it, I promise you, you will never get lost when it's of utmost importance that you don't typically, when the website is down and you have to investigate very quickly what's going on.

So it's really up to you. If you're undecided, please grant me the benefit of the doubt and give it a try. It's easier than you think, and you'll never regret it.

There is nothing more pitiful than a good developer who gets lost within an SSH connection to a server because they are used to their own custom set of tools, and only to that. Python can be used as a scripting language. In fact, it always proves itself very useful.

Scripts are files usually of small dimensions that you normally execute to do something like a task. Many developers end up having their own arsenal of tools that they fire when they need to perform a task. For example, you can have scripts to parse data in a format and render it into another different format.

Or you can use a script to work with files and folders. You can create or modify configuration files, and much more. Technically, there is not much that cannot be done in a script. It's quite common to have scripts running at a precise time on a server. For example, if your website database needs cleaning every 24 hours for example, the table that stores the user sessions, which expire pretty quickly but aren't cleaned automatically , you could set up a Cron job that fires your script at A.

I have Python scripts to do all the menial tasks that would take me minutes or more to do manually, and at some point, I decided to automate. Another way of running Python is by calling the interactive shell.

This is something we already saw when we typed python on the command line of our console. So, open a console, activate your virtual environment which by now should be second nature to you, right? You will be presented with a couple of lines that should look like this:.

They tell you that Python is waiting for you to type something. If you type a simple instruction, something that fits in one line, that's all you'll see. However, if you type something that requires more than one line of code, the shell will change the prompt to The last operation is showing you something incredible. We raise 2 to the power of , and Python is handling this task with no trouble at all. It won't work, unless you use special libraries to handle such big numbers. I use the interactive shell every day.

It's extremely useful to debug very quickly, for example, to check if a data structure supports an operation. Or maybe to inspect or run a piece of code. When you use Django a web framework , the interactive shell is coupled with it and allows you to work your way through the framework tools, to inspect the data in the database, and many more things. You will find that the interactive shell will soon become one of your dearest friends on the journey you are embarking on.

It's quite a simple IDE, which is intended mostly for beginners. It has a slightly larger set of capabilities than the naked interactive shell you get in the console, so you may want to explore it. It comes for free in the Windows Python installer and you can easily install it in any other system. You can find information about it on the Python website. Apart from being run as a script, and within the boundaries of a shell, Python can be coded and run as an application.

We'll see many examples throughout the book about this mode. And we'll understand more about it in a moment, when we'll talk about how Python code is organized and run. Python can also be run as a graphical user interface GUI.

There are several frameworks available, some of which are cross-platform and some others are platform-specific. Tkinter comes bundled with Python; therefore, it gives the programmer easy access to the GUI world, and for these reasons, I have chosen it to be the framework for the GUI examples that I'll present in this book. If GUIs are what you're looking for, remember to choose the one you want according to some principles. Make sure they:. Let's talk a little bit about how Python code is organized.

In this section, we'll start going down the rabbit hole a little bit more and introduce more technical names and concepts. Starting with the basics, how is Python code organized?

Of course, you write your code into files. When you save a file with the extension. It would be impractical to save all the code that it is required for software to work within one single file.

That solution works for scripts, which are usually not longer than a few hundred lines and often they are quite shorter than that. A complete Python application can be made of hundreds of thousands of lines of code, so you will have to scatter it through different modules, which is better, but not nearly good enough. It turns out that even like this, it would still be impractical to work with the code.

So Python gives you another structure, called package , which allows you to group modules together. As always, an example will make all of this much clearer. I have created an example structure in my book project, and when I type in my console:. Here's what the structure of a really simple application could look like:.

You can see that within the root of this example, we have two modules, core. Within core. On the other hand, within the run. Within the util package, I expect to find various utility tools, and in fact, we can guess that the modules there are named based on the types of tools they hold: db. Had this software been organized within modules only, it would have been harder to infer its structure.

It is a little harder to guess what each module does, right? Now, consider that this is just a simple example, so you can guess how much harder it would be to understand a real application if we couldn't organize the code in packages and modules. When a developer is writing an application, it is likely that they will need to apply the same piece of logic in different parts of it. For example, when writing a parser for the data that comes from a form that a user can fill in a web page, the application will have to validate whether a certain field is holding a number or not.

Regardless of how the logic for this kind of validation is written, it's likely that it will be needed in more than one place. For example, in a poll application, where the user is asked many questions, it's likely that several of them will require a numeric answer. For example:. This would violate the don't repeat yourself DRY principle, which states that you should never repeat the same piece of code more than once in your application.

I feel the need to stress the importance of this principle: you should never repeat the same piece of code more than once in your application pun intended.

There are several reasons why repeating the same piece of logic can be very bad, the most important ones being:. Python is a wonderful language and provides you with all the tools you need to apply all the coding best practices. For this particular example, we need to be able to reuse a piece of code.

