data-raw/DATASET.R
In ready4-dev/ready4use: Ingest, Label, Visualise and Share Health Economic Model Datasets
library(ready4)
library(ready4fun)
library(ready4show)
pkg_desc_ls <- ready4fun::make_pkg_desc_ls(pkg_title_1L_chr = "Ingest, Label, Visualise and Share Health Economic Model Datasets" %>% tools::toTitleCase(),
pkg_desc_1L_chr = "ready4use provides a set of tools for managing data for models developed with the ready4 framework.
For detailed documentation about the framework and how to use it visit <https://www.ready4-dev.com/>. For a background to the methodological issues that the framework is attempting to help solve, see Hamilton et al. (2024) <doi:10.1007/s40273-024-01378-8>.
This development version of the ready4use package has been made available as part of the process of testing and documenting the package. If you have any questions, please contact the authors (matthew.hamilton1@monash.edu).",
authors_prsn = c(utils::person(
given = "Matthew",family = "Hamilton", email =
"matthew.hamilton1@monash.edu",role = c("aut",
"cre", "cph"),comment = c(ORCID = "0000-0001-7407-9194")
),
utils::person("Glen", "Wiesner", #email = "Glen.Wiesner@vu.edu.au",
role = c("aut"), comment = c(ORCID = "0000-0002-0071-130X")),
utils::person("Orygen", role = c("cph", "fnd")),
utils::person("Australian Government Research Training Program", role =c("fnd")),
utils::person("VicHealth",role = c("fnd")),
utils::person("Victoria University", role =c("fnd"))
),
urls_chr = c("https://ready4-dev.github.io/ready4use/",
"https://github.com/ready4-dev/ready4use",
"https://www.ready4-dev.com/"))
x <- pkg_desc_ls %>%
ready4fun::make_manifest(addl_pkgs_ls = ready4fun::make_addl_pkgs_ls(#depends_chr = "ready4",
suggests_chr = c("rmarkdown")),
build_ignore_ls = ready4fun::make_build_ignore_ls(file_nms_chr = c("initial_setup.R")),
check_type_1L_chr = "ready4",
custom_dmt_ls = ready4fun::make_custom_dmt_ls(user_manual_fns_chr = c(#"add_dictionary",
"add_from_lup_prototype",
"add_labels_from_dictionary",
"add_latest_match",
# "add_with_join",
"assert_matches_chr",
"assert_single_row_tb",
#"bind_dyads",
"get_journal_palette_fn",
"get_r3_from_dv_csv",
"get_styles",
"make_imputed_distinct_cases",
"make_missing_report",
"update_column_names"#, "write_fls_to_dv_ds"
)),
copyright_holders_chr = "Matthew Hamilton and Orygen",
dev_pkgs_chr = c(#"ready4",
"ready4show"),
lifecycle_stage_1L_chr = "experimental",
path_to_pkg_logo_1L_chr = "../../../../../Documentation/Images/ready4use-logo/default.png",
piggyback_to_1L_chr = "ready4-dev/ready4",
ready4_type_1L_chr = "authoring",
zenodo_badge_1L_chr = "[](https://doi.org/10.5281/zenodo.5644336)")
y <- dplyr::bind_rows(
ready4class::make_pt_ready4class_constructor(make_s3_lgl = TRUE,
name_stub_chr = "distributions",
pt_ls = list(list("list")),
pt_chkr_pfx_ls = list(list("is.")),
pt_ns_ls = list(list("base")),
vals_ls = list(list(distribution_chr = "character(0)",
dstr_param_1_dbl = "numeric(0)",
dstr_param_2_dbl = "numeric(0)",
dstr_param_3_dbl = "numeric(0)",
dstr_param_4_dbl = "numeric(0)",
transformation_chr = "character(0)")),
class_desc_chr = "List object that summarises the parameters of each distribution"),
ready4class::make_pt_ready4class_constructor(make_s3_lgl = TRUE,
name_stub_chr = "dataverses",
pt_ls = list(list("tibble")),
pt_chkr_pfx_ls = list(list("is_")),
pt_ns_ls = list(list("tibble")),
vals_ls = list(list(file_type_chr = "character(0)",
file_name_chr = "character(0)",
data_repo_chr = "character(0)",
data_repo_ui_chr = "character(0)",
data_repo_db_ui_chr = "character(0)",
data_repo_file_ext_chr = "character(0)",
