SPARQLChunks : query SPARQL endpoints and run SPARQL chunks in R-markdown files. #656

aourednik · 2024-09-10T15:27:30Z

Submitting Author Name: André Ourendik
Submitting Author Github Handle: @aourednik
Repository: https://github.com/aourednik/SPARQLchunks
Version submitted:0.2.1
Submission type: Standard
Editor: TBD
Reviewers: TBD

Archive: TBD
Version accepted: TBD
Language: en

Paste the full DESCRIPTION file inside a code block below:

Package: SPARQLchunks
Title: Run SPARQL Chunks and Inline Functions to Retrieve Data
Version: 0.3.0
Authors@R: 
    person("Andre", "Ourednik", , "andre.ourednik@epfl.ch", role = c("aut", "cre"),
           comment = c(ORCID = "0000-0002-0309-8715"))
Description: Allows to run SPARQL chunks in R-markdown files. Also provides inline functions to send a SPARQL query to an endpoint and retrieve data in data frame or list form. 
License: GPL (>= 3)
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.2.3
Imports: 
    curl,
    httr,
    knitr,
    magrittr,
    xml2
VignetteBuilder: knitr
Suggests: 
    rmarkdown
URL: https://github.com/aourednik/SPARQLchunks
BugReports: https://github.com/aourednik/SPARQLchunks/issues

Scope

Please indicate which category or categories from our package fit policies this package falls under: (Please check an appropriate box below. If you are unsure, we suggest you make a pre-submission inquiry.):
- data retrieval
- data extraction
- data munging
- data deposition
- data validation and testing
- workflow automation
- version control
- citation management and bibliometrics
- scientific software wrappers
- field and lab reproducibility tools
- database software bindings
- geospatial data
- text analysis
Explain how and why the package falls under these categories (briefly, 1-2 sentences):

SPARQL is a major language for accessing, extracting and munging RDF data. While RStudio provides a number of convenient ways to access to write SQL code chunks in Rmarkdown, to run these chunks and to assign the value of the query result directly to a variable of your choice. No such thing is available out of the box for SPARQL queries. This is where the SPARQLchunks package steps in. It allows you to query SPARQL endpoints in two different ways: (1) run SPARQL chunks in Rmarkdown files.
(2) run inline functions to send SPARQL queries to a user-defined endpoint and retrieve data in dataframe form (sparql2df) or list form (sparql2list). Endpoints can also be reached from behind corporate firewalls on Windows machines thanks to automatic proxy detection.

Who is the target audience and what are scientific applications of this package?

All scientists working with RDF data repositories

Are there other R packages that accomplish the same thing? If so, how does yours differ or meet our criteria for best-in-category?

Not really, there used to be a "SPARQL" package, but it is deprecated. There is also the more genereic rdflib. No package except SPARQLChunks allows to write chunks of SPARQL in RMarkdown and retrieve the data directly into a data.frame or list object.

If you made a pre-submission inquiry, please paste the link to the corresponding issue, forum post, or other discussion, or @tag the editor you contacted.
Explain reasons for any pkgcheck items which your package is unable to pass.

The package does not pass the automatic CRAN checks, as storing the result of a chunk requires assigning to the global
environment to store the query result in the output.var. Example:

Technical checks

Confirm each of the following by checking the box.

I have read the rOpenSci packaging guide.
I have read the author guide and I expect to maintain this package for at least 2 years or to find a replacement.

This package:

does not violate the Terms of Service of any service it interacts with.
has a CRAN and OSI accepted license.
contains a README with instructions for installing the development version.
includes documentation with examples for all functions, created with roxygen2.
contains a vignette with examples of its essential functions and uses.
has a test suite.
has continuous integration, including reporting of test coverage.

Publication options

Do you intend for this package to go on CRAN?
Do you intend for this package to go on Bioconductor?
Do you wish to submit an Applications Article about your package to Methods in Ecology and Evolution? If so:

Code of conduct

I agree to abide by rOpenSci's Code of Conduct during the review process and in maintaining my package should it be accepted.

