nagoya-foundation / r-functions-performance Goto Github PK

Create a scalable way to write table of content:

1. Cannot be painfull to add everytime someone add new benchmark.
2. Cannot be painfull for contributors, to do it manually.
3. Guarantee is following the readme structure.

Hello guys. Interesting initiative here.
I committed a pull request to add some libraries to enhance reading some function in the repo. Here, I would like to fit into attention that when compiling main.R file, the process takes too much time and seems stopping halfway. I used rstudio cloud to do this. I think there is some issue on the analysed_results variable created there. When compiling sources manually, the process works normally without problems.
Good luck!

Need a new dataset.

Conditions

1. Not large enough to make it painfull to call functions 1000 times over it;
2. Not small enough to make size irrelevant;
3. Cannot be related to anything controversial, need to be something neutral;
4. Cannot be perfect, we need to simulate real life function calls (data missing and other stuff...);
5. Need to have a path, so we can give credits to the owner.

Structure src folder to be scalable

Map string packages and find related functions

There is no reference about forks

I need help to map functions that can provide the same result.

Example

to string functions

1. as.character()
2. paste()
3. toString()
4. sprintf()

Once you mapped at least two functions, open a pull request with the readme updated like this or source code in analyse.R

All informations that we are providing are necessary or just min time, max time, avg time?

Should we provide another, like "package" or "syntax"? @blmayer

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