data_repo_save_type_chr = "character(0)")),
class_desc_chr = "Tibble object lookup table of files to be imported from a dataverse."),
ready4class::make_pt_ready4class_constructor(make_s3_lgl = TRUE,
name_stub_chr = "imports",
pt_ls = list(list("tibble")),
pt_chkr_pfx_ls = list(list("is_")),
pt_ns_ls = list(list("tibble")),
vals_ls = list(list(local_file_src_chr = "character(0)",
path_to_make_script_chr = "character(0)",
download_url_chr = "character(0)",
inc_file_main_chr = "character(0)",
inc_fls_to_rename_ls = "list()",
new_nms_for_inc_fls_ls = "list()")),
class_desc_chr = "Tibble object lookup table of sources of raw (un-processed) data to import.",
parent_class_chr = "ready4use_dataverses"),
ready4class::make_pt_ready4class_constructor(make_s3_lgl = TRUE,
name_stub_chr = "mapes",
pt_ls = list(list("tibble")),
pt_chkr_pfx_ls = list(list("is_")),
pt_ns_ls = list(list("tibble")),
vals_ls = list(list(param_name_chr = "character(0)",
sex_age_band_chr = "character(0)",
mape_05_yr_mde_dbl = "numeric(0)",
mape_10_yr_mde_dbl = "numeric(0)",
mape_15_yr_mde_dbl = "numeric(0)",
mape_05_yr_min_dbl = "numeric(0)",
mape_10_yr_min_dbl = "numeric(0)",
mape_15_yr_min_dbl = "numeric(0)",
mape_05_yr_max_dbl = "numeric(0)",
mape_10_yr_max_dbl = "numeric(0)",
mape_15_yr_max_dbl = "numeric(0)",
mape_05_yr_shp_dbl = "numeric(0)",
mape_10_yr_shp_dbl = "numeric(0)",
mape_15_yr_shp_dbl = "numeric(0)")),
class_desc_chr = "Tibble object that stores simulation structural parameters relating to Mean Absolute Prediction Errors."),
ready4class::make_pt_ready4class_constructor(make_s3_lgl = T,
name_stub_chr = "dictionary",
pt_ls = list(list("tibble")),
pt_chkr_pfx_ls = list(list("is_")),
pt_ns_ls = list(list("tibble")),
vals_ls = list(list(var_nm_chr = "character(0)",
var_ctg_chr = "character(0)",
var_desc_chr = "character(0)",
var_type_chr = "character(0)")),
class_desc_chr= "A data dictionary tibble."),
ready4class::make_pt_ready4class_constructor(make_s3_lgl = FALSE,
name_stub_chr = "Files",
slots_ls = list("merge_itms_chr","raw_fls_dir_1L_chr","pkg_1L_chr","overwrite_1L_lgl", "write_1L_lgl") %>% list(), # Cut: "lup_tbs_r4",
pt_ls = list("character","character","character","logical", "logical") %>% list(), # Cut: "ready4class_lookup",
class_desc_chr= "Metadata for dataset(s) to be saved in local directory.",
parent_class_chr = "Ready4Module"), # NA_character_ # Cut: ,include_classes = list("ready4class_lookup")
ready4class::make_pt_ready4class_constructor(make_s3_lgl = FALSE,
name_stub_chr = "Raw",
slots_ls = list("write_type_1L_chr") %>% list(),
pt_ls = list("character") %>% list(),
vals_ls = list(write_type_1L_chr ="raw"),
allowed_vals_ls = list(write_type_1L_chr = "raw"),
class_desc_chr= "Metadata for dataset(s) to be saved in local directory in a raw (unprocessed) format.",
parent_class_chr = "Ready4useFiles"),
ready4class::make_pt_ready4class_constructor(make_s3_lgl = FALSE,
name_stub_chr = "Processed",
slots_ls = list("write_type_1L_chr","processed_fls_dir_1L_chr","imports_chr","path_to_seed_sf_1L_chr","imports_ls") %>% list(),
pt_ls = list("character","character","character","character","list") %>% list(),
vals_ls = list(write_type_1L_chr = "proc"),
allowed_vals_ls = list(write_type_1L_chr = "proc"),
class_desc_chr= "Metadata for dataset(s) to be saved in local directory in a processed (R) format.",
parent_class_chr = "Ready4useFiles"),
ready4class::make_pt_ready4class_constructor(make_s3_lgl = FALSE,
name_stub_chr = "Arguments",
slots_ls = list("crs_nbr_dbl") %>% list(), # Change
pt_ls = list("numeric") %>% list(),
