CRAN checks API
CRAN checks API is an API providing access to CRAN checks data in a machine-readable format.
For a recent overview of the API, check out the Overview of the CRAN checks API blog post on the R-Hub blog.
The API was created and is maintained by Scott Chamberlain.
Base URL
R package cchecks 📦
Most endpoints are supported in the cchecks R client.
remotes::install_github("ropenscilabs/cchecks")
library("cchecks")
HTTP methods
This is mostly a read only API. That is, we only allow GET (and HEAD) requests on this API.
Requests of all other types will be rejected with appropriate 405 code.
Media types
JSON mostly, image/svg+xml for badges.
Pagination
The query parameters limit (default = 10) and offset (default = 0) can be sent.
- limit (integer, optional)
- number of records to return. Default: 10. Max: see endpoint docs.
- offset (integer, optional)
- Record number to start at. Default: 0. Max: see endpoint docs.
Above parameters can be used only on /pkgs, /maintainers, and /pkgs/{package_name}/history.
The response body from the server will include data on records found in found and number returned in count.
Response codes
For this section of the docs, examples of (bad) requests are given in the Shell tab on the right, and the headers are in the Headers tab.
200 (OK)
Request good!
curl https://cranchecks.info/heartbeat | jq .
HTTP/2 200
access-control-allow-methods: HEAD, GET
access-control-allow-origin: *
cache-control: public, must-revalidate, max-age=60
content-type: application/json; charset=utf8
server: Caddy
x-content-type-options: nosniff
content-length: 256
date: Mon, 22 Mar 2021 13:00:35 GMT
{
"routes": [
"/",
"/docs",
"/heartbeat/?",
"/pkgs",
"/pkgs/:name",
"/maintainers",
"/maintainers/:email",
"/badges/:type/:package",
"/badges/flavor/:flavor/:package",
"/pkgs/:name/history",
"/history/:date",
"/search"
]
}
302 (Found)
The root /, redirects to /heartbeat, and /docs redirects to what you’re reading right now.
curl https://cranchecks.info/ | jq .
HTTP/2 302
access-control-allow-methods: HEAD, GET
access-control-allow-origin: *
cache-control: public, must-revalidate, max-age=60
content-type: application/json; charset=utf8
location: https://cranchecks.info/heartbeat
server: Caddy
x-content-type-options: nosniff
content-length: 0
date: Mon, 22 Mar 2021 13:00:36 GMT
400 (Bad request)
When you have a malformed request, fix it and try again
curl https://cranchecks.info/maintainers/blablabla | jq .
HTTP/2 400
access-control-allow-methods: HEAD, GET
access-control-allow-origin: *
cache-control: public, must-revalidate, max-age=60
content-type: application/json; charset=utf8
server: Caddy
x-content-type-options: nosniff
content-length: 52
date: Mon, 22 Mar 2021 13:00:36 GMT
{
"error": {
"message": "no results found"
},
"data": null
}
404 (Not found)
When you request a route that does not exist, fix it and try again. E.g. in the example here we misspell “maintainers” to “maintainer”. 🙈
curl https://cranchecks.info/maintainer | jq .
HTTP/2 404
content-type: application/json
server: Caddy
x-cascade: pass
x-content-type-options: nosniff
content-length: 27
date: Mon, 22 Mar 2021 13:00:36 GMT
{
"error": "route not found"
}
405 (Method not allowed)
When you use a prohibited HTTP method for a given route. Don’t do that. 😉
curl -XDELETE https://cranchecks.info/pkgs/ropenaq/
HTTP/2 405
content-type: application/json
server: Caddy
x-content-type-options: nosniff
content-length: 30
date: Mon, 22 Mar 2021 13:00:37 GMT
{
"error": "Method Not Allowed"
}
500 (Internal server error)
Server got itself in trouble 😱 😭; get in touch with us.
HTTP/2 500
date: Thu, 21 May 2020 16:53:33 GMT
content-type: text/html; charset=utf-8
content-length: 0
Root
This path redirects to /heartbeat
curl https://cranchecks.info/ | jq .
HTTP/2 302
access-control-allow-methods: HEAD, GET
access-control-allow-origin: *
cache-control: public, must-revalidate, max-age=60
content-type: application/json; charset=utf8
location: https://cranchecks.info/heartbeat
server: Caddy
x-content-type-options: nosniff
content-length: 0
date: Mon, 22 Mar 2021 13:00:37 GMT
Heartbeat
Get heartbeat for the API 💓 (i.e. the list of endpoints).
GET [/heartbeat]
Function of the cchecks R package: cch_heartbeat().
curl https://cranchecks.info/heartbeat | jq .
HTTP/2 200
access-control-allow-methods: HEAD, GET
access-control-allow-origin: *
cache-control: public, must-revalidate, max-age=60
content-type: application/json; charset=utf8
server: Caddy
x-content-type-options: nosniff
content-length: 256
date: Mon, 22 Mar 2021 13:00:18 GMT
{
"routes": [
"/",
"/docs",
"/heartbeat/?",
"/pkgs",
"/pkgs/:name",
"/maintainers",
"/maintainers/:email",
"/badges/:type/:package",
"/badges/flavor/:flavor/:package",
"/pkgs/:name/history",
"/history/:date",
"/search"
]
}
cchecks::cch_heartbeat()
$routes
[1] "/" "/docs"
[3] "/heartbeat/?" "/pkgs"
[5] "/pkgs/:name" "/maintainers"
[7] "/maintainers/:email" "/badges/:type/:package"
[9] "/badges/flavor/:flavor/:package" "/pkgs/:name/history"
[11] "/history/:date" "/search"
Docs
This path redirects to the docs (hopefully here! 😸). See Headers tab.
GET [/docs]
curl https://cranchecks.info/docs
HTTP/2 301
access-control-allow-methods: HEAD, GET
access-control-allow-origin: *
cache-control: public, must-revalidate, max-age=60
content-type: application/json; charset=utf8
location: https://docs.cranchecks.info/
server: Caddy
x-content-type-options: nosniff
content-length: 0
date: Mon, 22 Mar 2021 13:00:18 GMT
Maintainers
Get checks data by package maintainer.
Function of the cchecks R package: cch_maintainers().
Maintainers
Get checks summaries for all maintainers.
GET [/maintainers]
Default limit of 10, max of 1000.
Example with custom offset and limit.
curl https://cranchecks.info/maintainers/?limit=2&offset=5 | jq .
HTTP/2 200
access-control-allow-methods: HEAD, GET
access-control-allow-origin: *
cache-control: public, must-revalidate, max-age=60
content-type: application/json; charset=utf8
server: Caddy
x-content-type-options: nosniff
content-length: 1060
date: Mon, 22 Mar 2021 13:00:22 GMT
{
"found": 10726,
"count": 2,
"offset": 5,
"error": null,
"data": [
{
"email": "markus.boenn.sf_at_googlemail.com",
"name": "Markus Boenn",
"url": "https://cloud.r-project.org/web/checks/check_results_markus.boenn.sf_at_googlemail.com.html",
"date_updated": "2021-03-05T12:02:37.426Z",
"table": [
{
"package": "hypergea",
"any": true,
"ok": 6,
"note": 6,
"warn": 0,
"error": 0
}
],
"packages": [
{
"package": "hypergea",
"url": "https://cloud.r-project.org/web/checks/check_results_hypergea.html",
"check_result": [
{
"category": "NOTE",
"number_checks": 6
},
{
"category": "OK",
"number_checks": 6
}
],
"version": null
}
]
},
{
"email": "s.greilich_at_dkfz.de",
"name": "Steffen Greilich",
"url": "https://cloud.r-project.org/web/checks/check_results_s.greilich_at_dkfz.de.html",
"date_updated": "2021-03-05T12:02:37.426Z",
"table": [
{
"package": "libamtrack",
"any": true,
"ok": 2,
"note": 10,
"warn": 0,
"error": 0
}
],
"packages": [
{
"package": "libamtrack",
"url": "https://cloud.r-project.org/web/checks/check_results_libamtrack.html",
"check_result": [
{
"category": "NOTE",
"number_checks": 10
},
{
"category": "OK",
"number_checks": 2
}
],
"version": null
}
]
}
]
}
cchecks::cch_maintainers(limit = 2, offset = 5)
$found
[1] 10726
$count
[1] 2
$offset
[1] 5
$error
NULL
$data
email name
1 markus.boenn.sf_at_googlemail.com Markus Boenn
2 s.greilich_at_dkfz.de Steffen Greilich
url
1 https://cloud.r-project.org/web/checks/check_results_markus.boenn.sf_at_googlemail.com.html
2 https://cloud.r-project.org/web/checks/check_results_s.greilich_at_dkfz.de.html
date_updated table
1 2021-03-05T12:02:37.426Z hypergea, TRUE, 6, 6, 0, 0
2 2021-03-05T12:02:37.426Z libamtrack, TRUE, 2, 10, 0, 0
packages
1 hypergea, https://cloud.r-project.org/web/checks/check_results_hypergea.html, NOTE, OK, 6, 6, NA
2 libamtrack, https://cloud.r-project.org/web/checks/check_results_libamtrack.html, NOTE, OK, 10, 2, NA
Maintainers by email
Get checks data by email of the package maintainer.
GET [/maintainers/{email}]
⚠️ jane.doe@example.com has to be transformed to jane.doe_at_example.com.
curl https://cranchecks.info/maintainers/csardi.gabor_at_gmail.com | jq .
HTTP/2 200
access-control-allow-methods: HEAD, GET
access-control-allow-origin: *
cache-control: public, must-revalidate, max-age=60
content-type: application/json; charset=utf8
server: Caddy
x-content-type-options: nosniff
content-length: 13628
date: Mon, 22 Mar 2021 13:00:24 GMT
{
"error": null,
"data": {
"email": "csardi.gabor_at_gmail.com",
"name": "Gábor Csárdi",
"url": "https://cloud.r-project.org/web/checks/check_results_csardi.gabor_at_gmail.com.html",
"date_updated": "2021-03-05T12:02:37.986Z",
"table": [
{
"package": "asciicast",
"any": false,
"ok": 12,
"note": 0,
"warn": 0,
"error": 0
},
{
"package": "callr",
"any": false,
"ok": 12,
"note": 0,
"warn": 0,
"error": 0
},
{
"package": "cleancall",
"any": false,
"ok": 12,
"note": 0,
"warn": 0,
"error": 0
},
{
"package": "cli",
"any": false,
"ok": 12,
"note": 0,
"warn": 0,
"error": 0
},
{
"package": "cliapp",
"any": false,
"ok": 12,
"note": 0,
"warn": 0,
"error": 0
},
{
"package": "clisymbols",
"any": false,
"ok": 12,
"note": 0,
"warn": 0,
"error": 0
},
{
"package": "cranlike",
"any": false,
"ok": 12,
"note": 0,
"warn": 0,
"error": 0
},
{
"package": "cranlogs",
"any": false,
"ok": 12,
"note": 0,
"warn": 0,
"error": 0
},
{
"package": "crayon",
"any": false,
"ok": 12,
"note": 0,
"warn": 0,
"error": 0
},
{
"package": "debugme",
"any": false,
"ok": 12,
"note": 0,
"warn": 0,
"error": 0
},
{
"package": "desc",
"any": true,
"ok": 11,
"note": 0,
"warn": 0,
"error": 1
},
{
"package": "disposables",
"any": false,
"ok": 12,
"note": 0,
"warn": 0,
"error": 0
},
{
"package": "dotenv",
"any": false,
"ok": 12,
"note": 0,
"warn": 0,
"error": 0
},
{
"package": "filelock",
"any": false,
"ok": 12,
"note": 0,
"warn": 0,
"error": 0
},
{
"package": "franc",
"any": false,
"ok": 12,
"note": 0,
"warn": 0,
"error": 0
},
{
"package": "gh",
"any": false,
"ok": 12,
"note": 0,
"warn": 0,
"error": 0
},
{
"package": "gitcreds",
"any": false,
"ok": 12,
"note": 0,
"warn": 0,
"error": 0
},
{
"package": "igraph",
"any": true,
"ok": 5,
"note": 7,
"warn": 0,
"error": 0
},
{
"package": "igraphdata",
"any": false,
"ok": 12,
"note": 0,
"warn": 0,
"error": 0
},
{
"package": "isa2",
"any": false,
"ok": 12,
"note": 0,
"warn": 0,
"error": 0
},
{
"package": "keypress",
"any": false,
"ok": 12,
"note": 0,
"warn": 0,
"error": 0
},
{
"package": "keyring",
"any": true,
"ok": 10,
"note": 2,
"warn": 0,
"error": 0
},
{
"package": "liteq",
"any": false,
"ok": 12,
"note": 0,
"warn": 0,
"error": 0
},
{
"package": "lpSolve",
"any": false,
"ok": 12,
"note": 0,
"warn": 0,
"error": 0
},
{
"package": "oskeyring",
"any": false,
"ok": 12,
"note": 0,
"warn": 0,
"error": 0
},
{
"package": "pak",
"any": true,
"ok": 11,
"note": 1,
"warn": 0,
"error": 0
},
{
"package": "parsedate",
"any": false,
"ok": 12,
"note": 0,
"warn": 0,
"error": 0
},
{
"package": "pingr",
"any": false,
"ok": 12,
"note": 0,
"warn": 0,
"error": 0
},
{
"package": "pkgcache",
"any": true,
"ok": 11,
"note": 0,
"warn": 0,
"error": 1
},
{
"package": "pkgconfig",
"any": false,
"ok": 12,
"note": 0,
"warn": 0,
"error": 0
},
{
"package": "pkgsearch",
"any": false,
"ok": 12,
"note": 0,
"warn": 0,
"error": 0
},
{
"package": "praise",
"any": false,
"ok": 12,
"note": 0,
"warn": 0,
"error": 0
},
{
"package": "presser",
"any": true,
"ok": 11,
"note": 0,
"warn": 0,
"error": 1
},
{
"package": "prettycode",
"any": false,
"ok": 12,
"note": 0,
"warn": 0,
"error": 0
},
{
"package": "prettyunits",
"any": false,
"ok": 12,
"note": 0,
"warn": 0,
"error": 0
},
{
"package": "processx",
"any": false,
"ok": 12,
"note": 0,
"warn": 0,
"error": 0
},
{
"package": "progress",
"any": false,
"ok": 12,
"note": 0,
"warn": 0,
"error": 0
},
{
"package": "prompt",
"any": true,
"ok": 2,
"note": 0,
"warn": 0,
"error": 1
},
{
"package": "ps",
"any": false,
"ok": 12,
"note": 0,
"warn": 0,
"error": 0
},
{
"package": "rcmdcheck",
"any": true,
"ok": 11,
"note": 1,
"warn": 0,
"error": 0
},
{
"package": "rcorpora",
"any": true,
"ok": 5,
"note": 7,
"warn": 0,
"error": 0
},
{
"package": "rematch2",
"any": true,
"ok": 11,
"note": 1,
"warn": 0,
"error": 0
},
{
"package": "rhub",
"any": false,
"ok": 12,
"note": 0,
"warn": 0,
"error": 0
},
{
"package": "rversions",
"any": false,
"ok": 12,
"note": 0,
"warn": 0,
"error": 0
},
{
"package": "sankey",
"any": false,
"ok": 12,
"note": 0,
"warn": 0,
"error": 0
},
{
"package": "secret",
"any": false,
"ok": 12,
"note": 0,
"warn": 0,
"error": 0
},
{
"package": "sessioninfo",
"any": false,
"ok": 12,
"note": 0,
"warn": 0,
"error": 0
},
{
"package": "showimage",
"any": false,
"ok": 12,
"note": 0,
"warn": 0,
"error": 0
},
{
"package": "tracer",
"any": false,
"ok": 12,
"note": 0,
"warn": 0,
"error": 0
},
{
"package": "webdriver",
"any": false,
"ok": 12,
"note": 0,
"warn": 0,
"error": 0
},
{
"package": "webfakes",
"any": true,
"ok": 11,
"note": 0,
"warn": 0,
"error": 1
},
{
"package": "whoami",
"any": false,
"ok": 12,
"note": 0,
"warn": 0,
"error": 0
},
{
"package": "xmlparsedata",
"any": false,
"ok": 12,
"note": 0,
"warn": 0,
"error": 0
},
{
"package": "xopen",
"any": false,
"ok": 12,
"note": 0,
"warn": 0,
"error": 0
},
{
"package": "zip",
"any": true,
"ok": 11,
"note": 0,
"warn": 0,
"error": 1
}
],
"packages": [
{
"package": "asciicast",
"url": "https://cloud.r-project.org/web/checks/check_results_asciicast.html",
"check_result": [
{
"category": "OK",
"number_checks": 12
}
],
"version": null
},
{
"package": "callr",
"url": "https://cloud.r-project.org/web/checks/check_results_callr.html",
"check_result": [
{
"category": "OK",
"number_checks": 12
}
],
"version": null
},
{
"package": "cleancall",
"url": "https://cloud.r-project.org/web/checks/check_results_cleancall.html",
"check_result": [
{
"category": "OK",
"number_checks": 12
}
],
"version": null
},
{
"package": "cli",
"url": "https://cloud.r-project.org/web/checks/check_results_cli.html",
"check_result": [
{
"category": "OK",
"number_checks": 12
}
],
"version": null
},
{
"package": "cliapp",
"url": "https://cloud.r-project.org/web/checks/check_results_cliapp.html",
"check_result": [
{
"category": "OK",
"number_checks": 12
}
],
"version": null
},
{
"package": "clisymbols",
"url": "https://cloud.r-project.org/web/checks/check_results_clisymbols.html",
"check_result": [
{
"category": "OK",
"number_checks": 12
}
],
"version": null
},
{
"package": "cranlike",
"url": "https://cloud.r-project.org/web/checks/check_results_cranlike.html",
"check_result": [
{
"category": "OK",
"number_checks": 12
}
],
"version": null
},
{
"package": "cranlogs",
"url": "https://cloud.r-project.org/web/checks/check_results_cranlogs.html",
"check_result": [
{
"category": "OK",
"number_checks": 12
}
],
"version": null
},
{
"package": "crayon",
"url": "https://cloud.r-project.org/web/checks/check_results_crayon.html",
"check_result": [
{
"category": "OK",
"number_checks": 12
}
],
"version": null
},
{
"package": "debugme",
"url": "https://cloud.r-project.org/web/checks/check_results_debugme.html",
"check_result": [
{
"category": "OK",
"number_checks": 12
}
],
"version": null
},
{
"package": "desc",
"url": "https://cloud.r-project.org/web/checks/check_results_desc.html",
"check_result": [
{
"category": "ERROR",
"number_checks": 1
},
{
"category": "OK",
"number_checks": 11
}
],
"version": null
},
{
"package": "disposables",
"url": "https://cloud.r-project.org/web/checks/check_results_disposables.html",
"check_result": [
{
"category": "OK",
"number_checks": 12
}
],
"version": null