To be able to reuse a piece of code, we need to have a construct that will hold the code for us so that we can call that construct every time we need to repeat the logic inside it.

That construct exists, and it's called a function. I'm not going too deep into the specifics here, so please just remember that a function is a block of organized, reusable code that is used to perform a task.

Functions can assume many forms and names, according to what kind of environment they belong to, but for now this is not important. We'll see the details when we are able to appreciate them, later on, in the book.

Functions are the building blocks of modularity in your application, and they are almost indispensable. Unless you're writing a super-simple script, you'll use functions all the time. Python comes with a very extensive library, as I have already said a few pages ago.

Now, maybe it's a good time to define what a library is: a library is a collection of functions and objects that provide functionalities that enrich the abilities of a language. For example, within Python's math library, we can find a plethora of functions, one of which is the factorial function, which of course calculates the factorial of a number. So, if you wanted to use this function in your code, all you would have to do is to import it and call it with the right input values.

Don't worry too much if input values and the concept of calling is not very clear for now; please just concentrate on the import part.

We use a library by importing what we need from it, and then we use it. So, let's go back to our example, the one with core. In our example, the package util is our utility library. Our custom utility belt that holds all those reusable tools that is, functions , which we need in our application. Some of them will deal with databases db. We will see in detail how to import functions and use them in their dedicated chapter.

Let's now talk about another very important concept: Python's execution model. In this section, I would like to introduce you to a few very important concepts, such as scope, names, and namespaces. You can read all about Python's execution model in the official language reference, of course, but I would argue that it is quite technical and abstract, so let me give you a less formal explanation first.

Say you are looking for a book, so you go to the library and ask someone for the book you want to fetch. So you go up the stairs, look for Section X, and so on. It would be very different to enter a library where all the books are piled together in random order in one big room. No floors, no sections, no rows, no order.

Fetching a book would be extremely hard. When we write code, we have the same issue: we have to try and organize it so that it will be easy for someone who has no prior knowledge about it to find what they're looking for.

When software is structured correctly, it also promotes code reuse. On the other hand, disorganized software is more likely to expose scattered pieces of duplicated logic. First of all, let's start with the book. We refer to a book by its title and in Python lingo, that would be a name. Python names are the closest abstraction to what other languages call variables.

Names basically refer to objects and are introduced by name-binding operations. Let's make a quick example notice that anything that follows a is a comment :. We defined three objects in the preceding code do you remember what are the three features every Python object has? Don't worry, I know you're not supposed to know what a dictionary is.

So, what are n , address , and employee? They are names. Names that we can use to retrieve data within our code. They need to be kept somewhere so that whenever we need to retrieve those objects, we can use their names to fetch them.

We need some space to hold them, hence: namespaces! A namespace is therefore a mapping from names to objects. Examples are the set of built-in names containing functions that are always accessible in any Python program , the global names in a module, and the local names in a function.

Even the set of attributes of an object can be considered a namespace. The beauty of namespaces is that they allow you to define and organize your names with clarity, without overlapping or interference. For example, the namespace associated with that book we were looking for in the library can be used to import the book itself, like this:. We start from the library namespace, and by means of the dot.

Walking through a namespace will be clearer when we'll be dealing with real code examples. For now, just keep in mind that namespaces are places where names are associated with objects. There is another concept, which is closely related to that of a namespace, which I'd like to briefly talk about: the scope. Directly accessible means that when you're looking for an unqualified reference to a name, Python tries to find it in the namespace.

Scopes are determined statically, but actually, during runtime, they are used dynamically. This means that by inspecting the source code, you can tell what the scope of an object is, but this doesn't prevent the software from altering that during runtime.

There are four different scopes that Python makes accessible not necessarily all of them are present at the same time, of course :. The rule is the following: when we refer to a name, Python starts looking for it in the current namespace. If the name is not found, Python continues the search to the enclosing scope and this continues until the built-in scope is searched.

If a name hasn't been found after searching the built-in scope, then Python raises a NameError exception , which basically means that the name hasn't been defined you saw this in the preceding example. The order in which the namespaces are scanned when looking for a name is therefore: local , enclosing , global , built-in LEGB. This is all very theoretical, so let's see an example. In order to show you local and enclosing namespaces, I will have to define a few functions.

Don't worry if you are not familiar with their syntax for the moment. Just remember that in the following code, when you see def , it means I'm defining a function:. In the preceding example, we define the same name m , both in the global scope and in the local one the one defined by the local function.

When we execute this program with the following command have you activated your virtualenv? What happens is that the Python interpreter parses the file, top to bottom. First, it finds a couple of comment lines, which are skipped, then it parses the definition of the function local.

When called, this function does two things: it sets up a name to an object representing number 7 and prints it. The Python interpreter keeps going and it finds another name binding.