Last updated on 2025-12-25 19:51:00 CET.
| Package | ERROR | WARN | NOTE | OK |
|---|---|---|---|---|
| glow | 2 | 11 | ||
| qs | 3 | 2 | 7 | 1 |
| qs2 | 7 | 6 | ||
| seqtrie | 3 | 10 | ||
| stringfish | 7 | 6 |
Current CRAN status: NOTE: 2, OK: 11
Version: 0.13.0
Check: installed package size
Result: NOTE
installed size is 11.5Mb
sub-directories of 1Mb or more:
doc 1.3Mb
libs 9.9Mb
Flavors: r-oldrel-macos-arm64, r-oldrel-macos-x86_64
Current CRAN status: ERROR: 3, WARN: 2, NOTE: 7, OK: 1
Version: 0.27.3
Check: compiled code
Result: WARN
File ‘qs/libs/qs.so’:
Found non-API calls to R: ‘ATTRIB’, ‘CLOENV’, ‘ENCLOS’, ‘FRAME’,
‘HASHTAB’, ‘IS_S4_OBJECT’, ‘LEVELS’, ‘OBJECT’, ‘PRENV’,
‘Rf_allocSExp’, ‘SETLEVELS’, ‘SET_ATTRIB’, ‘SET_CLOENV’,
‘SET_ENCLOS’, ‘SET_FRAME’, ‘SET_HASHTAB’, ‘SET_OBJECT’,
‘SET_PRENV’, ‘SET_S4_OBJECT’, ‘SET_TRUELENGTH’
These entry points may be removed soon:
‘SET_FRAME’, ‘SET_HASHTAB’, ‘SET_ENCLOS’, ‘SET_S4_OBJECT’, ‘FRAME’, ‘HASHTAB’, ‘IS_S4_OBJECT’, ‘CLOENV’, ‘ENCLOS’, ‘OBJECT’, ‘SET_CLOENV’, ‘LEVELS’, ‘SETLEVELS’
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.
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc
Version: 0.27.3
Check: tests
Result: ERROR
Running ‘correctness_testing.R’ [149s/155s]
Running ‘qattributes_testing.R’ [36s/39s]
Running ‘qsavemload_testing.R’ [1s/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, 0.01481 s
strings: 1, 0.005167 s
strings: 2, 0.002054 s
strings: 4, 0.001519 s
strings: 8, 0.005831 s
strings: 31, 0.004086 s
strings: 33, 0.004516 s
strings: 32, 0.0003717 s
strings: 255, 0.005216 s
strings: 257, 0.0003949 s
strings: 256, 0.002359 s
strings: 65535, 0.001879 s
strings: 65537, 0.004685 s
strings: 65536, 0.00421 s
strings: 1e+06, 0.004878 s
Character Vectors: 0, 0.0004519 s
Character Vectors: 1, 0.004901 s
Character Vectors: 2, 0.004057 s
Character Vectors: 4, 0.0001047 s
Character Vectors: 8, 0.003676 s
Character Vectors: 31, 0.0002875 s
Character Vectors: 33, 0.0003109 s
Character Vectors: 32, 0.005622 s
Character Vectors: 255, 0.003344 s
Character Vectors: 257, 0.000104 s
Character Vectors: 256, 0.004525 s
Character Vectors: 65535, 0.0373 s
Character Vectors: 65537, 0.001958 s
Character Vectors: 65536, 0.006583 s
Stringfish: 0, 0.001453 s
Stringfish: 1, 0.002129 s
Stringfish: 2, 0.0003548 s
Stringfish: 4, 0.002038 s
Stringfish: 8, 0.003722 s
Stringfish: 31, 0.0001168 s
Stringfish: 33, 0.001518 s
Stringfish: 32, 0.001412 s
Stringfish: 255, 0.001336 s
Stringfish: 257, 0.002683 s
Stringfish: 256, 0.00293 s
Stringfish: 65535, 0.02936 s
Stringfish: 65537, 0.004027 s
Stringfish: 65536, 0.005308 s
Integers: 0, 0.00601 s
Integers: 1, 0.004566 s
Integers: 2, 0.0009998 s
Integers: 4, 0.00639 s
Integers: 8, 0.0004589 s
Integers: 31, 0.007602 s
Integers: 33, 0.01001 s
Integers: 32, 0.004214 s
Integers: 255, 0.001558 s
Integers: 257, 0.001318 s
Integers: 256, 0.006152 s
Integers: 65535, 0.0006669 s
Integers: 65537, 0.007399 s
Integers: 65536, 0.007449 s
Integers: 1e+06, 0.01718 s
Numeric: 0, 0.003168 s
Numeric: 1, 0.0004834 s
Numeric: 2, 0.002369 s
Numeric: 4, 0.002225 s
Numeric: 8, 0.000358 s
Numeric: 31, 0.0005854 s
Numeric: 33, 0.0005604 s
Numeric: 32, 0.0005297 s
