updateObject
is an R package that provides a set of tools built around the
updateObject() generic function to make it easy to work
with old serialized S4 instances.
The package is primarily useful to package maintainers who want to update the serialized S4 instances included in their package.
Out-of-sync objects (a.k.a. outdated or old objects) are R objects that got serialized at some point and became out-of-sync later on when the authors/maintainers of an S4 class made some changes to the internals of the class.
A typical example of this situation is when some slots of an S4 class
A get added, removed, or renamed. When this happens, any
object of class A (a.k.a. A instance)
that got serialized before this change (i.e. written to disk with
saveRDS(), save(), or
serialize()) becomes out-of-sync with the new class
definition.
Note that this is also the case of any A
derivative (i.e. any object that belongs to a class that
extends A), as well as any object that contains an
A instance or derivative. For example, if B
extends A, then any serialized list of A or
B objects is now an old object, and any S4 object
of class C that has A or B
objects in some of its slots now is also an old object.
An important thing to keep in mind is that, in fact, the exact parts
of a serialized object x that are out-of-sync with their
class definition can be deeply nested inside x.
updateObject() is the core function used in Bioconductor
for updating old R objects. The function is an S4 generic currently
defined in the BiocGenerics
package and with dozens of methods defined across many Bioconductor
packages. For example, the S4Vectors
package defines updateObject() methods for Vector,
SimpleList, DataFrame, and Hits objects, the SummarizedExperiment
package defines methods for SummarizedExperiment,
RangedSummarizedExperiment, and Assays objects, the MultiAssayExperiment
package defines a method for MultiAssayExperiment objects, the QFeatures
package a method for QFeatures objects, etc…
See ?BiocGenerics::updateObject in the BiocGenerics
package for more information.
Serialized objects are typically (but not exclusively) found in R packages. To update all the serialized objects contained in a given package, one usually needs to perform the following steps:
Identify all the files in the package that contain serialized R
objects. Serialized R objects are normally written to RDS or RDA files.
These files typically use file extensions .rds (for RDS
files), and .rda or .RData (for RDA
files).
Load each serialized object into R. This is usually done by
calling readRDS() on each RDS file, and load()
on each RDA file. Note that unlike RDS files which can only contain a
single object per file, RDA files can contain an arbitrary number of
objects per file.
Pass each object thru updateObject():
x <- updateObject(x)Note that if x doesn’t contain any out-of-sync parts
then updateObject() will act as a no-op, that is, it will
return an object that is strictly identical to the original
object.
Write each object back to its original file. This is done with
saveRDS() or save(), depending on whether the
object came from an RDS or RDA file. Note that this only needs to be
done for objects that actually contained out-of-sync parts
i.e. for objects on which updateObject() did not
act as a no-op.
In addition to the above steps, the package maintainer also needs to perform the usual steps required for updating a package and publishing its new version. In the case of a Bioconductor package, these steps are:
Bump the package version.
Set its Date field (if present) to the current
date.
Commit the changes.
Push the changes to git.bioconductor.org.
Performing all the above steps manually can be tedious and error prone, especially if the package contains many serialized objects, or if the entire procedure needs to be performed on a big collection of packages. The updateObject package provides a set of tools that intend to make this much easier.
updateBiocPackageRepoObjects() is the central function
in the updateObject
package. It takes care of updating the serialized objects contained in a
given Bioconductor package by performing all the steps described in the
previous section.
