Encore: What language should I learn?

The MicroBinfie podcast discusses the top programming languages for bioinformatics. Andrew, Lee, and Nabil agree that Python is a great starting point for its consistency and rigor. Its strict syntax is ideal for teaching programming fundamentals that are essential in any language. In contrast, Perl encourages multiple ways of doing the same thing, creating confusion and difficulties in keeping track of things. The hosts caution against starting with trendy languages that are constantly changing. Instead, stick with more established languages like Python, which have established libraries and concepts that will help you advance more easily. Trendy languages come and go like changing tides, making them riskier choices. Additionally, they highlight the importance of understanding databases and their primary keys and unique fields. SQL is useful, particularly in dealing with large datasets. It is consistent across flavors and unlikely to go away soon. It takes a lot of skill to optimize queries to work in milliseconds. The hosts emphasize that the language you choose to learn depends on your individual goals and environment. For instance, Lee suggests that you should look to who is in your space and what they are using and who is willing to help you. Once you understand the programming concepts, it is easier to transfer them to other languages, and it is just a question of understanding the syntax. Andrew, Lee, and Nabil also discuss their own trajectories of learning programming languages, revealing that it takes a long time to become an expert in a language, and it is something that needs to be appreciated. They highlight the difference between just learning the basics of a language and really getting into the depths of it and the frameworks and libraries. The hosts also mention languages that are important to pick up, like SQL and bash scripting, and languages that are popular for web development, like JavaScript. However, they caution that JavaScript and Java are not the same thing and that JavaScript has a reputation for being a weird language. When asked what language they would choose for a task, Nabil says he would use Perl, Lee mentions R for stats, while Andrew admits that he has to relearn R every time he comes back to it and therefore prefers Perl for quick scripts. They also discuss their love-hate relationship with R, mentioning that while it has useful libraries like GGplot and GGtree, its syntax is difficult to work with and has separate paradigms of approaching the same problem. The hosts conclude by acknowledging that there is no one-size-fits-all approach to learning programming languages. One should choose based on their goals, environment, and personal preferences. Python is a useful language to learn, even if one is not interested in bioinformatics. Additionally, they note that the fundamentals of databases and how they work are crucial to understand and utilized across fields.