Numeric: 255, 0.00154 s
Numeric: 257, 0.004539 s
Numeric: 256, 0.006278 s
Numeric: 65535, 0.00643 s
Numeric: 65537, 0.009739 s
Numeric: 65536, 0.01714 s
Numeric: 1e+06, 0.1769 s
Logical: 0, 0.0007337 s
Logical: 1, 0.002382 s
Logical: 2, 0.008147 s
Logical: 4, 0.002143 s
Logical: 8, 0.001658 s
Logical: 31, 0.00362 s
Logical: 33, 0.009357 s
Logical: 32, 0.002891 s
Logical: 255, 0.002355 s
Logical: 257, 0.001368 s
Logical: 256, 0.006432 s
Logical: 65535, 0.01493 s
Logical: 65537, 0.002055 s
Logical: 65536, 0.008248 s
Logical: 1e+06, 0.07607 s
List: 0, 0.001335 s
List: 1, 0.002473 s
List: 2, 0.001792 s
List: 4, 0.004096 s
List: 8, 0.004271 s
List: 31, 0.005114 s
List: 33, 0.002151 s
List: 32, 0.007273 s
List: 255, 0.005337 s
List: 257, 0.008183 s
List: 256, 0.007824 s
List: 65535, 0.01361 s
List: 65537, 0.01604 s
List: 65536, 0.01909 s
Data.frame test
Error: attributes_serialize_identical(z, x1) is not TRUE
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 0.27.3
Check: tests
Result: ERROR
Running ‘correctness_testing.R’ [268s/231s]
Running ‘qattributes_testing.R’ [56s/50s]
Running ‘qsavemload_testing.R’
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, 0.02195 s
strings: 1, 0.002825 s
strings: 2, 0.002177 s
strings: 4, 0.00292 s
strings: 8, 0.004484 s
strings: 31, 0.001032 s
strings: 33, 0.0005887 s
strings: 32, 0.002058 s
strings: 255, 0.006342 s
strings: 257, 0.000531 s
strings: 256, 0.001491 s
strings: 65535, 0.003628 s
strings: 65537, 0.00463 s
strings: 65536, 0.001364 s
strings: 1e+06, 0.009543 s
Character Vectors: 0, 0.0009336 s
Character Vectors: 1, 0.000179 s
Character Vectors: 2, 0.001052 s
Character Vectors: 4, 0.0006127 s
Character Vectors: 8, 0.001327 s
Character Vectors: 31, 0.0007842 s
Character Vectors: 33, 0.0009992 s
Character Vectors: 32, 0.0008057 s
Character Vectors: 255, 0.0007481 s
Character Vectors: 257, 0.001818 s
Character Vectors: 256, 0.0017 s
Character Vectors: 65535, 0.00486 s
Character Vectors: 65537, 0.00397 s
Character Vectors: 65536, 0.004183 s
Stringfish: 0, 0.0002044 s
Stringfish: 1, 0.000821 s
Stringfish: 2, 0.0008513 s
Stringfish: 4, 0.001974 s
Stringfish: 8, 0.001068 s
Stringfish: 31, 0.0004916 s
Stringfish: 33, 0.001715 s
Stringfish: 32, 0.0006591 s
Stringfish: 255, 0.000706 s
Stringfish: 257, 0.0007126 s
Stringfish: 256, 0.002343 s
Stringfish: 65535, 0.005258 s
Stringfish: 65537, 0.004229 s
Stringfish: 65536, 0.00368 s
Integers: 0, 0.002883 s
Integers: 1, 0.001193 s
Integers: 2, 0.003426 s
Integers: 4, 0.002935 s
Integers: 8, 0.002025 s
Integers: 31, 0.002448 s
Integers: 33, 0.001153 s
Integers: 32, 0.002059 s
Integers: 255, 0.00156 s
Integers: 257, 0.002224 s
Integers: 256, 0.002544 s
Integers: 65535, 0.004317 s
Integers: 65537, 0.009076 s
Integers: 65536, 0.002516 s
Integers: 1e+06, 0.08307 s
Numeric: 0, 0.001267 s
Numeric: 1, 0.003897 s
Numeric: 2, 0.00157 s
Numeric: 4, 0.00502 s
Numeric: 8, 0.002792 s
Numeric: 31, 0.0006868 s
Numeric: 33, 0.00121 s
Numeric: 32, 0.00317 s
Numeric: 255, 0.001732 s
Numeric: 257, 0.001848 s
Numeric: 256, 0.0013 s
Numeric: 65535, 0.01662 s
Numeric: 65537, 0.01363 s
Numeric: 65536, 0.008254 s
Numeric: 1e+06, 0.04625 s
Logical: 0, 0.001711 s