Let’s load updateObject:
and try updateBiocPackageRepoObjects() on the
RELEASE_3_14 branch of the BiSeq
package:
repopath <- file.path(tempdir(), "BiSeq")
updateBiocPackageRepoObjects(repopath, branch="RELEASE_3_14", use.https=TRUE)## Cloning into '/tmp/RtmpTKIw9I/BiSeq'...## ## RUNNING 'updatePackageObjects("/tmp/RtmpTKIw9I/BiSeq", bump.Version=TRUE)'...## File /tmp/RtmpTKIw9I/BiSeq/data/DMRs.RData: load().. ok [1 object(s)]; updateObject(GRanges, check=FALSE).. object updated; saving file.. OK ==> 1
## File /tmp/RtmpTKIw9I/BiSeq/data/betaResults.RData: load().. ok [1 object(s)]; updateObject(data.frame, check=FALSE).. no-op; nothing to update ==> 0
## File /tmp/RtmpTKIw9I/BiSeq/data/betaResultsNull.RData: load().. ok [1 object(s)]; updateObject(data.frame, check=FALSE).. no-op; nothing to update ==> 0
## File /tmp/RtmpTKIw9I/BiSeq/data/predictedMeth.RData: load().. ok [1 object(s)]; updateObject(BSrel, check=FALSE).. object updated; saving file.. OK ==> 1
## File /tmp/RtmpTKIw9I/BiSeq/data/promoters.RData: load().. ok [1 object(s)]; updateObject(GRanges, check=FALSE).. object updated; saving file.. OK ==> 1
## File /tmp/RtmpTKIw9I/BiSeq/data/rrbs.RData: load().. ok [1 object(s)]; updateObject(BSraw, check=FALSE).. object updated; saving file.. OK ==> 1
## File /tmp/RtmpTKIw9I/BiSeq/data/vario.RData: load().. ok [1 object(s)]; updateObject(list, check=FALSE).. no-op; nothing to update ==> 0## diff --git a/DESCRIPTION b/DESCRIPTION
## index df756f4..e28e396 100644
## --- a/DESCRIPTION
## +++ b/DESCRIPTION
## @@ -1,8 +1,8 @@
## Package: BiSeq
## Type: Package
## Title: Processing and analyzing bisulfite sequencing data
## -Version: 1.34.0
## -Date: 2020-03-27
## +Version: 1.34.1
## +Date: 2024-11-19
## Author: Katja Hebestreit, Hans-Ulrich Klein
## Maintainer: Katja Hebestreit <[email protected]>
## Depends: R (>= 2.15.2), methods, S4Vectors, IRanges (>= 1.17.24),
## diff --git a/data/DMRs.RData b/data/DMRs.RData
## index 4d94fd5..22847c2 100644
## Binary files a/data/DMRs.RData and b/data/DMRs.RData differ
## diff --git a/data/predictedMeth.RData b/data/predictedMeth.RData
## index c3d927e..4e9ffa5 100644
## Binary files a/data/predictedMeth.RData and b/data/predictedMeth.RData differ
## diff --git a/data/promoters.RData b/data/promoters.RData
## index ffb1482..408737d 100644
## Binary files a/data/promoters.RData and b/data/promoters.RData differ
## diff --git a/data/rrbs.RData b/data/rrbs.RData
## index a84972c..8884e3f 100644
## Binary files a/data/rrbs.RData and b/data/rrbs.RData differ
##
## [RELEASE_3_14 834c0eb] Pass serialized S4 instances thru updateObject()
## 5 files changed, 2 insertions(+), 2 deletions(-)##
## UPDATE OBJECTS >> UPDATE DESCRIPTION FILE >> COMMIT SUCCESSFUL.Important notes:
By default updateBiocPackageRepoObjects() does
not try to push the changes to
git.bioconductor.org. Only the authorized maintainers of
the BiSeq
package can do that. If you are using
updateBiocPackageRepoObjects() on a package that you
maintain and you wish to push the changes to
git.bioconductor.org, then do NOT use HTTPS access
(i.e. don’t use use.https=TRUE) and use
push=TRUE.
The RELEASE_3_14 branch of all Bioconductor packages
got frozen in April 2022. The above example is for illustrative purpose
only. A more realistic situation would be to use
updateBiocPackageRepoObjects() on the development version
(i.e. the devel branch) of a package that you maintain, and
to push the changes by calling the function with
push=TRUE:
updateBiocPackageRepoObjects(repopath, push=TRUE)See ?updateBiocPackageRepoObjects for more information
and more examples.
