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Building a Tagging Engine in Python using Dictionaries

01/05/2016 By debkr

I started playing around building a Tagging Engine in Python using Lists but now I’ve studied a bit more – particularly Dictionaries – I want to see how I can perfect what I was working on. Here are a couple of key things I added/changed in this program over the version I was working on earlier.

1. Using a dictionary instead of lists for faster counting and simpler recall. This is straight forward, using the get method as taught by Dr. Chuck (see Coding 101 part 7 for more details).

words = dict()
for word in wordlist :
____if word in excluded : continue
____words[word] = words.get(word,0) + 1

Coding 101 (part 6)

16/04/2016 By debkr

When strings become spaghetti:
Working with strings and files, particular when using the for {line} in {filehandle}: construct, allows us to do some cool manipulation of data, by finding, splitting and stripping the data into different chunks based on some repeating factor (such as a comma spearating each value in order), then sorting, counting and totalling those values through iterative loops. [Read more…]

Coding 101 (part 4)

10/04/2016 By debkr

This post follows on from earlier posts (Coding 101 (part 1) ~ (part 2) ~ (part 3)) and records my responses and learnings from the highly-recommended Python programming book and Coursera specialisation by Charles Severance (see References below).

A quick recap on strings:
Strings are computer-speak for characters, specifically where some object or value has the ‘type’ string. Type is an attribute Python applies to any given object or value so it knows how to handle that object or value, i.e. what kinds of operations can and cannot be applied to it. String, and two numeric types – integer and float – are the most common types within Python.

A string may contain one or more characters, so ‘a’ and ‘0’ are strings, just as ‘abcdefghij’ and ‘Hello world. I am Python.’ are. [Read more…] about Coding 101 (part 4)