10 changed files with 620 additions and 43 deletions
@ -0,0 +1,201 @@ |
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Apache License |
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@ -1,9 +1,14 @@ |
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#' Parse Browser User Agent Strings into Data Frames |
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#' Parse 'User-Agent' Strings |
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#' |
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#' Despite there being a section in RFC 7231 |
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#' <https://tools.ietf.org/html/rfc7231#section-5.5.3> defining a suggested |
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#' structure for 'User-Agent' headers this data is notoriously difficult |
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#' to parse consistently. Tools are provided that will take in user agent |
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#' strings and return structured R objects. This is a 'V8'-backed package |
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#' based on the 'ua-parser' project <https://github.com/ua-parser>. |
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#' |
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#' @name uaparserjs |
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#' @docType package |
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#' @author Bob Rudis (@@hrbrmstr) |
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#' @importFrom purrr map map_df |
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#' @import V8 |
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#' @importFrom dplyr as_tibble progress_estimated |
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#' @import V8 progress |
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NULL |
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@ -0,0 +1,320 @@ |
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# NOTE: At the bottom of this source file show the equivalents to purrr mappers |
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# |
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# NOTE these aren't 100% equivalent to the purrr mappers but cover very common use-cases |
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# |
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# NOTE formula function (e.g. ~{}) are 100% supported |
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# |
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# NOTE: THESE DO NOT SUPPORT list EXTRACTORS |
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set_names <- function(object = nm, nm) { |
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names(object) <- nm |
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object |
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} |
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map <- function(.x, .f, ..., .default) { |
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default_exists <- !missing(.default) |
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if (inherits(.f, "formula")) { |
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.body <- dimnames(attr(terms(.f), "factors"))[[1]] |
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.f <- function(.x, . = .x) {} |
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body(.f) <- as.expression(parse(text=.body)) |
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} |
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nm <- names(.x) |
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if (inherits(.f, "function")) { |
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lapply(.x, function(x) { |
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res <- .f(x, ...) |
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if ((length(res) == 0) & default_exists) res <- .default |
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res |
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}) -> out |
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} else if (is.numeric(.f) | is.character(.f)) { |
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lapply(.x, function(x) { |
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res <- try(x[[.f]], silent = TRUE) |
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if (inherits(res, "try-error")) res <- NULL |
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if ((length(res) == 0) & default_exists) res <- .default |
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res |
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}) -> out |
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} |
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if (length(nm) > 0) out <- set_names(out, nm) |
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out |
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} |
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map2 <- function(.x, .y, .f, ..., .default) { |
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default_exists <- !missing(.default) |
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if (inherits(.f, "formula")) { |
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.body <- dimnames(attr(terms(.f), "factors"))[[1]] |
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.f <- function(.x, .y, . = .x) {} |
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body(.f) <- as.expression(parse(text=.body)) |
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} |
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if (inherits(.f, "function")) { |
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mapply( |
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function(x, ...) { |
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res <- .f(x, ...) |
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if ((length(res) == 0) & default_exists) res <- .default |
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res |
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}, |
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.x, .y, |
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..., |
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SIMPLIFY=FALSE, USE.NAMES=FALSE |
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) |
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} |
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} |
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map_chr <- function(.x, .f, ...) { |
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nm <- names(.x) |
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out <- as.character((map(.x, .f, ..., .default = .default))) |
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if (length(nm) > 0) set_names(out, nm) else out |
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} |
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map2_chr <- function(.x, .y, .f, ...) { |
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as.character(unlist(map2(.x, .y, .f, ..., .default = .default))) |
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} |
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map_lgl <- function(.x, .f, ...) { |
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nm <- names(.x) |
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out <- as.logical(unlist(map(.x, .f, ..., .default = .default))) |
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if (length(nm) > 0) set_names(out, nm) else out |
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} |
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map2_lgl <- function(.x, .y, .f, ...) { |
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as.logical(unlist(map2(.x, .y, .f, ..., .default = .default))) |
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} |
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map_dbl <- function(.x, .f, ...) { |
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nm <- names(.x) |
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out <- as.double(unlist(map(.x, .f, ..., .default = .default))) |
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if (length(nm) > 0) set_names(out, nm) else out |
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} |
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map2_dbl <- function(.x, .y, .f, ...) { |
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as.double(unlist(map2(.x, .y, .f, ..., .default = .default))) |
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} |
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map_int <- function(.x, .f, ..., .default) { |
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nm <- names(.x) |
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out <- as.integer(unlist(map(.x, .f, ..., .default = .default))) |
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if (length(nm) > 0) set_names(out, nm) else out |
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} |
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map2_int <- function(.x, .y, .f, ...) { |
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as.integer(unlist(map2(.x, .y, .f, ..., .default = .default))) |
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} |
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map_df <- function(.x, .f, ..., .id=NULL) { |
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res <- map(.x, .f, ...) |
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out <- bind_rows(res, .id=.id) |
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out |
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} |
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map_dfr <- map_df |
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map_dfc <- function(.x, .f, ...) { |
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res <- map(.x, .f, ...) |
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out <- bind_cols(res) |
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out |
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} |
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map2_df <- function(.x, .y, .f, ..., .id=NULL) { |
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res <- map2(.x, .y, .f, ...) |
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out <- bind_rows(res, .id = .id) |
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out |
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} |
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map2_dfc <- function(.x, .y, .f, ...) { |
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res <- map2(.x, .y, .f, ...) |
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out <- bind_cols(res) |
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out |
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} |
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# this has limitations and is more like 75% of dplyr::bind_rows() |
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# this is also orders of magnitude slower than dplyr::bind_rows() |
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bind_rows <- function(..., .id = NULL) { |
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|
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res <- list(...) |
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if (length(res) == 1) res <- res[[1]] |
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cols <- unique(unlist(lapply(res, names), use.names = FALSE)) |
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if (!is.null(.id)) { |
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inthere <- cols[.id %in% cols] |
