Programming, Stuff

Measure Twice, Cut Twice

According to general wisdom one should measure twice and cut once. This makes sense in most professions and even generally in life; when you should think twice and open your mouth once. However, again, generally in programming, we have this ++ approach. There was C then C++ came out. Looking at the list of programming languages on Wiki, I can see 8 records with ++ in their names. Not every ++ is related to the programming language it’s named after. For example R++ has nothing to do with R which is a statistical programming language whereas R++ itself is C++ related.

That being said, I’m going to take a naive approach and apply ++ logic to measure twice and cut once and make it measure twice and cut twice.  First and foremost, this is going to be an empirical approach and my basis for this theory is the experience I have gained in 15 years of building static and dynamic websites, web and desktop applications. However, I hope that it’ll make sense to most of you, especially to those who obsess about details and perfectionism.

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Portfolio, Programming

Pythonicus Addendum

Posts in this series
  1. Pythonicus
  2. Pythonicus Addendum
  3. Pythonicus Finitum

In my previous Pythonicus article I briefly talked about my need to parse a list of NoSQL Databases at http://nosql-database.org. My solution back then was as it was presented in that article, using regular expressions to find child and sibling nodes. It was a bit crude but it got the job done.

I’m constantly fighting against the “get’er done” mentality on a daily basis so I’ll try to get the job done right this time by using BeautifulSoup. That’s actually where I left the article off so let’s see how tasty the soup is!

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Portfolio, Programming

Pythonicus

Posts in this series
  1. Pythonicus
  2. Pythonicus Addendum
  3. Pythonicus Finitum

I started to learn Python in May. I finished two introductory courses about it on Coursera. Then, after a summer full of indecisiveness and frustration about where I want to take my skills to, I came to the conclusion that becoming a data scientist would be the right move. I guess that was around the last week of October. Since then, I’ve finished a third Python course and the fourth one is starting pretty soon.

I can already feel that I’ve opened the doors to a whole other world about computing and programming. My feelings about Data Science deserves another article so I’ll only focus on Python in this one. More specifically, how I approached a specific problem and how I’ve been able to produce the same results with better tools.

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