class_desc_chr= "Arguments for a function that constructs a spatial object.",
parent_class_chr = "Ready4useProcessed"),
ready4class::make_pt_ready4class_constructor(make_s3_lgl = FALSE,
name_stub_chr = "Dyad",
slots_ls = list("ds_tb","dictionary_r3") %>% list(), # Change
pt_ls = list("tbl_df","ready4use_dictionary") %>% list(),
class_desc_chr= "A dataset and data dictionary pair.",
parent_class_chr = "Ready4Module"),
ready4class::make_pt_ready4class_constructor(make_s3_lgl = FALSE,
name_stub_chr = "Ingest",
slots_ls = list("objects_ls",#"names_chr",
"descriptions_chr") %>% list(), # Change
pt_ls = list("list",#"character",
"character") %>% list(),
class_desc_chr = "Ingested data and descriptive metadata.",
parent_class_chr = "Ready4Module"),
ready4class::make_pt_ready4class_constructor(make_s3_lgl = FALSE,
name_stub_chr = "Repos",
slots_ls = list("dv_nm_1L_chr","dv_ds_metadata_ls",
"dv_ds_nm_1L_chr","dv_server_1L_chr",
"dv_url_pfx_1L_chr","fl_nms_chr",
"gh_repo_1L_chr","gh_tag_1L_chr"
) %>% list(), # Change
pt_ls = list("character","list",
"character","character","character","character","character","character") %>% list(),
class_desc_chr= "Metadata about online data repositories.",
parent_class_chr = "Ready4Module"),
ready4class::make_pt_ready4class_constructor(make_s3_lgl = FALSE,
name_stub_chr = "Pointer",
slots_ls = list("a_Ready4usePaths","b_Ready4useRepos") %>% list(), # Change
pt_ls = list("Ready4Module","Ready4useRepos") %>% list(),
class_desc_chr = "Metadata on local and remote data storage locations.",
parent_class_chr = "Ready4Module",
inc_clss_ls = list("Ready4useRepos") %>% list()),
ready4class::make_pt_ready4class_constructor(make_s3_lgl = FALSE,
name_stub_chr = "Record",
slots_ls = list("a_Ready4usePointer","b_Ready4useIngest") %>% list(), # Change
pt_ls = list("Ready4usePointer","Ready4useIngest") %>% list(),
class_desc_chr= "Ingested data, descriptive metadata and provenance details.",
parent_class_chr = "Ready4Module",
inc_clss_ls = list("Ready4usePointer","Ready4useIngest") %>% list())
) %>%
ready4class::ready4class_constructor()
z <- ready4pack::make_pt_ready4pack_manifest(x,
constructor_r3 = y) %>%
ready4pack::ready4pack_manifest()
z <- author(z)
# ready4::write_extra_pkgs_to_actions(path_to_dir_1L_chr = ".github/workflows")
write_to_edit_workflow("pkgdown.yaml", consent_1L_chr = "Y") # In other packages, run for "test-coverage.yaml" as well.
# readme_chr <- readLines("README.md")
# readme_chr[-which(readme_chr %>% purrr::map_lgl(~startsWith(.x, "[![test-coverage]")))] %>%
# writeLines(con = "README.md")
write_to_tidy_pkg(manifest_ls, build_vignettes_1L_lgl = FALSE,
clean_license_1L_lgl = TRUE, consent_1L_chr = "Y",
examples_chr = character(0), project_1L_chr = "Framework", suggest_chr = "pkgload")
readLines("README.md") %>%
#gsub(pattern = "doi:10.48550/arXiv.([^&]+)", replacement = "https://arxiv.org/abs/\\1") %>%
gsub(pattern = "doi:([^&]+)", replacement = "https://doi.org/\\1") %>%
writeLines(con = "README.md")
paste0(".github/workflows/", c("pkgdown.yaml", "R-CMD-check.yaml")) %>%
purrr::walk(~{
path_1L_chr <- .x
matches_int <- which(readLines(path_1L_chr) %>% startsWith(" # Addresses issue with incompatibility between libcurl4-gnutls-dev and libcurl4-openssl-dev") | readLines(path_1L_chr) %>% startsWith(" # Addresses issue with incompatibility between libcurl4-gnutls-dev and libcurl4-openssl-dev"))
if(!identical(matches_int,integer(0))){
readLines(path_1L_chr)[- (matches_int%>%
purrr::map(~.x:(.x+6)) %>% purrr::flatten_int())] %>%
writeLines(path_1L_chr)
}
})
ready4-dev/ready4use documentation built on June 1, 2025, 2:06 p.m.