The text was updated successfully, but these errors were encountered:

ropensci-review-bot · 2024-09-10T15:27:32Z

Thanks for submitting to rOpenSci, our editors and @ropensci-review-bot will reply soon. Type @ropensci-review-bot help for help.

ropensci-review-bot · 2024-09-10T15:27:35Z

🚀

Editor check started

👋

ropensci-review-bot · 2024-09-10T15:35:48Z

Checks for SPARQLchunks (v0.2.1)

git hash: bcc65993

✔️ Package name is available
✖️ does not have a 'codemeta.json' file.
✖️ does not have a 'contributing' file.
✖️ The following functions have no documented return values: [autoproxyconfig, get_outcontent, sparql2df, sparql2list]
✔️ uses 'roxygen2'.
✔️ 'DESCRIPTION' has a URL field.
✔️ 'DESCRIPTION' has a BugReports field.
✔️ Package has at least one HTML vignette
✖️ These functions do not have examples: [autoproxyconfig, get_outcontent].
✖️ Package has no continuous integration checks.
✖️ Package coverage is 0.8% (should be at least 75%).
✔️ R CMD check found no errors.
✔️ R CMD check found no warnings.

Important: All failing checks above must be addressed prior to proceeding

Package License: GPL (>= 3)

1. Package Dependencies

Details of Package Dependency Usage (click to open)

The table below tallies all function calls to all packages ('ncalls'), both internal (r-base + recommended, along with the package itself), and external (imported and suggested packages). 'NA' values indicate packages to which no identified calls to R functions could be found. Note that these results are generated by an automated code-tagging system which may not be entirely accurate.

type	package	ncalls
internal	base	33
internal	SPARQLchunks	10
internal	utils	2
internal	stats	1
imports	httr	7
imports	xml2	2
imports	magrittr	1
imports	curl	NA
imports	knitr	NA
suggests	rmarkdown	NA
linking_to	NA	NA

Click below for tallies of functions used in each package. Locations of each call within this package may be generated locally by running 's <- pkgstats::pkgstats(<path/to/repo>)', and examining the 'external_calls' table.

base

paste (5), tempfile (5), c (3), url (3), file.path (2), gsub (2), list (2), readLines (2), tempdir (2), tryCatch (2), ifelse (1), is.null (1), length (1), return (1), textConnection (1)

SPARQLchunks

autoproxyconfig (3), get_outcontent (3), sparql2list (2), eng_sparql (1), sparql2df (1)

httr

use_proxy (3), add_headers (2), content (1), GET (1)

utils

download.file (1), read.csv (1)

xml2

as_list (1), read_xml (1)

magrittr

%>% (1)

stats

df (1)

NOTE: Some imported packages appear to have no associated function calls; please ensure with author that these 'Imports' are listed appropriately.

2. Statistical Properties

This package features some noteworthy statistical properties which may need to be clarified by a handling editor prior to progressing.

Details of statistical properties (click to open)

The package has:

code in R (100% in 2 files) and
1 authors
1 vignette
no internal data file
5 imported packages
5 exported functions (median 18 lines of code)
7 non-exported functions in R (median 18 lines of code)

Statistical properties of package structure as distributional percentiles in relation to all current CRAN packages
The following terminology is used:

loc = "Lines of Code"
fn = "function"
exp/not_exp = exported / not exported

All parameters are explained as tooltips in the locally-rendered HTML version of this report generated by the checks_to_markdown() function

The final measure (fn_call_network_size) is the total number of calls between functions (in R), or more abstract relationships between code objects in other languages. Values are flagged as "noteworthy" when they lie in the upper or lower 5th percentile.

