Packages intermittent failtures

Introduction

This report checks if the status of packages on CRAN are due to intermittent failures.

Failures defined as warnings, notes or errors without change on:

• R version used (if not stable the same svn snapshot)

• The package version (Note that CRAN might modify a package without changing the version)

• Their dependencies

Reasons of these failures might be because the packages depend on:

• Random generation numbers

• Flacky external resources

• Other ?

Why is this important?

Because package maintainers of dependencies of that package, R core and CRAN team need to check if the failures are false positives.

This report started because it was suggested as something that the R-repositories working group could help the CRAN team.

Retrieve data

It makes use of tools::CRAN_check_results to retrieve the data.

library("dplyr")
library("tools", include.only = c("package_dependencies", "CRAN_check_results"))
library("flextable", include.only = c("flextable", "autofit"))
# Use a LOCAL environment to check if files can be overwritten on my computer
local_build <- as.logical(Sys.getenv("LOCAL", "FALSE"))
yc <- readRDS("today.RDS")
tc <- CRAN_check_results()
# Added 2023/03/09: sometimes some flavors are reported without status: Omit those
tc <- tc[!is.na(tc$Status),]
if (!interactive() && !local_build) {
  message("Saving today's file.")
  saveRDS(tc, file = "today.RDS")
} 

The checks are from multiple flavors release, devel, old release and patched on multiple machines and configurations.

old_flavors <- readRDS("flavors.RDS")
flavors <- unique(tc$Flavor)
# One flavor now present in all is the r-devel-windows-x86_64: skip
flavors <- setdiff(flavors, "r-devel-windows-x86_64")
proto <- data.frame(r_version = character(),
                    os = character(),
                    architecture = character(),
                    other = character())
flavors_df <- strcapture(
  pattern = "r-([[:alnum:]]+)-([[:alnum:]]+)-([[:alnum:]_\\+]+)-?(.*)", 
  x = flavors,
  proto = proto)

# Extract R version used and svn id
h <- "https://www.r-project.org/nosvn/R.check/%s/ggplot2-00check.html"
links <- sprintf(h, flavors)
extract_revision <- function(x) {
  r <- readLines(x, 12)[12]
  version <- strcapture(pattern = "([[:digit:]]\\.[[:digit:]]\\.[[:digit:]])",  
                        x = r, proto = data.frame(version = character()))
  revision <- strcapture(pattern = "(r[[:digit:]]+)",  x = r,
                         proto = data.frame(revision = character()))
  cbind(version, revision)
}
revision <- data.frame(version = character(),
                       revision = character())
for (i in links) {
  revision <- rbind(revision, extract_revision(i))
}

flavors_df <- cbind(flavors = flavors, flavors_df, revision)
if (!interactive() && !local_build) {
  saveRDS(flavors_df, "flavors.RDS")
}

m <- match(tc$Flavor, flavors_df$flavors)
tc_flavors <- cbind(tc, flavors_df[m, ])
flextable(flavors_df) |> 
  autofit()

flavors	r_version	os	architecture	other	version	revision
r-devel-linux-x86_64-debian-clang	devel	linux	x86_64	debian-clang		r89916
r-devel-linux-x86_64-debian-gcc	devel	linux	x86_64	debian-gcc		r89950
r-devel-linux-x86_64-fedora-clang	devel	linux	x86_64	fedora-clang		r89950
r-devel-linux-x86_64-fedora-gcc	devel	linux	x86_64	fedora-gcc		r89943
r-devel-macos-arm64	devel	macos	arm64		4.6.0	r89937
r-patched-linux-x86_64	patched	linux	x86_64		4.6.0	r89932
r-release-linux-x86_64	release	linux	x86_64		4.5.3
r-release-macos-arm64	release	macos	arm64		4.5.2	r89382
r-release-macos-x86_64	release	macos	x86_64		4.5.2	r89382
r-release-windows-x86_64	release	windows	x86_64		4.5.3
r-oldrel-macos-arm64	oldrel	macos	arm64		4.4.3
r-oldrel-macos-x86_64	oldrel	macos	x86_64		4.4.3	r89409
r-oldrel-windows-x86_64	oldrel	windows	x86_64		4.4.3	r89426

It assumes that the same configuration in one package is used for all. Or in other words that the reports of the configuration (svn revision and version) for the A3 package is the same as for all the other packages.