R Package Documentation
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
library(ready4)
library(ready4fun)
library(ready4show)
pkg_desc_ls <- ready4fun::make_pkg_desc_ls(pkg_title_1L_chr = "Ingest, Label, Visualise and Share Health Economic Model Datasets" %>% tools::toTitleCase(),
pkg_desc_1L_chr = "ready4use provides a set of tools for managing data for models developed with the ready4 framework.
For detailed documentation about the framework and how to use it visit <https://www.ready4-dev.com/>. For a background to the methodological issues that the framework is attempting to help solve, see Hamilton et al. (2024) <doi:10.1007/s40273-024-01378-8>.
This development version of the ready4use package has been made available as part of the process of testing and documenting the package. If you have any questions, please contact the authors (matthew.hamilton1@monash.edu).",
authors_prsn = c(utils::person(
given = "Matthew",family = "Hamilton", email =
"matthew.hamilton1@monash.edu",role = c("aut",
"cre", "cph"),comment = c(ORCID = "0000-0001-7407-9194")
),
utils::person("Glen", "Wiesner", #email = "Glen.Wiesner@vu.edu.au",
role = c("aut"), comment = c(ORCID = "0000-0002-0071-130X")),
utils::person("Orygen", role = c("cph", "fnd")),
utils::person("Australian Government Research Training Program", role =c("fnd")),
utils::person("VicHealth",role = c("fnd")),
utils::person("Victoria University", role =c("fnd"))
),
urls_chr = c("https://ready4-dev.github.io/ready4use/",
"https://github.com/ready4-dev/ready4use",
"https://www.ready4-dev.com/"))
x <- pkg_desc_ls %>%
ready4fun::make_manifest(addl_pkgs_ls = ready4fun::make_addl_pkgs_ls(#depends_chr = "ready4",
suggests_chr = c("rmarkdown")),
build_ignore_ls = ready4fun::make_build_ignore_ls(file_nms_chr = c("initial_setup.R")),
check_type_1L_chr = "ready4",
custom_dmt_ls = ready4fun::make_custom_dmt_ls(user_manual_fns_chr = c(#"add_dictionary",
"add_from_lup_prototype",
"add_labels_from_dictionary",
"add_latest_match",
# "add_with_join",
"assert_matches_chr",
"assert_single_row_tb",
#"bind_dyads",
"get_journal_palette_fn",
"get_r3_from_dv_csv",
"get_styles",
"make_imputed_distinct_cases",
"make_missing_report",
"update_column_names"#, "write_fls_to_dv_ds"
)),
copyright_holders_chr = "Matthew Hamilton and Orygen",
dev_pkgs_chr = c(#"ready4",
"ready4show"),
lifecycle_stage_1L_chr = "experimental",
path_to_pkg_logo_1L_chr = "../../../../../Documentation/Images/ready4use-logo/default.png",
piggyback_to_1L_chr = "ready4-dev/ready4",
ready4_type_1L_chr = "authoring",
zenodo_badge_1L_chr = "[](https://doi.org/10.5281/zenodo.5644336)")
y <- dplyr::bind_rows(
ready4class::make_pt_ready4class_constructor(make_s3_lgl = TRUE,
name_stub_chr = "distributions",
pt_ls = list(list("list")),
pt_chkr_pfx_ls = list(list("is.")),
pt_ns_ls = list(list("base")),
vals_ls = list(list(distribution_chr = "character(0)",
dstr_param_1_dbl = "numeric(0)",
dstr_param_2_dbl = "numeric(0)",
dstr_param_3_dbl = "numeric(0)",
dstr_param_4_dbl = "numeric(0)",
transformation_chr = "character(0)")),
class_desc_chr = "List object that summarises the parameters of each distribution"),
ready4class::make_pt_ready4class_constructor(make_s3_lgl = TRUE,
name_stub_chr = "dataverses",
pt_ls = list(list("tibble")),
pt_chkr_pfx_ls = list(list("is_")),
pt_ns_ls = list(list("tibble")),
vals_ls = list(list(file_type_chr = "character(0)",
file_name_chr = "character(0)",
data_repo_chr = "character(0)",
data_repo_ui_chr = "character(0)",
data_repo_db_ui_chr = "character(0)",
data_repo_file_ext_chr = "character(0)",