},
{
"package": "dotenv",
"url": "https://cloud.r-project.org/web/checks/check_results_dotenv.html",
"check_result": [
{
"category": "OK",
"number_checks": 12
}
],
"version": null
},
{
"package": "filelock",
"url": "https://cloud.r-project.org/web/checks/check_results_filelock.html",
"check_result": [
{
"category": "OK",
"number_checks": 12
}
],
"version": null
},
{
"package": "franc",
"url": "https://cloud.r-project.org/web/checks/check_results_franc.html",
"check_result": [
{
"category": "OK",
"number_checks": 12
}
],
"version": null
},
{
"package": "gh",
"url": "https://cloud.r-project.org/web/checks/check_results_gh.html",
"check_result": [
{
"category": "OK",
"number_checks": 12
}
],
"version": null
},
{
"package": "gitcreds",
"url": "https://cloud.r-project.org/web/checks/check_results_gitcreds.html",
"check_result": [
{
"category": "OK",
"number_checks": 12
}
],
"version": null
},
{
"package": "igraph",
"url": "https://cloud.r-project.org/web/checks/check_results_igraph.html",
"check_result": [
{
"category": "NOTE",
"number_checks": 7
},
{
"category": "OK",
"number_checks": 5
}
],
"version": null
},
{
"package": "igraphdata",
"url": "https://cloud.r-project.org/web/checks/check_results_igraphdata.html",
"check_result": [
{
"category": "OK",
"number_checks": 12
}
],
"version": null
},
{
"package": "isa2",
"url": "https://cloud.r-project.org/web/checks/check_results_isa2.html",
"check_result": [
{
"category": "OK",
"number_checks": 12
}
],
"version": null
},
{
"package": "keypress",
"url": "https://cloud.r-project.org/web/checks/check_results_keypress.html",
"check_result": [
{
"category": "OK",
"number_checks": 12
}
],
"version": null
},
{
"package": "keyring",
"url": "https://cloud.r-project.org/web/checks/check_results_keyring.html",
"check_result": [
{
"category": "NOTE",
"number_checks": 2
},
{
"category": "OK",
"number_checks": 10
}
],
"version": null
},
{
"package": "liteq",
"url": "https://cloud.r-project.org/web/checks/check_results_liteq.html",
"check_result": [
{
"category": "OK",
"number_checks": 12
}
],
"version": null
},
{
"package": "lpSolve",
"url": "https://cloud.r-project.org/web/checks/check_results_lpSolve.html",
"check_result": [
{
"category": "OK",
"number_checks": 12
}
],
"version": null
},
{
"package": "oskeyring",
"url": "https://cloud.r-project.org/web/checks/check_results_oskeyring.html",
"check_result": [
{
"category": "OK",
"number_checks": 12
}
],
"version": null
},
{
"package": "pak",
"url": "https://cloud.r-project.org/web/checks/check_results_pak.html",
"check_result": [
{
"category": "NOTE",
"number_checks": 1
},
{
"category": "OK",
"number_checks": 11
}
],
"version": null
},
{
"package": "parsedate",
"url": "https://cloud.r-project.org/web/checks/check_results_parsedate.html",
"check_result": [
{
"category": "OK",
"number_checks": 12
}
],
"version": null
},
{
"package": "pingr",
"url": "https://cloud.r-project.org/web/checks/check_results_pingr.html",
"check_result": [
{
"category": "OK",
"number_checks": 12
}
],
"version": null
},
{
"package": "pkgcache",
"url": "https://cloud.r-project.org/web/checks/check_results_pkgcache.html",
"check_result": [
{
"category": "ERROR",
"number_checks": 1
},
{
"category": "OK",
"number_checks": 11
}
],
"version": null
},
{
"package": "pkgconfig",
"url": "https://cloud.r-project.org/web/checks/check_results_pkgconfig.html",
"check_result": [
{
"category": "OK",
"number_checks": 12
}
],
"version": null
},
{
"package": "pkgsearch",
"url": "https://cloud.r-project.org/web/checks/check_results_pkgsearch.html",
"check_result": [
{
"category": "OK",
"number_checks": 12
}
],
"version": null
},
{
"package": "praise",
"url": "https://cloud.r-project.org/web/checks/check_results_praise.html",
"check_result": [
{
"category": "OK",
"number_checks": 12
}
],
"version": null
},
{
"package": "presser",
"url": "https://cloud.r-project.org/web/checks/check_results_presser.html",
"check_result": [
{
"category": "ERROR",
"number_checks": 1
},
{
"category": "OK",
"number_checks": 11
}
],
"version": null
},
{
"package": "prettycode",
"url": "https://cloud.r-project.org/web/checks/check_results_prettycode.html",
"check_result": [
{
"category": "OK",
"number_checks": 12
}
],
"version": null
},
{
"package": "prettyunits",
"url": "https://cloud.r-project.org/web/checks/check_results_prettyunits.html",
"check_result": [
{
"category": "OK",
"number_checks": 12
}
],
"version": null
},
{
"package": "processx",
"url": "https://cloud.r-project.org/web/checks/check_results_processx.html",
"check_result": [
{
"category": "OK",
"number_checks": 12
}
],
"version": null
},
{
"package": "progress",
"url": "https://cloud.r-project.org/web/checks/check_results_progress.html",
"check_result": [
{
"category": "OK",
"number_checks": 12
}
],
"version": null
},
{
"package": "prompt",
"url": "https://cloud.r-project.org/web/checks/check_results_prompt.html",
"check_result": [
{
"category": "ERROR",
"number_checks": 1
},
{
"category": "OK",
"number_checks": 2
}
],
"version": null
},
{
"package": "ps",
"url": "https://cloud.r-project.org/web/checks/check_results_ps.html",
"check_result": [
{
"category": "OK",
"number_checks": 12
}
],
"version": null
},
{
"package": "rcmdcheck",
"url": "https://cloud.r-project.org/web/checks/check_results_rcmdcheck.html",
"check_result": [
{
"category": "NOTE",
"number_checks": 1
},
{
"category": "OK",
"number_checks": 11
}
],
"version": null
},
{
"package": "rcorpora",
"url": "https://cloud.r-project.org/web/checks/check_results_rcorpora.html",
"check_result": [
{
"category": "NOTE",
"number_checks": 7
},
{
"category": "OK",
"number_checks": 5
}
],
"version": null
},
{
"package": "rematch2",
"url": "https://cloud.r-project.org/web/checks/check_results_rematch2.html",
"check_result": [
{
"category": "NOTE",
"number_checks": 1
},
{
"category": "OK",
"number_checks": 11
}
],
"version": null
},
{
"package": "rhub",
"url": "https://cloud.r-project.org/web/checks/check_results_rhub.html",
"check_result": [
{
"category": "OK",
"number_checks": 12
}
],
"version": null
},
{
"package": "rversions",
"url": "https://cloud.r-project.org/web/checks/check_results_rversions.html",
"check_result": [
{
"category": "OK",
"number_checks": 12
}
],
"version": null
},
{
"package": "sankey",
"url": "https://cloud.r-project.org/web/checks/check_results_sankey.html",
"check_result": [
{
"category": "OK",
"number_checks": 12
}
],
"version": null
},
{
"package": "secret",
"url": "https://cloud.r-project.org/web/checks/check_results_secret.html",
"check_result": [
{
"category": "OK",
"number_checks": 12
}
],
"version": null
},
{
"package": "sessioninfo",
"url": "https://cloud.r-project.org/web/checks/check_results_sessioninfo.html",
"check_result": [
{
"category": "OK",
"number_checks": 12
}
],
"version": null
},
{
"package": "showimage",
"url": "https://cloud.r-project.org/web/checks/check_results_showimage.html",
"check_result": [
{
"category": "OK",
"number_checks": 12
}
],
"version": null
},
{
"package": "tracer",
"url": "https://cloud.r-project.org/web/checks/check_results_tracer.html",
"check_result": [
{
"category": "OK",
"number_checks": 12
}
],
"version": null
},
{
"package": "webdriver",
"url": "https://cloud.r-project.org/web/checks/check_results_webdriver.html",
"check_result": [
{
"category": "OK",
"number_checks": 12
}
],
"version": null
},
{
"package": "webfakes",
"url": "https://cloud.r-project.org/web/checks/check_results_webfakes.html",
"check_result": [
{
"category": "ERROR",
"number_checks": 1
},
{
"category": "OK",
"number_checks": 11
}
],
"version": null
},
{
"package": "whoami",
"url": "https://cloud.r-project.org/web/checks/check_results_whoami.html",
"check_result": [
{
"category": "OK",
"number_checks": 12
}
],
"version": null
},
{
"package": "xmlparsedata",
"url": "https://cloud.r-project.org/web/checks/check_results_xmlparsedata.html",
"check_result": [
{
"category": "OK",
"number_checks": 12
}
],
"version": null
},
{
"package": "xopen",
"url": "https://cloud.r-project.org/web/checks/check_results_xopen.html",
"check_result": [
{
"category": "OK",
"number_checks": 12
}
],
"version": null
},
{
"package": "zip",
"url": "https://cloud.r-project.org/web/checks/check_results_zip.html",
"check_result": [
{
"category": "ERROR",
"number_checks": 1
},
{
"category": "OK",
"number_checks": 11
}
],
"version": null
}
]
}
}
cchecks::cch_maintainers(x = "csardi.gabor_at_gmail.com")
$error
NULL
$data
$data$email
[1] "csardi.gabor_at_gmail.com"
$data$name
[1] "Gábor Csárdi"
$data$url
[1] "https://cloud.r-project.org/web/checks/check_results_csardi.gabor_at_gmail.com.html"
$data$date_updated
[1] "2021-03-05T12:02:37.986Z"
$data$table
package any ok note warn error
1 asciicast FALSE 12 0 0 0
2 callr FALSE 12 0 0 0
3 cleancall FALSE 12 0 0 0
4 cli FALSE 12 0 0 0
5 cliapp FALSE 12 0 0 0
6 clisymbols FALSE 12 0 0 0
7 cranlike FALSE 12 0 0 0
8 cranlogs FALSE 12 0 0 0
9 crayon FALSE 12 0 0 0
10 debugme FALSE 12 0 0 0
11 desc TRUE 11 0 0 1
12 disposables FALSE 12 0 0 0
13 dotenv FALSE 12 0 0 0
14 filelock FALSE 12 0 0 0
15 franc FALSE 12 0 0 0
16 gh FALSE 12 0 0 0
17 gitcreds FALSE 12 0 0 0
18 igraph TRUE 5 7 0 0
19 igraphdata FALSE 12 0 0 0
20 isa2 FALSE 12 0 0 0
21 keypress FALSE 12 0 0 0
22 keyring TRUE 10 2 0 0
23 liteq FALSE 12 0 0 0
24 lpSolve FALSE 12 0 0 0
25 oskeyring FALSE 12 0 0 0
26 pak TRUE 11 1 0 0
27 parsedate FALSE 12 0 0 0
28 pingr FALSE 12 0 0 0
29 pkgcache TRUE 11 0 0 1
30 pkgconfig FALSE 12 0 0 0
31 pkgsearch FALSE 12 0 0 0
32 praise FALSE 12 0 0 0
33 presser TRUE 11 0 0 1
34 prettycode FALSE 12 0 0 0
35 prettyunits FALSE 12 0 0 0
36 processx FALSE 12 0 0 0
37 progress FALSE 12 0 0 0
38 prompt TRUE 2 0 0 1
39 ps FALSE 12 0 0 0
40 rcmdcheck TRUE 11 1 0 0
41 rcorpora TRUE 5 7 0 0
42 rematch2 TRUE 11 1 0 0
43 rhub FALSE 12 0 0 0
44 rversions FALSE 12 0 0 0
45 sankey FALSE 12 0 0 0
46 secret FALSE 12 0 0 0
47 sessioninfo FALSE 12 0 0 0
48 showimage FALSE 12 0 0 0
49 tracer FALSE 12 0 0 0
50 webdriver FALSE 12 0 0 0
51 webfakes TRUE 11 0 0 1
52 whoami FALSE 12 0 0 0
53 xmlparsedata FALSE 12 0 0 0
54 xopen FALSE 12 0 0 0
55 zip TRUE 11 0 0 1
$data$packages
package
1 asciicast
2 callr
3 cleancall
4 cli
5 cliapp
6 clisymbols
7 cranlike
8 cranlogs
9 crayon
10 debugme
11 desc
12 disposables
13 dotenv
14 filelock
15 franc
16 gh
17 gitcreds
18 igraph
19 igraphdata
20 isa2
21 keypress
22 keyring
23 liteq
24 lpSolve
25 oskeyring
26 pak
27 parsedate
28 pingr
29 pkgcache
30 pkgconfig
31 pkgsearch
32 praise
33 presser
34 prettycode
35 prettyunits
36 processx
37 progress
38 prompt
39 ps
40 rcmdcheck
41 rcorpora
42 rematch2
43 rhub
44 rversions
45 sankey
46 secret
47 sessioninfo
48 showimage
49 tracer
50 webdriver
51 webfakes
52 whoami
53 xmlparsedata
54 xopen
55 zip
url
1 https://cloud.r-project.org/web/checks/check_results_asciicast.html
2 https://cloud.r-project.org/web/checks/check_results_callr.html
3 https://cloud.r-project.org/web/checks/check_results_cleancall.html
4 https://cloud.r-project.org/web/checks/check_results_cli.html
5 https://cloud.r-project.org/web/checks/check_results_cliapp.html
6 https://cloud.r-project.org/web/checks/check_results_clisymbols.html
7 https://cloud.r-project.org/web/checks/check_results_cranlike.html
8 https://cloud.r-project.org/web/checks/check_results_cranlogs.html
9 https://cloud.r-project.org/web/checks/check_results_crayon.html
10 https://cloud.r-project.org/web/checks/check_results_debugme.html
11 https://cloud.r-project.org/web/checks/check_results_desc.html
12 https://cloud.r-project.org/web/checks/check_results_disposables.html
13 https://cloud.r-project.org/web/checks/check_results_dotenv.html
14 https://cloud.r-project.org/web/checks/check_results_filelock.html
15 https://cloud.r-project.org/web/checks/check_results_franc.html
16 https://cloud.r-project.org/web/checks/check_results_gh.html
17 https://cloud.r-project.org/web/checks/check_results_gitcreds.html
18 https://cloud.r-project.org/web/checks/check_results_igraph.html
19 https://cloud.r-project.org/web/checks/check_results_igraphdata.html
20 https://cloud.r-project.org/web/checks/check_results_isa2.html
21 https://cloud.r-project.org/web/checks/check_results_keypress.html
22 https://cloud.r-project.org/web/checks/check_results_keyring.html
23 https://cloud.r-project.org/web/checks/check_results_liteq.html
24 https://cloud.r-project.org/web/checks/check_results_lpSolve.html
25 https://cloud.r-project.org/web/checks/check_results_oskeyring.html
26 https://cloud.r-project.org/web/checks/check_results_pak.html
27 https://cloud.r-project.org/web/checks/check_results_parsedate.html
28 https://cloud.r-project.org/web/checks/check_results_pingr.html
29 https://cloud.r-project.org/web/checks/check_results_pkgcache.html
30 https://cloud.r-project.org/web/checks/check_results_pkgconfig.html
31 https://cloud.r-project.org/web/checks/check_results_pkgsearch.html
32 https://cloud.r-project.org/web/checks/check_results_praise.html
33 https://cloud.r-project.org/web/checks/check_results_presser.html
34 https://cloud.r-project.org/web/checks/check_results_prettycode.html
35 https://cloud.r-project.org/web/checks/check_results_prettyunits.html
36 https://cloud.r-project.org/web/checks/check_results_processx.html
37 https://cloud.r-project.org/web/checks/check_results_progress.html
38 https://cloud.r-project.org/web/checks/check_results_prompt.html
39 https://cloud.r-project.org/web/checks/check_results_ps.html
40 https://cloud.r-project.org/web/checks/check_results_rcmdcheck.html
41 https://cloud.r-project.org/web/checks/check_results_rcorpora.html
42 https://cloud.r-project.org/web/checks/check_results_rematch2.html
43 https://cloud.r-project.org/web/checks/check_results_rhub.html
44 https://cloud.r-project.org/web/checks/check_results_rversions.html
45 https://cloud.r-project.org/web/checks/check_results_sankey.html
46 https://cloud.r-project.org/web/checks/check_results_secret.html
47 https://cloud.r-project.org/web/checks/check_results_sessioninfo.html
48 https://cloud.r-project.org/web/checks/check_results_showimage.html
49 https://cloud.r-project.org/web/checks/check_results_tracer.html
50 https://cloud.r-project.org/web/checks/check_results_webdriver.html
51 https://cloud.r-project.org/web/checks/check_results_webfakes.html
52 https://cloud.r-project.org/web/checks/check_results_whoami.html
53 https://cloud.r-project.org/web/checks/check_results_xmlparsedata.html
54 https://cloud.r-project.org/web/checks/check_results_xopen.html
55 https://cloud.r-project.org/web/checks/check_results_zip.html
check_result version
1 OK, 12 NA
2 OK, 12 NA
3 OK, 12 NA
4 OK, 12 NA
5 OK, 12 NA
6 OK, 12 NA
7 OK, 12 NA
8 OK, 12 NA
9 OK, 12 NA
10 OK, 12 NA
11 ERROR, OK, 1, 11 NA
12 OK, 12 NA
13 OK, 12 NA
14 OK, 12 NA
15 OK, 12 NA
16 OK, 12 NA
17 OK, 12 NA
18 NOTE, OK, 7, 5 NA
19 OK, 12 NA
20 OK, 12 NA
21 OK, 12 NA
22 NOTE, OK, 2, 10 NA
23 OK, 12 NA
24 OK, 12 NA
25 OK, 12 NA
26 NOTE, OK, 1, 11 NA
27 OK, 12 NA
28 OK, 12 NA
29 ERROR, OK, 1, 11 NA
30 OK, 12 NA
31 OK, 12 NA
32 OK, 12 NA
33 ERROR, OK, 1, 11 NA
34 OK, 12 NA
35 OK, 12 NA
36 OK, 12 NA
37 OK, 12 NA
38 ERROR, OK, 1, 2 NA
39 OK, 12 NA
40 NOTE, OK, 1, 11 NA
41 NOTE, OK, 7, 5 NA
42 NOTE, OK, 1, 11 NA
43 OK, 12 NA
44 OK, 12 NA
45 OK, 12 NA
46 OK, 12 NA
47 OK, 12 NA
48 OK, 12 NA
49 OK, 12 NA
50 OK, 12 NA
51 ERROR, OK, 1, 11 NA
52 OK, 12 NA
53 OK, 12 NA
54 OK, 12 NA
55 ERROR, OK, 1, 11 NA
Packages
Get packages based checks.
Function of the cchecks R package: cch_pkgs().
Packages
Get checks data for all packages.
GET [/pkgs]
Default limit of 10, max of 1000.
Example with custom offset and limit.
curl https://cranchecks.info/pkgs/?offset=5&limit=2 | jq .
