Summarizing the average performance of a set of things under different loads is a particularly tricky thing. The correct way to summarize performance is to use the geometric mean instead of the arithmetic mean. The tricky part is that the difference between the arithmetic and geometric mean is only significant under a certain condition, so the impact of using the arithmetic mean instead of the geometric may not be painfully obvious. Let’s start with an example.
Tonight I’m looking at some sorting algorithms in Python. First up are Bubble Sort and Selection sort, both with average and worst case runtime, and memory. Finally, I’ll look at an iterative and recursive implementation of Merge Sort.
This is a work in progress, there’s a lot of complex questions you can ask about graphs, but I though it was neat that you could produce an actual graphy looking thing in so few lines of code. This is a directed graph, and you use the graph object to first create nodes, and then define (unweighted) edges between them or to themselves. The
__repr__() method just lists the node data, whatever that is, with an ASCII arrow pointing to another node’s data.
Here is round two for linked lists, the doubly linked list. It’s not very much more complex than a singly linked list. Breaking things into cases using the
self.count attribute makes the code easier to read and reason about.
I’ve posted before about creating a tree in Python, but I like this implementation better. It uses a nested class to represent the nodes of the tree, and an interesting construction (line 11) that is a result of that nested class. Also, I do a simple pre-order traversal. I’ll flesh this guy out in later posts.
I was reading about data structures this evening and I worked out simple singly linked list. The neat thing about this implementation is that a I made it iterable, also. I’d originally wanted to provide a minimal working singly linked list, and then add features and testing with explanations, but it’s been a long day. This example assumes that you’re using Python2.7; version 3 provides a
__next__ class method.
Vagrant is a tool that you can use to set up, configure, and access a VM through the command line. This is a life changer. I love it. In this post I’ll walk through setting up an OEL6 virtual machine, installing a non-ancient version of Python, and configuring the port forwarding so that you can use it for backend web development. (The port forwarding is not obvious on RHEL/OEL.)
Recently, I thought I needed to use
simpleldap–it turned out that I instead needed to reconfigure NGINX. At any rate, this was my experience with
An alternate title might be: how to bind event handlers to new, or dynamically generated, table rows. When using jQuery, we attach sets of instructions to different parts of an HTML document using selectors. Suppose you wanted to attach some functionality to some text in a table, for example, when you click on a row in a table, it brings up a new table below the first table. This is actually kind of tricky, it turns out that there is a distinction between direct and delegated event handlers.