* using log directory 'd:/Rcompile/CRANpkg/local/4.5/qs.Rcheck'
* using R version 4.5.2 (2025-10-31 ucrt)
* using platform: x86_64-w64-mingw32
* R was compiled by
    gcc.exe (GCC) 14.3.0
    GNU Fortran (GCC) 14.3.0
* running under: Windows Server 2022 x64 (build 20348)
* using session charset: UTF-8
* checking for file 'qs/DESCRIPTION' ... OK
* checking extension type ... Package
* this is package 'qs' version '0.27.3'
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking whether package 'qs' can be installed ... OK
* used C++ compiler: 'g++.exe (GCC) 14.3.0'
* checking installed package size ... OK
* checking package directory ... OK
* checking 'build' directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... [1s] OK
* checking whether the package can be loaded with stated dependencies ... [0s] OK
* checking whether the package can be unloaded cleanly ... [0s] OK
* checking whether the namespace can be loaded with stated dependencies ... [0s] OK
* checking whether the namespace can be unloaded cleanly ... [1s] OK
* checking loading without being on the library search path ... [1s] OK
* checking whether startup messages can be suppressed ... [0s] OK
* checking use of S3 registration ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... [3s] OK
* checking Rd files ... [1s] OK
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of 'data' directory ... OK
* checking data for non-ASCII characters ... [0s] OK
* checking LazyData ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking line endings in shell scripts ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking line endings in Makefiles ... OK
* checking compilation flags in Makevars ... OK
* checking for GNU extensions in Makefiles ... OK
* checking for portable use of $(BLAS_LIBS) and $(LAPACK_LIBS) ... OK
* checking use of PKG_*FLAGS in Makefiles ... OK
* checking pragmas in C/C++ headers and code ... OK
* checking compiled code ... NOTE
File 'qs/libs/x64/qs.dll':
  Found non-API calls to R: 'CLOENV', 'ENCLOS', 'FRAME', 'HASHTAB',
    'IS_S4_OBJECT', 'LEVELS', 'OBJECT', 'PRENV', 'Rf_allocSExp',
    'SETLEVELS', 'SET_CLOENV', 'SET_ENCLOS', 'SET_FRAME',
    'SET_HASHTAB', 'SET_PRENV', 'SET_S4_OBJECT', 'SET_TRUELENGTH'

Compiled code should not call non-API entry points in R.

See 'Writing portable packages' in the 'Writing R Extensions' manual,
and section 'Moving into C API compliance' for issues with the use of
non-API entry points.
* checking installed files from 'inst/doc' ... OK
* checking files in 'vignettes' ... OK
* checking examples ... [4s] OK
* checking for unstated dependencies in 'tests' ... OK
* checking tests ... [189s] ERROR
  Running 'correctness_testing.R' [154s]
  Running 'qattributes_testing.R' [34s]
  Running 'qsavemload_testing.R' [2s]
Running the tests in 'tests/qattributes_testing.R' failed.
Complete output:
  > total_time <- Sys.time()
  > 
  > suppressMessages(library(Rcpp))
  > suppressMessages(library(dplyr))
  > suppressMessages(library(data.table))
  > suppressMessages(library(qs))
  > suppressMessages(library(stringfish))
  > options(warn = 1)
  > 
  > do_gc <- function() {
  +   if (utils::compareVersion(as.character(getRversion()), "3.5.0") != -1) {
  +     gc(full = TRUE)
  +   } else {
  +     gc()
  +   }
  + }
  > 
  > # because sourceCpp uses setwd, we need absolute path to R_TESTS when run within R CMD check
  > R_TESTS <- Sys.getenv("R_TESTS") # startup.Rs
  > if (nzchar(R_TESTS)) {
  +   R_TESTS_absolute <- normalizePath(R_TESTS)
  +   Sys.setenv(R_TESTS = R_TESTS_absolute)
  + }
  > sourceCpp(code="#include <Rcpp.h>
  + using namespace Rcpp;
  + // [[Rcpp::plugins(cpp11)]]
  + // [[Rcpp::export(rng=false)]]
  + CharacterVector splitstr(std::string x, std::vector<double> cuts){
  +   CharacterVector ret(cuts.size() - 1);
  +   for(uint64_t i=1; i<cuts.size(); i++) {
  +     ret[i-1] = x.substr(std::round(cuts[i-1])-1, std::round(cuts[i])-std::round(cuts[i-1]));
  +   }
  +   return ret;
  + }
  + // [[Rcpp::export(rng=false)]]
  + int setlev(SEXP x, int i) {
  +   return SETLEVELS(x,i);
  + }
  + // [[Rcpp::export(rng=false)]]
  + void setobj(SEXP x, int i) {
  +   return SET_OBJECT(x, i);
  + }
  + // [[Rcpp::export(rng=false)]]
  + List generateList(std::vector<int> list_elements){
  +   auto randchar = []() -> char
  +   {
  +     const char charset[] =
  +       \"0123456789\"
  +       \"ABCDEFGHIJKLMNOPQRSTUVWXYZ\"
  +       \"abcdefghijklmnopqrstuvwxyz\";
  +     const size_t max_index = (sizeof(charset) - 1);
  +     return charset[ rand() % max_index ];
  +   };
  +   List ret(list_elements.size());
  +   std::string str(10,0);
  +   for(size_t i=0; i<list_elements.size(); i++) {
  +     switch(list_elements[i]) {
  +     case 1:
  +       ret[i] = R_NilValue;
  +       break;
  +     case 2:
  +       std::generate_n( str.begin(), 10, randchar );
  +       ret[i] = str;
  +       break;
  +     case 3:
  +       ret[i] = rand();
  +       break;
  +     case 4:
  +       ret[i] = static_cast<double>(rand());
  +       break;
  +     }
  +   }
  +   return ret;
  + }")
  > if (nzchar(R_TESTS)) Sys.setenv(R_TESTS = R_TESTS)
  > 
  > args <- commandArgs(T)
  > if (nzchar(R_TESTS) || ((length(args) > 0) && args[1] == "check")) { # do fewer tests within R CMD check so it completes within a reasonable amount of time
  +   reps <- 2
  +   test_points <- c(0, 1, 2, 4, 8, 2^5 - 1, 2^5 + 1, 2^5, 2^8 - 1, 2^8 + 1, 2^8, 2^16 - 1, 2^16 + 1, 2^16, 1e6)
  +   test_points_slow <- c(0, 1, 2, 4, 8, 2^5 - 1, 2^5 + 1, 2^5, 2^8 - 1, 2^8 + 1, 2^8, 2^16 - 1, 2^16 + 1, 2^16) # for Character Vector, stringfish and list
  +   max_size <- 1e6
  + } else {
  +   reps <- 3
  +   test_points <- c(0, 1, 2, 4, 8, 2^5 - 1, 2^5 + 1, 2^5, 2^8 - 1, 2^8 + 1, 2^8, 2^16 - 1, 2^16 + 1, 2^16, 1e6, 1e7)
  +   test_points_slow <- test_points
  +   max_size <- 1e7
  + }
  > myfile <- tempfile()
  > 
  > obj_size <- 0
  > get_obj_size <- function() {
  +   get("obj_size", envir = globalenv())
  + }
  > set_obj_size <- function(x) {
  +   assign("obj_size", get_obj_size() + as.numeric(object.size(x)), envir = globalenv())
  +   return(get_obj_size());
  + }
  > random_object_generator <- function(N, with_envs = FALSE) { # additional input: global obj_size, max_size
  +   if (sample(3, 1) == 1) {
  +     ret <- as.list(1:N)
  +   } else if (sample(2, 1) == 1) {
  +     ret <- as.pairlist(1:N)
  +   } else {
  +     ret <- as.pairlist(1:N)
  +     setlev(ret, sample(2L^12L, 1L) - 1L)
  +     setobj(ret, 1L)
  +   }
  + 
  +   for (i in 1:N) {
  +     if (get_obj_size() > get("max_size", envir = globalenv())) break;
  +     otype <- sample(12, size = 1)
  +     z <- NULL
  +     is_attribute <- ifelse(i == 1, F, sample(c(F, T), size = 1))
  +     if (otype == 1) {z <- rnorm(1e4); set_obj_size(z);}
  +     else if (otype == 2) { z <- sample(1e4) - 5e2; set_obj_size(z); }
  +     else if (otype == 3) { z <- sample(c(T, F, NA), size = 1e4, replace = T); set_obj_size(z); }
  +     else if (otype == 4) { z <- (sample(256, size = 1e4, replace = T) - 1) %>% as.raw; set_obj_size(z); }
  +     else if (otype == 5) { z <- replicate(sample(1e4, size = 1), {rep(letters, length.out = sample(10, size = 1)) %>% paste(collapse = "")}); set_obj_size(z); }
  +     else if (otype == 6) { z <- rep(letters, length.out = sample(1e4, size = 1)) %>% paste(collapse = ""); set_obj_size(z); }
  +     else if (otype == 7) { z <- as.formula("y ~ a + b + c : d", env = globalenv()); attr(z, "blah") <- sample(1e4) - 5e2; set_obj_size(z); }
  +     else if (with_envs && otype %in% c(8, 9)) { z <- function(x) {x + runif(1)} }
  +     # else if(with_envs && otype %in% c(10,11)) { z <- new.env(); z$x <- random_object_generator(N, with_envs); makeActiveBinding("y", function() runif(1), z) }
  +     else { z <- random_object_generator(N, with_envs) }
  +     if (is_attribute) {
  +       attr(ret[[i - 1]], runif(1) %>% as.character()) <- z
  +     } else {
  +       ret[[i]] <- z
  +     }
  +   }
  +   return(ret)
  + }
  > 
  > rand_strings <- function(n) {
  +   s <- sample(0:100, size = n, replace = T)
  +   x <- lapply(unique(s), function(si) {
  +     stringfish::random_strings(sum(s == si), si, vector_mode = "normal")
  +   }) %>% unlist %>% sample
  +   x[sample(n, size = n/10)] <- NA
  +   return(x)
  + }
  > 
  > nested_tibble <- function() {
  +   sub_tibble <- function(nr = 600, nc = 4) {
  +     z <- lapply(1:nc, function(i) rand_strings(nr)) %>%
  +       setNames(make.unique(paste0(sample(letters, nc), rand_strings(nc)))) %>%
  +       bind_cols %>%
  +       as_tibble
  +   }
  +   tibble(
  +     col1 = rand_strings(100),
  +     col2 = rand_strings(100),
  +     col3 = lapply(1:100, function(i) sub_tibble(nr = 600, nc = 4)),
  +     col4 = lapply(1:100, function(i) sub_tibble(nr = 600, nc = 4)),
  +     col5 = lapply(1:100, function(i) sub_tibble(nr = 600, nc = 4))
  +   ) %>% setNames(make.unique(paste0(sample(letters, 5), rand_strings(5))))
  + }
  > 
  > printCarriage <- function(x) {
  +   cat(x, "\r")
  + }
  > 
  > attributes_serialize_identical <- function(attributes, full_object) {
  +   identical(serialize(attributes(full_object), NULL), serialize(attributes, NULL))
  + }
  > 
  > attributes_identical <- function(attributes, full_object) {
  +   identical(attributes, attributes(full_object))
  + }
  > 
  > ################################################################################################
  > 
  > qsave_rand <- function(x, file) {
  +   alg <- sample(c("lz4", "zstd", "lz4hc", "zstd_stream", "uncompressed"), 1)
  +   # alg <- "zstd_stream"
  +   nt <- sample(5,1)
  +   sc <- sample(0:15,1)
  +   cl <- sample(10,1)
  +   ch <- sample(c(T,F),1)
  +   qsave(x, file = file, preset = "custom", algorithm = alg,
  +       compress_level = cl, shuffle_control = sc, nthreads = nt, check_hash = ch)
  + }
  > 
  > qattributes_rand <- function(file) {
  +   # ar <- sample(c(T,F),1)
  +   # don't use altrep to avoid serialization differences
  +   # attributes_serialize_identical won't pass with ALTREP
  +   ar <- FALSE
  +   nt <- sample(5,1)
  +   qattributes(file, use_alt_rep = ar, nthreads = nt, strict = T)
  + }
  > 
  > ################################################################################################
