remove the :: and ::: patterns

Author: soodoku

DESCRIPTION

@@ -6,8 +6,6 @@ Authors@R: c(
     person("Kate", "Lyons", , "k.lyons7@gmail.com", role = "ctb"),
     person("John", "Muschelli", , "muschellij2@gmail.com", role = "ctb")
   )
-Author: Gaurav Sood [aut, cre], Kate Lyons [ctb], John Muschelli [ctb]
-Maintainer: Gaurav Sood <gsood07@gmail.com>
 Description: Get comments posted on YouTube videos, information on how
     many times a video has been liked, search for videos with particular
     content, and much more. You can also scrape captions from a few
@@ -31,7 +29,6 @@ Imports:
     mime,
     plyr,
     purrr,
-    R6,
     rlang (>= 1.1.0),
     tibble,
     tidyr,

NAMESPACE

@@ -73,7 +73,6 @@ export(yt_set_key)
 export(yt_set_quota_limit)
 export(yt_token)
 export(yt_topic_search)
-importFrom(R6,R6Class)
 importFrom(askpass,askpass)
 importFrom(checkmate,assert)
 importFrom(checkmate,assert_character)
@@ -91,11 +90,17 @@ importFrom(checkmate,check_character)
 importFrom(checkmate,check_list)
 importFrom(checkmate,check_null)
 importFrom(digest,digest)
+importFrom(dplyr,arrange)
 importFrom(dplyr,bind_rows)
+importFrom(dplyr,desc)
 importFrom(dplyr,filter)
+importFrom(dplyr,group_by)
 importFrom(dplyr,mutate)
+importFrom(dplyr,n)
 importFrom(dplyr,pull)
+importFrom(dplyr,rename)
 importFrom(dplyr,select)
+importFrom(dplyr,summarise)
 importFrom(hms,as_hms)
 importFrom(httr,DELETE)
 importFrom(httr,GET)
@@ -126,6 +131,7 @@ importFrom(httr2,resp_headers)
 importFrom(httr2,resp_status)
 importFrom(httr2,secret_decrypt)
 importFrom(httr2,secret_encrypt)
+importFrom(jsonlite,fromJSON)
 importFrom(jsonlite,toJSON)
 importFrom(magrittr,"%>%")
 importFrom(mime,guess_type)
@@ -146,6 +152,7 @@ importFrom(tibble,enframe)
 importFrom(tidyr,pivot_wider)
 importFrom(tidyr,unnest)
 importFrom(tidyr,unnest_longer)
+importFrom(tidyr,unnest_wider)
 importFrom(tidyselect,all_of)
 importFrom(tidyselect,everything)
 importFrom(utils,browseURL)

R/caching.R

@@ -119,7 +119,7 @@ generate_cache_key <- function(endpoint, query, auth) {
   query_str <- paste(names(query_sorted), query_sorted, sep = "=", collapse = "&")
 
   key_parts <- c(endpoint, auth, query_str)
-  cache_key <- paste0("cache_", digest::digest(key_parts, algo = "md5"))
+  cache_key <- paste0("cache_", digest(key_parts, algo = "md5"))
 
   return(cache_key)
 }

R/extended_endpoints.R

@@ -94,7 +94,7 @@ get_live_streams <- function(stream_id = NULL,
 
   if (simplify) {
     result <- tryCatch({
-      purrr::map_df(result$items, ~ flatten(.x))
+      map_df(result$items, ~ flatten(.x))
     }, error = function(e) {
       warning("Failed to convert to data frame: ", e$message, ". Returning list format.", call. = FALSE)
       result
@@ -192,7 +192,7 @@ get_video_thumbnails <- function(video_id,
 
   if (simplify) {
     result <- tryCatch({
-      dplyr::bind_rows(thumbnail_data)
+      bind_rows(thumbnail_data)
     }, error = function(e) {
       warning("Failed to convert to data frame: ", e$message, ". Returning list format.", call. = FALSE)
       thumbnail_data
@@ -282,7 +282,7 @@ get_channel_sections <- function(channel_id = NULL,
 
