Beginning Programming with Python For Dummies
Overview
Create simple, easy programs in the popular Python language
Beginning Programming with Python For Dummies is the trusted way to learn the foundations of programming using the Python programming language. Python is one of the top-ranked languages, and there’s no better way to get started in computer programming than this friendly guide. You’ll learn the basics of coding and the process of creating simple, fun programs right away. This updated edition features new chapters, including coverage of Google Colab, plus expanded information on functions and objects, and new examples and graphics that are relevant to today’s beginning coders. Dummies helps you discover the wealth of things you can achieve with Python.
- Employ an online coding environment to avoid installation woes and code anywhere, any time
- Learn the basics of programming using the popular Python language
- Create easy, fun projects to show off your new coding chops
- Fix errors in your code and use Python with external data sets
Beginning Programming with Python For Dummies will get new programmers started—the easy way.
Read More
About The Author
John Mueller is an experienced technology writer with more than 100 titles to his name. He has experience with networking, AI, data, and programming. He is the author of the previous editions of Beginning Programming with Python For Dummies and many other For Dummies titles.
Sample Chapters
beginning programming with python for dummies
CHEAT SHEET
Python is an incredibly flexible language that has significant third-party support and is used in a broad range of applications. The applications you build will run on any platform that Python supports without any modification as long as you create a pure Python solution. Of course, you want to ensure that your applications have the best chance possible of working exactly as you anticipated everywhere they're run, which is why you need the information in this cheat sheet.
View Cheat Sheet
View Cheat Sheet
HAVE THIS BOOK?
View Book Companion Site
Access practice tests
Additional Book Resources
Articles from
the book
Many organizations are using Python these days to perform major tasks. You don't necessarily hear about them because organizations are usually reserved about giving out their trade secrets. However, Python is still there making a big difference in the way organizations work and toward keeping the bottom line from bottoming out.
Python
Python is an incredibly flexible language that has significant third-party support and is used in a broad range of applications. The applications you build will run on any platform that Python supports without any modification as long as you create a pure Python solution. Of course, you want to ensure that your applications have the best chance possible of working exactly as you anticipated everywhere they're run, which is why you need the information in this cheat sheet.
Jupyter Notebook relies on the literate programming approach originally advanced by Donald Knuth. This means that the Integrated Development Environment (IDE) produces output that looks more like a report than the complex coding environments that most people rely on. The magic functions add to this capability by creating an environment in which you can choose something other than the expected result.
Operators help determine the interactions between elements in a Python statement. For example, when you write 2 + 3, it means to add (using the + operator) the value 2 to the value 3 for a sum of 5. It's important to know which operators Python supports, and remembering them all is not always easy. The following table provides a quick summary.
A stack is a handy programming structure because you can use it to save a Python application execution environment (the state of variables and other attributes of the application environment at any given time) or as a means of determining an order of execution. Unfortunately, Python doesn’t provide a stack as a collection.
As you might imagine, creating a fully functional, production-grade class (one that is used in a real-world Python application actually running on a system that is accessed by users) is time consuming because real classes perform a lot of tasks. Fortunately, Python supports a feature called inheritance.By using inheritance, you can obtain the features you want from a parent class when creating a child class.
Python
You don’t need to understand absolutely every detail about how permanent storage works with Python in order to use it. For example, just how the drive spins (assuming that it spins at all) is unimportant. However, most platforms adhere to a basic set of principles when it comes to permanent storage. These principles have developed over a period of time, starting with mainframe systems in the earliest days of computing.
While you can use Python to delete information from files, you may find you no longer need the file at all. The following steps describe how to delete files that you no longer need.
Open a Python File window.
You see an editor in which you can type the example code.
Type the following code into the window — pressing Enter after each line:
Choose Run→Run ModuleThe application displays the File Removed!
Python
As you might imagine, creating a fully functional, production-grade class in Python (one that is used in a real-world application actually running on a system that is accessed by users) is time consuming because real classes perform a lot of tasks. Fortunately, Python supports a feature called inheritance. By using inheritance, you can obtain the features you want from a parent class when creating a child class.
In the Python programming language, to use code in a package, Python must be able to locate the package and load it into memory. The location information is stored as paths within Python. Whenever you request that Python import a package, Python looks at all the files in its list of paths to find it. The path information comes from three sources.
You can format strings in a number of ways using Python. The main emphasis of formatting is to present the string in a form that is both pleasing to the user and easy to understand. Formatting doesn’t mean adding effects in this case, but refers merely to the presentation of the data. For example, the user might want a fixed-point number rather than a decimal number as output.
The Pythonware site doesn’t look all that interesting until you start clicking the links. It provides you with access to a number of third-party libraries that help you perform additional tasks using Python. Although all the links provide you with useful resources, the “Downloads (downloads.effbot.org)” link is the one you should look at first.
Situations will sometimes arise for which you may not know how to handle an error event in Python during the application design process. Perhaps you can’t even handle the error at a particular level and need to pass it up to some other level to handle. In short, in some situations, your application must generate an exception.
You can do many things with lists. As a Python programmer, you have lots of options. Those lists may not do you much good if you don’t know what is in the list. To make that job even easier, you can sort lists to make information easier to find.
Searching lists
Modifying a list isn’t very easy when you don’t know what the list contains.
There are times with Python when you need to locate specific information in a string. For example, you may want to know whether a string contains the word Hello in it. One of the essential purposes behind creating and maintaining data is to be able to search it later to locate specific bits of information.Strings are no different — they’re most useful when you can find what you need quickly and without any problems.