measure	value	percentile	noteworthy
files_R	2	11.1
files_vignettes	1	62.0
files_tests	0	0.0	TRUE
loc_R	155	17.9
loc_vignettes	102	24.4
num_vignettes	1	59.0
n_fns_r	12	17.0
n_fns_r_exported	5	25.4
n_fns_r_not_exported	7	16.5
n_fns_per_file_r	6	75.5
num_params_per_fn	4	51.1
loc_per_fn_r	18	55.2
loc_per_fn_r_exp	18	42.6
loc_per_fn_r_not_exp	18	58.6
rel_whitespace_R	4	6.3
rel_whitespace_vignettes	36	26.4
doclines_per_fn_exp	22	18.0
doclines_per_fn_not_exp	0	0.0	TRUE
fn_call_network_size	6	24.5

2a. Network visualisation

Click to see the interactive network visualisation of calls between objects in package

3. `goodpractice` and other checks

Details of goodpractice checks (click to open)

3b. `goodpractice` results

`R CMD check` with rcmdcheck

rcmdcheck found no errors, warnings, or notes

Test coverage with covr

Package coverage: 0.8

The following files are not completely covered by tests:

file	coverage
R/sparqlchunks.R	0.8%

Cyclocomplexity with cyclocomp

No functions have cyclocomplexity >= 15

Static code analyses with lintr

lintr found no issues with this package!

Package Versions

package	version
pkgstats	0.1.6.17
pkgcheck	0.1.2.58

Editor-in-Chief Instructions:

Processing may not proceed until the items marked with ✖️ have been resolved.

adamhsparks · 2024-10-15T02:19:52Z

Hi @aourednik, have you made any progress addressing the issues that the bot flagged?

Please let me know how I can assist you in correcting any of these issues.

adamhsparks · 2024-10-31T01:23:50Z

@ropensci-review-bot check package

ropensci-review-bot · 2024-10-31T01:23:51Z

Thanks, about to send the query.

ropensci-review-bot · 2024-10-31T01:23:54Z

🚀

Editor check started

👋

ropensci-review-bot · 2024-10-31T02:35:26Z

Checks for SPARQLchunks (v0.2.1)

git hash: e89ea3ff

✔️ Package name is available
✖️ does not have a 'codemeta.json' file.
✖️ does not have a 'contributing' file.
✖️ The following functions have no documented return values: [autoproxyconfig, get_outcontent, sparql2df, sparql2list]
✔️ uses 'roxygen2'.
✔️ 'DESCRIPTION' has a URL field.
✔️ 'DESCRIPTION' has a BugReports field.
✔️ Package has at least one HTML vignette
✖️ These functions do not have examples: [autoproxyconfig, get_outcontent].
✖️ Package has no continuous integration checks.
✖️ Package coverage is 0.8% (should be at least 75%).
✔️ R CMD check found no errors.
✖️ R CMD check found 1 warning.

Important: All failing checks above must be addressed prior to proceeding

Package License: GPL (>= 3)

1. Package Dependencies

Details of Package Dependency Usage (click to open)

The table below tallies all function calls to all packages ('ncalls'), both internal (r-base + recommended, along with the package itself), and external (imported and suggested packages). 'NA' values indicate packages to which no identified calls to R functions could be found. Note that these results are generated by an automated code-tagging system which may not be entirely accurate.

type	package	ncalls
internal	base	33
internal	SPARQLchunks	10
internal	utils	2
internal	stats	1
imports	httr	7
imports	xml2	2
imports	magrittr	1
imports	curl	NA
imports	knitr	NA
suggests	rmarkdown	NA
linking_to	NA	NA

Click below for tallies of functions used in each package. Locations of each call within this package may be generated locally by running 's <- pkgstats::pkgstats(<path/to/repo>)', and examining the 'external_calls' table.

base

paste (5), tempfile (5), c (3), url (3), file.path (2), gsub (2), list (2), readLines (2), tempdir (2), tryCatch (2), ifelse (1), is.null (1), length (1), return (1), textConnection (1)

SPARQLchunks

autoproxyconfig (3), get_outcontent (3), sparql2list (2), eng_sparql (1), sparql2df (1)

httr

use_proxy (3), add_headers (2), content (1), GET (1)

utils

download.file (1), read.csv (1)

xml2

as_list (1), read_xml (1)

magrittr

%>% (1)

stats

df (1)

NOTE: Some imported packages appear to have no associated function calls; please ensure with author that these 'Imports' are listed appropriately.