Warning: This assumption is not always true, but this would require to check each log file on each flavor to verify the R and svn id of each package (which could take too much time and resources).

Overview

Briefly an introduction of how much effort goes into checking

library("ggplot2")
theme_set(theme_minimal())
tc |> 
  filter(!is.na(T_install)) |> 
  ggplot() +
  geom_violin(aes(T_install, Flavor)) +
  scale_x_log10() +
  labs(x = "seconds", title = "Time to install", y = element_blank())

Distribution of install time on each machine.

This means that just to install all the packages on the multiple flavors with a single CPU would take 69 days.

tc |> 
  filter(!is.na(T_check)) |> 
  ggplot() +
  geom_violin(aes(T_check, Flavor), trim = FALSE) +
  scale_x_log10() +
  labs(x = "seconds", title = "Time to check", y = element_blank())

Distribution of checking time on each machine.

This means that to check all the packages on the multiple flavors with a single CPU would take 338 days.

tc |> 
  filter(!is.na(T_total)) |> 
  ggplot() +
  geom_violin(aes(T_total, Flavor)) +
  scale_x_log10() +
  labs(x = "seconds", title = "Time to check and install", y = element_blank())

Distribution of total time on each machine.

This means that to install and check all the packages with a single CPU would take 420 days.

I don’t know the computational cost of 266 days of CPU (every day), but a rough calculation of 2.5 cents per hour means 252.07 dollars daily dedicated to this.

tc |> 
  group_by(Package) |> 
  summarize(Versions = n_distinct(Version)) |> 
  ungroup() |> 
  count(Versions, name = "Packages", sort = TRUE) |> 
  flextable() |> 
  autofit()

Versions	Packages
1	22,430
2	1,265
3	49
4	1

This was surprising, but sometimes checks have multiple versions. Probably when a new version is added and the system don’t catch it for a certain machine.

tc |> 
  group_by(Package) |> 
  summarize(Flavors = n_distinct(Flavor)) |> 
  ungroup() |> 
  count(Flavors, name = "Packages", sort = TRUE) |> 
  flextable() |> 
  autofit()

Flavors	Packages
14	23,212
13	312
11	128
10	47
3	17
12	16
2	8
9	4
8	1

Similarly, often packages are only tested on few configurations.

Combining both we can have packages with few configurations that have multiple versions being tested.

tc |> 
  group_by(Package) |> 
  summarize(Versions = as.character(n_distinct(Version)),
            Flavors = n_distinct(Flavor)) |> 
  ungroup() |> 
  count(Flavors, Versions, name = "Packages") |> 
  ggplot() +
  geom_tile(aes(Flavors, Versions, fill = log10(Packages))) +
  scale_x_continuous(expand = expansion())

Most packages are just tested one version.

But focusing on those that have just one version of the package being tested, most of the machines have packages either OK or with some notes.

man_colors <- c("OK" = "green", "NOTE" = "darkgreen", 
                "WARNING" = "yellow", "ERROR" = "red", "FAILURE" = "black")
tc |> 
  group_by(Package) |> 
  filter(n_distinct(Version) == 1) |> 
  ungroup() |> 
  group_by(Flavor) |> 
  count(Status, name = "packages") |> 
  mutate(perc = packages/sum(packages),
         Status = forcats::fct_relevel(Status, names(man_colors))) |> 
  ggplot() + 
  geom_col(aes(perc, Flavor, fill = Status)) +
  scale_x_continuous(expand = expansion(), labels = scales::percent_format()) +
  scale_fill_manual(values = man_colors) +
  labs(title = "Packages check status", x = element_blank())

Most frequent status is OK or NOTE on all machines.

