Even worse, there is a trade-off between code speed and code readability we’ve already made this trade-off once by using readable, (but slow) R compared with verbose C code!įor this reason this chapter is covered towards the latter half of the book. This means that time spent optimizing code early in the developmental stage could be wasted. When developing code, the causes of inefficiencies may shift so that what originally caused slowness at the beginning of your work may not be relevant at a later stage. Knuth’s point is that it is easy to undertake code optimisation inefficiently. The real problem is that programmers have spent far too much time worrying about efficiency in the wrong places and at the wrong times premature optimisation is the root of all evil (or at least most of it) in programming. On the subject of optimisation he gives this advice: 9.3.4 Branches, forks, pulls and clonesĭonald Knuth is a legendary American computer scientist who developed a number of the key algorithms that we use today (see for example ?Random).9.1 Top 5 tips for efficient collaboration.8.5 Operating systems: 32-bit or 64-bit.7.5.1 Parallel versions of apply functions.7.4 Example: Optimising the move_square() function. ![]() ![]() 7.1 Top 5 tips for efficient performance.6.4 Efficient data processing with dplyr.6.3.2 Split joint variables with separate().6.3.1 Make wide tables long with pivot_longer().6.3 Tidying data with tidyr and regular expressions.6.1 Top 5 tips for efficient data carpentry.5.4.1 Native binary formats: Rdata or Rds?.5.3.1 Differences between fread() and read_csv().4.5.1 Dynamic documents with R Markdown.Informative output: message() and cat().3.1 Top 5 tips for efficient programming.2.6.3 Useful BLAS/benchmarking resources.2.6.1 Testing performance gains from BLAS. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |