Export workflows
systemPipeR workflow management system allows one to translate workflow into
reproducible code and export the
workflow build interactively to R Markdown template format or an executable bash script.
This feature advances the reusability of the workflow, as well as the flexibility
for workflow execution.
suppressPackageStartupMessages({
library(systemPipeR)
})
We still use the simple workflow to demonstrate.
sal <- SPRproject()
## Creating directory: /home/lab/Desktop/spr/systemPipeR.github.io/content/en/sp/spr/sp_run/data
## Creating directory: /home/lab/Desktop/spr/systemPipeR.github.io/content/en/sp/spr/sp_run/param
## Creating directory: /home/lab/Desktop/spr/systemPipeR.github.io/content/en/sp/spr/sp_run/results
## Creating directory '/home/lab/Desktop/spr/systemPipeR.github.io/content/en/sp/spr/sp_run/.SPRproject'
## Creating file '/home/lab/Desktop/spr/systemPipeR.github.io/content/en/sp/spr/sp_run/.SPRproject/SYSargsList.yml'
sal <- importWF(sal, file_path = system.file("extdata", "spr_simple_wf.Rmd", package = "systemPipeR"), verbose = FALSE)
sal
## Instance of 'SYSargsList':
## WF Steps:
## 1. load_library --> Status: Pending
## 2. export_iris --> Status: Pending
## 3. gzip --> Status: Pending
## Total Files: 3 | Existing: 0 | Missing: 3
## 3.1. gzip
## cmdlist: 3 | Pending: 3
## 4. gunzip --> Status: Pending
## Total Files: 3 | Existing: 0 | Missing: 3
## 4.1. gunzip
## cmdlist: 3 | Pending: 3
## 5. stats --> Status: Pending
##
R Markdown file
sal2rmd function takes an SYSargsList workflow container and translates it to
SPR workflow template R markdown format. This file can be imported with the
importWF function. This is very similar to the
text-enriched report, but with all text removed.
sal2rmd(sal)
## sal2rmd starts, pre-checks...
## Open spr_template.Rmd to write
## Write Rmd header and description
## Now writing step 1 load_library
## Now writing step 2 export_iris
## Now writing step 3 gzip
## Now writing step 4 gunzip
## Now writing step 5 stats
## Success! File created at spr_template.Rmd
Bash script
sal2bash function takes an SYSargsList workflow container and translates
it to an executable bash script, The benefit of this is that if the workflow is
only composed with command-line steps, no R step (LineWise) step in involved, then
one could generate the workflow on one computer and run in another computer without
installing SPR or R at all.
sal2bash(sal)
## Success: Make sure the script 'spr_wf.sh' and directory ./spr_bash is there before executing.
It will be generated on the project root an executable bash script, called by
default the spr_wf.sh. Also, a directory ./spr_wf will be created and store
all the R scripts based on the workflow steps. Please note that this function will
“collapse” adjacent R steps into one file as much as possible.
fs::dir_tree("spr_bash")
## spr_bash
## ├── rscript_step1_2.R
## ├── rscript_step5.R
## └── spr_wf.RData
Session
sessionInfo()
## R version 4.2.1 (2022-06-23)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 20.04.5 LTS
##
## Matrix products: default
## BLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.9.0
## LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.9.0
##
## locale:
## [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
## [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
## [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
##
## attached base packages:
## [1] stats4 stats graphics grDevices utils datasets methods
## [8] base
##
## other attached packages:
## [1] systemPipeR_2.3.5 ShortRead_1.54.0
## [3] GenomicAlignments_1.32.1 SummarizedExperiment_1.26.1
## [5] Biobase_2.56.0 MatrixGenerics_1.8.1
## [7] matrixStats_0.62.0 BiocParallel_1.30.4
## [9] Rsamtools_2.12.0 Biostrings_2.64.1
## [11] XVector_0.36.0 GenomicRanges_1.48.0
## [13] GenomeInfoDb_1.32.4 IRanges_2.30.1
## [15] S4Vectors_0.34.0 BiocGenerics_0.42.0
##
## loaded via a namespace (and not attached):
## [1] sass_0.4.2 jsonlite_1.8.3 bslib_0.4.0
## [4] assertthat_0.2.1 latticeExtra_0.6-30 GenomeInfoDbData_1.2.8
## [7] yaml_2.3.6 pillar_1.8.1 lattice_0.20-45
## [10] glue_1.6.2 digest_0.6.30 RColorBrewer_1.1-3
## [13] colorspace_2.0-3 htmltools_0.5.3 Matrix_1.5-1
## [16] pkgconfig_2.0.3 bookdown_0.29 zlibbioc_1.42.0
## [19] scales_1.2.1 jpeg_0.1-9 tibble_3.1.8
## [22] generics_0.1.3 ggplot2_3.3.6 cachem_1.0.6
## [25] cli_3.4.1 magrittr_2.0.3 crayon_1.5.2
## [28] deldir_1.0-6 evaluate_0.17 fs_1.5.2
## [31] fansi_1.0.3 hwriter_1.3.2.1 blogdown_1.13
## [34] tools_4.2.1 lifecycle_1.0.3 stringr_1.4.1
## [37] interp_1.1-3 munsell_0.5.0 DelayedArray_0.22.0
## [40] compiler_4.2.1 jquerylib_0.1.4 rlang_1.0.6
## [43] grid_4.2.1 RCurl_1.98-1.9 rstudioapi_0.14
## [46] htmlwidgets_1.5.4 bitops_1.0-7 rmarkdown_2.17
## [49] gtable_0.3.1 codetools_0.2-18 DBI_1.1.3
## [52] R6_2.5.1 knitr_1.40 dplyr_1.0.10
## [55] fastmap_1.1.0 utf8_1.2.2 stringi_1.7.8
## [58] parallel_4.2.1 Rcpp_1.0.9 vctrs_0.4.2
## [61] png_0.1-7 tidyselect_1.2.0 xfun_0.34