Logical: 1, 0.004304 s
Logical: 2, 0.002129 s
Logical: 4, 0.003874 s
Logical: 8, 0.002074 s
Logical: 31, 0.002092 s
Logical: 33, 0.002488 s
Logical: 32, 0.003268 s
Logical: 255, 0.004204 s
Logical: 257, 0.0007268 s
Logical: 256, 0.002124 s
Logical: 65535, 0.003318 s
Logical: 65537, 0.003569 s
Logical: 65536, 0.009047 s
Logical: 1e+06, 0.03434 s
List: 0, 0.003053 s
List: 1, 0.004374 s
List: 2, 0.001698 s
List: 4, 0.004354 s
List: 8, 0.002009 s
List: 31, 0.00342 s
List: 33, 0.002135 s
List: 32, 0.003174 s
List: 255, 0.002543 s
List: 257, 0.001803 s
List: 256, 0.002026 s
List: 65535, 0.04378 s
List: 65537, 0.05758 s
List: 65536, 0.05531 s
Data.frame test
Error: attributes_serialize_identical(z, x1) is not TRUE
Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 0.27.3
Check: tests
Result: ERROR
Running ‘correctness_testing.R’ [259s/226s]
Running ‘qattributes_testing.R’ [52s/49s]
Running ‘qsavemload_testing.R’
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, 0.01568 s
strings: 1, 0.0005397 s
strings: 2, 0.0005956 s
strings: 4, 0.001674 s
strings: 8, 0.003209 s
strings: 31, 0.007463 s
strings: 33, 0.004372 s
strings: 32, 0.001823 s
strings: 255, 0.001735 s
strings: 257, 0.001726 s
strings: 256, 0.001495 s
strings: 65535, 0.004394 s
strings: 65537, 0.002096 s
strings: 65536, 0.00315 s
strings: 1e+06, 0.01653 s
Character Vectors: 0, 0.002053 s
Character Vectors: 1, 0.0002075 s
Character Vectors: 2, 0.000495 s
Character Vectors: 4, 0.001187 s
Character Vectors: 8, 0.001044 s
Character Vectors: 31, 0.00159 s
Character Vectors: 33, 0.001147 s
Character Vectors: 32, 0.0001561 s
Character Vectors: 255, 0.002022 s
Character Vectors: 257, 0.0003315 s
Character Vectors: 256, 0.0009503 s
Character Vectors: 65535, 0.005587 s
Character Vectors: 65537, 0.006392 s
Character Vectors: 65536, 0.004471 s
Stringfish: 0, 0.001206 s
Stringfish: 1, 0.002059 s
Stringfish: 2, 0.001952 s
Stringfish: 4, 0.0008779 s
Stringfish: 8, 0.0002288 s
Stringfish: 31, 0.001316 s
Stringfish: 33, 0.0008913 s
Stringfish: 32, 0.0009786 s
Stringfish: 255, 0.001261 s
Stringfish: 257, 0.0004921 s
Stringfish: 256, 0.0008632 s
Stringfish: 65535, 0.004601 s
Stringfish: 65537, 0.003876 s
Stringfish: 65536, 0.00389 s
Integers: 0, 0.001276 s
Integers: 1, 0.001618 s
Integers: 2, 0.004518 s
Integers: 4, 0.0016 s
Integers: 8, 0.004515 s
Integers: 31, 0.004372 s
Integers: 33, 0.003146 s
Integers: 32, 0.001462 s
Integers: 255, 0.001817 s
Integers: 257, 0.004133 s
Integers: 256, 0.001988 s
Integers: 65535, 0.007733 s
Integers: 65537, 0.01301 s
Integers: 65536, 0.01383 s
Integers: 1e+06, 0.114 s
Numeric: 0, 0.001843 s
Numeric: 1, 0.001764 s
Numeric: 2, 0.001527 s
Numeric: 4, 0.003182 s
Numeric: 8, 0.001939 s
Numeric: 31, 0.004883 s
Numeric: 33, 0.002716 s
Numeric: 32, 0.002519 s
Numeric: 255, 0.001441 s
Numeric: 257, 0.001657 s
Numeric: 256, 0.002522 s
Numeric: 65535, 0.01635 s
Numeric: 65537, 0.01493 s
Numeric: 65536, 0.007214 s
Numeric: 1e+06, 0.44 s
Logical: 0, 0.002033 s
Logical: 1, 0.00158 s
Logical: 2, 0.00169 s
Logical: 4, 0.002272 s
Logical: 8, 0.004576 s
Logical: 31, 0.001243 s
Logical: 33, 0.0021 s
Logical: 32, 0.001079 s
Logical: 255, 0.002612 s
Logical: 257, 0.002022 s
Logical: 256, 0.002032 s
Logical: 65535, 0.003966 s
Logical: 65537, 0.008276 s
Logical: 65536, 0.02089 s
Logical: 1e+06, 0.1287 s
List: 0, 0.001066 s
List: 1, 0.002157 s
List: 2, 0.002229 s
List: 4, 0.00161 s
List: 8, 0.001365 s
List: 31, 0.002018 s
List: 33, 0.002926 s
List: 32, 0.003515 s
List: 255, 0.00188 s
List: 257, 0.00296 s
List: 256, 0.003326 s
List: 65535, 0.04281 s
List: 65537, 0.02039 s
List: 65536, 0.03929 s
Data.frame test
Error: attributes_serialize_identical(z, x1) is not TRUE
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc
Version: 0.27.3
Check: compiled code
Result: WARN
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_OBJECT', 'SET_PRENV', 'SET_S4_OBJECT',
'SET_TRUELENGTH'
These entry points may be removed soon:
'SET_FRAME', 'SET_HASHTAB', 'SET_ENCLOS', 'SET_S4_OBJECT', 'FRAME', 'HASHTAB', 'IS_S4_OBJECT', 'CLOENV', 'ENCLOS', 'OBJECT', 'SET_CLOENV', 'LEVELS', 'SETLEVELS'
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.
Flavor: r-devel-windows-x86_64
Version: 0.27.3
Check: compiled code
Result: NOTE
File ‘qs/libs/qs.so’:
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.
Flavors: r-patched-linux-x86_64, r-release-linux-x86_64, r-release-macos-arm64, r-release-macos-x86_64
Version: 0.27.3
Check: compiled code
Result: 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.
Flavor: r-release-windows-x86_64
Version: 0.27.3
Check: installed package size
Result: NOTE
installed size is 9.2Mb
sub-directories of 1Mb or more:
doc 1.1Mb
libs 7.8Mb
Flavors: r-oldrel-macos-arm64, r-oldrel-macos-x86_64
Current CRAN status: NOTE: 7, OK: 6
Version: 0.1.6
Check: compiled code
Result: NOTE
File ‘qs2/libs/qs2.so’:
Found non-API calls to R: ‘ATTRIB’, ‘SET_ATTRIB’
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.
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc
Version: 0.1.6
Check: installed package size
Result: NOTE
installed size is 8.8Mb
sub-directories of 1Mb or more:
libs 8.6Mb
Flavors: r-oldrel-macos-arm64, r-oldrel-macos-x86_64
Version: 0.1.6
Check: for GNU extensions in Makefiles
Result: NOTE
GNU make is a SystemRequirements.
Flavors: r-oldrel-macos-arm64, r-oldrel-macos-x86_64, r-oldrel-windows-x86_64
Current CRAN status: NOTE: 3, OK: 10
Version: 0.3.5
Check: installed package size
Result: NOTE
installed size is 6.0Mb
sub-directories of 1Mb or more:
data 1.1Mb
libs 4.4Mb
Flavors: r-oldrel-macos-arm64, r-oldrel-macos-x86_64
Version: 0.3.5
Check: for GNU extensions in Makefiles
Result: NOTE
GNU make is a SystemRequirements.
Flavors: r-oldrel-macos-arm64, r-oldrel-macos-x86_64, r-oldrel-windows-x86_64
Version: 0.3.5
Check: package dependencies
Result: NOTE
Package suggested but not available for checking: ‘pwalign’
Flavor: r-oldrel-macos-x86_64
Current CRAN status: NOTE: 7, OK: 6
Version: 0.17.0
Check: compiled code
Result: NOTE
File ‘stringfish/libs/stringfish.so’:
Found non-API call to R: ‘ATTRIB’
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.
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc
Version: 0.17.0
Check: for GNU extensions in Makefiles
Result: NOTE
GNU make is a SystemRequirements.
Flavors: r-oldrel-macos-arm64, r-oldrel-macos-x86_64, r-oldrel-windows-x86_64