Programming Python, Part I
A blog is not a blog if we can't add new posts, so let's do that:
>>> blog = blog + ["A new post."] >>> blog ['My first post', 'Python is cool', 'A new post.']
Here we set blog to a new value, which is the old blog, and a new post. Remembering all that merely to add a new post is not pleasant though, so we can encapsulate it in what is called a function:
>>> def add_post(blog, new_post): ... return blog + [new_post] ... >>>
def is the keyword used to define a new function or method (more on functions in structured or functional programming and methods in object-oriented programming later in this article). What follows is the name of the function. Inside the parentheses, we have the formal parameters. Those are like variables that will be defined by the caller of the function. After the colon, the prompt has changed from >>> to ... to show that we are inside a definition. The function is composed of all those lines with a level of indentation below the level of the def line.
So, where other programming languages use curly braces or begin/end keywords, Python uses indentation. The idea is that if you are a good programmer, you'd indent it anyway, so we'll use that indentation and make you a good programmer at the same time. Indeed, it's a controversial issue; I didn't like it at first, but I learned to live with it.
While working with the REPL, you safely can press Tab to make an indentation level, and although a Tab character can do it, using four spaces is the strongly recommended way. Many text editors know to put four spaces when you press Tab when editing a Python file. Whatever you do, never, I repeat, never, mix Tabs with spaces. In other programming languages, it may make the community dislike you, but in Python, it'll make your program fail with weird error messages.
Being practical, to reproduce what I did, simply type the class header, def add_post(blog, new_post):, press Enter, press Tab, type return blog + [new_post], press Enter, press Enter again, and that's it. Let's see the function in action:
>>> blog = add_post(blog, "Fourth post") >>> blog ['My first post', 'Python is cool', 'A new post.', 'Fourth post'] >>>
add_post takes two parameters. The first is the blog itself, and it gets assigned to blog. This is tricky. The blog inside the function is not the same as the blog outside the function. They are in different scopes. That's why the following:
>>> def add_post(blog, new_post): ... blog = blog + [new_post]
doesn't work. blog is modified only inside the function. By now, you might know that new_post contains the post passed to the function.
Our blog is growing, and it is time to see that the posts are simply strings, but we want to have a title and a body. One way to do this is to use tuples, like this:
>>> blog =  >>> blog = add_post(blog, ("New blog", "First post")) >>> blog = add_post(blog, ("Cool", "Python is cool")) >>> blog [('New blog', 'First post'), ('Cool', 'Python and is cool')] >>>
In the first line, I reset the blog to be an empty list. Then, I added two posts. See the double parentheses? The outside parentheses are part of the function call, and the inside parentheses are the creation of a tuple.
A tuple is created by parentheses, and its members are separated by commas. They are similar to lists, but semantically, they are different. For example, you can't update the members of a tuple. Tuples are used to build some kind of structure with a fixed set of elements. Let's see a tuple outside of our blog:
>>> (1,2,3) (1, 2, 3)
Accessing each part of the posts is similar to accessing each part of the blog:
>>> blog 'New blog' >>> blog 'This is my first post'
This might be a good solution if we want to store only a title and a body. But, how long until we want to add the date and time, excerpts, tags or messages? You may begin thinking you'll need to hang a sheet of paper on the wall, as shown in Figure 1, to remember the index of each field—not pleasant at all. To solve this problem, and some others, Python gives us object-oriented programming.
Fast/Flexible Linux OS Recovery
On Demand Now
In this live one-hour webinar, learn how to enhance your existing backup strategies for complete disaster recovery preparedness using Storix System Backup Administrator (SBAdmin), a highly flexible full-system recovery solution for UNIX and Linux systems.
Join Linux Journal's Shawn Powers and David Huffman, President/CEO, Storix, Inc.
Free to Linux Journal readers.Register Now!
- Download "Linux Management with Red Hat Satellite: Measuring Business Impact and ROI"
- ServersCheck's Thermal Imaging Camera Sensor
- The Italian Army Switches to LibreOffice
- Petros Koutoupis' RapidDisk
- Linux Mint 18
- Oracle vs. Google: Round 2
- The FBI and the Mozilla Foundation Lock Horns over Known Security Hole
- Ben Rady's Serverless Single Page Apps (The Pragmatic Programmers)
- Privacy and the New Math
Until recently, IBM’s Power Platform was looked upon as being the system that hosted IBM’s flavor of UNIX and proprietary operating system called IBM i. These servers often are found in medium-size businesses running ERP, CRM and financials for on-premise customers. By enabling the Power platform to run the Linux OS, IBM now has positioned Power to be the platform of choice for those already running Linux that are facing scalability issues, especially customers looking at analytics, big data or cloud computing.
￼Running Linux on IBM’s Power hardware offers some obvious benefits, including improved processing speed and memory bandwidth, inherent security, and simpler deployment and management. But if you look beyond the impressive architecture, you’ll also find an open ecosystem that has given rise to a strong, innovative community, as well as an inventory of system and network management applications that really help leverage the benefits offered by running Linux on Power.Get the Guide