data_repo_save_type_chr = "character(0)")),
class_desc_chr = "Tibble object lookup table of files to be imported from a dataverse."),
ready4class::make_pt_ready4class_constructor(make_s3_lgl = TRUE,
name_stub_chr = "imports",
pt_ls = list(list("tibble")),
pt_chkr_pfx_ls = list(list("is_")),
pt_ns_ls = list(list("tibble")),
vals_ls = list(list(local_file_src_chr = "character(0)",
path_to_make_script_chr = "character(0)",
download_url_chr = "character(0)",
inc_file_main_chr = "character(0)",
inc_fls_to_rename_ls = "list()",
new_nms_for_inc_fls_ls = "list()")),
class_desc_chr = "Tibble object lookup table of sources of raw (un-processed) data to import.",
parent_class_chr = "ready4use_dataverses"),
ready4class::make_pt_ready4class_constructor(make_s3_lgl = TRUE,
name_stub_chr = "mapes",
pt_ls = list(list("tibble")),
pt_chkr_pfx_ls = list(list("is_")),
pt_ns_ls = list(list("tibble")),
vals_ls = list(list(param_name_chr = "character(0)",
sex_age_band_chr = "character(0)",
mape_05_yr_mde_dbl = "numeric(0)",
mape_10_yr_mde_dbl = "numeric(0)",
mape_15_yr_mde_dbl = "numeric(0)",
mape_05_yr_min_dbl = "numeric(0)",
mape_10_yr_min_dbl = "numeric(0)",
mape_15_yr_min_dbl = "numeric(0)",
mape_05_yr_max_dbl = "numeric(0)",
mape_10_yr_max_dbl = "numeric(0)",
mape_15_yr_max_dbl = "numeric(0)",
mape_05_yr_shp_dbl = "numeric(0)",
mape_10_yr_shp_dbl = "numeric(0)",
mape_15_yr_shp_dbl = "numeric(0)")),
class_desc_chr = "Tibble object that stores simulation structural parameters relating to Mean Absolute Prediction Errors."),
ready4class::make_pt_ready4class_constructor(make_s3_lgl = T,
name_stub_chr = "dictionary",
pt_ls = list(list("tibble")),
pt_chkr_pfx_ls = list(list("is_")),
pt_ns_ls = list(list("tibble")),
vals_ls = list(list(var_nm_chr = "character(0)",
var_ctg_chr = "character(0)",
var_desc_chr = "character(0)",
var_type_chr = "character(0)")),
class_desc_chr= "A data dictionary tibble."),
ready4class::make_pt_ready4class_constructor(make_s3_lgl = FALSE,
name_stub_chr = "Files",
slots_ls = list("merge_itms_chr","raw_fls_dir_1L_chr","pkg_1L_chr","overwrite_1L_lgl", "write_1L_lgl") %>% list(), # Cut: "lup_tbs_r4",
pt_ls = list("character","character","character","logical", "logical") %>% list(), # Cut: "ready4class_lookup",
class_desc_chr= "Metadata for dataset(s) to be saved in local directory.",
parent_class_chr = "Ready4Module"), # NA_character_ # Cut: ,include_classes = list("ready4class_lookup")
ready4class::make_pt_ready4class_constructor(make_s3_lgl = FALSE,
name_stub_chr = "Raw",
slots_ls = list("write_type_1L_chr") %>% list(),
pt_ls = list("character") %>% list(),
vals_ls = list(write_type_1L_chr ="raw"),
allowed_vals_ls = list(write_type_1L_chr = "raw"),
class_desc_chr= "Metadata for dataset(s) to be saved in local directory in a raw (unprocessed) format.",
parent_class_chr = "Ready4useFiles"),
ready4class::make_pt_ready4class_constructor(make_s3_lgl = FALSE,
name_stub_chr = "Processed",
slots_ls = list("write_type_1L_chr","processed_fls_dir_1L_chr","imports_chr","path_to_seed_sf_1L_chr","imports_ls") %>% list(),
pt_ls = list("character","character","character","character","list") %>% list(),
vals_ls = list(write_type_1L_chr = "proc"),
allowed_vals_ls = list(write_type_1L_chr = "proc"),
class_desc_chr= "Metadata for dataset(s) to be saved in local directory in a processed (R) format.",
parent_class_chr = "Ready4useFiles"),
ready4class::make_pt_ready4class_constructor(make_s3_lgl = FALSE,
name_stub_chr = "Arguments",
slots_ls = list("crs_nbr_dbl") %>% list(), # Change
pt_ls = list("numeric") %>% list(),
