Convention dictates that I should bore you with the fundamental building blocks of programming, so we can slowly work up to building something useful. Here is a complete, working Python program. It probably makes absolutely no sense to you. Don’t worry about that, because you’re going to dissect it line by line. But read through it first and see what, if anything, you can make of it. On Windows, it will look something like this.
What just happened? You executed your first Python program. You called the Python interpreter on the command line, and you passed the name of the script you wanted Python to execute. The script defines a single function, the approximate.
If you display a folder of documents as a multi- column list, it will display a table with the document icon, the document name, the size, type, last- modified date, and so on. If the folder contains a 1. TODO, your file manager won’t display TODO 1. TODO 1 KB instead.
That’s what the approximate. These are function calls — first calling the approximate. The print() function is built- in; you’ll never see an explicit declaration of it. You can just use it, anytime, anywhere.
Patience, grasshopper.). So why does running the script on the command line give you the same output every time? First, let’s look at that approximate. When you need a function, just declare it, like this. The keyword def starts the function declaration, followed by the function name, followed by the arguments in parentheses. Multiple arguments are separated with commas. Python functions do not specify the datatype of their return value; they don’t even specify whether or not they return a value.
There are no subroutines in Python. Everything is a function, all functions return a value (even if it’s None), and all functions start with def. In Python, variables are never explicitly typed. Python figures out what type a variable is and keeps track of it internally. Furthermore, arguments can be specified in any order by using named arguments. This means the argument is optional; you can call the function without it, and Python will act as if you had called it with True as a second parameter.
There are 3 exercises that go with the first sections of Google\'s Python class. They are located in the \'basic\' directory within the google-python. Python Scripts and Programs available at Hot Scripts. You can find all the Python Scripts and Programs you need today for download and purchase.
Just know that code is written once but read many times, and the most important audience for your code is yourself, six months after writing it (i. Python makes it easy to write readable code, so take advantage of it. You’ll thank me in six months. In this program, the approximate. Everything between the start and end quotes is part of a single string, including carriage returns, leading white space, and other quote characters. You can use them anywhere, but you’ll see them most often used when defining a docstring. A docstring, if it exists, must be the first thing defined in a function (that is, on the next line after the function declaration).
You don’t technically need to give your function a docstring, but you always should. I know you’ve heard this in every programming class you’ve ever taken, but Python gives you an added incentive: the docstring is available at runtime as an attribute of the function. Python looks in several places when you try to import a module. Specifically, it looks in all the directories defined in sys. This is just a list, and you can easily view it or modify it with standard list methods. A function, like everything else in Python, is an object. All functions have a built- in attribute .
A Quick Introduction to Python 3 Programming. This Quick Introduction to Python 3 aims to teach you just enough Python, so that you can get started. How to Develop a Simple Python Program Last Revision: July, 2010 ( McCann) Students always seem to have trouble understanding (or maybe just doing) what I expect of.
The sys module is an object which has (among other things) an attribute called path. In some, it means that all objects must have attributes and methods; in others, it means that all objects are subclassable. In Python, the definition is looser. Some objects have neither attributes nor methods, but they could. Not all objects are subclassable. But everything is an object in the sense that it can be assigned to a variable or passed as an argument to a function. In Python, functions are first- class objects.
You can pass a function as an argument to another function. Modules are first- class objects.
You can pass an entire module as an argument to a function. Classes are first- class objects, and individual instances of a class are also first- class objects. Functions are objects. Class instances are objects.
Even modules are objects. The only delimiter is a colon (: ) and the indentation of the code itself. One major benefit is that all Python programs look similar, since indentation is a language requirement and not a matter of style. This makes it easier to read and understand other people’s Python code. Virtually every module in the standard Python library uses them, and Python itself will raise them in a lot of different circumstances. You’ll see them repeatedly throughout this book.
Usually it’s an error, an indication that something went wrong. Python encourages the use of exceptions, which you handle. This is called an unhandled exception. When the exception was raised, there was no code to explicitly notice it and deal with it, so it bubbled its way back up to the top level of the Python Shell, which spits out some debugging information and calls it a day. In the shell, that\'s no big deal, but if that happened while your actual Python program was running, the entire program would come to a screeching halt if nothing handles the exception.
Maybe that’s what you want, maybe it isn’t. Exceptions can be handled. Sometimes an exception is really because you have a bug in your code (like accessing a variable that doesn’t exist), but sometimes an exception is something you can anticipate. If you’re opening a file, it might not exist. If you’re importing a module, it might not be installed.
If you’re connecting to a database, it might be unavailable, or you might not have the correct security credentials to access it. If you know a line of code may raise an exception, you should handle the exception using a try.. Use the raise statement, followed by the exception name, and an optional human- readable string for debugging purposes. The syntax is reminiscent of calling a function. But we’re getting ahead of ourselves!). If one function doesn’t handle it, the exception is passed to the calling function, then that function’s calling function, and so on “up the stack.” If the exception is never handled, your program will crash, Python will print a “traceback” to standard error, and that’s the end of that.
Again, maybe that’s what you want; it depends on what your program does. This can happen for a variety of reasons, but the simplest case is when the module doesn’t exist in your import search path. You can use this to include optional features in your program. For example, the chardet library provides character encoding auto- detection. Perhaps your program wants to use this library if it exists, but continue gracefully if the user hasn’t installed it.
You can do this with a try. For example, the XML chapter talks about two modules that implement a common API, called the Element.
Tree. API. The first, lxml, is a third- party module that you need to download and install yourself. The second, xml. etree. Element. Tree, is slower but is part of the Python 3 standard library. Since both modules implement a common API, the rest of your code doesn’t need to keep checking which module got imported. And since the module that did get imported is always called etree, the rest of your code doesn’t need to be littered with if statements to call differently- named modules.
That’s OK, because Python lets you do that. What Python will not let you do is reference a variable that has never been assigned a value. Trying to do so will raise a Name. Error exception. If you can get it, set it, call it, construct it, import it, or raise it, it’s case- sensitive.
You can use this to easily test your modules as you write them, by including a special block of code that executes when you run the Python file on the command line. Take the last few lines of humansize.
So what makes this if statement special? If you import the module, then .
Python will evaluate this if statement, find a true expression, and execute the if code block. In this case, to print two values.