HTTP/2 200
access-control-allow-methods: HEAD, GET
access-control-allow-origin: *
cache-control: public, must-revalidate, max-age=60
content-type: application/json; charset=utf8
server: Caddy
x-content-type-options: nosniff
content-length: 6584
date: Mon, 22 Mar 2021 13:00:33 GMT
{
"found": 18764,
"count": 2,
"offset": 5,
"error": null,
"data": [
{
"package": "quantable",
"url": "https://cloud.r-project.org/web/checks/check_results_quantable.html",
"date_updated": "2021-03-22T12:04:37.342Z",
"summary": {
"any": false,
"ok": 13,
"note": 0,
"warn": 0,
"error": 0,
"fail": 0
},
"checks": [
{
"flavor": "r-devel-linux-x86_64-debian-clang",
"version": "0.3.6",
"tinstall": 15.14,
"tcheck": 146.67,
"ttotal": 161.81,
"status": "OK",
"check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-debian-clang/quantable-00check.html"
},
{
"flavor": "r-devel-linux-x86_64-debian-gcc",
"version": "0.3.6",
"tinstall": 13.12,
"tcheck": 110,
"ttotal": 123.12,
"status": "OK",
"check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-debian-gcc/quantable-00check.html"
},
{
"flavor": "r-devel-linux-x86_64-fedora-clang",
"version": "0.3.6",
"tinstall": 0,
"tcheck": 0,
"ttotal": 197.37,
"status": "OK",
"check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-fedora-clang/quantable-00check.html"
},
{
"flavor": "r-devel-linux-x86_64-fedora-gcc",
"version": "0.3.6",
"tinstall": 0,
"tcheck": 0,
"ttotal": 188.05,
"status": "OK",
"check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-fedora-gcc/quantable-00check.html"
},
{
"flavor": "r-devel-windows-ix86+x86_64",
"version": "0.3.6",
"tinstall": 31,
"tcheck": 188,
"ttotal": 219,
"status": "OK",
"check_url": "https://www.R-project.org/nosvn/R.check/r-devel-windows-ix86+x86_64/quantable-00check.html"
},
{
"flavor": "r-devel-windows-x86_64-gcc10-UCRT",
"version": "0.3.6",
"tinstall": 0,
"tcheck": 0,
"ttotal": 0,
"status": "OK",
"check_url": "https://www.R-project.org/nosvn/R.check/r-devel-windows-x86_64-gcc10-UCRT/quantable-00check.html"
},
{
"flavor": "r-patched-linux-x86_64",
"version": "0.3.6",
"tinstall": 14.34,
"tcheck": 137.8,
"ttotal": 152.14,
"status": "OK",
"check_url": "https://www.R-project.org/nosvn/R.check/r-patched-linux-x86_64/quantable-00check.html"
},
{
"flavor": "r-patched-solaris-x86",
"version": "0.3.6",
"tinstall": 0,
"tcheck": 0,
"ttotal": 269.1,
"status": "OK",
"check_url": "https://www.R-project.org/nosvn/R.check/r-patched-solaris-x86/quantable-00check.html"
},
{
"flavor": "r-release-linux-x86_64",
"version": "0.3.6",
"tinstall": 14.58,
"tcheck": 137.45,
"ttotal": 152.03,
"status": "OK",
"check_url": "https://www.R-project.org/nosvn/R.check/r-release-linux-x86_64/quantable-00check.html"
},
{
"flavor": "r-release-macos-x86_64",
"version": "0.3.6",
"tinstall": 0,
"tcheck": 0,
"ttotal": 0,
"status": "OK",
"check_url": "https://www.R-project.org/nosvn/R.check/r-release-macos-x86_64/quantable-00check.html"
},
{
"flavor": "r-release-windows-ix86+x86_64",
"version": "0.3.6",
"tinstall": 38,
"tcheck": 183,
"ttotal": 221,
"status": "OK",
"check_url": "https://www.R-project.org/nosvn/R.check/r-release-windows-ix86+x86_64/quantable-00check.html"
},
{
"flavor": "r-oldrel-macos-x86_64",
"version": "0.3.6",
"tinstall": 0,
"tcheck": 0,
"ttotal": 0,
"status": "OK",
"check_url": "https://www.R-project.org/nosvn/R.check/r-oldrel-macos-x86_64/quantable-00check.html"
},
{
"flavor": "r-oldrel-windows-ix86+x86_64",
"version": "0.3.6",
"tinstall": 26,
"tcheck": 142,
"ttotal": 168,
"status": "OK",
"check_url": "https://www.R-project.org/nosvn/R.check/r-oldrel-windows-ix86+x86_64/quantable-00check.html"
}
],
"check_details": null
},
{
"package": "ibb",
"url": "https://cloud.r-project.org/web/checks/check_results_ibb.html",
"date_updated": "2021-03-22T12:04:37.342Z",
"summary": {
"any": true,
"ok": 7,
"note": 6,
"warn": 0,
"error": 0,
"fail": 0
},
"checks": [
{
"flavor": "r-devel-linux-x86_64-debian-clang",
"version": "0.0.2",
"tinstall": 2.35,
"tcheck": 28.08,
"ttotal": 30.43,
"status": "OK",
"check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-debian-clang/ibb-00check.html"
},
{
"flavor": "r-devel-linux-x86_64-debian-gcc",
"version": "0.0.2",
"tinstall": 1.83,
"tcheck": 21.76,
"ttotal": 23.59,
"status": "OK",
"check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-debian-gcc/ibb-00check.html"
},
{
"flavor": "r-devel-linux-x86_64-fedora-clang",
"version": "0.0.2",
"tinstall": 0,
"tcheck": 0,
"ttotal": 45.87,
"status": "NOTE",
"check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-fedora-clang/ibb-00check.html"
},
{
"flavor": "r-devel-linux-x86_64-fedora-gcc",
"version": "0.0.2",
"tinstall": 0,
"tcheck": 0,
"ttotal": 36.1,
"status": "NOTE",
"check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-fedora-gcc/ibb-00check.html"
},
{
"flavor": "r-devel-windows-ix86+x86_64",
"version": "0.0.2",
"tinstall": 6,
"tcheck": 46,
"ttotal": 52,
"status": "OK",
"check_url": "https://www.R-project.org/nosvn/R.check/r-devel-windows-ix86+x86_64/ibb-00check.html"
},
{
"flavor": "r-devel-windows-x86_64-gcc10-UCRT",
"version": "0.0.2",
"tinstall": 0,
"tcheck": 0,
"ttotal": 0,
"status": "NOTE",
"check_url": "https://www.R-project.org/nosvn/R.check/r-devel-windows-x86_64-gcc10-UCRT/ibb-00check.html"
},
{
"flavor": "r-patched-linux-x86_64",
"version": "0.0.2",
"tinstall": 2.33,
"tcheck": 27.84,
"ttotal": 30.17,
"status": "OK",
"check_url": "https://www.R-project.org/nosvn/R.check/r-patched-linux-x86_64/ibb-00check.html"
},
{
"flavor": "r-patched-solaris-x86",
"version": "0.0.2",
"tinstall": 0,
"tcheck": 0,
"ttotal": 55.8,
"status": "NOTE",
"check_url": "https://www.R-project.org/nosvn/R.check/r-patched-solaris-x86/ibb-00check.html"
},
{
"flavor": "r-release-linux-x86_64",
"version": "0.0.2",
"tinstall": 2.27,
"tcheck": 28.07,
"ttotal": 30.34,
"status": "OK",
"check_url": "https://www.R-project.org/nosvn/R.check/r-release-linux-x86_64/ibb-00check.html"
},
{
"flavor": "r-release-macos-x86_64",
"version": "0.0.2",
"tinstall": 0,
"tcheck": 0,
"ttotal": 0,
"status": "NOTE",
"check_url": "https://www.R-project.org/nosvn/R.check/r-release-macos-x86_64/ibb-00check.html"
},
{
"flavor": "r-release-windows-ix86+x86_64",
"version": "0.0.2",
"tinstall": 6,
"tcheck": 47,
"ttotal": 53,
"status": "OK",
"check_url": "https://www.R-project.org/nosvn/R.check/r-release-windows-ix86+x86_64/ibb-00check.html"
},
{
"flavor": "r-oldrel-macos-x86_64",
"version": "0.0.2",
"tinstall": 0,
"tcheck": 0,
"ttotal": 0,
"status": "NOTE",
"check_url": "https://www.R-project.org/nosvn/R.check/r-oldrel-macos-x86_64/ibb-00check.html"
},
{
"flavor": "r-oldrel-windows-ix86+x86_64",
"version": "0.0.2",
"tinstall": 3,
"tcheck": 34,
"ttotal": 37,
"status": "OK",
"check_url": "https://www.R-project.org/nosvn/R.check/r-oldrel-windows-ix86+x86_64/ibb-00check.html"
}
],
"check_details": {
"details": [
{
"version": "0.0.2",
"output": " Note: found 359 marked UTF-8 strings",
"check": "data for non-ASCII characters",
"flavors": [
"r-devel-linux-x86_64-fedora-clang",
"r-devel-linux-x86_64-fedora-gcc",
"r-devel-windows-x86_64-gcc10-UCRT",
"r-patched-solaris-x86",
"r-release-macos-x86_64",
"r-oldrel-macos-x86_64"
]
}
],
"additional_issues": null
}
}
]
}
cchecks::cch_pkgs(
limit = 2,
offset = 5
)
$found
[1] 18764
$count
[1] 2
$offset
[1] 5
$error
NULL
$data
package url
1 quantable https://cloud.r-project.org/web/checks/check_results_quantable.html
2 ibb https://cloud.r-project.org/web/checks/check_results_ibb.html
date_updated summary.any summary.ok summary.note summary.warn
1 2021-03-22T12:04:37.342Z FALSE 13 0 0
2 2021-03-22T12:04:37.342Z TRUE 7 6 0
summary.error summary.fail
1 0 0
2 0 0
checks
1 r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-ix86+x86_64, r-devel-windows-x86_64-gcc10-UCRT, r-patched-linux-x86_64, r-patched-solaris-x86, r-release-linux-x86_64, r-release-macos-x86_64, r-release-windows-ix86+x86_64, r-oldrel-macos-x86_64, r-oldrel-windows-ix86+x86_64, 0.3.6, 0.3.6, 0.3.6, 0.3.6, 0.3.6, 0.3.6, 0.3.6, 0.3.6, 0.3.6, 0.3.6, 0.3.6, 0.3.6, 0.3.6, 15.14, 13.12, 0, 0, 31, 0, 14.34, 0, 14.58, 0, 38, 0, 26, 146.67, 110, 0, 0, 188, 0, 137.8, 0, 137.45, 0, 183, 0, 142, 161.81, 123.12, 197.37, 188.05, 219, 0, 152.14, 269.1, 152.03, 0, 221, 0, 168, OK, OK, OK, OK, OK, OK, OK, OK, OK, OK, OK, OK, OK, https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-debian-clang/quantable-00check.html, https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-debian-gcc/quantable-00check.html, https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-fedora-clang/quantable-00check.html, https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-fedora-gcc/quantable-00check.html, https://www.R-project.org/nosvn/R.check/r-devel-windows-ix86+x86_64/quantable-00check.html, https://www.R-project.org/nosvn/R.check/r-devel-windows-x86_64-gcc10-UCRT/quantable-00check.html, https://www.R-project.org/nosvn/R.check/r-patched-linux-x86_64/quantable-00check.html, https://www.R-project.org/nosvn/R.check/r-patched-solaris-x86/quantable-00check.html, https://www.R-project.org/nosvn/R.check/r-release-linux-x86_64/quantable-00check.html, https://www.R-project.org/nosvn/R.check/r-release-macos-x86_64/quantable-00check.html, https://www.R-project.org/nosvn/R.check/r-release-windows-ix86+x86_64/quantable-00check.html, https://www.R-project.org/nosvn/R.check/r-oldrel-macos-x86_64/quantable-00check.html, https://www.R-project.org/nosvn/R.check/r-oldrel-windows-ix86+x86_64/quantable-00check.html
2 r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-ix86+x86_64, r-devel-windows-x86_64-gcc10-UCRT, r-patched-linux-x86_64, r-patched-solaris-x86, r-release-linux-x86_64, r-release-macos-x86_64, r-release-windows-ix86+x86_64, r-oldrel-macos-x86_64, r-oldrel-windows-ix86+x86_64, 0.0.2, 0.0.2, 0.0.2, 0.0.2, 0.0.2, 0.0.2, 0.0.2, 0.0.2, 0.0.2, 0.0.2, 0.0.2, 0.0.2, 0.0.2, 2.35, 1.83, 0, 0, 6, 0, 2.33, 0, 2.27, 0, 6, 0, 3, 28.08, 21.76, 0, 0, 46, 0, 27.84, 0, 28.07, 0, 47, 0, 34, 30.43, 23.59, 45.87, 36.1, 52, 0, 30.17, 55.8, 30.34, 0, 53, 0, 37, OK, OK, NOTE, NOTE, OK, NOTE, OK, NOTE, OK, NOTE, OK, NOTE, OK, https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-debian-clang/ibb-00check.html, https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-debian-gcc/ibb-00check.html, https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-fedora-clang/ibb-00check.html, https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-fedora-gcc/ibb-00check.html, https://www.R-project.org/nosvn/R.check/r-devel-windows-ix86+x86_64/ibb-00check.html, https://www.R-project.org/nosvn/R.check/r-devel-windows-x86_64-gcc10-UCRT/ibb-00check.html, https://www.R-project.org/nosvn/R.check/r-patched-linux-x86_64/ibb-00check.html, https://www.R-project.org/nosvn/R.check/r-patched-solaris-x86/ibb-00check.html, https://www.R-project.org/nosvn/R.check/r-release-linux-x86_64/ibb-00check.html, https://www.R-project.org/nosvn/R.check/r-release-macos-x86_64/ibb-00check.html, https://www.R-project.org/nosvn/R.check/r-release-windows-ix86+x86_64/ibb-00check.html, https://www.R-project.org/nosvn/R.check/r-oldrel-macos-x86_64/ibb-00check.html, https://www.R-project.org/nosvn/R.check/r-oldrel-windows-ix86+x86_64/ibb-00check.html
check_details.details
1 NULL
2 0.0.2, Note: found 359 marked UTF-8 strings, data for non-ASCII characters, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-x86_64-gcc10-UCRT, r-patched-solaris-x86, r-release-macos-x86_64, r-oldrel-macos-x86_64
check_details.additional_issues
1 NA
2 NA
Packages by name
Get checks summary by package name.
Function of the cchecks package: cch_pkgs_history()
GET [/pkgs/{package}]
curl https://cranchecks.info/pkgs/rhub | jq .
HTTP/2 200
access-control-allow-methods: HEAD, GET
access-control-allow-origin: *
cache-control: public, must-revalidate, max-age=60
content-type: application/json; charset=utf8
server: Caddy
x-content-type-options: nosniff
content-length: 3072
date: Mon, 22 Mar 2021 13:00:33 GMT
{
"error": null,
"data": {
"package": "rhub",
"url": "https://cloud.r-project.org/web/checks/check_results_rhub.html",
"date_updated": "2021-03-22T12:04:37.632Z",
"summary": {
"any": false,
"ok": 13,
"note": 0,
"warn": 0,
"error": 0,
"fail": 0
},
"checks": [
{
"flavor": "r-devel-linux-x86_64-debian-clang",
"version": "1.1.1",
"tinstall": 8.18,
"tcheck": 50.72,
"ttotal": 58.9,
"status": "OK",
"check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-debian-clang/rhub-00check.html"
},
{
"flavor": "r-devel-linux-x86_64-debian-gcc",
"version": "1.1.1",
"tinstall": 6.16,
"tcheck": 38.81,
"ttotal": 44.97,
"status": "OK",
"check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-debian-gcc/rhub-00check.html"
},
{
"flavor": "r-devel-linux-x86_64-fedora-clang",
"version": "1.1.1",
"tinstall": 0,
"tcheck": 0,
"ttotal": 76.56,
"status": "OK",
"check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-fedora-clang/rhub-00check.html"
},
{
"flavor": "r-devel-linux-x86_64-fedora-gcc",
"version": "1.1.1",
"tinstall": 0,
"tcheck": 0,
"ttotal": 83.08,
"status": "OK",
"check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-fedora-gcc/rhub-00check.html"
},
{
"flavor": "r-devel-windows-ix86+x86_64",
"version": "1.1.1",
"tinstall": 16,
"tcheck": 76,
"ttotal": 92,
"status": "OK",
"check_url": "https://www.R-project.org/nosvn/R.check/r-devel-windows-ix86+x86_64/rhub-00check.html"
},
{
"flavor": "r-devel-windows-x86_64-gcc10-UCRT",
"version": "1.1.1",
"tinstall": 0,
"tcheck": 0,
"ttotal": 0,
"status": "OK",
"check_url": "https://www.R-project.org/nosvn/R.check/r-devel-windows-x86_64-gcc10-UCRT/rhub-00check.html"
},
{
"flavor": "r-patched-linux-x86_64",
"version": "1.1.1",
"tinstall": 6.96,
"tcheck": 48.12,
"ttotal": 55.08,
"status": "OK",
"check_url": "https://www.R-project.org/nosvn/R.check/r-patched-linux-x86_64/rhub-00check.html"
},
{
"flavor": "r-patched-solaris-x86",
"version": "1.1.1",
"tinstall": 0,
"tcheck": 0,
"ttotal": 89.8,
"status": "OK",
"check_url": "https://www.R-project.org/nosvn/R.check/r-patched-solaris-x86/rhub-00check.html"
},
{
"flavor": "r-release-linux-x86_64",
"version": "1.1.1",
"tinstall": 7.31,
"tcheck": 48.85,
"ttotal": 56.16,
"status": "OK",
"check_url": "https://www.R-project.org/nosvn/R.check/r-release-linux-x86_64/rhub-00check.html"
},
{
"flavor": "r-release-macos-x86_64",
"version": "1.1.1",
"tinstall": 0,
"tcheck": 0,
"ttotal": 0,
"status": "OK",
"check_url": "https://www.R-project.org/nosvn/R.check/r-release-macos-x86_64/rhub-00check.html"
},
{
"flavor": "r-release-windows-ix86+x86_64",
"version": "1.1.1",
"tinstall": 18,
"tcheck": 71,
"ttotal": 89,
"status": "OK",
"check_url": "https://www.R-project.org/nosvn/R.check/r-release-windows-ix86+x86_64/rhub-00check.html"
},
{
"flavor": "r-oldrel-macos-x86_64",
"version": "1.1.1",
"tinstall": 0,
"tcheck": 0,
"ttotal": 0,
"status": "OK",
"check_url": "https://www.R-project.org/nosvn/R.check/r-oldrel-macos-x86_64/rhub-00check.html"
},
{
"flavor": "r-oldrel-windows-ix86+x86_64",
"version": "1.1.1",
"tinstall": 8,
"tcheck": 54,
"ttotal": 62,
"status": "OK",
"check_url": "https://www.R-project.org/nosvn/R.check/r-oldrel-windows-ix86+x86_64/rhub-00check.html"
}
],
"check_details": null
}
}
cchecks::cch_pkgs(x = "rhub")
$error
NULL
$data
$data$package
[1] "rhub"
$data$url
[1] "https://cloud.r-project.org/web/checks/check_results_rhub.html"
$data$date_updated
[1] "2021-03-22T12:04:37.632Z"
$data$summary
$data$summary$any
[1] FALSE
$data$summary$ok
[1] 13
$data$summary$note
[1] 0
$data$summary$warn
[1] 0
$data$summary$error
[1] 0
$data$summary$fail
[1] 0
$data$checks
flavor version tinstall tcheck ttotal status
1 r-devel-linux-x86_64-debian-clang 1.1.1 8.18 50.72 58.90 OK
2 r-devel-linux-x86_64-debian-gcc 1.1.1 6.16 38.81 44.97 OK
3 r-devel-linux-x86_64-fedora-clang 1.1.1 0.00 0.00 76.56 OK
4 r-devel-linux-x86_64-fedora-gcc 1.1.1 0.00 0.00 83.08 OK
5 r-devel-windows-ix86+x86_64 1.1.1 16.00 76.00 92.00 OK
6 r-devel-windows-x86_64-gcc10-UCRT 1.1.1 0.00 0.00 0.00 OK
7 r-patched-linux-x86_64 1.1.1 6.96 48.12 55.08 OK
8 r-patched-solaris-x86 1.1.1 0.00 0.00 89.80 OK
9 r-release-linux-x86_64 1.1.1 7.31 48.85 56.16 OK
10 r-release-macos-x86_64 1.1.1 0.00 0.00 0.00 OK
11 r-release-windows-ix86+x86_64 1.1.1 18.00 71.00 89.00 OK
12 r-oldrel-macos-x86_64 1.1.1 0.00 0.00 0.00 OK
13 r-oldrel-windows-ix86+x86_64 1.1.1 8.00 54.00 62.00 OK
check_url
1 https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-debian-clang/rhub-00check.html
2 https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-debian-gcc/rhub-00check.html
3 https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-fedora-clang/rhub-00check.html
4 https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-fedora-gcc/rhub-00check.html
5 https://www.R-project.org/nosvn/R.check/r-devel-windows-ix86+x86_64/rhub-00check.html
6 https://www.R-project.org/nosvn/R.check/r-devel-windows-x86_64-gcc10-UCRT/rhub-00check.html
7 https://www.R-project.org/nosvn/R.check/r-patched-linux-x86_64/rhub-00check.html
8 https://www.R-project.org/nosvn/R.check/r-patched-solaris-x86/rhub-00check.html
9 https://www.R-project.org/nosvn/R.check/r-release-linux-x86_64/rhub-00check.html
10 https://www.R-project.org/nosvn/R.check/r-release-macos-x86_64/rhub-00check.html
11 https://www.R-project.org/nosvn/R.check/r-release-windows-ix86+x86_64/rhub-00check.html
12 https://www.R-project.org/nosvn/R.check/r-oldrel-macos-x86_64/rhub-00check.html
13 https://www.R-project.org/nosvn/R.check/r-oldrel-windows-ix86+x86_64/rhub-00check.html
$data$check_details
NULL
Packages by name (history)
Get checks history by package name.
GET [/pkgs]
Default limit of 10, max of 50.
GET [/pkgs/{package}/history]
curl https://cranchecks.info/pkgs/rhub/history | jq .
