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They’re essential. Until a short while ago, data analysts concentrated on algorithms, and containers were merely there to help. However with the avalanche of data we’re currently seeing in the Big Data era, deciding what data containers we’re going to use for our analysis is critical to be able to handle data efficiently. In fact, a suboptimal choice of container may mean the difference between being able to make a Big Data analysis or not.
As I said before, it’s essential. High-yield compression in fast disks (SSD) can mean being able to store large quantities of data on laptops or single servers which would otherwise require a cluster with many nodes. And while clusters take a lot of time and experience to develop, it’s much simpler and faster to develop systems with a single node, and speeds up the whole development process.
Although I’m not 100% familiar with Ruby and PHP, my impression is that PHP is more geared to developing web applications very fast. You can do this with Python too, but with the extra bonus of structuring –and therefore maintainability– that you don’t get from PHP.
Basically the fact that this is a simple but very powerful language, with an enormous ecosystem of packages that work very efficiently, and in many cases have inherited the simplicity of the language in their APIs.
This is part of the initial design, so I guess that Guido Van Rossum, the creator of the language and BDFL (Benevolent Dictator For Life), can take much of the blame for that.
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