=======Code Reading Club=======
|"Nobody would try to become an author without being an active reader. Why should becoming a programmer be different?" |
| -- freely adapted from raichoo.|
=====Why attend this course?=====
"Code is read much more often than it is written", "The ratio of time spent reading versus writing is well over 10 to 1. We are constantly reading old code as part of the effort to write new code [...] Making it easy to read makes it easier to write." - these are just some quotes for you to get an idea of how important reading and readability of code is, especially in industry jobs (see our github for sources). Also, any programmer who has ever worked on a project that consisted of more than some throwaway scripts knows the frustrating situation of spending inordinate amounts of time trying to understand code you or someone else wrote months ago - preferably to fix a bug right before an important deadline. Like any skill, we believe that becoming proficient (and efficient) at reading code can be trained by practice. A more than welcome side effect of reading other people's code is that you get to learn how they think and organize their software, becoming a better programmer on the way - and there are many open source repositories of great coders to learn from out there!
=====What we will do=====
In this course, we adapt the concept of a //Journal Club// to reading code. Instead of reading a new paper, we will be finding our way around a new code base every week. As a bioinformatics group, our focus is on bioinformatics tools and the languages C, C++ and python. However, you are welcome to bring projects in other languages or from other fields if you want.
We will start the course by learning about how to get into an unfamiliar code base, after which each of you can choose a repository to read in depth and present in one of the following weeks. You can either bring your own or choose from a list we will provide.
Every session after that will work just like a "normal" journal club: Preparing for the session everyone reads (parts of) the repository and tries to understand it while the "presenter" reads it more in depth and tries to become more of an expert on it than the others. In the actual session, we will develop an understanding of the code base together as well as re-read those parts of the code that we did not quite understand or that are simply critical/interesting/cool.
=====Who this is for=====
If you're thinking of attending this course, most likely you have all that is needed. If you have at least some knowledge about C(++) and python and have done at least done some bigger project in any language (experience from "Grundlagen des Softwareengineering" or equivalent is probably enough here), you should be fine :)
This course is for motivated beginners as well as more experienced programmers, who just want to start reading more code instead of telling themselves that they will get to it eventually. Incidentally, this is also how the idea for this course emerged.
===== Organizational Stuff =====
Github:
https://github.com/lucaparmigiani/Coding-Reading-Club
Schedule:
| **Date** | **Topic** |
| 04.04. | Organizational Matters |
| 11.04. | (Leonard on conference) |
| 18.04. | (Leonard on conference) |
| 25.04. | (Leonard sick) |
| 02.05. | Topic Selection/Dabbling in edlib |
| 09.05. | Myers 1986/edlib|
| 16.05. | Shahriari et al. 2015 |
| 23.05. | Bayesian Optimization |
| 30.05. | Solomon & Kingsford 2016 / (Sequence Bloom Tree)|
| 06.06. | Sequence Bloom Tree teaser |
| 13.06. | Sequence Bloom Tree |
| 20.06. | Rempel & Wittler 2021 |
| 27.06. | SANS |
| 04.07 | KNN by chingisooinar **and** sklearn - KNN |
| 11.07. | No session planned |
=====Topics=====
| **Tool** | **Repository** | **Paper(s)** | **Presenting** |
| edlib | [[https://github.com/Martinsos/edlib]] | [[ https://dl.acm.org/doi/abs/10.1145/316542.316550 | Myers 1999 ]] | Luca & Leonard |
| sans-kc | [[ https://gitlab.ub.uni-bielefeld.de/gi/sans/tree/kc ]] | [[https://academic.oup.com/bioinformatics/article/37/24/4868/6300510 | Rempel & Wittler 2021]] | Talgat |
| prodigal | [[ https://github.com/hyattpd/Prodigal ]] | | |
| columba | [[ https://github.com/biointec/columba ]] | | |
| gsa-is | [[ https://github.com/felipelouza/gsa-is.git ]] | TBA | Presian |
|wg-sim | [[ https://github.com/lh3/wgsim ]] | | |
| Bayesian Optimization | [[https://github.com/fmfn/BayesianOptimization ]] | [[ https://ieeexplore.ieee.org/document/7352306 | Shahriari et al. 2015]] | Adrian |
| Sequence Bloom Tree | [[https://github.com/Kingsford-Group/bloomtree]] | [[https://www.nature.com/articles/nbt.3442 | Solomon & Kingsford 2016]] | Andreas |
| sklearn - KNN | [[ https://github.com/scikit-learn/scikit-learn/blob/364c77e04/sklearn/neighbors/_classification.py#L24 ]] | [[ https://github.com/chingisooinar/KNN-python-implementation/tree/main ]] | Ben |