HTTP/2 200
access-control-allow-methods: HEAD, GET
access-control-allow-origin: *
cache-control: public, must-revalidate, max-age=60
content-type: application/json; charset=utf8
server: Caddy
x-content-type-options: nosniff
content-length: 27907
date: Mon, 22 Mar 2021 13:00:34 GMT
{
"error": null,
"data": {
"package": "rhub",
"history": [
{
"date_updated": "2021-03-21T15:04:03.000Z",
"summary": {
"any": false,
"ok": 13,
"note": 0,
"warn": 0,
"error": 0,
"fail": 0
},
"checks": [
{
"flavor": "r-devel-linux-x86_64-debian-clang",
"version": "1.1.1",
"tinstall": 7.29,
"tcheck": 50.91,
"ttotal": 58.2,
"status": "OK",
"check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-debian-clang/rhub-00check.html"
},
{
"flavor": "r-devel-linux-x86_64-debian-gcc",
"version": "1.1.1",
"tinstall": 5.59,
"tcheck": 39.05,
"ttotal": 44.64,
"status": "OK",
"check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-debian-gcc/rhub-00check.html"
},
{
"flavor": "r-devel-linux-x86_64-fedora-clang",
"version": "1.1.1",
"tinstall": 0,
"tcheck": 0,
"ttotal": 76.56,
"status": "OK",
"check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-fedora-clang/rhub-00check.html"
},
{
"flavor": "r-devel-linux-x86_64-fedora-gcc",
"version": "1.1.1",
"tinstall": 0,
"tcheck": 0,
"ttotal": 83.47,
"status": "OK",
"check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-fedora-gcc/rhub-00check.html"
},
{
"flavor": "r-devel-windows-ix86+x86_64",
"version": "1.1.1",
"tinstall": 16,
"tcheck": 76,
"ttotal": 92,
"status": "OK",
"check_url": "https://www.R-project.org/nosvn/R.check/r-devel-windows-ix86+x86_64/rhub-00check.html"
},
{
"flavor": "r-devel-windows-x86_64-gcc10-UCRT",
"version": "1.1.1",
"tinstall": 0,
"tcheck": 0,
"ttotal": 0,
"status": "OK",
"check_url": "https://www.R-project.org/nosvn/R.check/r-devel-windows-x86_64-gcc10-UCRT/rhub-00check.html"
},
{
"flavor": "r-patched-linux-x86_64",
"version": "1.1.1",
"tinstall": 6.96,
"tcheck": 48.12,
"ttotal": 55.08,
"status": "OK",
"check_url": "https://www.R-project.org/nosvn/R.check/r-patched-linux-x86_64/rhub-00check.html"
},
{
"flavor": "r-patched-solaris-x86",
"version": "1.1.1",
"tinstall": 0,
"tcheck": 0,
"ttotal": 89.8,
"status": "OK",
"check_url": "https://www.R-project.org/nosvn/R.check/r-patched-solaris-x86/rhub-00check.html"
},
{
"flavor": "r-release-linux-x86_64",
"version": "1.1.1",
"tinstall": 7.31,
"tcheck": 48.85,
"ttotal": 56.16,
"status": "OK",
"check_url": "https://www.R-project.org/nosvn/R.check/r-release-linux-x86_64/rhub-00check.html"
},
{
"flavor": "r-release-macos-x86_64",
"version": "1.1.1",
"tinstall": 0,
"tcheck": 0,
"ttotal": 0,
"status": "OK",
"check_url": "https://www.R-project.org/nosvn/R.check/r-release-macos-x86_64/rhub-00check.html"
},
{
"flavor": "r-release-windows-ix86+x86_64",
"version": "1.1.1",
"tinstall": 18,
"tcheck": 71,
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{
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{
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"check_url": "https://www.R-project.org/nosvn/R.check/r-release-linux-x86_64/rhub-00check.html"
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{
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{
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{
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"check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-fedora-clang/rhub-00check.html"
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"check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-fedora-gcc/rhub-00check.html"
},
{
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"check_url": "https://www.R-project.org/nosvn/R.check/r-devel-windows-x86_64-gcc10-UCRT/rhub-00check.html"
},
{
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"status": "OK",
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{
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{
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{
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{
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},
{
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}
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},
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},
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},
{
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},
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},
{
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"status": "OK",
"check_url": "https://www.R-project.org/nosvn/R.check/r-release-macos-x86_64/rhub-00check.html"
},
{
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},
{
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},
{
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}
],
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}
]
}
}
cchecks::cch_pkgs_history(x = "rhub")
$error
NULL
$data
$data$package
[1] "rhub"
$data$history
# A tibble: 30 x 4
date_updated summary$any $ok $note $warn $error $fail checks check_details
<chr> <lgl> <int> <int> <int> <int> <int> <list> <lgl>
1 2021-03-21T1… FALSE 13 0 0 0 0 <df[,… NA
2 2021-03-20T1… FALSE 13 0 0 0 0 <df[,… NA
3 2021-03-19T1… FALSE 13 0 0 0 0 <df[,… NA
4 2021-03-18T1… FALSE 13 0 0 0 0 <df[,… NA
5 2021-03-17T1… FALSE 12 0 0 0 0 <df[,… NA
6 2021-03-16T1… FALSE 12 0 0 0 0 <df[,… NA
7 2021-03-15T1… FALSE 11 0 0 0 0 <df[,… NA
8 2021-03-14T1… FALSE 11 0 0 0 0 <df[,… NA
9 2021-03-13T1… FALSE 11 0 0 0 0 <df[,… NA
10 2021-03-12T1… FALSE 13 0 0 0 0 <df[,… NA
# … with 20 more rows
For historical data across packages see the history endpoint.
Badges
Get packages based checks to display in your package README for instance.
In a Markdown-based README to add a badge you just need something like .
You might want the badge to point at either the CRAN results page or the CRAN checks API page i.e. either
[](https://cran.r-project.org/web/checks/check_results_rhub.html) to obtain .
or
[](https://cranchecks.info/pkgs/rhub) to obtain .
Summary badges
Get badge for CRAN checks summary by package name.
GET [/badges/summary/{package_name}]
[](https://cranchecks.info/pkgs/rhub) gives .
curl https://cranchecks.info/badges/summary/rhub
HTTP/2 200
cache-control: max-age=300, public
content-type: image/svg+xml; charset=utf-8
expires: Mon, 22 Mar 2021 13:05:17 GMT
server: Caddy
x-content-type-options: nosniff
content-length: 855
date: Mon, 22 Mar 2021 13:00:17 GMT
<?xml version="1.0" encoding="UTF-8"?>
<svg xmlns="http://www.w3.org/2000/svg" width="70" height="20">
<linearGradient id="b" x2="0" y2="100%">
<stop offset="0" stop-color="#bbb" stop-opacity=".1"/>
<stop offset="1" stop-opacity=".1"/>
</linearGradient>
<mask id="a">
<rect width="70" height="20" rx="3" fill="#fff"/>
</mask>
<g mask="url(#a)">
<path fill="#555" d="M0 0h43v20H0z"/>
<path fill="#4c1" d="M43 0h46.5v20H43z"/>
<path fill="url(#b)" d="M0 0h70v20H0z"/>
</g>
<g fill="#fff" text-anchor="middle" font-family="DejaVu Sans,Verdana,Geneva,sans-serif" font-size="11">
<text x="21.5" y="15" fill="#010101" fill-opacity=".3">
CRAN
</text>
<text x="21.5" y="14">
CRAN
</text>
<text x="55.5" y="15" fill="#010101" fill-opacity=".3">
OK
</text>
<text x="55.5" y="14">
OK
</text>
</g>
</svg>
Worst badges
Get badge for CRAN checks worst result by package name. 😰
GET [/badges/worst/{package_name}]
[](https://cranchecks.info/pkgs/rhub) gives .
curl https://cranchecks.info/badges/worst/rhub
HTTP/2 200
cache-control: max-age=300, public
content-type: image/svg+xml; charset=utf-8
expires: Mon, 22 Mar 2021 13:05:17 GMT
server: Caddy
x-content-type-options: nosniff
content-length: 855
date: Mon, 22 Mar 2021 13:00:17 GMT
<?xml version="1.0" encoding="UTF-8"?>
<svg xmlns="http://www.w3.org/2000/svg" width="70" height="20">
<linearGradient id="b" x2="0" y2="100%">
<stop offset="0" stop-color="#bbb" stop-opacity=".1"/>
<stop offset="1" stop-opacity=".1"/>
</linearGradient>
<mask id="a">
<rect width="70" height="20" rx="3" fill="#fff"/>
</mask>
<g mask="url(#a)">
<path fill="#555" d="M0 0h43v20H0z"/>
<path fill="#4c1" d="M43 0h46.5v20H43z"/>
<path fill="url(#b)" d="M0 0h70v20H0z"/>
</g>
<g fill="#fff" text-anchor="middle" font-family="DejaVu Sans,Verdana,Geneva,sans-serif" font-size="11">
<text x="21.5" y="15" fill="#010101" fill-opacity=".3">
CRAN
</text>
<text x="21.5" y="14">
CRAN
</text>
<text x="55.5" y="15" fill="#010101" fill-opacity=".3">
OK
</text>
<text x="55.5" y="14">
OK
</text>
</g>
</svg>
Flavor badges
Get badge for summary of CRAN checks by flavor and package name.
GET [/badges/flavor/{flavor}/{package}]
[](https://cranchecks.info/pkgs/rhub) gives .
curl https://cranchecks.info/badges/flavor/r-devel-linux-x86_64-debian-clang/rhub
HTTP/2 200
cache-control: max-age=300, public
content-type: image/svg+xml; charset=utf-8
expires: Mon, 22 Mar 2021 13:05:17 GMT
server: Caddy
x-content-type-options: nosniff
content-length: 855
date: Mon, 22 Mar 2021 13:00:17 GMT
<?xml version="1.0" encoding="UTF-8"?>
<svg xmlns="http://www.w3.org/2000/svg" width="70" height="20">
<linearGradient id="b" x2="0" y2="100%">
<stop offset="0" stop-color="#bbb" stop-opacity=".1"/>
<stop offset="1" stop-opacity=".1"/>
</linearGradient>
<mask id="a">
<rect width="70" height="20" rx="3" fill="#fff"/>
</mask>
<g mask="url(#a)">
<path fill="#555" d="M0 0h43v20H0z"/>
<path fill="#4c1" d="M43 0h46.5v20H43z"/>
<path fill="url(#b)" d="M0 0h70v20H0z"/>
</g>
<g fill="#fff" text-anchor="middle" font-family="DejaVu Sans,Verdana,Geneva,sans-serif" font-size="11">
<text x="21.5" y="15" fill="#010101" fill-opacity=".3">
CRAN
</text>
<text x="21.5" y="14">
CRAN
</text>
<text x="55.5" y="15" fill="#010101" fill-opacity=".3">
OK
</text>
<text x="55.5" y="14">
OK
</text>
</g>
</svg>
History
The /history/:date route allows GET requests only. The route is intended for fetching compressed new-line delimited JSON for an individual date, where all CRAN checks data across all packages is combined.
Parameter:
:date- should be of the form
YYYY-MM-DD, the minimal value is 2018-12-18.
A request to /history/:date leads to a redirect (http status 302) and a returned JSON body with a message telling the user to follow the link in the Location response header in case they aren’t familiar with redirects. The link to follow is a temporary Amazon S3 link to the JSON file for the given date.
One can automatically get the link to the JSON file by following the redirect. You can do this in curl with the -L flag, or in R by using the followlocation curl option like followlocation=1.
An important note is the data in the JSON file is NOT valid JSON as an entire entity. Each line of the file IS valid JSON; called newline delimited JSON (NDJSON). You don’t have to worry about these details if you use cchecks::cch_history(), which takes care of downloading the file and reading in the compressed NDJSON. On the command line, you can do e.g, download the file, save to a .json.gz gzip-compressed file extension, then in the next line decompress the file with gzip, then pipe to jq, and use head to get the first 10 lines
curl -vL https://cranchecks.info/history/2020-04-01 > 2020-04-01.json.gz
gzip -dc 2020-04-01.json.gz | jq . | head -n 2
% Total % Received % Xferd Average Speed Time Time Time Current
Dload Upload Total Spent Left Speed
0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0* Trying 52.34.4.0:443...
* Connected to cranchecks.info (52.34.4.0) port 443 (#0)
* ALPN, offering h2
* ALPN, offering http/1.1
} [5 bytes data]
* TLSv1.3 (OUT), TLS handshake, Client hello (1):
} [512 bytes data]
* TLSv1.3 (IN), TLS handshake, Server hello (2):
{ [122 bytes data]
* TLSv1.3 (IN), TLS handshake, Encrypted Extensions (8):
{ [15 bytes data]
* TLSv1.3 (IN), TLS handshake, Certificate (11):
{ [2263 bytes data]
* TLSv1.3 (IN), TLS handshake, CERT verify (15):
{ [79 bytes data]
* TLSv1.3 (IN), TLS handshake, Finished (20):
{ [36 bytes data]
* TLSv1.3 (OUT), TLS change cipher, Change cipher spec (1):
} [1 bytes data]
* TLSv1.3 (OUT), TLS handshake, Finished (20):
} [36 bytes data]
* SSL connection using TLSv1.3 / TLS_AES_128_GCM_SHA256
* ALPN, server accepted to use h2
* Server certificate:
* subject: CN=cranchecks.info
* start date: Mar 17 16:07:34 2021 GMT
* expire date: Jun 15 16:07:34 2021 GMT
* subjectAltName: host "cranchecks.info" matched cert's "cranchecks.info"
* issuer: C=US; O=Let's Encrypt; CN=R3
* SSL certificate verify ok.
0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0* Using HTTP2, server supports multi-use
* Connection state changed (HTTP/2 confirmed)
* Copying HTTP/2 data in stream buffer to connection buffer after upgrade: len=0
} [5 bytes data]
* Using Stream ID: 1 (easy handle 0x7fda72012000)
} [5 bytes data]
> GET /history/2020-04-01 HTTP/2
> Host: cranchecks.info
> user-agent: curl/7.75.0
> accept: */*
>
{ [5 bytes data]
* TLSv1.3 (IN), TLS handshake, Newsession Ticket (4):
{ [130 bytes data]
* Connection state changed (MAX_CONCURRENT_STREAMS == 250)!
} [5 bytes data]
< HTTP/2 302
< access-control-allow-methods: HEAD, GET
< access-control-allow-origin: *
< cache-control: public, must-revalidate, max-age=60
< content-type: application/json; charset=utf8
< location: https://cchecks-history.s3.us-west-2.amazonaws.com/2020-04-01.json.gz?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAIE65F6ZPF3JF7JTA%2F20210322%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20210322T130021Z&X-Amz-Expires=900&X-Amz-SignedHeaders=host&X-Amz-Signature=e85e440762c9a26672fbbbec9d6623d0afc867547cb22382584d7c95172d9565
< server: Caddy
< x-content-type-options: nosniff
< content-length: 101
< date: Mon, 22 Mar 2021 13:00:21 GMT
<
{ [5 bytes data]
* Ignoring the response-body
{ [101 bytes data]
100 101 100 101 0 0 195 0 --:--:-- --:--:-- --:--:-- 195
* Connection #0 to host cranchecks.info left intact
* Issue another request to this URL: 'https://cchecks-history.s3.us-west-2.amazonaws.com/2020-04-01.json.gz?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAIE65F6ZPF3JF7JTA%2F20210322%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20210322T130021Z&X-Amz-Expires=900&X-Amz-SignedHeaders=host&X-Amz-Signature=e85e440762c9a26672fbbbec9d6623d0afc867547cb22382584d7c95172d9565'
* Trying 52.218.144.5:443...
* Connected to cchecks-history.s3.us-west-2.amazonaws.com (52.218.144.5) port 443 (#1)
* ALPN, offering h2
* ALPN, offering http/1.1
} [5 bytes data]
* TLSv1.3 (OUT), TLS handshake, Client hello (1):
} [512 bytes data]
* TLSv1.3 (IN), TLS handshake, Server hello (2):
{ [91 bytes data]
* TLSv1.2 (IN), TLS handshake, Certificate (11):
{ [3269 bytes data]
* TLSv1.2 (IN), TLS handshake, Server key exchange (12):
{ [333 bytes data]
* TLSv1.2 (IN), TLS handshake, Server finished (14):
{ [4 bytes data]
* TLSv1.2 (OUT), TLS handshake, Client key exchange (16):
} [70 bytes data]
* TLSv1.2 (OUT), TLS change cipher, Change cipher spec (1):
} [1 bytes data]
* TLSv1.2 (OUT), TLS handshake, Finished (20):
} [16 bytes data]
* TLSv1.2 (IN), TLS handshake, Finished (20):
{ [16 bytes data]
* SSL connection using TLSv1.2 / ECDHE-RSA-AES128-GCM-SHA256
* ALPN, server did not agree to a protocol
* Server certificate:
* subject: C=US; ST=Washington; L=Seattle; O=Amazon.com, Inc.; CN=*.s3-us-west-2.amazonaws.com
* start date: Jul 30 00:00:00 2020 GMT
* expire date: Aug 4 12:00:00 2021 GMT
* subjectAltName: host "cchecks-history.s3.us-west-2.amazonaws.com" matched cert's "*.s3.us-west-2.amazonaws.com"
* issuer: C=US; O=DigiCert Inc; OU=www.digicert.com; CN=DigiCert Baltimore CA-2 G2
* SSL certificate verify ok.
} [5 bytes data]
> GET /2020-04-01.json.gz?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAIE65F6ZPF3JF7JTA%2F20210322%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20210322T130021Z&X-Amz-Expires=900&X-Amz-SignedHeaders=host&X-Amz-Signature=e85e440762c9a26672fbbbec9d6623d0afc867547cb22382584d7c95172d9565 HTTP/1.1
> Host: cchecks-history.s3.us-west-2.amazonaws.com
> User-Agent: curl/7.75.0
> Accept: */*
>
{ [5 bytes data]
* Mark bundle as not supporting multiuse
< HTTP/1.1 200 OK
< x-amz-id-2: C5ZiHkliqQykDdnlHk93GGIxuGZIau0FOk7+KPqdrDrcCdku/4p8//hahtkeR9YDDw2RDQzqi/0=
< x-amz-request-id: AS9SGKGRPB4VEJCF
< Date: Mon, 22 Mar 2021 13:00:22 GMT
< Last-Modified: Wed, 01 Apr 2020 16:36:04 GMT
< ETag: "a7d74593672aa52dace5cd9e62db9351"
< Content-Encoding: gzip
< Accept-Ranges: bytes
< Content-Type: application/json
< Content-Length: 5180606
< Server: AmazonS3
<
{ [5 bytes data]
1 5059k 1 68217 0 0 57909 0 0:01:29 0:00:01 0:01:28 57909
100 5059k 100 5059k 0 0 2792k 0 0:00:01 0:00:01 --:--:-- 7887k
* Connection #1 to host cchecks-history.s3.us-west-2.amazonaws.com left intact
{
"package": "localIV",
⚠️ 💡 For historical data by package refer to the package history endpoint.
cchecks::cch_history("2020-04-01")
# opening file input connection.
Found 500 records...
Found 1000 records...
Found 1500 records...
Found 2000 records...
Found 2500 records...
Found 3000 records...
Found 3500 records...
Found 4000 records...
Found 4500 records...
Found 5000 records...
Found 5500 records...
Found 6000 records...
Found 6500 records...
Found 7000 records...
Found 7500 records...
Found 8000 records...
Found 8500 records...
Found 9000 records...
Found 9500 records...
Found 10000 records...
Found 10500 records...
Found 11000 records...
Found 11500 records...
Found 12000 records...
Found 12500 records...
Found 13000 records...
Found 13500 records...
Found 14000 records...
Found 14500 records...
Found 15000 records...
Found 15500 records...
Found 16000 records...
Found 16327 records...
Imported 16327 records. Simplifying...
# closing file input connection.
# A tibble: 16,327 x 5
package summary checks check_details date_updated
<chr> <chr> <chr> <chr> <chr>
1 localIV "{\"any\":false,\… "[{\"flavor\":\"r-… "null" 2020-04-01 1…
2 di "{\"any\":false,\… "[{\"flavor\":\"r-… "null" 2020-04-01 1…
3 GAR "{\"any\":true,\"… "[{\"flavor\":\"r-… "{\"version\":\"1.1\",\"… 2020-04-01 1…
4 MetABEL "{\"any\":true,\"… "[{\"flavor\":\"r-… "{\"version\":\"0.2-0\",… 2020-04-01 1…
5 quantab… "{\"any\":false,\… "[{\"flavor\":\"r-… "null" 2020-04-01 1…
6 ChIPtest "{\"any\":true,\"… "[{\"flavor\":\"r-… "{\"version\":\"1.0\",\"… 2020-04-01 1…
7 TSF "{\"any\":false,\… "[{\"flavor\":\"r-… "null" 2020-04-01 1…
8 apercu "{\"any\":true,\"… "[{\"flavor\":\"r-… "{\"version\":\"0.2.4\",… 2020-04-01 1…
9 SPRT "{\"any\":true,\"… "[{\"flavor\":\"r-… "{\"version\":\"1.0\",\"… 2020-04-01 1…
10 W2CWM2C "{\"any\":false,\… "[{\"flavor\":\"r-… "null" 2020-04-01 1…
# … with 16,317 more rows
Search
Search package history data.
This is a full text search ONLY of the output in check_details field.
Function of the cchecks package: cch_pkgs_search()
GET [/search]
Parameters:
- q (string)
- full text query, e.g, q=memory
- package (string)
- a package name. limit results to a single package, e.g, package=taxize
- one_each (boolean)
- if true, return a single result for each package; useful if you want to find out what packages have match a particular query, and don’t care which day that match happened. default: false; e.g., one_each=true
- fields (string)
- comma separated string with field to return, e.g., fields=package,check_details
- limit/offset
- see pagination docs. Max of 50.
curl https://cranchecks.info/search?q=memory | jq .