  > 
  > for (q in 1:reps) {
  +   cat("Rep",  q, "of", reps, "\n")
  +   # String correctness
  +   time <- vector("numeric", length = 3)
  +   for (tp in test_points) {
  +     for (i in 1:3) {
  +       x1 <- rep(letters, length.out = tp) %>% paste(collapse = "")
  +       x1 <- c(NA, "", x1)
  +       time[i] <- Sys.time()
  +       qsave_rand(x1, file = myfile)
  +       z <- qattributes_rand(file = myfile)
  +       time[i] <- Sys.time() - time[i]
  +       do_gc()
  +       stopifnot(attributes_identical(z, x1))
  +     }
  +     printCarriage(sprintf("strings: %s, %s s",tp, signif(mean(time), 4)))
  +   }
  +   cat("\n")
  + 
  +   # Character vectors
  +   time <- vector("numeric", length = 3)
  +   for (tp in test_points_slow) {
  +     for (i in 1:3) {
  +       # qs_use_alt_rep(F)
  +       x1 <- rep(as.raw(sample(255)), length.out = tp*10) %>% rawToChar
  +       cuts <- sample(tp*10, tp + 1) %>% sort %>% as.numeric
  +       x1 <- splitstr(x1, cuts)
  +       x1 <- c(NA, "", x1)
  +       qsave_rand(x1, file = myfile)
  +       time[i] <- Sys.time()
  +       z <- qattributes_rand(file = myfile)
  +       time[i] <- Sys.time() - time[i]
  +       do_gc()
  +       stopifnot(attributes_identical(z, x1))
  +     }
  +     printCarriage(sprintf("Character Vectors: %s, %s s",tp, signif(mean(time), 4)))
  +   }
  +   cat("\n")
  + 
  +   # stringfish character vectors -- require R > 3.5.0
  +   if (utils::compareVersion(as.character(getRversion()), "3.5.0") != -1) {
  +     time <- vector("numeric", length = 3)
  +     for (tp in test_points_slow) {
  +       for (i in 1:3) {
  +         x1 <- rep(as.raw(sample(255)), length.out = tp*10) %>% rawToChar
  +         cuts <- sample(tp*10, tp + 1) %>% sort %>% as.numeric
  +         x1 <- splitstr(x1, cuts)
  +         x1 <- c(NA, "", x1)
  +         x1 <- stringfish::convert_to_sf(x1)
  +         qsave_rand(x1, file = myfile)
  +         time[i] <- Sys.time()
  +         z <- qattributes_rand(file = myfile)
  +         time[i] <- Sys.time() - time[i]
  +         do_gc()
  +         stopifnot(attributes_identical(z, x1))
  +       }
  +       printCarriage(sprintf("Stringfish: %s, %s s",tp, signif(mean(time), 4)))
  +     }
  +     cat("\n")
  +   }
  + 
  +   # Integers
  +   time <- vector("numeric", length = 3)
  +   for (tp in test_points) {
  +     for (i in 1:3) {
  +       x1 <- sample(1:tp, replace = T)
  +       x1 <- c(NA, x1)
  +       time[i] <- Sys.time()
  +       qsave_rand(x1, file = myfile)
  +       z <- qattributes_rand(file = myfile)
  +       time[i] <- Sys.time() - time[i]
  +       do_gc()
  +       stopifnot(attributes_identical(z, x1))
  +     }
  +     printCarriage(sprintf("Integers: %s, %s s",tp, signif(mean(time), 4)))
  +   }
  +   cat("\n")
  + 
  +   # Doubles
  +   time <- vector("numeric", length = 3)
  +   for (tp in test_points) {
  +     for (i in 1:3) {
  +       x1 <- rnorm(tp)
  +       x1 <- c(NA, x1)
  +       time[i] <- Sys.time()
  +       qsave_rand(x1, file = myfile)
  +       z <- qattributes_rand(file = myfile)
  +       time[i] <- Sys.time() - time[i]
  +       do_gc()
  +       stopifnot(attributes_identical(z, x1))
  +     }
  +     printCarriage(sprintf("Numeric: %s, %s s",tp, signif(mean(time), 4)))
  +   }
  +   cat("\n")
  + 
  +   # Logical
  +   time <- vector("numeric", length = 3)
  +   for (tp in test_points) {
