agrep | approximate GREP for fast fuzzy string

all is an upper limit which always applies, regardless of other max.distance controls (other than cost). It defaults to 10%.

Maybe the following can solve your problem. It uses stringdistmatrix in package stringdist, which can become a memory problem if the vectors v1 and v2 are larger.

Is there another way to approach this?

Looking for fuzzy matches is easy with Python. You just need to install the PyPi regex module by running the following in the terminal:

I think this can be done really well using a tidy approach. The problem you already solved can be done (probably much quicker) using tidytext:

If I understood you correctly, you want to extract from your vector the verbs (i.e., the middle substring) iff the words on the left and on the right of it are maximally 2 insertions/deletions etc. distant from the "today \\w+ Oscar"pattern.

If that premise is correct you can first subset your vector on those strings that meet that condition using agrep (or agrepl) and second capture the substring in the middle in a capturing group (...) and refer to it using backreference \\1 in sub's replacement argument:

This isn't base r nor data.table, but here's one way using tidyverse to detect duplicates:

Great question. The long and short of it is "You cant" (in many cases) unless the function is visible in one of the header files in "src/include/". At least not that easily.

Not long ago I had a similar fun challenge, where I tried to get access to the do_docall function (called by do.call), and it is not a simple task. First of all, it is not directly possible to just #include (or something similar). That file simply isn't available for inclusion, as it is not a part of the "src/include". It is compiled and the uncompiled file is removed (not to mention that one should never "include" a .c file).

If one is willing to go the mile, then the next step one could look at is "copying" and "altering" the source code. Basically find the function in "src/main/agrep.c", copy it into your package and then fix any errors you find.

Problems with this approach:

1. As documented in R-exts the internal structures of sexprec_info is not made public (this is the base structure for all objects in R). Many internal function use the fields within this structure, so one has to "copy" the structure into your source code, to make it public to your code specifically.
2. If you ever #include prior to this file, you will need to go through each and every call to internal functions and likely add either R_ or Rf_.
3. The function may contain calls to other "internal" functions, that further needs to be copied and altered for it to work.
4. You will also need to get a clear understanding of what CDR, CAR and similar does. The internal functions have a documented structure, where the first argument contains the full call passed to the function, and function like those 2 are used to access parts of the call. I did myself a solid and rewrote do_docall changing the input format, to avoid having to consider this. But this takes time. The alternative is to create a pairlist according to the documentation, set its type as a call-sexp (the exact name is lost to me at the moment) and pass the appropriate arguments for op, args and env.
5. And lastly, if you go through the steps, and find that it is necessary to copy the internal structures of sexprec_info (as described later), then you will need to be very careful about when you include Rinternals and Rcpp, as any one of these causes your code to crash and burn in the most beautiful and silent way if you include your header and these in the wrong order! Note that this even goes for [[Rcpp::export]], which may indeed turn out to include them in the wrong arbitrary order!

If you are willing to go this far down the drainage, I would suggest carefully reading adv-R "R's C interface" and Chapter 2, 5 and 6 of R-ext and maybe even the R internal manual, and finally once that is done take a look at do_docall from src/main/coerce.c and compare it to the implementation in my repository cmdline.arguments/src/utils/{cmd_coerce.h, cmd_coerce.c}. In this version I have

1. Added all the internal structures that are not public, so that I can access their unmodified form (unmodified by the current session).
   • This includes the table used to store the currently used SEXP's, that was used as a lookup. This caused a problem as I can't access the modified version, so my code is slightly altered with the old code blocked by the macro #if --- defined(CMDLINE_ARGUMENTS_MAYBE_IN_THE_FUTURE). Luckily the code causing a problem had a static answer, so I could work around this (but this might not always be the case).
2. I added quite a few Rf_s as their macro version is not available (since I #include at some point)
3. The code has been split into smaller functions to make it more readable (for my own sake).
4. The function has one additional argument (name), that is not used in the internal function, with some added errors (for my specific need).

This implementation will be frozen "for all time to come" as I've moved on to another branch (and this one is frozen for my own future benefit, if I ever want to walk down this path again).

I spent a few days scouring the internet for information on this and found 2 different posts, talking about how this could be achieved, and my approach basically copies this. Whether this is actually allowed in a cran package, is an whole other question (and not one that I will be testing out).

This approach goes again if you want to use not-public code from other packages. While often here it is as simple as "copy-paste" their files into your repository.

As a final side note, you mention the intend is to "speed up" your code for when you have to perform millions upon millions of calls to agrep. It seems that this is a time where one should consider performing the task in parallel. Even after going through the steps outlined above, creating N parallel sessions to take care of K evaluations each (say 100.000), would be the first step to reduce computing time. Of course each session should be given a batch and not a single call to agrep.

Converting my comment to an answer.

A description of character and string can be found in the R Language Definition:

R has six basic (‘atomic’) vector types: logical, integer, real, complex, string (or character) and raw. The modes and storage modes for the different vector types are listed in the following table.

[...]

String vectors have mode and storage mode "character". A single element of a character vector is often referred to as a character string.

The e in your for loop has no connection with original ern list hence, it is not possible to add any new information in the list. You should iterate over the index of the list instead.