HTTP/2 200
access-control-allow-methods: HEAD, GET
access-control-allow-origin: *
cache-control: public, must-revalidate, max-age=60
content-type: application/json; charset=utf8
server: Caddy
x-content-type-options: nosniff
content-length: 186661
date: Mon, 22 Mar 2021 13:01:03 GMT
{
"error": null,
"count": 1215,
"returned": 10,
"data": [
{
"package": "clusternor",
"date_updated": "2021-02-23T15:03:48.000Z",
"summary": {
"any": true,
"ok": 0,
"note": 10,
"warn": 0,
"error": 2,
"fail": 0
},
"checks": [
{
"flavor": "r-devel-linux-x86_64-debian-clang",
"version": "0.0-4",
"tinstall": 90.11,
"tcheck": 35.4,
"ttotal": 125.51,
"status": "NOTE",
"check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-debian-clang/clusternor-00check.html"
},
{
"flavor": "r-devel-linux-x86_64-debian-gcc",
"version": "0.0-4",
"tinstall": 59.62,
"tcheck": 26.08,
"ttotal": 85.7,
"status": "ERROR",
"check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-debian-gcc/clusternor-00check.html"
},
{
"flavor": "r-devel-linux-x86_64-fedora-clang",
"version": "0.0-4",
"tinstall": 0,
"tcheck": 0,
"ttotal": 207.18,
"status": "NOTE",
"check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-fedora-clang/clusternor-00check.html"
},
{
"flavor": "r-devel-linux-x86_64-fedora-gcc",
"version": "0.0-4",
"tinstall": 0,
"tcheck": 0,
"ttotal": 156.15,
"status": "NOTE",
"check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-fedora-gcc/clusternor-00check.html"
},
{
"flavor": "r-devel-windows-ix86+x86_64",
"version": "0.0-4",
"tinstall": 153,
"tcheck": 58,
"ttotal": 211,
"status": "NOTE",
"check_url": "https://www.R-project.org/nosvn/R.check/r-devel-windows-ix86+x86_64/clusternor-00check.html"
},
{
"flavor": "r-patched-linux-x86_64",
"version": "0.0-4",
"tinstall": 72.33,
"tcheck": 32.6,
"ttotal": 104.93,
"status": "NOTE",
"check_url": "https://www.R-project.org/nosvn/R.check/r-patched-linux-x86_64/clusternor-00check.html"
},
{
"flavor": "r-patched-solaris-x86",
"version": "0.0-4",
"tinstall": 0,
"tcheck": 0,
"ttotal": 152.6,
"status": "ERROR",
"check_url": "https://www.R-project.org/nosvn/R.check/r-patched-solaris-x86/clusternor-00check.html"
},
{
"flavor": "r-release-linux-x86_64",
"version": "0.0-4",
"tinstall": 72.46,
"tcheck": 33.01,
"ttotal": 105.47,
"status": "NOTE",
"check_url": "https://www.R-project.org/nosvn/R.check/r-release-linux-x86_64/clusternor-00check.html"
},
{
"flavor": "r-release-macos-x86_64",
"version": "0.0-4",
"tinstall": 0,
"tcheck": 0,
"ttotal": 0,
"status": "NOTE",
"check_url": "https://www.R-project.org/nosvn/R.check/r-release-macos-x86_64/clusternor-00check.html"
},
{
"flavor": "r-release-windows-ix86+x86_64",
"version": "0.0-4",
"tinstall": 183,
"tcheck": 83,
"ttotal": 266,
"status": "NOTE",
"check_url": "https://www.R-project.org/nosvn/R.check/r-release-windows-ix86+x86_64/clusternor-00check.html"
},
{
"flavor": "r-oldrel-macos-x86_64",
"version": "0.0-4",
"tinstall": 0,
"tcheck": 0,
"ttotal": 0,
"status": "NOTE",
"check_url": "https://www.R-project.org/nosvn/R.check/r-oldrel-macos-x86_64/clusternor-00check.html"
},
{
"flavor": "r-oldrel-windows-ix86+x86_64",
"version": "0.0-4",
"tinstall": 149,
"tcheck": 72,
"ttotal": 221,
"status": "NOTE",
"check_url": "https://www.R-project.org/nosvn/R.check/r-oldrel-windows-ix86+x86_64/clusternor-00check.html"
}
],
"check_details": {
"details": [
{
"version": "0.0-4",
"output": "GNU make is a SystemRequirements.",
"check": "for GNU extensions in Makefiles",
"flavors": [
"r-devel-linux-x86_64-debian-clang",
"r-devel-linux-x86_64-debian-gcc",
"r-devel-linux-x86_64-fedora-clang",
"r-devel-linux-x86_64-fedora-gcc",
"r-devel-windows-ix86+x86_64",
"r-patched-linux-x86_64",
"r-patched-solaris-x86",
"r-release-linux-x86_64",
"r-release-macos-x86_64",
"r-release-windows-ix86+x86_64",
"r-oldrel-macos-x86_64",
"r-oldrel-windows-ix86+x86_64"
]
},
{
"version": "0.0-4",
"output": " Running ‘testthat.R’ [1s/2s]\nRunning the tests in ‘tests/testthat.R’ failed.\nComplete output:\n > library(testthat)\n > library(clusternor)\n Loading required package: Rcpp\n > \n > test_check(\"clusternor\")\n \n \n ***Running test for fcmeans***\n \n Data ==> memory, centroids ==> memory\n \n Warning: stack imbalance in '{', 55 then 54\n Warning: stack imbalance in '<-', 50 then 49\n Data ==> memory, centroids ==> memory\n \n Data ==> memory, centroids ==> compute\n \n $nrow\n [1] 50\n \n $ncol\n [1] 5\n \n $iters\n [1] 21\n \n $k\n [1] 8\n \n $centers\n [,1] [,2] [,3] [,4] [,5]\n [1,] 3.064769 2.934908 2.738242 3.298497 2.844551\n [2,] 3.015320 3.013633 2.770685 2.955266 3.051938\n [3,] 4.513284 3.880610 4.156640 4.325825 3.100727\n [4,] 2.849448 2.974869 2.946936 2.447302 3.327008\n [5,] 2.491785 2.790580 3.414452 1.913792 3.267746\n [6,] 3.096226 2.912256 2.765275 3.344278 2.809726\n [7,] 2.887287 3.006538 2.990962 2.472479 3.301115\n [8,] 3.248763 4.155510 1.973610 3.654074 2.660320\n \n $cluster\n [1] 2 1 5 5 8 5 5 4 4 6 7 8 5 8 6 2 6 7 8 5 8 5 5 3 5 5 5 2 3 1 4 6 6 8 8 5 1 3\n [39] 4 3 8 3 8 3 5 8 3 3 6 3\n \n $size\n [1] 3 3 9 4 13 6 2 10\n \n Data ==> memory, centroids ==> compute\n \n $nrow\n [1] 50\n \n $ncol\n [1] 5\n \n $iters\n [1] 21\n \n $k\n [1] 8\n \n $centers\n [,1] [,2] [,3] [,4] [,5]\n [1,] 3.064769 2.934908 2.738242 3.298497 2.844551\n [2,] 3.015320 3.013633 2.770685 2.955266 3.051938\n [3,] 4.513284 3.880610 4.156640 4.325825 3.100727\n [4,] 2.849448 2.974869 2.946936 2.447302 3.327008\n [5,] 2.491785 2.790580 3.414452 1.913792 3.267746\n [6,] 3.096226 2.912256 2.765275 3.344278 2.809726\n [7,] 2.887287 3.006538 2.990962 2.472479 3.301115\n [8,] 3.248763 4.155510 1.973610 3.654074 2.660320\n \n $cluster\n [1] 2 1 5 5 8 5 5 4 4 6 7 8 5 8 6 2 6 7 8 5 8 5 5 3 5 5 5 2 3 1 4 6 6 8 8 5 1 3\n [39] 4 3 8 3 8 3 5 8 3 3 6 3\n \n $size\n [1] 3 3 9 4 13 6 2 10\n \n Data ==> disk, centroids ==> compute\n \n $nrow\n [1] 50\n \n $ncol\n [1] 5\n \n $iters\n [1] 21\n \n $k\n [1] 8\n \n $centers\n [,1] [,2] [,3] [,4] [,5]\n [1,] 2.977810 2.870101 3.038839 3.304946 3.270245\n [2,] 2.977707 2.870096 3.038940 3.304566 3.270613\n [3,] 2.977625 2.870094 3.039058 3.304200 3.270973\n [4,] 2.977839 2.870101 3.038744 3.305169 3.270018\n [5,] 2.977842 2.870101 3.038733 3.305195 3.269992\n [6,] 2.977807 2.870099 3.038780 3.305043 3.270142\n [7,] 2.977696 2.870096 3.038949 3.304530 3.270648\n [8,] 2.977984 2.870108 3.038509 3.305866 3.269326\n \n $cluster\n [1] 3 3 3 3 8 8 3 3 8 3 3 8 8 3 8 8 8 3 8 3 8 8 8 3 3 8 8 3 8 3 3 3 3 8 8 8 3 3\n [39] 8 3 8 8 3 3 8 8 8 8 3 3\n \n $size\n [1] 0 0 25 0 0 0 0 25\n \n Data ==> disk, centroids ==> compute\n \n $nrow\n [1] 50\n \n $ncol\n [1] 5\n \n $iters\n [1] 21\n \n $k\n [1] 8\n \n $centers\n [,1] [,2] [,3] [,4] [,5]\n [1,] 2.977810 2.870101 3.038839 3.304946 3.270245\n [2,] 2.977707 2.870096 3.038940 3.304566 3.270613\n [3,] 2.977625 2.870094 3.039058 3.304200 3.270973\n [4,] 2.977839 2.870101 3.038744 3.305169 3.270018\n [5,] 2.977842 2.870101 3.038733 3.305195 3.269992\n [6,] 2.977807 2.870099 3.038780 3.305043 3.270142\n [7,] 2.977696 2.870096 3.038949 3.304530 3.270648\n [8,] 2.977984 2.870108 3.038509 3.305866 3.269326\n \n $cluster\n [1] 3 3 3 3 8 8 3 3 8 3 3 8 8 3 8 8 8 3 8 3 8 8 8 3 3 8 8 3 8 3 3 3 3 8 8 8 3 3\n [39] 8 3 8 8 3 3 8 8 8 8 3 3\n \n $size\n [1] 0 0 25 0 0 0 0 25\n \n \n \n ***Running test for hmeans***\n \n Data ==> ,centroids ==> memory\n \n $nrow\n [1] 50\n \n $ncol\n [1] 5\n \n $iters\n [1] 20\n \n $k\n [1] 8\n \n $centers\n [,1] [,2] [,3] [,4] [,5]\n [1,] 2.426766 2.953499 4.043335 2.244559 3.710492\n [2,] 4.122332 2.465384 3.589322 2.166748 3.575502\n [3,] 2.626000 3.584148 2.022466 2.295955 4.134119\n [4,] 1.943198 1.376050 2.189751 3.513497 4.592882\n [5,] 4.307359 2.781234 3.196755 4.311270 3.415023\n [6,] 2.795000 3.228041 4.430282 4.288907 1.526741\n [7,] 1.580627 3.095462 1.962946 4.057300 1.642651\n [8,] 2.477416 2.417114 2.200970 4.737974 2.761689\n \n $cluster\n [1] 5 1 3 2 7 8 1 1 8 1 4 7 6 1 5 5 5 1 5 2 6 5 2 3 4 5 1 2 7 3 3 4 3 7 5 8 1 1\n [39] 6 5 5 6 2 3 7 3 5 7 2 3\n \n $size\n [1] 9 6 8 3 11 4 6 3\n \n Data ==> memory, centroids ==> memory\n \n Fatal error: *** recursive gc invocation",
"check": "tests",
"flavors": [
"r-devel-linux-x86_64-debian-gcc"
]
},
{
"version": "0.0-4",
"output": " installed size is 7.3Mb\n sub-directories of 1Mb or more:\n libs 7.2Mb",
"check": "installed package size",
"flavors": [
"r-devel-linux-x86_64-fedora-clang",
"r-release-macos-x86_64",
"r-oldrel-macos-x86_64"
]
},
{
"version": "0.0-4",
"output": " Running ‘testthat.R’ [5s/22s]\nRunning the tests in ‘tests/testthat.R’ failed.\nComplete output:\n > library(testthat)\n > library(clusternor)\n Loading required package: Rcpp\n > \n > test_check(\"clusternor\")\n \n \n ***Running test for fcmeans***\n \n Data ==> memory, centroids ==> memory\n \n Data ==> memory, centroids ==> memory\n \n Data ==> memory, centroids ==> compute\n \n $nrow\n [1] 50\n \n $ncol\n [1] 5\n \n $iters\n [1] 17\n \n $k\n [1] 8\n \n $centers\n [,1] [,2] [,3] [,4] [,5]\n [1,] 1.944158 1.873933 1.811169 1.829127 1.705401\n [2,] 1.944158 1.873933 1.811169 1.829127 1.705401\n [3,] 1.944158 1.873933 1.811169 1.829127 1.705401\n [4,] 1.944158 1.873933 1.811169 1.829127 1.705401\n [5,] 1.944158 1.873933 1.811169 1.829127 1.705401\n [6,] 1.944158 1.873933 1.811169 1.829127 1.705401\n [7,] 1.944158 1.873933 1.811169 1.829127 1.705402\n [8,] 1.944158 1.873933 1.811169 1.829127 1.705401\n \n $cluster\n [1] 7 3 7 7 3 7 7 7 7 3 7 3 7 3 3 7 3 7 3 7 3 7 7 3 3 7 7 3 3 3 7 3 3 7 3 7 3 3\n [39] 7 3 3 3 3 3 7 3 3 3 3 3\n \n $size\n [1] 0 0 29 0 0 0 21 0\n \n Data ==> memory, centroids ==> compute\n \n $nrow\n [1] 50\n \n $ncol\n [1] 5\n \n $iters\n [1] 17\n \n $k\n [1] 8\n \n $centers\n [,1] [,2] [,3] [,4] [,5]\n [1,] 1.944158 1.873933 1.811169 1.829127 1.705401\n [2,] 1.944158 1.873933 1.811169 1.829127 1.705401\n [3,] 1.944158 1.873933 1.811169 1.829127 1.705401\n [4,] 1.944158 1.873933 1.811169 1.829127 1.705401\n [5,] 1.944158 1.873933 1.811169 1.829127 1.705401\n [6,] 1.944158 1.873933 1.811169 1.829127 1.705401\n [7,] 1.944158 1.873933 1.811169 1.829127 1.705402\n [8,] 1.944158 1.873933 1.811169 1.829127 1.705401\n \n $cluster\n [1] 7 3 7 7 3 7 7 7 7 3 7 3 7 3 3 7 3 7 3 7 3 7 7 3 3 7 7 3 3 3 7 3 3 7 3 7 3 3\n [39] 7 3 3 3 3 3 7 3 3 3 3 3\n \n $size\n [1] 0 0 29 0 0 0 21 0\n \n Data ==> disk, centroids ==> compute\n \n $nrow\n [1] 50\n \n $ncol\n [1] 5\n \n $iters\n [1] 21\n \n $k\n [1] 8\n \n $centers\n [,1] [,2] [,3] [,4] [,5]\n [1,] 1.651749 1.554835 1.669196 1.823017 1.698992\n [2,] 1.582700 1.565456 1.712063 1.644104 1.870101\n [3,] 1.651755 1.554831 1.669235 1.822900 1.699119\n [4,] 1.585971 1.557177 1.766105 1.665046 1.818082\n [5,] 1.651741 1.554840 1.669151 1.823152 1.698843\n [6,] 1.651740 1.554839 1.669146 1.823166 1.698828\n [7,] 1.651750 1.554834 1.669202 1.822998 1.699012\n [8,] 1.651711 1.554861 1.668998 1.823611 1.698337\n \n $cluster\n [1] 4 4 4 4 8 8 4 4 8 4 4 8 4 4 4 4 4 4 8 4 4 8 4 4 4 8 4 4 8 4 4 2 2 8 8 4 4 4\n [39] 4 4 4 8 4 2 8 4 8 4 4 2\n \n $size\n [1] 0 4 0 33 0 0 0 13\n \n Data ==> disk, centroids ==> compute\n \n $nrow\n [1] 50\n \n $ncol\n [1] 5\n \n $iters\n [1] 21\n \n $k\n [1] 8\n \n $centers\n [,1] [,2] [,3] [,4] [,5]\n [1,] 1.649158 1.506655 1.712068 1.711550 1.8009668\n [2,] 1.649642 1.506697 1.711777 1.713693 1.7990922\n [3,] 1.649705 1.506705 1.711741 1.713967 1.7988480\n [4,] 1.649686 1.506702 1.711749 1.713894 1.7989162\n [5,] 1.085162 2.038530 1.079136 2.106897 0.9808955\n [6,] 1.649685 1.506701 1.711749 1.713891 1.7989196\n [7,] 1.649647 1.506697 1.711774 1.713714 1.7990740\n [8,] 1.649792 1.506719 1.711683 1.714379 1.7984872\n \n $cluster\n [1] 1 1 1 1 5 8 1 1 8 1 1 8 8 1 1 8 8 1 8 1 8 8 8 1 1 8 8 1 5 1 1 1 1 5 8 8 1 1\n [39] 8 1 8 8 1 1 8 1 8 8 1 1\n \n $size\n [1] 27 0 0 0 3 0 0 20\n \n \n \n ***Running test for hmeans***\n \n Data ==> ,centroids ==> memory\n \n $nrow\n [1] 50\n \n $ncol\n [1] 5\n \n $iters\n [1] 20\n \n $k\n [1] 8\n \n $centers\n [,1] [,2] [,3] [,4] [,5]\n [1,] 2.426766 2.953499 4.043335 2.244559 3.710492\n [2,] 4.122332 2.465384 3.589322 2.166748 3.575502\n [3,] 2.626000 3.584148 2.022466 2.295955 4.134119\n [4,] 1.943198 1.376050 2.189751 3.513497 4.592882\n [5,] 4.307359 2.781234 3.196755 4.311270 3.415023\n [6,] 2.795000 3.228041 4.430282 4.288907 1.526741\n [7,] 1.580627 3.095462 1.962946 4.057300 1.642651\n [8,] 2.477416 2.417114 2.200970 4.737974 2.761689\n \n $cluster\n [1] 5 1 3 2 7 8 1 1 8 1 4 7 6 1 5 5 5 1 5 2 6 5 2 3 4 5 1 2 7 3 3 4 3 7 5 8 1 1\n [39] 6 5 5 6 2 3 7 3 5 7 2 3\n \n $size\n [1] 9 6 8 3 11 4 6 3\n \n Data ==> memory, centroids ==> memory\n \n $nrow\n [1] 50\n \n $ncol\n [1] 5\n \n $iters\n [1] 20\n \n $k\n [1] 8\n \n $centers\n [,1] [,2] [,3] [,4] [,5]\n [1,] 2.888524 2.603497 2.066828 2.375178 4.408128\n [2,] 2.221906 3.679545 2.487253 2.001356 4.078200\n [3,] 3.363949 1.514688 3.809288 1.941361 3.547053\n [4,] 2.513951 3.081818 4.215258 1.409905 3.593325\n [5,] 1.676915 3.191770 2.080428 4.447292 2.429021\n [6,] 3.672408 1.905373 2.369369 4.077653 2.867364\n [7,] 3.815225 4.217887 1.862281 2.514782 2.702868\n [8,] 3.703079 4.045515 3.700746 3.861883 2.418166\n \n $cluster\n [1] 1 6 3 4 7 4 3 3 2 6 3 8 2 7 6 7 6 7 5 4 5 1 4 8 8 4 4 8 8 5 1 6 8 2 7 8 6 8\n [39] 1 8 7 8 5 8 2 8 6 8 5 8\n \n $size\n [1] 4 4 4 6 5 7 6 14\n ",
"check": "tests",
"flavors": [
"r-patched-solaris-x86"
]
}
],
"additional_issues": null
}
},
{
"package": "clusternor",
"date_updated": "2021-02-26T15:03:50.000Z",
"summary": {
"any": true,
"ok": 0,
"note": 10,
"warn": 0,
"error": 2,
"fail": 0
},
"checks": [
{
"flavor": "r-devel-linux-x86_64-debian-clang",
"version": "0.0-4",
"tinstall": 86.91,
"tcheck": 34.97,
"ttotal": 121.88,
"status": "NOTE",
"check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-debian-clang/clusternor-00check.html"
},
{
"flavor": "r-devel-linux-x86_64-debian-gcc",
"version": "0.0-4",
"tinstall": 59.99,
"tcheck": 26.32,
"ttotal": 86.31,
"status": "ERROR",
"check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-debian-gcc/clusternor-00check.html"
},
{
"flavor": "r-devel-linux-x86_64-fedora-clang",
"version": "0.0-4",
"tinstall": 0,
"tcheck": 0,
"ttotal": 207.18,
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"check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-fedora-clang/clusternor-00check.html"
},
{
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"tinstall": 0,
"tcheck": 0,
"ttotal": 156.15,
"status": "NOTE",
"check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-fedora-gcc/clusternor-00check.html"
},
{
"flavor": "r-devel-windows-ix86+x86_64",
"version": "0.0-4",
"tinstall": 153,
"tcheck": 58,
"ttotal": 211,
"status": "NOTE",
"check_url": "https://www.R-project.org/nosvn/R.check/r-devel-windows-ix86+x86_64/clusternor-00check.html"
},
{
"flavor": "r-patched-linux-x86_64",
"version": "0.0-4",
"tinstall": 73.64,
"tcheck": 32.75,
"ttotal": 106.39,
"status": "NOTE",
"check_url": "https://www.R-project.org/nosvn/R.check/r-patched-linux-x86_64/clusternor-00check.html"
},
{
"flavor": "r-patched-solaris-x86",
"version": "0.0-4",
"tinstall": 0,
"tcheck": 0,
"ttotal": 152.6,
"status": "ERROR",
"check_url": "https://www.R-project.org/nosvn/R.check/r-patched-solaris-x86/clusternor-00check.html"
},
{
"flavor": "r-release-linux-x86_64",
"version": "0.0-4",
"tinstall": 71.68,
"tcheck": 32.53,
"ttotal": 104.21,
"status": "NOTE",
"check_url": "https://www.R-project.org/nosvn/R.check/r-release-linux-x86_64/clusternor-00check.html"
},
{
"flavor": "r-release-macos-x86_64",
"version": "0.0-4",
"tinstall": 0,
"tcheck": 0,
"ttotal": 0,
"status": "NOTE",
"check_url": "https://www.R-project.org/nosvn/R.check/r-release-macos-x86_64/clusternor-00check.html"
},
{
"flavor": "r-release-windows-ix86+x86_64",
"version": "0.0-4",
"tinstall": 183,
"tcheck": 83,
"ttotal": 266,
"status": "NOTE",
"check_url": "https://www.R-project.org/nosvn/R.check/r-release-windows-ix86+x86_64/clusternor-00check.html"
},
{
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"tinstall": 0,
"tcheck": 0,
"ttotal": 0,
"status": "NOTE",
"check_url": "https://www.R-project.org/nosvn/R.check/r-oldrel-macos-x86_64/clusternor-00check.html"
},
{
"flavor": "r-oldrel-windows-ix86+x86_64",
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"tinstall": 149,
"tcheck": 72,
"ttotal": 221,
"status": "NOTE",
"check_url": "https://www.R-project.org/nosvn/R.check/r-oldrel-windows-ix86+x86_64/clusternor-00check.html"
}
],
"check_details": {
"details": [
{
"version": "0.0-4",
"output": "GNU make is a SystemRequirements.",
"check": "for GNU extensions in Makefiles",
"flavors": [
"r-devel-linux-x86_64-debian-clang",
"r-devel-linux-x86_64-debian-gcc",
"r-devel-linux-x86_64-fedora-clang",
"r-devel-linux-x86_64-fedora-gcc",
"r-devel-windows-ix86+x86_64",
"r-patched-linux-x86_64",
"r-patched-solaris-x86",
"r-release-linux-x86_64",
"r-release-macos-x86_64",
"r-release-windows-ix86+x86_64",
"r-oldrel-macos-x86_64",
"r-oldrel-windows-ix86+x86_64"
]
},
{
"version": "0.0-4",