  +     for (i in 1:3) {
  + 
  +       x1 <- sample(c(T, F, NA), replace = T, size = tp)
  +       time[i] <- Sys.time()
  +       qsave_rand(x1, file = myfile)
  +       z <- qattributes_rand(file = myfile)
  +       time[i] <- Sys.time() - time[i]
  +       do_gc()
  +       stopifnot(attributes_identical(z, x1))
  +     }
  +     printCarriage(sprintf("Logical: %s, %s s",tp, signif(mean(time),4)))
  +   }
  +   cat("\n")
  + 
  +   # List
  +   time <- vector("numeric", length = 3)
  +   for (tp in test_points_slow) {
  +     for (i in 1:3) {
  +       x1 <- generateList(sample(1:4, replace = T, size = tp))
  +       time[i] <- Sys.time()
  +       qsave_rand(x1, file = myfile)
  +       z <- qattributes_rand(file = myfile)
  +       time[i] <- Sys.time() - time[i]
  +       do_gc()
  +       stopifnot(attributes_identical(z, x1))
  +     }
  +     printCarriage(sprintf("List: %s, %s s",tp, signif(mean(time),4)))
  +   }
  +   cat("\n")
  + 
  +   for (i in 1:3) {
  +     x1 <- rep( replicate(1000, { rep(letters, length.out = 2^7 + sample(10, size = 1)) %>% paste(collapse = "") }), length.out = 1e6 )
  +     x1 <- data.frame(str = x1,num = runif(1:1000), stringsAsFactors = F)
  +     qsave_rand(x1, file = myfile)
  +     z <- qattributes_rand(file = myfile)
  +     do_gc()
  +     stopifnot(attributes_identical(z, x1))
  +   }
  +   cat("Data.frame test")
  +   cat("\n")
  + 
  +   for (i in 1:3) {
  +     x1 <- rep( replicate(1000, { rep(letters, length.out = 2^7 + sample(10, size = 1)) %>% paste(collapse = "") }), length.out = 1e6 )
  +     x1 <- data.table(str = x1,num = runif(1:1e6))
  +     qsave_rand(x1, file = myfile)
  +     z <- qattributes_rand(file = myfile)
  +     do_gc()
  +     stopifnot(attributes_serialize_identical(z, x1))
  +   }
  +   cat("Data.table test")
  +   cat("\n")
  + 
  +   for (i in 1:3) {
  +     x1 <- rep( replicate(1000, { rep(letters, length.out = 2^7 + sample(10, size = 1)) %>% paste(collapse = "") }), length.out = 1e6 )
  +     x1 <- tibble(str = x1,num = runif(1:1e6))
  +     qsave_rand(x1, file = myfile)
  +     z <- qattributes_rand(file = myfile)
  +     do_gc()
  +     stopifnot(attributes_identical(z, x1))
  +   }
  +   cat("Tibble test")
  +   cat("\n")
  + 
  +   # Encoding test
  +   if (Sys.info()[['sysname']] != "Windows") {
  +     for (i in 1:3) {
  +       x1 <- "己所不欲，勿施于人" # utf 8
  +       x2 <- x1
  +       Encoding(x2) <- "latin1"
  +       x3 <- x1
  +       Encoding(x3) <- "bytes"
  +       x4 <- rep(x1, x2, length.out = 1e4) %>% paste(collapse = ";")
  +       x1 <- c(x1, x2, x3, x4)
  +       qsave_rand(x1, file = myfile)
  +       z <- qattributes_rand(file = myfile)
  +       do_gc()
  +       stopifnot(attributes_identical(z, x1))
  +     }
  +     printCarriage("Encoding test")
  +   } else {
  +     printCarriage("(Encoding test not run on windows)")
  +   }
  +   cat("\n")
  + 
  +   # complex vectors
  +   time <- vector("numeric", length = 3)
  +   for (tp in test_points) {
  +     for (i in 1:3) {
  +       re <- rnorm(tp)
  +       im <- runif(tp)
  +       x1 <- complex(real = re, imaginary = im)
  +       x1 <- c(NA_complex_, x1)
  +       time[i] <- Sys.time()
  +       qsave_rand(x1, file = myfile)
  +       z <- qattributes_rand(file = myfile)
  +       time[i] <- Sys.time() - time[i]
  +       do_gc()
  +       stopifnot(attributes_identical(z, x1))
  +     }