If we look at the most frequent status report for packages we can see this table:

ts <- tc |> 
  group_by(Package) |> 
  filter(n_distinct(Version) == 1) |> 
  count(Status, name = "flavors") |> 
  ungroup() |> 
  tidyr::pivot_wider(values_from = flavors, names_from = Status, 
                     values_fill = 0) |> 
  count(OK, NOTE, WARNING, ERROR, FAILURE, name = "packages", sort = TRUE)
download.file("https://cran.r-project.org/web/packages/packages.rds", 
              destfile = "packages.RDS") # From the help page
ap <- readRDS("packages.RDS") |> 
  as.data.frame() |> 
  distinct(Package, .keep_all = TRUE)
ap_bioc <- available.packages(repos = BiocManager::repositories()[1:5])
ap_bioc <- cbind(ap_bioc, Additional_repositories = NA)
ap_colm <- intersect(colnames(ap), colnames(ap_bioc))
ap <- rbind(ap[, ap_colm], ap_bioc[, ap_colm])
head(ts) |> 
  flextable() |> 
  autofit()

OK	NOTE	WARNING	ERROR	FAILURE	packages
14	0	0	0	0	12,980
12	2	0	0	0	4,282
11	3	0	0	0	1,440
0	14	0	0	0	908
9	5	0	0	0	773
10	4	0	0	0	279

We can see that the most common occurrences are some sort of OK and notes on checks. We can also check the official results on CRAN.

We can see that 0.86%, 0.84%, 0.62%, 0.08%, 0.00% of packages pass all checks without notes.

Now let’s see which of the notes or failures are due to intermittent issues.

Compare

First we need to make sure that we compare the right configurations. They must be the same machine, the same R version and the same svn revision between yesterday and today.

# Compare the previous flavor with today's
m_flavor <- which(flavors_df$flavors %in% old_flavors$flavors)
m_version <- which(flavors_df$version %in% old_flavors$version)
m_revision <- which(flavors_df$revision %in% old_flavors$revision)
tm <- table(c(m_flavor, m_version, m_revision))
compare <- flavors_df$flavors[tm == 3] # Only missing the packages version

All changes

Next, compare the status of the packages if the version of the package is the same.

# Find package on the flavors to compare that haven't changed versions
library("dplyr")
tcc <- filter(tc, Flavor %in% compare) |> 
  select(Flavor, Package, Version, Status) |> 
  arrange(Flavor, Package)
ycc <- filter(yc, Flavor %in% compare) |> 
  select(Flavor, Package, Version, Status) |> 
  arrange(Flavor, Package)

all_checks <- merge(tcc, ycc, by = c("Flavor", "Package"), 
                    suffixes = c(".t", ".y"), all = TRUE) 

possible_packages <- all_checks |> 
  filter(Version.t == Version.y & # Same version
           Status.t != Status.y & # Different status
           !is.na(Status.y) & # No new version or removed package
           !is.na(Status.t)) |> 
  rename(Today = Status.t, Yesterday = Status.y)
possible_packages |> 
  select(Package, Flavor, Today, Yesterday, -Version.t, -Version.y) |> 
  arrange(Package, Flavor) |> 
  flextable() |> 
  autofit()