"output": " Running ‘testthat.R’ [1s/2s]\nRunning the tests in ‘tests/testthat.R’ failed.\nComplete output:\n > library(testthat)\n > library(clusternor)\n Loading required package: Rcpp\n > \n > test_check(\"clusternor\")\n \n \n ***Running test for fcmeans***\n \n Data ==> memory, centroids ==> memory\n \n Data ==> memory, centroids ==> memory\n \n Warning: stack imbalance in '{', 55 then 56\n Warning: stack imbalance in '<-', 50 then 51\n Data ==> memory, centroids ==> compute\n \n $nrow\n [1] 50\n \n $ncol\n [1] 5\n \n $iters\n [1] 21\n \n $k\n [1] 8\n \n $centers\n [,1] [,2] [,3] [,4] [,5]\n [1,] 3.064769 2.934908 2.738242 3.298497 2.844551\n [2,] 3.015320 3.013633 2.770685 2.955266 3.051938\n [3,] 4.513284 3.880610 4.156640 4.325825 3.100727\n [4,] 2.849448 2.974869 2.946936 2.447302 3.327008\n [5,] 2.491785 2.790580 3.414452 1.913792 3.267746\n [6,] 3.096226 2.912256 2.765275 3.344278 2.809726\n [7,] 2.887287 3.006538 2.990962 2.472479 3.301115\n [8,] 3.248763 4.155510 1.973610 3.654074 2.660320\n \n $cluster\n [1] 2 1 5 5 8 5 5 4 4 6 7 8 5 8 6 2 6 7 8 5 8 5 5 3 5 5 5 2 3 1 4 6 6 8 8 5 1 3\n [39] 4 3 8 3 8 3 5 8 3 3 6 3\n \n $size\n [1] 3 3 9 4 13 6 2 10\n \n Data ==> memory, centroids ==> compute\n \n $nrow\n [1] 50\n \n $ncol\n [1] 5\n \n $iters\n [1] 21\n \n $k\n [1] 8\n \n $centers\n [,1] [,2] [,3] [,4] [,5]\n [1,] 3.064769 2.934908 2.738242 3.298497 2.844551\n [2,] 3.015320 3.013633 2.770685 2.955266 3.051938\n [3,] 4.513284 3.880610 4.156640 4.325825 3.100727\n [4,] 2.849448 2.974869 2.946936 2.447302 3.327008\n [5,] 2.491785 2.790580 3.414452 1.913792 3.267746\n [6,] 3.096226 2.912256 2.765275 3.344278 2.809726\n [7,] 2.887287 3.006538 2.990962 2.472479 3.301115\n [8,] 3.248763 4.155510 1.973610 3.654074 2.660320\n \n $cluster\n [1] 2 1 5 5 8 5 5 4 4 6 7 8 5 8 6 2 6 7 8 5 8 5 5 3 5 5 5 2 3 1 4 6 6 8 8 5 1 3\n [39] 4 3 8 3 8 3 5 8 3 3 6 3\n \n $size\n [1] 3 3 9 4 13 6 2 10\n \n Data ==> disk, centroids ==> compute\n \n $nrow\n [1] 50\n \n $ncol\n [1] 5\n \n $iters\n [1] 21\n \n $k\n [1] 8\n \n $centers\n [,1] [,2] [,3] [,4] [,5]\n [1,] 2.977810 2.870101 3.038839 3.304946 3.270245\n [2,] 2.977707 2.870096 3.038940 3.304566 3.270613\n [3,] 2.977625 2.870094 3.039058 3.304200 3.270973\n [4,] 2.977839 2.870101 3.038744 3.305169 3.270018\n [5,] 2.977842 2.870101 3.038733 3.305195 3.269992\n [6,] 2.977807 2.870099 3.038780 3.305043 3.270142\n [7,] 2.977696 2.870096 3.038949 3.304530 3.270648\n [8,] 2.977984 2.870108 3.038509 3.305866 3.269326\n \n $cluster\n [1] 3 3 3 3 8 8 3 3 8 3 3 8 8 3 8 8 8 3 8 3 8 8 8 3 3 8 8 3 8 3 3 3 3 8 8 8 3 3\n [39] 8 3 8 8 3 3 8 8 8 8 3 3\n \n $size\n [1] 0 0 25 0 0 0 0 25\n \n Data ==> disk, centroids ==> compute\n \n $nrow\n [1] 50\n \n $ncol\n [1] 5\n \n $iters\n [1] 21\n \n $k\n [1] 8\n \n $centers\n [,1] [,2] [,3] [,4] [,5]\n [1,] 2.977810 2.870101 3.038839 3.304946 3.270245\n [2,] 2.977707 2.870096 3.038940 3.304566 3.270613\n [3,] 2.977625 2.870094 3.039058 3.304200 3.270973\n [4,] 2.977839 2.870101 3.038744 3.305169 3.270018\n [5,] 2.977842 2.870101 3.038733 3.305195 3.269992\n [6,] 2.977807 2.870099 3.038780 3.305043 3.270142\n [7,] 2.977696 2.870096 3.038949 3.304530 3.270648\n [8,] 2.977984 2.870108 3.038509 3.305866 3.269326\n \n $cluster\n [1] 3 3 3 3 8 8 3 3 8 3 3 8 8 3 8 8 8 3 8 3 8 8 8 3 3 8 8 3 8 3 3 3 3 8 8 8 3 3\n [39] 8 3 8 8 3 3 8 8 8 8 3 3\n \n $size\n [1] 0 0 25 0 0 0 0 25\n \n \n \n ***Running test for hmeans***\n \n Data ==> ,centroids ==> memory\n \n $nrow\n [1] 50\n \n $ncol\n [1] 5\n \n $iters\n [1] 20\n \n $k\n [1] 8\n \n $centers\n [,1] [,2] [,3] [,4] [,5]\n [1,] 2.426766 2.953499 4.043335 2.244559 3.710492\n [2,] 4.122332 2.465384 3.589322 2.166748 3.575502\n [3,] 2.626000 3.584148 2.022466 2.295955 4.134119\n [4,] 1.943198 1.376050 2.189751 3.513497 4.592882\n [5,] 4.307359 2.781234 3.196755 4.311270 3.415023\n [6,] 2.795000 3.228041 4.430282 4.288907 1.526741\n [7,] 1.580627 3.095462 1.962946 4.057300 1.642651\n [8,] 2.477416 2.417114 2.200970 4.737974 2.761689\n \n $cluster\n [1] 5 1 3 2 7 8 1 1 8 1 4 7 6 1 5 5 5 1 5 2 6 5 2 3 4 5 1 2 7 3 3 4 3 7 5 8 1 1\n [39] 6 5 5 6 2 3 7 3 5 7 2 3\n \n $size\n [1] 9 6 8 3 11 4 6 3\n \n Data ==> memory, centroids ==> memory\n \n Fatal error: *** recursive gc invocation",
"check": "tests",
"flavors": [
"r-devel-linux-x86_64-debian-gcc"
]
},
{
"version": "0.0-4",
"output": " installed size is 7.3Mb\n sub-directories of 1Mb or more:\n libs 7.2Mb",
"check": "installed package size",
"flavors": [
"r-devel-linux-x86_64-fedora-clang",
"r-release-macos-x86_64",
"r-oldrel-macos-x86_64"
]
},
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"version": "0.0-4",
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"output": "Rd file 'allan-package.Rd':\n \\examples lines wider than 100 characters:\n bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=smallchunk,weights=~cont0)\n\nRd file 'allanVarSelect.Rd':\n \\usage lines wider than 90 characters:\n allanVarSelect(BaseModel, TrnDataSetFile, ValDataSetFile, ResponseCol = 1, NumOfSteps = 10, criteria = \"AIC\", currentchunksize = -1, si ... [TRUNCATED]\n \\examples lines wider than 100 characters:\n bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n\nRd file 'fitvbiglm.Rd':\n \\usage lines wider than 90 characters:\n fitvbiglm(BaseModel, filename, currentchunksize = -1, silent = TRUE, MemoryAllowed = 0.5, TestedRows = 1000, AdjFactor = 0.095)\n \\examples lines wider than 100 characters:\n bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n\nRd file 'getbestchunksize.Rd':\n \\usage lines wider than 90 characters:\n getbestchunksize(filename, MemoryAllowed = 0.5, TestedRows = 1000, AdjFactor = 0.095, silent = TRUE)\n \\examples lines wider than 100 characters:\n #This is done by reading in a number of rows(1000 by default)and then measuring the size of the memory\n #used. Memory allwed is specified in Gb. The adjfactor is a factor used to adjust memory for overhead\n\nRd file 'predictvbiglm.Rd':\n \\usage lines wider than 90 characters:\n predictvbiglm(BaseModel, ValFileName, currentchunksize = -1, ResponseCol = 1, silent = TRUE, MemoryAllowed = 0.5, TestedRows = 1000, Ad ... [TRUNCATED]\n \\examples lines wider than 100 characters:\n bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n predictvbiglm<-function(BaseModel,ValFileName,currentchunksize=-1,ResponseCol=1,silent=TRUE,MemoryAllowed=0.5,TestedRows=1000,AdjFactor ... [TRUNCATED]\n currentchunksize<-getbestchunksize(ValFileName,MemoryAllowed=MemoryAllowed,TestedRows=TestedRows,AdjFactor=AdjFactor,si ... [TRUNCATED]\n weightvector<-as.vector(eval(parse(text=paste(\"CurrentDataSet\",\"$\",weightname,sep=\"\"))))\n CurrentVariance=sum(((CurrentDataSet[,ResponseCol]-CurrentMean)^2)*weightvector)/sum(weightvector)\n\nRd file 'readinbigdata.Rd':\n \\examples lines wider than 100 characters:\n #The return value is either the next chunk of data or NULL if there is no additional data left.\n #Additionally if a reset=TRUE flag is passed, then the data stream goes back to the beginning.\n\nThese lines will be truncated in the PDF manual.",
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"output": "Running examples in 'allan-Ex.R' failed\nThe error most likely occurred in:\n\n> ### Name: allanVarSelect\n> ### Title: Memory Unlimited Forward Stepwise Variable Selection for Linear\n> ### Models\n> ### Aliases: allanVarSelect\n> ### Keywords: stepwise linear regression memory\n> \n> ### ** Examples\n> \n> #Get external data. For your own data skip this next line and replace all\n> #instance of SampleData with \"YourFile.csv\".\n> SampleData=system.file(\"extdata\",\"SampleDataFile.csv\", package = \"allan\")\n> \n> #fit smaller data to biglm object\n> columnnames<-names(read.csv(SampleData, nrows=2,header=TRUE))\n> datafeed<-readinbigdata(SampleData,chunksize=1000,col.names=columnnames)\n> datafeed(TRUE)\n> firstchunk<-datafeed(FALSE)\n> \n> #create a biglm model from the small chunk with all variables that will be consdered\n> #for variable selection.\n> bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n> \n> #now run variable selection\n> FinalModel<-allanVarSelect(bigmodel,SampleData,SampleData,NumOfSteps=2,criteria=\"MSE\",silent=FALSE)\n[1] \"Total memory usage for 1000 lines:\"\n110560 bytes\n[1] \"Chunksize for dataframe after adjustment factor:\"\n[1] 429630\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n AICValue BICValue MSEValue \n \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\" \n \n \"cont3\" \"1\" \n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n AICValue BICValue MSEValue \n \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\" \n \n \"cont1\" \"2\" \n[1] \"Final Results of Variable Selection:\"\n AICValue BICValue MSEValue \nIterationSummary \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\"\nIterationSummary \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\"\n \nIterationSummary \"cont3\" \"1\"\nIterationSummary \"cont1\" \"2\"\n[1] \"Results Stored in $SelectionSummary\"\n> \n> \n> \n> \n> \n> \n> \n> cleanEx()\nWarning in .Internal(gc(verbose, reset, full)) :\n closing unused connection 3 (D:/temp/RtmpukHfZE/RLIBS_c44c28153910/allan/extdata/SampleDataFile.csv)\nError: connections left open:\n\tD:/temp/RtmpukHfZE/RLIBS_c44c28153910/allan/extdata/SampleDataFile.csv (file)\nExecution halted",
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"output": "Running examples in 'allan-Ex.R' failed\nThe error most likely occurred in:\n\n> ### Name: allanVarSelect\n> ### Title: Memory Unlimited Forward Stepwise Variable Selection for Linear\n> ### Models\n> ### Aliases: allanVarSelect\n> ### Keywords: stepwise linear regression memory\n> \n> ### ** Examples\n> \n> #Get external data. For your own data skip this next line and replace all\n> #instance of SampleData with \"YourFile.csv\".\n> SampleData=system.file(\"extdata\",\"SampleDataFile.csv\", package = \"allan\")\n> \n> #fit smaller data to biglm object\n> columnnames<-names(read.csv(SampleData, nrows=2,header=TRUE))\n> datafeed<-readinbigdata(SampleData,chunksize=1000,col.names=columnnames)\n> datafeed(TRUE)\n> firstchunk<-datafeed(FALSE)\n> \n> #create a biglm model from the small chunk with all variables that will be consdered\n> #for variable selection.\n> bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n> \n> #now run variable selection\n> FinalModel<-allanVarSelect(bigmodel,SampleData,SampleData,NumOfSteps=2,criteria=\"MSE\",silent=FALSE)\n[1] \"Total memory usage for 1000 lines:\"\n110560 bytes\n[1] \"Chunksize for dataframe after adjustment factor:\"\n[1] 429630\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n AICValue BICValue MSEValue \n \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\" \n \n \"cont3\" \"1\" \n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n AICValue BICValue MSEValue \n \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\" \n \n \"cont1\" \"2\" \n[1] \"Final Results of Variable Selection:\"\n AICValue BICValue MSEValue \nIterationSummary \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\"\nIterationSummary \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\"\n \nIterationSummary \"cont3\" \"1\"\nIterationSummary \"cont1\" \"2\"\n[1] \"Results Stored in $SelectionSummary\"\n> \n> \n> \n> \n> \n> \n> \n> cleanEx()\nWarning in .Internal(gc(verbose, reset, full)) :\n closing unused connection 3 (D:/temp/RtmpE9PIOK/RLIBS_eb3860833110/allan/extdata/SampleDataFile.csv)\nError: connections left open:\n\tD:/temp/RtmpE9PIOK/RLIBS_eb3860833110/allan/extdata/SampleDataFile.csv (file)\nExecution halted",
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"output": "Running examples in 'allan-Ex.R' failed\nThe error most likely occurred in:\n\n> ### Name: allanVarSelect\n> ### Title: Memory Unlimited Forward Stepwise Variable Selection for Linear\n> ### Models\n> ### Aliases: allanVarSelect\n> ### Keywords: stepwise linear regression memory\n> \n> ### ** Examples\n> \n> #Get external data. For your own data skip this next line and replace all\n> #instance of SampleData with \"YourFile.csv\".\n> SampleData=system.file(\"extdata\",\"SampleDataFile.csv\", package = \"allan\")\n> \n> #fit smaller data to biglm object\n> columnnames<-names(read.csv(SampleData, nrows=2,header=TRUE))\n> datafeed<-readinbigdata(SampleData,chunksize=1000,col.names=columnnames)\n> datafeed(TRUE)\n> firstchunk<-datafeed(FALSE)\n> \n> #create a biglm model from the small chunk with all variables that will be consdered\n> #for variable selection.\n> bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n> \n> #now run variable selection\n> FinalModel<-allanVarSelect(bigmodel,SampleData,SampleData,NumOfSteps=2,criteria=\"MSE\",silent=FALSE)\n[1] \"Total memory usage for 1000 lines:\"\n110560 bytes\n[1] \"Chunksize for dataframe after adjustment factor:\"\n[1] 429630\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n AICValue BICValue MSEValue \n \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\" \n \n \"cont3\" \"1\" \n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n AICValue BICValue MSEValue \n \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\" \n \n \"cont1\" \"2\" \n[1] \"Final Results of Variable Selection:\"\n AICValue BICValue MSEValue \nIterationSummary \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\"\nIterationSummary \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\"\n \nIterationSummary \"cont3\" \"1\"\nIterationSummary \"cont1\" \"2\"\n[1] \"Results Stored in $SelectionSummary\"\n> \n> \n> \n> \n> \n> \n> \n> cleanEx()\nWarning in .Internal(gc(verbose, reset, full)) :\n closing unused connection 3 (D:/temp/RtmpukHfZE/RLIBS_c44c28153910/allan/extdata/SampleDataFile.csv)\nError: connections left open:\n\tD:/temp/RtmpukHfZE/RLIBS_c44c28153910/allan/extdata/SampleDataFile.csv (file)\nExecution halted",
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"output": "Running examples in 'allan-Ex.R' failed\nThe error most likely occurred in:\n\n> ### Name: allanVarSelect\n> ### Title: Memory Unlimited Forward Stepwise Variable Selection for Linear\n> ### Models\n> ### Aliases: allanVarSelect\n> ### Keywords: stepwise linear regression memory\n> \n> ### ** Examples\n> \n> #Get external data. For your own data skip this next line and replace all\n> #instance of SampleData with \"YourFile.csv\".\n> SampleData=system.file(\"extdata\",\"SampleDataFile.csv\", package = \"allan\")\n> \n> #fit smaller data to biglm object\n> columnnames<-names(read.csv(SampleData, nrows=2,header=TRUE))\n> datafeed<-readinbigdata(SampleData,chunksize=1000,col.names=columnnames)\n> datafeed(TRUE)\n> firstchunk<-datafeed(FALSE)\n> \n> #create a biglm model from the small chunk with all variables that will be consdered\n> #for variable selection.\n> bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n> \n> #now run variable selection\n> FinalModel<-allanVarSelect(bigmodel,SampleData,SampleData,NumOfSteps=2,criteria=\"MSE\",silent=FALSE)\n[1] \"Total memory usage for 1000 lines:\"\n110560 bytes\n[1] \"Chunksize for dataframe after adjustment factor:\"\n[1] 429630\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n AICValue BICValue MSEValue \n \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\" \n \n \"cont3\" \"1\" \n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n AICValue BICValue MSEValue \n \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\" \n \n \"cont1\" \"2\" \n[1] \"Final Results of Variable Selection:\"\n AICValue BICValue MSEValue \nIterationSummary \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\"\nIterationSummary \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\"\n \nIterationSummary \"cont3\" \"1\"\nIterationSummary \"cont1\" \"2\"\n[1] \"Results Stored in $SelectionSummary\"\n> \n> \n> \n> \n> \n> \n> \n> cleanEx()\nWarning in .Internal(gc(verbose, reset, full)) :\n closing unused connection 3 (D:/temp/RtmpEHUBR4/RLIBS_12fec2e8ba2c/allan/extdata/SampleDataFile.csv)\nError: connections left open:\n\tD:/temp/RtmpEHUBR4/RLIBS_12fec2e8ba2c/allan/extdata/SampleDataFile.csv (file)\nExecution halted",
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"output": "Running examples in 'allan-Ex.R' failed\nThe error most likely occurred in:\n\n> ### Name: allanVarSelect\n> ### Title: Memory Unlimited Forward Stepwise Variable Selection for Linear\n> ### Models\n> ### Aliases: allanVarSelect\n> ### Keywords: stepwise linear regression memory\n> \n> ### ** Examples\n> \n> #Get external data. For your own data skip this next line and replace all\n> #instance of SampleData with \"YourFile.csv\".\n> SampleData=system.file(\"extdata\",\"SampleDataFile.csv\", package = \"allan\")\n> \n> #fit smaller data to biglm object\n> columnnames<-names(read.csv(SampleData, nrows=2,header=TRUE))\n> datafeed<-readinbigdata(SampleData,chunksize=1000,col.names=columnnames)\n> datafeed(TRUE)\n> firstchunk<-datafeed(FALSE)\n> \n> #create a biglm model from the small chunk with all variables that will be consdered\n> #for variable selection.\n> bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n> \n> #now run variable selection\n> FinalModel<-allanVarSelect(bigmodel,SampleData,SampleData,NumOfSteps=2,criteria=\"MSE\",silent=FALSE)\n[1] \"Total memory usage for 1000 lines:\"\n110560 bytes\n[1] \"Chunksize for dataframe after adjustment factor:\"\n[1] 429630\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n AICValue BICValue MSEValue \n \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\" \n \n \"cont3\" \"1\" \n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n AICValue BICValue MSEValue \n \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\" \n \n \"cont1\" \"2\" \n[1] \"Final Results of Variable Selection:\"\n AICValue BICValue MSEValue \nIterationSummary \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\"\nIterationSummary \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\"\n \nIterationSummary \"cont3\" \"1\"\nIterationSummary \"cont1\" \"2\"\n[1] \"Results Stored in $SelectionSummary\"\n> \n> \n> \n> \n> \n> \n> \n> cleanEx()\nWarning in .Internal(gc(verbose, reset, full)) :\n closing unused connection 3 (D:/temp/RtmpukHfZE/RLIBS_c44c28153910/allan/extdata/SampleDataFile.csv)\nError: connections left open:\n\tD:/temp/RtmpukHfZE/RLIBS_c44c28153910/allan/extdata/SampleDataFile.csv (file)\nExecution halted",