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if (length(inthere) > 0) { |
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.id <- make.unique(c(inthere, .id))[2] |
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} |
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} |
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id_vals <- if (is.null(names(res))) 1:length(res) else names(res) |
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saf <- default.stringsAsFactors() |
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options(stringsAsFactors = FALSE) |
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on.exit(options(stringsAsFactors = saf)) |
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idx <- 1 |
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do.call( |
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rbind.data.frame, |
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lapply(res, function(.x) { |
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x_names <- names(.x) |
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moar_names <- setdiff(cols, x_names) |
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if (length(moar_names) > 0) { |
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for (i in 1:length(moar_names)) { |
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.x[[moar_names[i]]] <- rep(NA, length(.x[[1]])) |
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} |
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} |
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if (!is.null(.id)) { |
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.x[[.id]] <- id_vals[idx] |
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idx <<- idx + 1 |
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} |
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.x |
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}) |
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) -> out |
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|
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rownames(out) <- NULL |
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|
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class(out) <- c("tbl_df", "tbl", "data.frame") |
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|
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out |
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|
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} |
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|
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bind_cols <- function(...) { |
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|
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res <- list(...) |
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|
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row_mismatch <- lapply(res, nrow) != nrow(res[[1]]) |
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|
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if (any(row_mismatch)) { |
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first_mismatch_pos <- which(row_mismatch)[1] |
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stop(paste0("Argument ", first_mismatch_pos, |
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" must be length ", nrow(res[[1]]), |
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", not ", nrow(res[[first_mismatch_pos]]))) |
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} |
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|
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if (length(res) == 1) res <- res[[1]] |
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|
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col_names <- unlist(lapply(res, names), use.names = FALSE) |
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col_names <- make.unique(col_names, sep = "") |
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|
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saf <- default.stringsAsFactors() |
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options(stringsAsFactors = FALSE) |
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on.exit(options(stringsAsFactors = saf)) |
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|
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out <- do.call(cbind.data.frame, res) |
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|
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names(out) <- col_names |
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rownames(out) <- NULL |
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|
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class(out) <- c("tbl_df", "tbl", "data.frame") |
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|
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out |
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|
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} |
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|
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|
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# set.seed(1) |
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# 1:10 %>% |
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# map(rnorm, n = 10) %>% |
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# map_dbl(mean) |
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# |
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# set.seed(1) |
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# 1:10 %>% |
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# purrr::map(rnorm, n = 10) %>% |
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# purrr::map_dbl(mean) |
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# |
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# |
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# # Or use an anonymous function |
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# set.seed(1) |
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# 1:10 %>% |
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# map(function(x) rnorm(10, x)) |
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# |
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# set.seed(1) |
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# 1:10 %>% |
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# purrr::map(function(x) rnorm(10, x)) |
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# |
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# # Or a formula |
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# set.seed(1) |
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# 1:10 %>% |
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# map(~ rnorm(10, .x)) |
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# |
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# set.seed(1) |
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# 1:10 %>% |
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# purrr::map(~ rnorm(10, .x)) |
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# |
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# # Extract by name or position |
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# # .default specifies value for elements that are missing or NULL |
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# l1 <- list(list(a = 1L), list(a = NULL, b = 2L), list(b = 3L)) |
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# l1 %>% map("a", .default = "???") |
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# l1 %>% purrr::map("a", .default = "???") |
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# |
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# l1 %>% map_int("b", .default = NA) |
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# l1 %>% purrr::map_int("b", .default = NA) |
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# |
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# l1 %>% map_int(2, .default = NA) |
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# l1 %>% purrr::map_int(2, .default = NA) |
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# |
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# # Supply multiple values to index deeply into a list |
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# l2 <- list( |
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# list(num = 1:3, letters[1:3]), |
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# list(num = 101:103, letters[4:6]), |
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# list() |
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# ) |
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# l2 %>% map(c(2, 2)) |
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# l2 %>% purrr::map(c(2, 2)) |
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# |
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# |
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# # A more realistic example: split a data frame into pieces, fit a |
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# # model to each piece, summarise and extract R^2 |
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# mtcars %>% |
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# split(.$cyl) %>% |
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# map(~ lm(mpg ~ wt, data = .x)) %>% |
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# map(summary) %>% |
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# map_dbl("r.squared") |
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# |
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# mtcars %>% |
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# split(.$cyl) %>% |
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# purrr::map(~ lm(mpg ~ wt, data = .x)) %>% |
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# purrr::map(summary) %>% |
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# purrr::map_dbl("r.squared") |
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# |
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# |
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# # Use map_lgl(), map_dbl(), etc to reduce to a vector. |
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# # * list |
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# mtcars %>% map(sum) |
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# mtcars %>% purrr::map(sum) |
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# # * vector |
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# mtcars %>% map_dbl(sum) |
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# mtcars %>% purrr::map_dbl(sum) |
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# |
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# # If each element of the output is a data frame, use |
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# # map_dfr to row-bind them together: |
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# mtcars %>% |
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# split(.$cyl) %>% |
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# map(~ lm(mpg ~ wt, data = .x)) %>% |
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# map_dfr(~ as.data.frame(t(as.matrix(coef(.))))) |
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# |
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# mtcars %>% |
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# split(.$cyl) %>% |
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# purrr::map(~ lm(mpg ~ wt, data = .x)) %>% |
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# purrr::map_dfr(~ as.data.frame(t(as.matrix(coef(.))))) |
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Reference in new issue