2. Statistical Properties

This package features some noteworthy statistical properties which may need to be clarified by a handling editor prior to progressing.

Details of statistical properties (click to open)

The package has:

code in R (100% in 2 files) and
1 authors
1 vignette
no internal data file
5 imported packages
5 exported functions (median 18 lines of code)
7 non-exported functions in R (median 18 lines of code)

Statistical properties of package structure as distributional percentiles in relation to all current CRAN packages
The following terminology is used:

loc = "Lines of Code"
fn = "function"
exp/not_exp = exported / not exported

All parameters are explained as tooltips in the locally-rendered HTML version of this report generated by the checks_to_markdown() function

The final measure (fn_call_network_size) is the total number of calls between functions (in R), or more abstract relationships between code objects in other languages. Values are flagged as "noteworthy" when they lie in the upper or lower 5th percentile.

measure	value	percentile	noteworthy
files_R	2	11.1
files_vignettes	1	61.9
files_tests	0	0.0	TRUE
loc_R	155	17.9
loc_vignettes	102	24.4
num_vignettes	1	58.8
n_fns_r	12	17.0
n_fns_r_exported	5	25.3
n_fns_r_not_exported	7	16.4
n_fns_per_file_r	6	75.7
num_params_per_fn	4	51.2
loc_per_fn_r	18	55.1
loc_per_fn_r_exp	18	42.5
loc_per_fn_r_not_exp	18	58.5
rel_whitespace_R	4	6.2
rel_whitespace_vignettes	36	26.2
doclines_per_fn_exp	22	18.0
doclines_per_fn_not_exp	0	0.0	TRUE
fn_call_network_size	6	24.5

2a. Network visualisation

Click to see the interactive network visualisation of calls between objects in package

3. `goodpractice` and other checks

Details of goodpractice checks (click to open)

3b. `goodpractice` results

`R CMD check` with rcmdcheck

R CMD check generated the following warning:

checking package subdirectories ... WARNING
Invalid citation information in ‘inst/CITATION’:
Error in (function (bibtype, textVersion, header = NULL, footer = NULL, key = NULL, ..., other = list()) { bibtype <- as.character(bibtype) stopifnot(length(bibtype) == 1L) pos <- match(tolower(bibtype), tolower(BibTeX_names)) if (is.na(pos)) stop(gettextf("%s has to be one of %s", sQuote("bibtype"), paste(BibTeX_names, collapse = ", ")), domain = NA) bibtype <- BibTeX_names[pos] rval <- c(list(...), other) rval <- rval[!vapply(rval, .is_not_nonempty_text, NA)] fields <- tolower(names(rval)) names(rval) <- fields attr(rval, "bibtype") <- bibtype .bibentry_check_bibentry1(rval) pos <- fields %in% c("author", "editor") if (any(pos)) { for (i in which(pos)) rval[[i]] <- as.person(rval[[i]]) } if (any(!pos)) { for (i in which(!pos)) { s <- trimws(as.character(rval[[i]])) rval[[i]] <- paste(s[!is.na(s) & nzchar(s)], collapse = " ") } } attr(rval, "key") <- if (is.null(key)) NULL else as.character(key) if (!is.null(textVersion)) attr(rval, "textVersion") <- as.character(textVersion) if (!.is_not_nonempty_text(header)) attr(rval, "header") <- paste(header, collapse = "\n") if (!.is_not_nonempty_text(footer)) attr(rval, "footer") <- paste(footer, collapse = "\n") return(rval)})(bibtype = "Software", textVersion = NULL, header = NULL, footer = NULL, key = NULL, title = "SPARQLChunks", author = "André Ourednik", url = "https://github.com/aourednik/SPARQLchunks", year = "2024", other = list()): ‘bibtype’ has to be one of Article, Book, Booklet, InBook, InCollection, InProceedings, Manual, MastersThesis, Misc, PhdThesis, Proceedings, TechReport, Unpublished