Package	Flavor	Today	Yesterday
AutoWMM	r-release-windows-x86_64	ERROR	OK
BSL	r-oldrel-windows-x86_64	ERROR	NOTE
BSL	r-release-windows-x86_64	ERROR	NOTE
Cascade	r-oldrel-windows-x86_64	WARNING	OK
Cascade	r-release-windows-x86_64	WARNING	OK
DRviaSPCN	r-oldrel-windows-x86_64	OK	ERROR
DiagrammeR	r-oldrel-windows-x86_64	ERROR	OK
DiagrammeR	r-release-windows-x86_64	ERROR	OK
EloChoice	r-oldrel-windows-x86_64	ERROR	NOTE
EloChoice	r-release-windows-x86_64	ERROR	NOTE
FracFixR	r-oldrel-windows-x86_64	FAILURE	OK
GSEMA	r-oldrel-windows-x86_64	OK	ERROR
ManifoldOptim	r-oldrel-windows-x86_64	ERROR	OK
ManifoldOptim	r-release-windows-x86_64	ERROR	OK
PathwayVote	r-release-windows-x86_64	OK	ERROR
PerformanceAnalytics	r-release-windows-x86_64	OK	FAILURE
SDPDmod	r-release-windows-x86_64	OK	ERROR
SPACO	r-oldrel-windows-x86_64	OK	ERROR
SubtypeDrug	r-oldrel-windows-x86_64	ERROR	OK
SubtypeDrug	r-release-windows-x86_64	ERROR	OK
Sysrecon	r-oldrel-windows-x86_64	OK	ERROR
TaxaNorm	r-oldrel-windows-x86_64	OK	ERROR
TaxaNorm	r-release-windows-x86_64	OK	ERROR
TrialSimulator	r-oldrel-windows-x86_64	OK	ERROR
autograph	r-release-windows-x86_64	ERROR	OK
biomartr	r-oldrel-windows-x86_64	OK	ERROR
bmstdr	r-release-windows-x86_64	OK	ERROR
centerline	r-release-windows-x86_64	OK	ERROR
cli	r-release-windows-x86_64	OK	ERROR
clintrialx	r-oldrel-windows-x86_64	OK	ERROR
commonmark	r-release-windows-x86_64	OK	ERROR
data.table	r-oldrel-windows-x86_64	ERROR	NOTE
data.table	r-release-windows-x86_64	ERROR	NOTE
dci	r-release-windows-x86_64	OK	ERROR
delimtools	r-release-windows-x86_64	OK	ERROR
dplyr	r-oldrel-windows-x86_64	OK	ERROR
fastmit	r-oldrel-windows-x86_64	ERROR	NOTE
fastmit	r-release-windows-x86_64	ERROR	NOTE
fdrDiscreteNull	r-oldrel-windows-x86_64	OK	ERROR
flan	r-oldrel-windows-x86_64	ERROR	OK
flan	r-release-windows-x86_64	ERROR	OK
ggautomap	r-release-windows-x86_64	ERROR	OK
hockeystick	r-release-windows-x86_64	ERROR	OK
icosa	r-release-windows-x86_64	ERROR	OK
jewel	r-oldrel-windows-x86_64	ERROR	OK
jewel	r-release-windows-x86_64	ERROR	OK
jlview	r-release-windows-x86_64	ERROR	FAILURE
jsonlite	r-release-windows-x86_64	OK	ERROR
junco	r-oldrel-windows-x86_64	ERROR	NOTE
junco	r-release-windows-x86_64	ERROR	OK
lakefetch	r-release-windows-x86_64	OK	ERROR
mapsf	r-release-windows-x86_64	OK	ERROR
ml	r-release-windows-x86_64	OK	ERROR
potential	r-release-windows-x86_64	ERROR	OK
qPRAentry	r-release-windows-x86_64	ERROR	OK
rAccess	r-release-windows-x86_64	OK	ERROR
rFIA	r-oldrel-windows-x86_64	WARNING	NOTE
rFIA	r-release-windows-x86_64	WARNING	OK
rGhanaCensus	r-oldrel-windows-x86_64	ERROR	NOTE
rGhanaCensus	r-release-windows-x86_64	ERROR	NOTE
rSpectral	r-oldrel-windows-x86_64	ERROR	OK
rSpectral	r-release-windows-x86_64	ERROR	OK
rlang	r-release-windows-x86_64	NOTE	ERROR
robregcc	r-oldrel-windows-x86_64	ERROR	NOTE
robregcc	r-release-windows-x86_64	ERROR	NOTE
rsat	r-oldrel-windows-x86_64	ERROR	OK
rsat	r-release-windows-x86_64	ERROR	OK
rsi	r-release-windows-x86_64	ERROR	OK
scPOEM	r-release-windows-x86_64	OK	ERROR
sdmTMB	r-release-windows-x86_64	ERROR	OK
seasonal	r-release-windows-x86_64	NOTE	ERROR
sfclust	r-release-windows-x86_64	ERROR	OK
sfdep	r-release-windows-x86_64	OK	ERROR
sfhotspot	r-release-windows-x86_64	OK	ERROR
sfnetworks	r-oldrel-windows-x86_64	ERROR	OK
sfnetworks	r-release-windows-x86_64	ERROR	OK
sftime	r-release-windows-x86_64	OK	ERROR
sims	r-release-windows-x86_64	OK	FAILURE
spMaps	r-release-windows-x86_64	ERROR	OK
spacemodR	r-release-windows-x86_64	OK	ERROR
spatialrisk	r-oldrel-windows-x86_64	ERROR	NOTE
spatialrisk	r-release-windows-x86_64	ERROR	OK
spatsoc	r-release-windows-x86_64	ERROR	OK
stars	r-release-windows-x86_64	NOTE	ERROR
starsExtra	r-release-windows-x86_64	ERROR	OK
tibble	r-oldrel-windows-x86_64	OK	ERROR
tidypmc	r-release-windows-x86_64	ERROR	OK
tidysdm	r-release-windows-x86_64	OK	ERROR
tmap.networks	r-oldrel-windows-x86_64	ERROR	OK
tmap.networks	r-release-windows-x86_64	ERROR	OK
tsbox	r-oldrel-windows-x86_64	OK	ERROR
tsmarch	r-release-windows-x86_64	OK	ERROR
waterquality	r-oldrel-windows-x86_64	ERROR	OK
waterquality	r-release-windows-x86_64	ERROR	OK
waver	r-release-windows-x86_64	OK	ERROR
whSample	r-oldrel-windows-x86_64	WARNING	OK
whSample	r-release-windows-x86_64	WARNING	OK
xfun	r-release-windows-x86_64	OK	ERROR