The package provides the following tools:
updateBiocPackageRepoObjects(): See above.
updatePackageObjects(): A simpler version of
updateBiocPackageRepoObjects() that doesn’t know anything
about Git. That is, updatePackageObjects() will do the same
thing as updateBiocPackageRepoObjects() except that it
won’t commit or push the changes. This means that the function can be
used on any local package source tree, whether it’s a Git clone or not,
and whether it’s a Bioconductor package or not.
updateAllBiocPackageRepoObjects() and
updateAllPackageObjects(): Similar to
updateBiocPackageRepoObjects() and
updatePackageObjects() but for processing a set of
Bioconductor package Git repositories (for
updateAllBiocPackageRepoObjects()) and a set of
packages (for updateAllPackageObjects()).
updateSerializedObjects(): The workhorse behind the
above functions.
See individual man pages in the package for more information e.g.
?updatePackageObjects.
## R version 4.4.2 (2024-10-31)
## Platform: x86_64-pc-linux-gnu
## Running under: Ubuntu 24.04.1 LTS
##
## Matrix products: default
## BLAS: /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3
## LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.26.so; LAPACK version 3.12.0
##
## locale:
## [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
## [3] LC_TIME=en_US.UTF-8 LC_COLLATE=C
## [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
## [7] LC_PAPER=en_US.UTF-8 LC_NAME=C
## [9] LC_ADDRESS=C LC_TELEPHONE=C
## [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
##
## time zone: Etc/UTC
## tzcode source: system (glibc)
##
## attached base packages:
## [1] stats4 stats graphics grDevices utils datasets methods
## [8] base
##
## other attached packages:
## [1] SummarizedExperiment_1.37.0 BiSeq_1.47.0
## [3] IRanges_2.41.1 GenomicRanges_1.59.1
## [5] updateObject_1.11.0 S4Vectors_0.45.2
## [7] BiocGenerics_0.53.3 generics_0.1.3
## [9] BiocStyle_2.35.0
##
## loaded via a namespace (and not attached):
## [1] blob_1.2.4 Biostrings_2.75.1 bitops_1.0-9
## [4] fastmap_1.2.0 RCurl_1.98-1.16 GenomicAlignments_1.43.0
## [7] XML_3.99-0.17 digest_0.6.37 globaltest_5.61.0
## [10] lifecycle_1.0.4 survival_3.7-0 KEGGREST_1.47.0
## [13] RSQLite_2.3.8 compiler_4.4.2 rlang_1.1.4
## [16] sass_0.4.9 tools_4.4.2 yaml_2.3.10
## [19] rtracklayer_1.67.0 knitr_1.49 S4Arrays_1.7.1
## [22] bit_4.5.0 curl_6.0.1 DelayedArray_0.33.2
## [25] abind_1.4-8 BiocParallel_1.41.0 sys_3.4.3
## [28] nnet_7.3-19 grid_4.4.2 xtable_1.8-4
## [31] betareg_3.2-1 cli_3.6.3 rmarkdown_2.29
## [34] crayon_1.5.3 httr_1.4.7 rjson_0.2.23
## [37] DBI_1.2.3 cachem_1.1.0 zlibbioc_1.52.0
## [40] modeltools_0.2-23 splines_4.4.2 parallel_4.4.2
## [43] AnnotationDbi_1.69.0 BiocManager_1.30.25 XVector_0.47.0
## [46] restfulr_0.0.15 lokern_1.1-12 matrixStats_1.4.1
## [49] vctrs_0.6.5 Matrix_1.7-1 sandwich_3.1-1
## [52] jsonlite_1.8.9 bit64_4.5.2 Formula_1.2-5
## [55] maketools_1.3.1 jquerylib_0.1.4 annotate_1.85.0
## [58] codetools_0.2-20 GenomeInfoDb_1.43.1 sfsmisc_1.1-20
## [61] BiocIO_1.17.0 UCSC.utils_1.3.0 lmtest_0.9-40
## [64] htmltools_0.5.8.1 GenomeInfoDbData_1.2.13 R6_2.5.1
## [67] evaluate_1.0.1 lattice_0.22-6 Biobase_2.67.0
## [70] png_0.1-8 Rsamtools_2.23.0 memoise_2.0.1
## [73] bslib_0.8.0 flexmix_2.3-19 SparseArray_1.7.2
## [76] xfun_0.49 MatrixGenerics_1.19.0 zoo_1.8-12
## [79] buildtools_1.0.0