  +     printCarriage(sprintf("Complex: %s, %s s",tp, signif(mean(time), 4)))
  +   }
  +   cat("\n")
  + 
  +   # factors
  +   for (tp in test_points) {
  +     time <- vector("numeric", length = 3)
  +     for (i in 1:3) {
  +       x1 <- factor(rep(letters, length.out = tp), levels = sample(letters), ordered = TRUE)
  +       time[i] <- Sys.time()
  +       qsave_rand(x1, file = myfile)
  +       z <- qattributes_rand(file = myfile)
  +       time[i] <- Sys.time() - time[i]
  +       do_gc()
  +       stopifnot(attributes_identical(z, x1))
  +     }
  +     printCarriage(sprintf("Factors: %s, %s s",tp, signif(mean(time), 4)))
  +   }
  +   cat("\n")
  + 
  +   # Random objects
  +   time <- vector("numeric", length = 8)
  +   for (i in 1:8) {
  +     # qs_use_alt_rep(sample(c(T, F), size = 1))
  +     obj_size <- 0
  +     x1 <- random_object_generator(12)
  +     printCarriage(sprintf("Random objects: %s bytes", object.size(x1) %>% as.numeric))
  +     time[i] <- Sys.time()
  +     qsave_rand(x1, file = myfile)
  +     z <- qattributes_rand(file = myfile)
  +     time[i] <- Sys.time() - time[i]
  +     do_gc()
  +     stopifnot(attributes_identical(z, x1))
  +   }
  +   printCarriage(sprintf("Random objects: %s s", signif(mean(time), 4)))
  +   cat("\n")
  + 
  +   # nested attributes
  +   time <- vector("numeric", length = 3)
  +   for (i in 1:3) {
  +     x1 <- as.list(1:26)
  +     attr(x1[[26]], letters[26]) <- rnorm(100)
  +     for (i in 25:1) {
  +       attr(x1[[i]], letters[i]) <- x1[[i + 1]]
  +     }
  +     time[i] <- Sys.time()
  +     for(j in 1:length(x1)) {
  +       qsave_rand(x1[[j]], file = myfile)
  +       z <- qattributes_rand(file = myfile)
  +       time[i] <- Sys.time() - time[i]
  +       do_gc()
  +       stopifnot(attributes_identical(z, x1[[j]]))
  +     }
  +   }
  +   printCarriage(sprintf("Nested attributes: %s s", signif(mean(time), 4)))
  +   cat("\n")
  + 
  +   # alt-rep -- should serialize the unpacked object
  +   time <- vector("numeric", length = 3)
  +   for (i in 1:3) {
  +     x1 <- 1:max_size
  +     time[i] <- Sys.time()
  +     qsave_rand(x1, file = myfile)
  +     z <- qattributes_rand(file = myfile)
  +     time[i] <- Sys.time() - time[i]
  +     do_gc()
  +     stopifnot(attributes_identical(z, x1))
  +   }
  +   printCarriage(sprintf("Alt rep integer: %s s", signif(mean(time), 4)))
  +   cat("\n")
  + 
  + 
  +   # Environment test
  +   time <- vector("numeric", length = 3)
  +   for (i in 1:3) {
  +     x1 <- new.env()
  +     x1[["a"]] <- 1:max_size
  +     x1[["b"]] <- runif(max_size)
  +     x1[["c"]] <- stringfish::random_strings(1e4, vector_mode = "normal")
  +     time[i] <- Sys.time()
  +     qsave_rand(x1, file = myfile)
  +     z <- qattributes_rand(file = myfile)
  +     stopifnot(attributes_identical(z[["a"]], x1[["a"]]))
  +     stopifnot(attributes_identical(z[["b"]], x1[["b"]]))
  +     stopifnot(attributes_identical(z[["c"]], x1[["c"]]))
  +     time[i] <- Sys.time() - time[i]
  +     do_gc()
  +   }
  +   printCarriage(sprintf("Environment test: %s s", signif(mean(time), 4)))
  +   cat("\n")
  + 
  +   time <- vector("numeric", length = 3)
  +   for (i in 1:3) {
  +     x1 <- nested_tibble()
  +     time[i] <- Sys.time()
  +     qsave_rand(x1, file = myfile)
  +     z <- qattributes_rand(file = myfile)
  +     stopifnot(attributes_identical(z, x1))
  +     time[i] <- Sys.time() - time[i]
  +     do_gc()