Test coverage with covr

Package coverage: 0.8

The following files are not completely covered by tests:

file	coverage
R/sparqlchunks.R	0.8%

Cyclocomplexity with cyclocomp

No functions have cyclocomplexity >= 15

Static code analyses with lintr

lintr found no issues with this package!

Package Versions

package	version
pkgstats	0.2.0.46
pkgcheck	0.1.2.63

Editor-in-Chief Instructions:

Processing may not proceed until the items marked with ✖️ have been resolved.

emilyriederer · 2024-11-10T23:54:07Z

Hey @aourednik - I'm replacing @adamhsparks as Editor in Chief this quarter. Wanted to check in with you: are you still interested in resolving the issues flagged by the bot and moving forward with the review?

adamhsparks self-assigned this Sep 10, 2024

adamhsparks added the 0/editorial-team-prep label Sep 10, 2024

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SPARQLChunks : query SPARQL endpoints and run SPARQL chunks in R-markdown files. #656

SPARQLChunks : query SPARQL endpoints and run SPARQL chunks in R-markdown files. #656

aourednik commented Sep 10, 2024

ropensci-review-bot commented Sep 10, 2024

ropensci-review-bot commented Sep 10, 2024

ropensci-review-bot commented Sep 10, 2024

3b. `goodpractice` results

`R CMD check` with rcmdcheck

Test coverage with covr

Cyclocomplexity with cyclocomp

Static code analyses with lintr

adamhsparks commented Oct 15, 2024

adamhsparks commented Oct 31, 2024

ropensci-review-bot commented Oct 31, 2024

ropensci-review-bot commented Oct 31, 2024

ropensci-review-bot commented Oct 31, 2024

3b. `goodpractice` results

`R CMD check` with rcmdcheck

Test coverage with covr

Cyclocomplexity with cyclocomp

Static code analyses with lintr

emilyriederer commented Nov 10, 2024

SPARQLChunks : query SPARQL endpoints and run SPARQL chunks in R-markdown files. #656

SPARQLChunks : query SPARQL endpoints and run SPARQL chunks in R-markdown files. #656

Comments

aourednik commented Sep 10, 2024

Scope

Technical checks

Publication options

Code of conduct

ropensci-review-bot commented Sep 10, 2024

ropensci-review-bot commented Sep 10, 2024

ropensci-review-bot commented Sep 10, 2024

Checks for SPARQLchunks (v0.2.1)

1. Package Dependencies

2. Statistical Properties

2a. Network visualisation

3. goodpractice and other checks

3b. goodpractice results

R CMD check with rcmdcheck

Test coverage with covr

Cyclocomplexity with cyclocomp

Static code analyses with lintr

Editor-in-Chief Instructions:

adamhsparks commented Oct 15, 2024

adamhsparks commented Oct 31, 2024

ropensci-review-bot commented Oct 31, 2024

ropensci-review-bot commented Oct 31, 2024

ropensci-review-bot commented Oct 31, 2024

Checks for SPARQLchunks (v0.2.1)

1. Package Dependencies

2. Statistical Properties

2a. Network visualisation

3. goodpractice and other checks

3b. goodpractice results

R CMD check with rcmdcheck

Test coverage with covr

Cyclocomplexity with cyclocomp

Static code analyses with lintr

Editor-in-Chief Instructions:

emilyriederer commented Nov 10, 2024

3. `goodpractice` and other checks

3b. `goodpractice` results

`R CMD check` with rcmdcheck

3. `goodpractice` and other checks

3b. `goodpractice` results

`R CMD check` with rcmdcheck