class_desc_chr= "Arguments for a function that constructs a spatial object.",
parent_class_chr = "Ready4useProcessed"),
ready4class::make_pt_ready4class_constructor(make_s3_lgl = FALSE,
name_stub_chr = "Dyad",
slots_ls = list("ds_tb","dictionary_r3") %>% list(), # Change
pt_ls = list("tbl_df","ready4use_dictionary") %>% list(),
class_desc_chr= "A dataset and data dictionary pair.",
parent_class_chr = "Ready4Module"),
ready4class::make_pt_ready4class_constructor(make_s3_lgl = FALSE,
name_stub_chr = "Ingest",
slots_ls = list("objects_ls",#"names_chr",
"descriptions_chr") %>% list(), # Change
pt_ls = list("list",#"character",
"character") %>% list(),
class_desc_chr = "Ingested data and descriptive metadata.",
parent_class_chr = "Ready4Module"),
ready4class::make_pt_ready4class_constructor(make_s3_lgl = FALSE,
name_stub_chr = "Repos",
slots_ls = list("dv_nm_1L_chr","dv_ds_metadata_ls",
"dv_ds_nm_1L_chr","dv_server_1L_chr",
"dv_url_pfx_1L_chr","fl_nms_chr",
"gh_repo_1L_chr","gh_tag_1L_chr"
) %>% list(), # Change
pt_ls = list("character","list",
"character","character","character","character","character","character") %>% list(),
class_desc_chr= "Metadata about online data repositories.",
parent_class_chr = "Ready4Module"),
ready4class::make_pt_ready4class_constructor(make_s3_lgl = FALSE,
name_stub_chr = "Pointer",
slots_ls = list("a_Ready4usePaths","b_Ready4useRepos") %>% list(), # Change
pt_ls = list("Ready4Module","Ready4useRepos") %>% list(),
class_desc_chr = "Metadata on local and remote data storage locations.",
parent_class_chr = "Ready4Module",
inc_clss_ls = list("Ready4useRepos") %>% list()),
ready4class::make_pt_ready4class_constructor(make_s3_lgl = FALSE,
name_stub_chr = "Record",
slots_ls = list("a_Ready4usePointer","b_Ready4useIngest") %>% list(), # Change
pt_ls = list("Ready4usePointer","Ready4useIngest") %>% list(),
class_desc_chr= "Ingested data, descriptive metadata and provenance details.",
parent_class_chr = "Ready4Module",
inc_clss_ls = list("Ready4usePointer","Ready4useIngest") %>% list())
) %>%
ready4class::ready4class_constructor()
z <- ready4pack::make_pt_ready4pack_manifest(x,
constructor_r3 = y) %>%
ready4pack::ready4pack_manifest()
z <- author(z)
# ready4::write_extra_pkgs_to_actions(path_to_dir_1L_chr = ".github/workflows")
write_to_edit_workflow("pkgdown.yaml", consent_1L_chr = "Y") # In other packages, run for "test-coverage.yaml" as well.
# readme_chr <- readLines("README.md")
# readme_chr[-which(readme_chr %>% purrr::map_lgl(~startsWith(.x, "[![test-coverage]")))] %>%
# writeLines(con = "README.md")
write_to_tidy_pkg(manifest_ls, build_vignettes_1L_lgl = FALSE,
clean_license_1L_lgl = TRUE, consent_1L_chr = "Y",
examples_chr = character(0), project_1L_chr = "Framework", suggest_chr = "pkgload")
readLines("README.md") %>%
#gsub(pattern = "doi:10.48550/arXiv.([^&]+)", replacement = "https://arxiv.org/abs/\\1") %>%
gsub(pattern = "doi:([^&]+)", replacement = "https://doi.org/\\1") %>%
writeLines(con = "README.md")
paste0(".github/workflows/", c("pkgdown.yaml", "R-CMD-check.yaml")) %>%
purrr::walk(~{
path_1L_chr <- .x
matches_int <- which(readLines(path_1L_chr) %>% startsWith(" # Addresses issue with incompatibility between libcurl4-gnutls-dev and libcurl4-openssl-dev") | readLines(path_1L_chr) %>% startsWith(" # Addresses issue with incompatibility between libcurl4-gnutls-dev and libcurl4-openssl-dev"))
if(!identical(matches_int,integer(0))){
readLines(path_1L_chr)[- (matches_int%>%
purrr::map(~.x:(.x+6)) %>% purrr::flatten_int())] %>%
writeLines(path_1L_chr)
}
})
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