对多个dplyr过滤器条件使用tidy eval

我是tidy eval的新手,尝试编写泛型函数——目前我正在努力解决的一件事是为分类变量编写多个过滤条件。这就是我现在使用的-

create_expr <- function(name, val){
   if(!is.null(val))
     val <- paste0("c('", paste0(val, collapse = "','"), "')")
   paste(name, "%in%", val)
}

my_filter <- function(df, cols, conds){
#   Args: 
#     df: dataframe which is to be filtered
#     cols: list of column names which are to be filtered
#     conds: corresponding values for each column which need to be filtered

cols <- as.list(cols)
conds <- as.list(conds)

args <- mapply(create_expr, cols, conds, SIMPLIFY = F)

if(!length(args))
  stop(cat("No filters provided"))

df <- df %>% filter_(paste(unlist(args), collapse = " & "))
return(df)
}

my_filter(gapminder, cols = list("continent", "country"), 
                     conds = list("Europe", c("Albania", "France")))

我想知道如何使用整洁的评估实践重新编写。我找到了关于对多个参数使用quos()的材料,但正如您所见,我这里有两个不同的参数列表,需要相互映射。

非常感谢您的帮助,谢谢!