   if (simplify) {
     result <- tryCatch({
-      purrr::map_df(result$items, ~ flatten(.x))
+      map_df(result$items, ~ flatten(.x))
     }, error = function(e) {
       warning("Failed to convert to data frame: ", e$message, ". Returning list format.", call. = FALSE)
       result
@@ -377,7 +377,7 @@ search_shorts <- function(query,
   if (simplify) {
     result <- tryCatch({
       # Convert to data frame with shorts-specific fields
-      shorts_df <- purrr::map_df(result$items, function(item) {
+      shorts_df <- map_df(result$items, function(item) {
         data.frame(
           video_id = item$id$videoId %||% NA_character_,
           title = item$snippet$title %||% NA_character_,
@@ -481,7 +481,7 @@ get_premiere_info <- function(video_id,
 
   if (simplify) {
     result <- tryCatch({
-      dplyr::bind_rows(premiere_data)
+      bind_rows(premiere_data)
     }, error = function(e) {
       warning("Failed to convert to data frame: ", e$message, ". Returning list format.", call. = FALSE)
       premiere_data

R/get_all_channel_video_stats.R

@@ -121,9 +121,30 @@ get_all_channel_video_stats <- function(channel_id = NULL, mine = FALSE, ...) {
     return(data.frame())
   }
 
-  # Standardize column names and add URL
+  # Map complex column names from get_video_details to expected simple names
   result_df <- video_data
 
+  # Map column names from get_video_details output to expected names
+  # Note: get_video_details returns flattened column names directly
+  column_mapping <- c(
+    "title" = "title",
+    "publication_date" = "publishedAt", 
+    "description" = "description",
+    "channel_id" = "channelId",
+    "channel_title" = "channelTitle",
+    "view_count" = "viewCount",
+    "like_count" = "likeCount", 
+    "comment_count" = "commentCount"
+  )
+  
+  # Rename columns that exist
+  for (new_name in names(column_mapping)) {
+    old_name <- column_mapping[[new_name]]
+    if (old_name %in% names(result_df)) {
+      names(result_df)[names(result_df) == old_name] <- new_name
+    }
+  }
+  
   # Add video URL
   result_df$url <- paste0("https://www.youtube.com/watch?v=", result_df$id)
 
@@ -132,9 +153,15 @@ get_all_channel_video_stats <- function(channel_id = NULL, mine = FALSE, ...) {
                      "channel_id", "channel_title", "view_count", "like_count", 
                      "comment_count", "url")
 
-  # Select available columns
-  available_columns <- intersect(final_columns, names(result_df))
-  result_df <- result_df[, available_columns, drop = FALSE]
+  # Add missing columns as NA if they don't exist
+  for (col in final_columns) {
+    if (!col %in% names(result_df)) {
+      result_df[[col]] <- NA
+    }
+  }
+  
+  # Select final columns in the right order
+  result_df <- result_df[, final_columns, drop = FALSE]
 
   message("Successfully retrieved data for ", nrow(result_df), " videos")
 

R/get_channel_stats.R

@@ -275,7 +275,7 @@ list_my_channel <- function(...) {
 
 # Helper function to flatten channel data to data frame
 flatten_channel_data <- function(items) {
-  purrr::map_df(items, function(item) {
+  map_df(items, function(item) {
     # Flatten the nested structure
     flat_item <- list()
 

R/get_comment_threads.R

@@ -183,7 +183,7 @@ get_comment_threads <- function(filter = NULL, part = "snippet",
 
     # Trim to actual size and combine efficiently
     all_items <- all_items[seq_len(item_count)]
-    agg_res_df <- dplyr::bind_rows(lapply(all_items, as.data.frame, stringsAsFactors = FALSE))
+    agg_res_df <- bind_rows(lapply(all_items, as.data.frame, stringsAsFactors = FALSE))
     # Unicode handling already applied above, no need to repeat
     if ("publishedAt" %in% colnames(agg_res_df)) {
       agg_res_df <- agg_res_df[order(agg_res_df$publishedAt), , drop = FALSE]