If the machine and R versions is the same but the check of the package is different there might be some discrepancy between the dependencies.

# Extract dependencies
dependencies <- package_dependencies(unique(possible_packages$Package),
                                     # Should it check all the recursive dependencies or only direct?
                                     db = ap, # Only considering those dependencies on CRAN and Bioconductor but not any Additional_repositories. 
                                     recursive = TRUE, 
                                     which = c("Depends", "Imports", "LinkingTo", "Suggests"))

# Prepare to compare versions (as they are sorted by everything else we can compare directly)
intermittent_failures <- rep(FALSE, length(dependencies))
names(intermittent_failures) <- names(dependencies)
dep_0 <- lengths(dependencies) == 0
intermittent_failures[dep_0] <- TRUE

If they do not have any recursive dependency on Depends, Imports, LinkingTo and Suggests they might be have some intermittent problems on the packages. These is only on dependencies on CRAN and Bioconductor but not in other additional repositories (There are 196 packages with additional repositories).

If they have some dependencies and those dependencies didn’t change as far as we can tell then there might be some problems with random numbers or connectivity.

for (pkg in names(intermittent_failures[!intermittent_failures])) {
  dep <- dependencies[[pkg]]
  fl <- possible_packages$Flavor[possible_packages$Package == pkg]
  intermittent_failures[pkg] <- all_checks |> 
    filter(Package %in% dep,
           Flavor %in% fl,
           Version.t == Version.y,
           Status.t != Status.y) |> 
    nrow() == 0 # If packages outside || any(!dep %in% rownames(ap)) 
}
packages <- names(intermittent_failures)[intermittent_failures]

We finally show the differences on the status of those without any dependency change on version or status¹:

keep_files <- filter(possible_packages, Package %in% packages) |> 
  merge(y = flavors_df, by.x = "Flavor", by.y = "flavors", all.x = TRUE, all.y = FALSE) |> 
  select(Package, Flavor, Version = Version.t, R_version = r_version, OS = os, 
         architecture, other, version, revision) |> 
  mutate(Date = Sys.time())

if (nrow(keep_files >= 1)) {
  write.csv(keep_files, 
            paste0("cran-failing-", format(Sys.time(), "%Y%m%dT%H%M"), ".csv"),
            row.names = FALSE,
            quote = FALSE,
  )
}

filter(possible_packages, Package %in% packages) |> 
  select(Package, Flavor, Today, Yesterday, -Version.t, -Version.y) |> 
  flextable() |> 
  autofit()

Conclusion

cat("There are no packages detected with differences between yesterday and today attributable to intermittent failures.\n")

There are no packages detected with differences between yesterday and today attributable to intermittent failures.

knitr::knit_exit()

---

1. I think a new version might not propagate to check other packages until 24 hours later as checks might have already started for that day.↩︎