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"output": "Running examples in 'allan-Ex.R' failed\nThe error most likely occurred in:\n\n> ### Name: allanVarSelect\n> ### Title: Memory Unlimited Forward Stepwise Variable Selection for Linear\n> ### Models\n> ### Aliases: allanVarSelect\n> ### Keywords: stepwise linear regression memory\n> \n> ### ** Examples\n> \n> #Get external data. For your own data skip this next line and replace all\n> #instance of SampleData with \"YourFile.csv\".\n> SampleData=system.file(\"extdata\",\"SampleDataFile.csv\", package = \"allan\")\n> \n> #fit smaller data to biglm object\n> columnnames<-names(read.csv(SampleData, nrows=2,header=TRUE))\n> datafeed<-readinbigdata(SampleData,chunksize=1000,col.names=columnnames)\n> datafeed(TRUE)\n> firstchunk<-datafeed(FALSE)\n> \n> #create a biglm model from the small chunk with all variables that will be consdered\n> #for variable selection.\n> bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n> \n> #now run variable selection\n> FinalModel<-allanVarSelect(bigmodel,SampleData,SampleData,NumOfSteps=2,criteria=\"MSE\",silent=FALSE)\n[1] \"Total memory usage for 1000 lines:\"\n110560 bytes\n[1] \"Chunksize for dataframe after adjustment factor:\"\n[1] 429630\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n AICValue BICValue MSEValue \n \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\" \n \n \"cont3\" \"1\" \n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n AICValue BICValue MSEValue \n \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\" \n \n \"cont1\" \"2\" \n[1] \"Final Results of Variable Selection:\"\n AICValue BICValue MSEValue \nIterationSummary \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\"\nIterationSummary \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\"\n \nIterationSummary \"cont3\" \"1\"\nIterationSummary \"cont1\" \"2\"\n[1] \"Results Stored in $SelectionSummary\"\n> \n> \n> \n> \n> \n> \n> \n> cleanEx()\nWarning in .Internal(gc(verbose, reset, full)) :\n closing unused connection 3 (D:/temp/RtmpEHUBR4/RLIBS_12fec2e8ba2c/allan/extdata/SampleDataFile.csv)\nError: connections left open:\n\tD:/temp/RtmpEHUBR4/RLIBS_12fec2e8ba2c/allan/extdata/SampleDataFile.csv (file)\nExecution halted",
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"output": "Running examples in 'allan-Ex.R' failed\nThe error most likely occurred in:\n\n> ### Name: allanVarSelect\n> ### Title: Memory Unlimited Forward Stepwise Variable Selection for Linear\n> ### Models\n> ### Aliases: allanVarSelect\n> ### Keywords: stepwise linear regression memory\n> \n> ### ** Examples\n> \n> #Get external data. For your own data skip this next line and replace all\n> #instance of SampleData with \"YourFile.csv\".\n> SampleData=system.file(\"extdata\",\"SampleDataFile.csv\", package = \"allan\")\n> \n> #fit smaller data to biglm object\n> columnnames<-names(read.csv(SampleData, nrows=2,header=TRUE))\n> datafeed<-readinbigdata(SampleData,chunksize=1000,col.names=columnnames)\n> datafeed(TRUE)\n> firstchunk<-datafeed(FALSE)\n> \n> #create a biglm model from the small chunk with all variables that will be consdered\n> #for variable selection.\n> bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n> \n> #now run variable selection\n> FinalModel<-allanVarSelect(bigmodel,SampleData,SampleData,NumOfSteps=2,criteria=\"MSE\",silent=FALSE)\n[1] \"Total memory usage for 1000 lines:\"\n110560 bytes\n[1] \"Chunksize for dataframe after adjustment factor:\"\n[1] 429630\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n AICValue BICValue MSEValue \n \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\" \n \n \"cont3\" \"1\" \n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n AICValue BICValue MSEValue \n \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\" \n \n \"cont1\" \"2\" \n[1] \"Final Results of Variable Selection:\"\n AICValue BICValue MSEValue \nIterationSummary \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\"\nIterationSummary \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\"\n \nIterationSummary \"cont3\" \"1\"\nIterationSummary \"cont1\" \"2\"\n[1] \"Results Stored in $SelectionSummary\"\n> \n> \n> \n> \n> \n> \n> \n> cleanEx()\nWarning in .Internal(gc(verbose, reset, full)) :\n closing unused connection 3 (D:/temp/RtmpE9PIOK/RLIBS_eb3860833110/allan/extdata/SampleDataFile.csv)\nError: connections left open:\n\tD:/temp/RtmpE9PIOK/RLIBS_eb3860833110/allan/extdata/SampleDataFile.csv (file)\nExecution halted",
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"output": "Running examples in 'allan-Ex.R' failed\nThe error most likely occurred in:\n\n> ### Name: allanVarSelect\n> ### Title: Memory Unlimited Forward Stepwise Variable Selection for Linear\n> ### Models\n> ### Aliases: allanVarSelect\n> ### Keywords: stepwise linear regression memory\n> \n> ### ** Examples\n> \n> #Get external data. For your own data skip this next line and replace all\n> #instance of SampleData with \"YourFile.csv\".\n> SampleData=system.file(\"extdata\",\"SampleDataFile.csv\", package = \"allan\")\n> \n> #fit smaller data to biglm object\n> columnnames<-names(read.csv(SampleData, nrows=2,header=TRUE))\n> datafeed<-readinbigdata(SampleData,chunksize=1000,col.names=columnnames)\n> datafeed(TRUE)\n> firstchunk<-datafeed(FALSE)\n> \n> #create a biglm model from the small chunk with all variables that will be consdered\n> #for variable selection.\n> bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n> \n> #now run variable selection\n> FinalModel<-allanVarSelect(bigmodel,SampleData,SampleData,NumOfSteps=2,criteria=\"MSE\",silent=FALSE)\n[1] \"Total memory usage for 1000 lines:\"\n110560 bytes\n[1] \"Chunksize for dataframe after adjustment factor:\"\n[1] 429630\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n AICValue BICValue MSEValue \n \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\" \n \n \"cont3\" \"1\" \n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n AICValue BICValue MSEValue \n \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\" \n \n \"cont1\" \"2\" \n[1] \"Final Results of Variable Selection:\"\n AICValue BICValue MSEValue \nIterationSummary \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\"\nIterationSummary \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\"\n \nIterationSummary \"cont3\" \"1\"\nIterationSummary \"cont1\" \"2\"\n[1] \"Results Stored in $SelectionSummary\"\n> \n> \n> \n> \n> \n> \n> \n> cleanEx()\nWarning in .Internal(gc(verbose, reset, full)) :\n closing unused connection 3 (D:/temp/RtmpukHfZE/RLIBS_c44c28153910/allan/extdata/SampleDataFile.csv)\nError: connections left open:\n\tD:/temp/RtmpukHfZE/RLIBS_c44c28153910/allan/extdata/SampleDataFile.csv (file)\nExecution halted",
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"output": "Running examples in 'allan-Ex.R' failed\nThe error most likely occurred in:\n\n> ### Name: allanVarSelect\n> ### Title: Memory Unlimited Forward Stepwise Variable Selection for Linear\n> ### Models\n> ### Aliases: allanVarSelect\n> ### Keywords: stepwise linear regression memory\n> \n> ### ** Examples\n> \n> #Get external data. For your own data skip this next line and replace all\n> #instance of SampleData with \"YourFile.csv\".\n> SampleData=system.file(\"extdata\",\"SampleDataFile.csv\", package = \"allan\")\n> \n> #fit smaller data to biglm object\n> columnnames<-names(read.csv(SampleData, nrows=2,header=TRUE))\n> datafeed<-readinbigdata(SampleData,chunksize=1000,col.names=columnnames)\n> datafeed(TRUE)\n> firstchunk<-datafeed(FALSE)\n> \n> #create a biglm model from the small chunk with all variables that will be consdered\n> #for variable selection.\n> bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n> \n> #now run variable selection\n> FinalModel<-allanVarSelect(bigmodel,SampleData,SampleData,NumOfSteps=2,criteria=\"MSE\",silent=FALSE)\n[1] \"Total memory usage for 1000 lines:\"\n110560 bytes\n[1] \"Chunksize for dataframe after adjustment factor:\"\n[1] 429630\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n AICValue BICValue MSEValue \n \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\" \n \n \"cont3\" \"1\" \n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n AICValue BICValue MSEValue \n \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\" \n \n \"cont1\" \"2\" \n[1] \"Final Results of Variable Selection:\"\n AICValue BICValue MSEValue \nIterationSummary \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\"\nIterationSummary \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\"\n \nIterationSummary \"cont3\" \"1\"\nIterationSummary \"cont1\" \"2\"\n[1] \"Results Stored in $SelectionSummary\"\n> \n> \n> \n> \n> \n> \n> \n> cleanEx()\nWarning in .Internal(gc(verbose, reset, full)) :\n closing unused connection 3 (D:/temp/RtmpEHUBR4/RLIBS_12fec2e8ba2c/allan/extdata/SampleDataFile.csv)\nError: connections left open:\n\tD:/temp/RtmpEHUBR4/RLIBS_12fec2e8ba2c/allan/extdata/SampleDataFile.csv (file)\nExecution halted",
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"output": "Running examples in 'allan-Ex.R' failed\nThe error most likely occurred in:\n\n> ### Name: allanVarSelect\n> ### Title: Memory Unlimited Forward Stepwise Variable Selection for Linear\n> ### Models\n> ### Aliases: allanVarSelect\n> ### Keywords: stepwise linear regression memory\n> \n> ### ** Examples\n> \n> #Get external data. For your own data skip this next line and replace all\n> #instance of SampleData with \"YourFile.csv\".\n> SampleData=system.file(\"extdata\",\"SampleDataFile.csv\", package = \"allan\")\n> \n> #fit smaller data to biglm object\n> columnnames<-names(read.csv(SampleData, nrows=2,header=TRUE))\n> datafeed<-readinbigdata(SampleData,chunksize=1000,col.names=columnnames)\n> datafeed(TRUE)\n> firstchunk<-datafeed(FALSE)\n> \n> #create a biglm model from the small chunk with all variables that will be consdered\n> #for variable selection.\n> bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n> \n> #now run variable selection\n> FinalModel<-allanVarSelect(bigmodel,SampleData,SampleData,NumOfSteps=2,criteria=\"MSE\",silent=FALSE)\n[1] \"Total memory usage for 1000 lines:\"\n110560 bytes\n[1] \"Chunksize for dataframe after adjustment factor:\"\n[1] 429630\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n AICValue BICValue MSEValue \n \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\" \n \n \"cont3\" \"1\" \n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n AICValue BICValue MSEValue \n \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\" \n \n \"cont1\" \"2\" \n[1] \"Final Results of Variable Selection:\"\n AICValue BICValue MSEValue \nIterationSummary \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\"\nIterationSummary \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\"\n \nIterationSummary \"cont3\" \"1\"\nIterationSummary \"cont1\" \"2\"\n[1] \"Results Stored in $SelectionSummary\"\n> \n> \n> \n> \n> \n> \n> \n> cleanEx()\nWarning in .Internal(gc(verbose, reset, full)) :\n closing unused connection 3 (D:/temp/RtmpE9PIOK/RLIBS_eb3860833110/allan/extdata/SampleDataFile.csv)\nError: connections left open:\n\tD:/temp/RtmpE9PIOK/RLIBS_eb3860833110/allan/extdata/SampleDataFile.csv (file)\nExecution halted",
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"output": "Running examples in 'allan-Ex.R' failed\nThe error most likely occurred in:\n\n> ### Name: allanVarSelect\n> ### Title: Memory Unlimited Forward Stepwise Variable Selection for Linear\n> ### Models\n> ### Aliases: allanVarSelect\n> ### Keywords: stepwise linear regression memory\n> \n> ### ** Examples\n> \n> #Get external data. For your own data skip this next line and replace all\n> #instance of SampleData with \"YourFile.csv\".\n> SampleData=system.file(\"extdata\",\"SampleDataFile.csv\", package = \"allan\")\n> \n> #fit smaller data to biglm object\n> columnnames<-names(read.csv(SampleData, nrows=2,header=TRUE))\n> datafeed<-readinbigdata(SampleData,chunksize=1000,col.names=columnnames)\n> datafeed(TRUE)\n> firstchunk<-datafeed(FALSE)\n> \n> #create a biglm model from the small chunk with all variables that will be consdered\n> #for variable selection.\n> bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n> \n> #now run variable selection\n> FinalModel<-allanVarSelect(bigmodel,SampleData,SampleData,NumOfSteps=2,criteria=\"MSE\",silent=FALSE)\n[1] \"Total memory usage for 1000 lines:\"\n110560 bytes\n[1] \"Chunksize for dataframe after adjustment factor:\"\n[1] 429630\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n AICValue BICValue MSEValue \n \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\" \n \n \"cont3\" \"1\" \n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n AICValue BICValue MSEValue \n \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\" \n \n \"cont1\" \"2\" \n[1] \"Final Results of Variable Selection:\"\n AICValue BICValue MSEValue \nIterationSummary \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\"\nIterationSummary \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\"\n \nIterationSummary \"cont3\" \"1\"\nIterationSummary \"cont1\" \"2\"\n[1] \"Results Stored in $SelectionSummary\"\n> \n> \n> \n> \n> \n> \n> \n> cleanEx()\nWarning in .Internal(gc(verbose, reset, full)) :\n closing unused connection 3 (D:/temp/RtmpukHfZE/RLIBS_c44c28153910/allan/extdata/SampleDataFile.csv)\nError: connections left open:\n\tD:/temp/RtmpukHfZE/RLIBS_c44c28153910/allan/extdata/SampleDataFile.csv (file)\nExecution halted",
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"output": "Running examples in 'allan-Ex.R' failed\nThe error most likely occurred in:\n\n> ### Name: allanVarSelect\n> ### Title: Memory Unlimited Forward Stepwise Variable Selection for Linear\n> ### Models\n> ### Aliases: allanVarSelect\n> ### Keywords: stepwise linear regression memory\n> \n> ### ** Examples\n> \n> #Get external data. For your own data skip this next line and replace all\n> #instance of SampleData with \"YourFile.csv\".\n> SampleData=system.file(\"extdata\",\"SampleDataFile.csv\", package = \"allan\")\n> \n> #fit smaller data to biglm object\n> columnnames<-names(read.csv(SampleData, nrows=2,header=TRUE))\n> datafeed<-readinbigdata(SampleData,chunksize=1000,col.names=columnnames)\n> datafeed(TRUE)\n> firstchunk<-datafeed(FALSE)\n> \n> #create a biglm model from the small chunk with all variables that will be consdered\n> #for variable selection.\n> bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n> \n> #now run variable selection\n> FinalModel<-allanVarSelect(bigmodel,SampleData,SampleData,NumOfSteps=2,criteria=\"MSE\",silent=FALSE)\n[1] \"Total memory usage for 1000 lines:\"\n110560 bytes\n[1] \"Chunksize for dataframe after adjustment factor:\"\n[1] 429630\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n AICValue BICValue MSEValue \n \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\" \n \n \"cont3\" \"1\" \n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n AICValue BICValue MSEValue \n \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\" \n \n \"cont1\" \"2\" \n[1] \"Final Results of Variable Selection:\"\n AICValue BICValue MSEValue \nIterationSummary \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\"\nIterationSummary \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\"\n \nIterationSummary \"cont3\" \"1\"\nIterationSummary \"cont1\" \"2\"\n[1] \"Results Stored in $SelectionSummary\"\n> \n> \n> \n> \n> \n> \n> \n> cleanEx()\nWarning in .Internal(gc(verbose, reset, full)) :\n closing unused connection 3 (D:/temp/RtmpEHUBR4/RLIBS_12fec2e8ba2c/allan/extdata/SampleDataFile.csv)\nError: connections left open:\n\tD:/temp/RtmpEHUBR4/RLIBS_12fec2e8ba2c/allan/extdata/SampleDataFile.csv (file)\nExecution halted",
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"output": "Running examples in 'allan-Ex.R' failed\nThe error most likely occurred in:\n\n> ### Name: allanVarSelect\n> ### Title: Memory Unlimited Forward Stepwise Variable Selection for Linear\n> ### Models\n> ### Aliases: allanVarSelect\n> ### Keywords: stepwise linear regression memory\n> \n> ### ** Examples\n> \n> #Get external data. For your own data skip this next line and replace all\n> #instance of SampleData with \"YourFile.csv\".\n> SampleData=system.file(\"extdata\",\"SampleDataFile.csv\", package = \"allan\")\n> \n> #fit smaller data to biglm object\n> columnnames<-names(read.csv(SampleData, nrows=2,header=TRUE))\n> datafeed<-readinbigdata(SampleData,chunksize=1000,col.names=columnnames)\n> datafeed(TRUE)\n> firstchunk<-datafeed(FALSE)\n> \n> #create a biglm model from the small chunk with all variables that will be consdered\n> #for variable selection.\n> bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n> \n> #now run variable selection\n> FinalModel<-allanVarSelect(bigmodel,SampleData,SampleData,NumOfSteps=2,criteria=\"MSE\",silent=FALSE)\n[1] \"Total memory usage for 1000 lines:\"\n110560 bytes\n[1] \"Chunksize for dataframe after adjustment factor:\"\n[1] 429630\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n AICValue BICValue MSEValue \n \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\" \n \n \"cont3\" \"1\" \n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n AICValue BICValue MSEValue \n \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\" \n \n \"cont1\" \"2\" \n[1] \"Final Results of Variable Selection:\"\n AICValue BICValue MSEValue \nIterationSummary \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\"\nIterationSummary \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\"\n \nIterationSummary \"cont3\" \"1\"\nIterationSummary \"cont1\" \"2\"\n[1] \"Results Stored in $SelectionSummary\"\n> \n> \n> \n> \n> \n> \n> \n> cleanEx()\nWarning in .Internal(gc(verbose, reset, full)) :\n closing unused connection 3 (D:/temp/RtmpE9PIOK/RLIBS_eb3860833110/allan/extdata/SampleDataFile.csv)\nError: connections left open:\n\tD:/temp/RtmpE9PIOK/RLIBS_eb3860833110/allan/extdata/SampleDataFile.csv (file)\nExecution halted",