You find IDLE in the Python 3.10 folder on your system as IDLE (Python 3.10 64-bit). When you click or double-click this entry (depending on your platform), you see the IDLE editor. The two lines of text contain information about the Python host and provide suggestions on the commands you can try.The precise information you see differs by platform.
Python gives you several different ways to view package content. The method that most developers use is to work with the dir() function, which tells you about the attributes that the package provides.Function attributes are automatically generated by Python for you. These attributes perform the following tasks or contain the following information:
__builtins__: Contains a listing of all the built-in attributes that are accessible from the package.
You can use the doc() function whenever needed to get quick help. However, you have a better way to study the packages and libraries located in the Python path — the Python Package Documentation. This feature often appears as Package Docs in the Python folder on your system. It’s also referred to as Pydoc. Whatever you call it, the Python Package Documentation makes life a lot easier for developers.
Python
The kernel is the server that enables Python programmers to run cells within Notebook. You typically see the kernel commands in a separate command or terminal window. The kernel displays its commands in a separate Jupyter Notebook window.Each entry shows the time the kernel executed the task, which application the command executed, the task it performed, and any resources affected.
Python
Cells are what make Notebook considerably different from using other IDEs. By using the functionality that cells provide, you can perform all sorts of application manipulations that would otherwise be difficult or error prone using other IDEs, such as moving related code around as a chunk, rather than line-by-line.
People create lists to organize information and make it easier to access and change. You use lists in Python for the same reason. In many situations, you really do need some sort of organizational aid to hold data. For example, you might want to create a single place to look for days of the week or months of the year.
Python provides myriad ways to output information. In fact, the number of ways would amaze you. Real-world printing can become complex, so you need to know a few additional printing techniques to get you started. Using these techniques is actually a lot easier if you play with them as you go along.
Type the following code into the notebook — pressing Enter after each line:Colors = ["Red", "Orange", "Yellow", "Green", "Blue">
print(*Colors, sep='\n')
You use a for loop to print the individual items.
Operator
Description
()
Parentheses are used to group expressions and to override the default precedence so that you can force an operation of lower precedence (such as addition) to take precedence over an operation of higher precedence (such as multiplication).
**
Exponentiation raises the value of the left operand to the power of the right operand.
Python
You might be able to divine the potential sources of error in your Python application by reading tea leaves, but that’s hardly an efficient way to do things. Errors actually fall into well-defined categories that help you predict (to some degree) when and where they’ll occur. By thinking about these categories as you work through your application, you’re far more likely to discover potential errors sources before they occur and cause potential damage.
You might be a nonprogrammer or a developer who isn't interested in learning some new arcane method of writing code. If so, Python is the a great language for you. Most programming languages use just one coding style, which reduces flexibility for the programmer. Python is different, though. You can use a number of coding styles with it to achieve differing effects.
Python
A class is essentially a method for packaging Python code. The idea is to simplify code reuse, make applications more reliable, and reduce the potential for security breaches. Well-designed classes are black boxes that accept certain inputs and provide specific outputs based on those inputs. In short, a class shouldn’t create any surprises for anyone and should have known (quantifiable) behaviors.
The decision-making process often happens in levels, both in real life and in Python programming. For example, when you go to the restaurant and choose eggs for breakfast, you have made a first-level decision. Now the server asks you what type of toast you want with your eggs. The server wouldn’t ask this question if you had ordered pancakes, so the selection of toast becomes a second-level decision.
Python
Environment variables are special settings that are part of the command line or terminal environment for your operating system. They serve to configure Python in a consistent manner. Environment variables perform many of the same tasks as do the options that you supply when you start Python, but you can make environment variables permanent so that you can configure Python the same way every time you start it without having to manually supply the option.
A good question to ask is, why do you need an IDE to work with Python if the command-line tool works fine? For that matter, Python actually comes with a limited IDE called Integrated DeveLopement Environment (IDLE). Most people probably question the need for anything more during the learning process and possibly to develop full-fledged applications.
Checkpoints are a Notebook-specific feature that can save Python programmers a huge amount of time and embarrassment when used correctly. A checkpoint is a kind of interim save and source control combined into a single package. What you get is a picture of your application at a specific point in time.
Defining the uses of checkpoints
Unlike many application saves, a checkpoint is an individual entry.
A deque is simply a queue where you can remove and add items from either end. In many languages, a queue or stack starts out as a deque. Specialized code serves to limit deque functionality to what is needed to perform a particular task.When working with a deque, you need to think of the deque as a sort of horizontal line.
Methods are simply another kind of function that reside in classes. You create and work with methods in Python in precisely the same way that you do functions, except that methods are always associated with a class. You can create two kinds of methods: those associated with the class itself and those associated with an instance of a class.
Sometimes you have a data source and you simply need to know how often things happen in Python (such as the appearance of a certain item in the list). When you have a short list, you can simply count the items. However, when you have a really long list, getting an accurate count is nearly impossible. For example, consider what it would take if you had a really long novel like War and Peace in a list and wanted to know the frequency of the words the novel used.
Load More Articles
Related Books
0:00
0:00
https://cdn.prod.website-files.com/6630d85d73068bc09c7c436c/69195ee32d5c606051d9f433_4.%20All%20For%20You.mp3
Frequently Asked Questions
No items found.