R/get_playlist_items.R

@@ -138,7 +138,7 @@ get_playlist_items <- function(filter = NULL, part = "contentDetails",
     })
 
     # Combine all rows into single data.frame
-    res <- do.call(plyr::rbind.fill, simplified_items)
+    res <- do.call(rbind.fill, simplified_items)
 
     # Add attributes to simplified result
     res <- add_tuber_attributes(

R/get_video_details.R

@@ -1,7 +1,7 @@
 # helpers for data frame conversion in `get_video_details()`
 conditional_unnest_wider <- function(data_input, var) {
   if (var %in% names(data_input)) {
-    tidyr::unnest_wider(data_input, var, names_sep = "_")
+    unnest_wider(data_input, var, names_sep = "_")
   } else {
     data_input
   }
@@ -12,16 +12,16 @@ utils::globalVariables(c("kind", "etag", "items", "snippet"))
 
 json_to_df <- function(res) {
   intermediate <- res %>%
-    tibble::enframe() %>%
-    tidyr::pivot_wider() %>%
-    tidyr::unnest(cols = c(kind, etag)) %>%
+    enframe() %>%
+    pivot_wider() %>%
+    unnest(cols = c(kind, etag)) %>%
     # reflect level of nesting in column name
-    dplyr::rename(response_kind = kind, response_etag = etag) %>%
-    tidyr::unnest(items) %>%
-    tidyr::unnest_wider(col = items) %>%
+    rename(response_kind = kind, response_etag = etag) %>%
+    unnest(items) %>%
+    unnest_wider(col = items) %>%
     # reflect level of nesting in column name for those that may not be unique
-    dplyr::rename(items_kind = kind, items_etag = etag) %>%
-    tidyr::unnest_wider(snippet)
+    rename(items_kind = kind, items_etag = etag) %>%
+    unnest_wider(snippet)
 
   intermediate_2 <- intermediate %>%
     # fields that may not be available:
@@ -184,7 +184,7 @@ get_video_details <- function(video_ids,
 
     if (simplify) {
       raw_res <- tryCatch({
-        purrr::map_df(raw_res$items, ~ flatten(.x))
+        map_df(raw_res$items, ~ flatten(.x))
       }, error = function(e) {
         warn("Failed to convert to data frame",
              message = e$message,
@@ -263,7 +263,7 @@ get_video_details <- function(video_ids,
 
   if (simplify) {
     result <- tryCatch({
-      purrr::map_df(result$items, ~ flatten(.x))
+      map_df(result$items, ~ flatten(.x))
     }, error = function(e) {
       warn("Failed to convert to data frame",
            message = e$message,

R/helper_functions.R

@@ -384,21 +384,21 @@ analyze_trends <- function(search_terms,
 
   # Combine all results
   if (length(all_results) > 0) {
-    combined_data <- dplyr::bind_rows(all_results)
+    combined_data <- bind_rows(all_results)
 
     # Calculate trend metrics
     trend_summary <- combined_data %>%
-      dplyr::group_by(search_term) %>%
-      dplyr::summarise(
-        total_videos = dplyr::n(),
+      group_by(search_term) %>%
+      summarise(
+        total_videos = n(),
         avg_views = mean(view_count, na.rm = TRUE),
         total_views = sum(view_count, na.rm = TRUE),
         avg_engagement = mean(like_count / pmax(view_count, 1), na.rm = TRUE),
         top_video_views = max(view_count, na.rm = TRUE),
         trending_score = log10(total_views + 1) * avg_engagement * 100,
         .groups = "drop"
       ) %>%
-      dplyr::arrange(dplyr::desc(trending_score))
+      arrange(desc(trending_score))
 
     result <- list(
       detailed_results = combined_data,