  +   }
  +   printCarriage(sprintf("nested tibble test: %s s", signif(mean(time), 4)))
  +   cat("\n")
  + }
  Rep 1 of 2 
  strings: 0, 0.0106 s 
  strings: 1, 0.008283 s 
  strings: 2, 0.004269 s 
  strings: 4, 0.005753 s 
  strings: 8, 0.005574 s 
  strings: 31, 0.002247 s 
  strings: 33, 0.009361 s 
  strings: 32, 0.003393 s 
  strings: 255, 0.001864 s 
  strings: 257, 0.001429 s 
  strings: 256, 0.00136 s 
  strings: 65535, 0.002476 s 
  strings: 65537, 0.001956 s 
  strings: 65536, 0.007701 s 
  strings: 1e+06, 0.006205 s 
  Character Vectors: 0, 0.00142 s 
  Character Vectors: 1, 0.0005451 s 
  Character Vectors: 2, 0.0007296 s 
  Character Vectors: 4, 0.0005297 s 
  Character Vectors: 8, 0.0007843 s 
  Character Vectors: 31, 0.0009487 s 
  Character Vectors: 33, 0.0007296 s 
  Character Vectors: 32, 0.0008783 s 
  Character Vectors: 255, 0.0005128 s 
  Character Vectors: 257, 0.000485 s 
  Character Vectors: 256, 0.001994 s 
  Character Vectors: 65535, 0.001983 s 
  Character Vectors: 65537, 0.002551 s 
  Character Vectors: 65536, 0.002857 s 
  Stringfish: 0, 0.001294 s 
  Stringfish: 1, 0.0008726 s 
  Stringfish: 2, 0.002131 s 
  Stringfish: 4, 0.0001967 s 
  Stringfish: 8, 0.001501 s 
  Stringfish: 31, 0.001254 s 
  Stringfish: 33, 0.0003486 s 
  Stringfish: 32, 0.0005236 s 
  Stringfish: 255, 0.0005213 s 
  Stringfish: 257, 0.001738 s 
  Stringfish: 256, 0.0006554 s 
  Stringfish: 65535, 0.002706 s 
  Stringfish: 65537, 0.00316 s 
  Stringfish: 65536, 0.003185 s 
  Integers: 0, 0.003843 s 
  Integers: 1, 0.002611 s 
  Integers: 2, 0.001732 s 
  Integers: 4, 0.003502 s 
  Integers: 8, 0.001636 s 
  Integers: 31, 0.002827 s 
  Integers: 33, 0.002001 s 
  Integers: 32, 0.0009127 s 
  Integers: 255, 0.00718 s 
  Integers: 257, 0.0009964 s 
  Integers: 256, 0.00296 s 
  Integers: 65535, 0.02443 s 
  Integers: 65537, 0.002784 s 
  Integers: 65536, 0.00515 s 
  Integers: 1e+06, 0.0408 s 
  Numeric: 0, 0.006081 s 
  Numeric: 1, 0.003539 s 
  Numeric: 2, 0.0009766 s 
  Numeric: 4, 0.003765 s 
  Numeric: 8, 0.002266 s 
  Numeric: 31, 0.002184 s 
  Numeric: 33, 0.002085 s 
  Numeric: 32, 0.001454 s 
  Numeric: 255, 0.002458 s 
  Numeric: 257, 0.002992 s 
  Numeric: 256, 0.002185 s 
  Numeric: 65535, 0.003392 s 
  Numeric: 65537, 0.01443 s 
  Numeric: 65536, 0.02439 s 
  Numeric: 1e+06, 0.02478 s 
  Logical: 0, 0.001316 s 
  Logical: 1, 0.002531 s 
  Logical: 2, 0.001236 s 
  Logical: 4, 0.004502 s 
  Logical: 8, 0.002527 s 
  Logical: 31, 0.002143 s 
  Logical: 33, 0.002053 s 
  Logical: 32, 0.001166 s 
  Logical: 255, 0.0008576 s 
  Logical: 257, 0.002974 s 
  Logical: 256, 0.004734 s 
  Logical: 65535, 0.003047 s 
  Logical: 65537, 0.01405 s 
  Logical: 65536, 0.01174 s 
  Logical: 1e+06, 0.08285 s 
  List: 0, 0.001613 s 
  List: 1, 0.003009 s 
  List: 2, 0.002302 s 
  List: 4, 0.002401 s 
  List: 8, 0.002243 s 
  List: 31, 0.0009689 s 
  List: 33, 0.004668 s 
  List: 32, 0.001657 s 
  List: 255, 0.002199 s 
  List: 257, 0.001996 s 
  List: 256, 0.002073 s 
  List: 65535, 0.02277 s 
  List: 65537, 0.03213 s 
  List: 65536, 0.01141 s 
  Data.frame test
  Error: attributes_serialize_identical(z, x1) is not TRUE
  Execution halted
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking re-building of vignette outputs ... [2s] OK
* checking PDF version of manual ... [20s] OK
* checking HTML version of manual ... [6s] OK
* DONE
Status: 1 ERROR, 1 NOTE