Try to add {col_contains} column selector, which is based on content of the column

[bedantaguru]

Here is the prototype

require(magrittr)
#> Loading required package: magrittr

select.df <- function(.x, ...) {
  pos <- tidyselect::eval_select(rlang::expr(c(...)), .x)
  rlang::set_names(.x[pos], names(pos))
}
rename.df <- function(.x, ...) {
  pos <- tidyselect::eval_rename(rlang::expr(c(...)), .x)
  names(.x)[pos] <- names(pos)
  .x
}

col_contains <- function(str, dat = tidyselect::peek_data(fn = "col_contains"), .ignore_case = T) {
  if(.ignore_case){
    str <- tolower(str)
    dat %>% 
      purrr::map_lgl(~.x %>% tolower() %>% stringr::str_detect(str) %>% any) %>% 
      colnames(dat)[.]
  }else{
    dat %>% 
      purrr::map_lgl(~stringr::str_detect(.x, str) %>% any) %>% 
      colnames(dat)[.]
  }

}

d <- iris
class(d)<- c( "df", class(d))

d %>% dplyr::rename(tst = col_contains("seto")) %>% head()
#>   Sepal.Length Sepal.Width Petal.Length Petal.Width    tst
#> 1          5.1         3.5          1.4         0.2 setosa
#> 2          4.9         3.0          1.4         0.2 setosa
#> 3          4.7         3.2          1.3         0.2 setosa
#> 4          4.6         3.1          1.5         0.2 setosa
#> 5          5.0         3.6          1.4         0.2 setosa
#> 6          5.4         3.9          1.7         0.4 setosa
d %>% dplyr::select(col_contains("ginica")) %>% head()
#>   Species
#> 1  setosa
#> 2  setosa
#> 3  setosa
#> 4  setosa
#> 5  setosa
#> 6  setosa

^{Created on 2020-04-03 by the reprex package (v0.3.0)}

[bedantaguru]

This requires all output objects to be marked as {df} class (whichever are data.frames)

[bedantaguru]

for {df} class create rename method with snake_case and camelCase options..