Start by reading the open issues, choose one you want to tackle and try fixing it. Code structure can be confusing and hard to understand, consider contacting contributors and asking them questions you have. Rinse, repeat.
Another good idea is to browse through the closed PRs, including the code's diff tab. Communication there has evidence on how friendly and helpful the maintainers are, what are some easy contributions you can make and so on.
You have not even glanced at the referred article, have you? It is not conceptually harder, pretty much the same thing.
I played with some similar tasks for my native Russian. You can just add up a layer of hash tables/dictionaries to link to the original word. There are inflections in English too (and it is even harder for spelling purposes as the difference is often by one character) so it is conceptually similar.
Human Genome project is an example of complete DNA sequencing while 23andMe only tests for specific variations at specific loci. 23andMe and similar companies use commercially available solutions like DNA microarrays [1] with probes preprogrammed [2] for specific target variations and they cannot "read" arbitrary DNAs.
The p-value [1] criterion is often used to test a proposed hypothesis in medical and social science research papers. When you stumble upon something along the lines of "studies that shown that eating broccoli makes people happy" in your everyday life, it comes down to the p-value calculation being small enough <0.05 for the before and after gathered datasets.
The p-value method is practically a standard for scientific reporting in some fields. It also has some drastic shortcomings, including, e,g., dramatic instability for tests with only little data [2].
Naturally, people realize that and try to use additional tools and criteria when available. However, scientists are pretty brutally incentivized to publish positive results and, as a result, more often than it should be, too much weight is put on the single p-value criterion.
With issues like this in mind, in my opinion, it makes sense to be somewhat skeptical when seeing reports in the news that "A effects B" and definitely not to rush with the conclusions. Trivial, I know.
The [3] video pretty much sums it up and by all means is worth a watch.
My experience shows me that there are no magic snake instant solutions. The only way to improve productivity is to gradually change your everyday routine for the better. One can do it by trying different things and sticking to the ones that work for you.
One thing that is certain is that guilt and self-loathing are as unproductive as it gets. This approach won't get you far because the brain doesn't work that way. I am sure we all have read plenty articles on this issue [1].
For example, try something along the lines of Magic Work Cycle [2] or Pomodoro technique [3]. Caffeine and other nootropics can also be helpful. Jogging is the best nootropic I know.
The best introduction to Calculus is classic "Calculus Made Easy" by Silvanus P. Thompson. It is in public domain, is a de-facto standard and is praised by many working scientists (Antony Zee, for example).
It gives you a working knowledge to get going with almost any practical problem you may encounter that needs to be approached with mahtematical analysis.
I would say that Spivak books are more about learning the culture of working mathematicians, and while with its merits one must be careful with commitment of investing her personal time to it.
Also, here is a great page to learn about good (and usually public) books for different branches of mathematics and physics by a Nobel-winning theoretical physicist G. t'Hooft
http://www.staff.science.uu.nl/~hooft101/theorist.html
May I recommend here a specific album that goes along your lines in terms of repetitive nature and intense rhythm pattern, of high quality and definetely works caffeine-like for me?