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"output": "Running examples in 'allan-Ex.R' failed\nThe error most likely occurred in:\n\n> ### Name: allanVarSelect\n> ### Title: Memory Unlimited Forward Stepwise Variable Selection for Linear\n> ### Models\n> ### Aliases: allanVarSelect\n> ### Keywords: stepwise linear regression memory\n> \n> ### ** Examples\n> \n> #Get external data. For your own data skip this next line and replace all\n> #instance of SampleData with \"YourFile.csv\".\n> SampleData=system.file(\"extdata\",\"SampleDataFile.csv\", package = \"allan\")\n> \n> #fit smaller data to biglm object\n> columnnames<-names(read.csv(SampleData, nrows=2,header=TRUE))\n> datafeed<-readinbigdata(SampleData,chunksize=1000,col.names=columnnames)\n> datafeed(TRUE)\n> firstchunk<-datafeed(FALSE)\n> \n> #create a biglm model from the small chunk with all variables that will be consdered\n> #for variable selection.\n> bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n> \n> #now run variable selection\n> FinalModel<-allanVarSelect(bigmodel,SampleData,SampleData,NumOfSteps=2,criteria=\"MSE\",silent=FALSE)\n[1] \"Total memory usage for 1000 lines:\"\n110560 bytes\n[1] \"Chunksize for dataframe after adjustment factor:\"\n[1] 429630\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n AICValue BICValue MSEValue \n \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\" \n \n \"cont3\" \"1\" \n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n AICValue BICValue MSEValue \n \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\" \n \n \"cont1\" \"2\" \n[1] \"Final Results of Variable Selection:\"\n AICValue BICValue MSEValue \nIterationSummary \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\"\nIterationSummary \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\"\n \nIterationSummary \"cont3\" \"1\"\nIterationSummary \"cont1\" \"2\"\n[1] \"Results Stored in $SelectionSummary\"\n> \n> \n> \n> \n> \n> \n> \n> cleanEx()\nWarning in .Internal(gc(verbose, reset, full)) :\n closing unused connection 3 (D:/temp/RtmpukHfZE/RLIBS_c44c28153910/allan/extdata/SampleDataFile.csv)\nError: connections left open:\n\tD:/temp/RtmpukHfZE/RLIBS_c44c28153910/allan/extdata/SampleDataFile.csv (file)\nExecution halted",
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"output": "Running examples in 'allan-Ex.R' failed\nThe error most likely occurred in:\n\n> ### Name: allanVarSelect\n> ### Title: Memory Unlimited Forward Stepwise Variable Selection for Linear\n> ### Models\n> ### Aliases: allanVarSelect\n> ### Keywords: stepwise linear regression memory\n> \n> ### ** Examples\n> \n> #Get external data. For your own data skip this next line and replace all\n> #instance of SampleData with \"YourFile.csv\".\n> SampleData=system.file(\"extdata\",\"SampleDataFile.csv\", package = \"allan\")\n> \n> #fit smaller data to biglm object\n> columnnames<-names(read.csv(SampleData, nrows=2,header=TRUE))\n> datafeed<-readinbigdata(SampleData,chunksize=1000,col.names=columnnames)\n> datafeed(TRUE)\n> firstchunk<-datafeed(FALSE)\n> \n> #create a biglm model from the small chunk with all variables that will be consdered\n> #for variable selection.\n> bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n> \n> #now run variable selection\n> FinalModel<-allanVarSelect(bigmodel,SampleData,SampleData,NumOfSteps=2,criteria=\"MSE\",silent=FALSE)\n[1] \"Total memory usage for 1000 lines:\"\n110560 bytes\n[1] \"Chunksize for dataframe after adjustment factor:\"\n[1] 429630\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n AICValue BICValue MSEValue \n \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\" \n \n \"cont3\" \"1\" \n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n AICValue BICValue MSEValue \n \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\" \n \n \"cont1\" \"2\" \n[1] \"Final Results of Variable Selection:\"\n AICValue BICValue MSEValue \nIterationSummary \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\"\nIterationSummary \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\"\n \nIterationSummary \"cont3\" \"1\"\nIterationSummary \"cont1\" \"2\"\n[1] \"Results Stored in $SelectionSummary\"\n> \n> \n> \n> \n> \n> \n> \n> cleanEx()\nWarning in .Internal(gc(verbose, reset, full)) :\n closing unused connection 3 (D:/temp/RtmpEHUBR4/RLIBS_12fec2e8ba2c/allan/extdata/SampleDataFile.csv)\nError: connections left open:\n\tD:/temp/RtmpEHUBR4/RLIBS_12fec2e8ba2c/allan/extdata/SampleDataFile.csv (file)\nExecution halted",
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"output": "Running examples in 'allan-Ex.R' failed\nThe error most likely occurred in:\n\n> ### Name: allanVarSelect\n> ### Title: Memory Unlimited Forward Stepwise Variable Selection for Linear\n> ### Models\n> ### Aliases: allanVarSelect\n> ### Keywords: stepwise linear regression memory\n> \n> ### ** Examples\n> \n> #Get external data. For your own data skip this next line and replace all\n> #instance of SampleData with \"YourFile.csv\".\n> SampleData=system.file(\"extdata\",\"SampleDataFile.csv\", package = \"allan\")\n> \n> #fit smaller data to biglm object\n> columnnames<-names(read.csv(SampleData, nrows=2,header=TRUE))\n> datafeed<-readinbigdata(SampleData,chunksize=1000,col.names=columnnames)\n> datafeed(TRUE)\n> firstchunk<-datafeed(FALSE)\n> \n> #create a biglm model from the small chunk with all variables that will be consdered\n> #for variable selection.\n> bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n> \n> #now run variable selection\n> FinalModel<-allanVarSelect(bigmodel,SampleData,SampleData,NumOfSteps=2,criteria=\"MSE\",silent=FALSE)\n[1] \"Total memory usage for 1000 lines:\"\n110560 bytes\n[1] \"Chunksize for dataframe after adjustment factor:\"\n[1] 429630\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n AICValue BICValue MSEValue \n \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\" \n \n \"cont3\" \"1\" \n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n AICValue BICValue MSEValue \n \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\" \n \n \"cont1\" \"2\" \n[1] \"Final Results of Variable Selection:\"\n AICValue BICValue MSEValue \nIterationSummary \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\"\nIterationSummary \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\"\n \nIterationSummary \"cont3\" \"1\"\nIterationSummary \"cont1\" \"2\"\n[1] \"Results Stored in $SelectionSummary\"\n> \n> \n> \n> \n> \n> \n> \n> cleanEx()\nWarning in .Internal(gc(verbose, reset, full)) :\n closing unused connection 3 (D:/temp/RtmpE9PIOK/RLIBS_eb3860833110/allan/extdata/SampleDataFile.csv)\nError: connections left open:\n\tD:/temp/RtmpE9PIOK/RLIBS_eb3860833110/allan/extdata/SampleDataFile.csv (file)\nExecution halted",
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"output": "Running examples in 'allan-Ex.R' failed\nThe error most likely occurred in:\n\n> ### Name: allanVarSelect\n> ### Title: Memory Unlimited Forward Stepwise Variable Selection for Linear\n> ### Models\n> ### Aliases: allanVarSelect\n> ### Keywords: stepwise linear regression memory\n> \n> ### ** Examples\n> \n> #Get external data. For your own data skip this next line and replace all\n> #instance of SampleData with \"YourFile.csv\".\n> SampleData=system.file(\"extdata\",\"SampleDataFile.csv\", package = \"allan\")\n> \n> #fit smaller data to biglm object\n> columnnames<-names(read.csv(SampleData, nrows=2,header=TRUE))\n> datafeed<-readinbigdata(SampleData,chunksize=1000,col.names=columnnames)\n> datafeed(TRUE)\n> firstchunk<-datafeed(FALSE)\n> \n> #create a biglm model from the small chunk with all variables that will be consdered\n> #for variable selection.\n> bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n> \n> #now run variable selection\n> FinalModel<-allanVarSelect(bigmodel,SampleData,SampleData,NumOfSteps=2,criteria=\"MSE\",silent=FALSE)\n[1] \"Total memory usage for 1000 lines:\"\n110560 bytes\n[1] \"Chunksize for dataframe after adjustment factor:\"\n[1] 429630\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n AICValue BICValue MSEValue \n \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\" \n \n \"cont3\" \"1\" \n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n AICValue BICValue MSEValue \n \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\" \n \n \"cont1\" \"2\" \n[1] \"Final Results of Variable Selection:\"\n AICValue BICValue MSEValue \nIterationSummary \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\"\nIterationSummary \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\"\n \nIterationSummary \"cont3\" \"1\"\nIterationSummary \"cont1\" \"2\"\n[1] \"Results Stored in $SelectionSummary\"\n> \n> \n> \n> \n> \n> \n> \n> cleanEx()\nWarning in .Internal(gc(verbose, reset, full)) :\n closing unused connection 3 (D:/temp/RtmpukHfZE/RLIBS_c44c28153910/allan/extdata/SampleDataFile.csv)\nError: connections left open:\n\tD:/temp/RtmpukHfZE/RLIBS_c44c28153910/allan/extdata/SampleDataFile.csv (file)\nExecution halted",
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"output": "Running examples in 'allan-Ex.R' failed\nThe error most likely occurred in:\n\n> ### Name: allanVarSelect\n> ### Title: Memory Unlimited Forward Stepwise Variable Selection for Linear\n> ### Models\n> ### Aliases: allanVarSelect\n> ### Keywords: stepwise linear regression memory\n> \n> ### ** Examples\n> \n> #Get external data. For your own data skip this next line and replace all\n> #instance of SampleData with \"YourFile.csv\".\n> SampleData=system.file(\"extdata\",\"SampleDataFile.csv\", package = \"allan\")\n> \n> #fit smaller data to biglm object\n> columnnames<-names(read.csv(SampleData, nrows=2,header=TRUE))\n> datafeed<-readinbigdata(SampleData,chunksize=1000,col.names=columnnames)\n> datafeed(TRUE)\n> firstchunk<-datafeed(FALSE)\n> \n> #create a biglm model from the small chunk with all variables that will be consdered\n> #for variable selection.\n> bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n> \n> #now run variable selection\n> FinalModel<-allanVarSelect(bigmodel,SampleData,SampleData,NumOfSteps=2,criteria=\"MSE\",silent=FALSE)\n[1] \"Total memory usage for 1000 lines:\"\n110560 bytes\n[1] \"Chunksize for dataframe after adjustment factor:\"\n[1] 429630\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n AICValue BICValue MSEValue \n \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\" \n \n \"cont3\" \"1\" \n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n AICValue BICValue MSEValue \n \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\" \n \n \"cont1\" \"2\" \n[1] \"Final Results of Variable Selection:\"\n AICValue BICValue MSEValue \nIterationSummary \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\"\nIterationSummary \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\"\n \nIterationSummary \"cont3\" \"1\"\nIterationSummary \"cont1\" \"2\"\n[1] \"Results Stored in $SelectionSummary\"\n> \n> \n> \n> \n> \n> \n> \n> cleanEx()\nWarning in .Internal(gc(verbose, reset, full)) :\n closing unused connection 3 (D:/temp/RtmpEHUBR4/RLIBS_12fec2e8ba2c/allan/extdata/SampleDataFile.csv)\nError: connections left open:\n\tD:/temp/RtmpEHUBR4/RLIBS_12fec2e8ba2c/allan/extdata/SampleDataFile.csv (file)\nExecution halted",
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"output": "Running examples in 'allan-Ex.R' failed\nThe error most likely occurred in:\n\n> ### Name: allanVarSelect\n> ### Title: Memory Unlimited Forward Stepwise Variable Selection for Linear\n> ### Models\n> ### Aliases: allanVarSelect\n> ### Keywords: stepwise linear regression memory\n> \n> ### ** Examples\n> \n> #Get external data. For your own data skip this next line and replace all\n> #instance of SampleData with \"YourFile.csv\".\n> SampleData=system.file(\"extdata\",\"SampleDataFile.csv\", package = \"allan\")\n> \n> #fit smaller data to biglm object\n> columnnames<-names(read.csv(SampleData, nrows=2,header=TRUE))\n> datafeed<-readinbigdata(SampleData,chunksize=1000,col.names=columnnames)\n> datafeed(TRUE)\n> firstchunk<-datafeed(FALSE)\n> \n> #create a biglm model from the small chunk with all variables that will be consdered\n> #for variable selection.\n> bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n> \n> #now run variable selection\n> FinalModel<-allanVarSelect(bigmodel,SampleData,SampleData,NumOfSteps=2,criteria=\"MSE\",silent=FALSE)\n[1] \"Total memory usage for 1000 lines:\"\n110560 bytes\n[1] \"Chunksize for dataframe after adjustment factor:\"\n[1] 429630\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n AICValue BICValue MSEValue \n \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\" \n \n \"cont3\" \"1\" \n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n AICValue BICValue MSEValue \n \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\" \n \n \"cont1\" \"2\" \n[1] \"Final Results of Variable Selection:\"\n AICValue BICValue MSEValue \nIterationSummary \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\"\nIterationSummary \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\"\n \nIterationSummary \"cont3\" \"1\"\nIterationSummary \"cont1\" \"2\"\n[1] \"Results Stored in $SelectionSummary\"\n> \n> \n> \n> \n> \n> \n> \n> cleanEx()\nWarning in .Internal(gc(verbose, reset, full)) :\n closing unused connection 3 (D:/temp/RtmpE9PIOK/RLIBS_eb3860833110/allan/extdata/SampleDataFile.csv)\nError: connections left open:\n\tD:/temp/RtmpE9PIOK/RLIBS_eb3860833110/allan/extdata/SampleDataFile.csv (file)\nExecution halted",
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"output": "Running examples in 'allan-Ex.R' failed\nThe error most likely occurred in:\n\n> ### Name: allanVarSelect\n> ### Title: Memory Unlimited Forward Stepwise Variable Selection for Linear\n> ### Models\n> ### Aliases: allanVarSelect\n> ### Keywords: stepwise linear regression memory\n> \n> ### ** Examples\n> \n> #Get external data. For your own data skip this next line and replace all\n> #instance of SampleData with \"YourFile.csv\".\n> SampleData=system.file(\"extdata\",\"SampleDataFile.csv\", package = \"allan\")\n> \n> #fit smaller data to biglm object\n> columnnames<-names(read.csv(SampleData, nrows=2,header=TRUE))\n> datafeed<-readinbigdata(SampleData,chunksize=1000,col.names=columnnames)\n> datafeed(TRUE)\n> firstchunk<-datafeed(FALSE)\n> \n> #create a biglm model from the small chunk with all variables that will be consdered\n> #for variable selection.\n> bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n> \n> #now run variable selection\n> FinalModel<-allanVarSelect(bigmodel,SampleData,SampleData,NumOfSteps=2,criteria=\"MSE\",silent=FALSE)\n[1] \"Total memory usage for 1000 lines:\"\n110560 bytes\n[1] \"Chunksize for dataframe after adjustment factor:\"\n[1] 429630\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n AICValue BICValue MSEValue \n \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\" \n \n \"cont3\" \"1\" \n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n AICValue BICValue MSEValue \n \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\" \n \n \"cont1\" \"2\" \n[1] \"Final Results of Variable Selection:\"\n AICValue BICValue MSEValue \nIterationSummary \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\"\nIterationSummary \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\"\n \nIterationSummary \"cont3\" \"1\"\nIterationSummary \"cont1\" \"2\"\n[1] \"Results Stored in $SelectionSummary\"\n> \n> \n> \n> \n> \n> \n> \n> cleanEx()\nWarning in .Internal(gc(verbose, reset, full)) :\n closing unused connection 3 (D:/temp/RtmpukHfZE/RLIBS_c44c28153910/allan/extdata/SampleDataFile.csv)\nError: connections left open:\n\tD:/temp/RtmpukHfZE/RLIBS_c44c28153910/allan/extdata/SampleDataFile.csv (file)\nExecution halted",
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"output": "Running examples in 'allan-Ex.R' failed\nThe error most likely occurred in:\n\n> ### Name: allanVarSelect\n> ### Title: Memory Unlimited Forward Stepwise Variable Selection for Linear\n> ### Models\n> ### Aliases: allanVarSelect\n> ### Keywords: stepwise linear regression memory\n> \n> ### ** Examples\n> \n> #Get external data. For your own data skip this next line and replace all\n> #instance of SampleData with \"YourFile.csv\".\n> SampleData=system.file(\"extdata\",\"SampleDataFile.csv\", package = \"allan\")\n> \n> #fit smaller data to biglm object\n> columnnames<-names(read.csv(SampleData, nrows=2,header=TRUE))\n> datafeed<-readinbigdata(SampleData,chunksize=1000,col.names=columnnames)\n> datafeed(TRUE)\n> firstchunk<-datafeed(FALSE)\n> \n> #create a biglm model from the small chunk with all variables that will be consdered\n> #for variable selection.\n> bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n> \n> #now run variable selection\n> FinalModel<-allanVarSelect(bigmodel,SampleData,SampleData,NumOfSteps=2,criteria=\"MSE\",silent=FALSE)\n[1] \"Total memory usage for 1000 lines:\"\n110560 bytes\n[1] \"Chunksize for dataframe after adjustment factor:\"\n[1] 429630\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n AICValue BICValue MSEValue \n \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\" \n \n \"cont3\" \"1\" \n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n AICValue BICValue MSEValue \n \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\" \n \n \"cont1\" \"2\" \n[1] \"Final Results of Variable Selection:\"\n AICValue BICValue MSEValue \nIterationSummary \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\"\nIterationSummary \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\"\n \nIterationSummary \"cont3\" \"1\"\nIterationSummary \"cont1\" \"2\"\n[1] \"Results Stored in $SelectionSummary\"\n> \n> \n> \n> \n> \n> \n> \n> cleanEx()\nWarning in .Internal(gc(verbose, reset, full)) :\n closing unused connection 3 (D:/temp/RtmpEHUBR4/RLIBS_12fec2e8ba2c/allan/extdata/SampleDataFile.csv)\nError: connections left open:\n\tD:/temp/RtmpEHUBR4/RLIBS_12fec2e8ba2c/allan/extdata/SampleDataFile.csv (file)\nExecution halted",
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"output": "Running examples in 'allan-Ex.R' failed\nThe error most likely occurred in:\n\n> ### Name: allanVarSelect\n> ### Title: Memory Unlimited Forward Stepwise Variable Selection for Linear\n> ### Models\n> ### Aliases: allanVarSelect\n> ### Keywords: stepwise linear regression memory\n> \n> ### ** Examples\n> \n> #Get external data. For your own data skip this next line and replace all\n> #instance of SampleData with \"YourFile.csv\".\n> SampleData=system.file(\"extdata\",\"SampleDataFile.csv\", package = \"allan\")\n> \n> #fit smaller data to biglm object\n> columnnames<-names(read.csv(SampleData, nrows=2,header=TRUE))\n> datafeed<-readinbigdata(SampleData,chunksize=1000,col.names=columnnames)\n> datafeed(TRUE)\n> firstchunk<-datafeed(FALSE)\n> \n> #create a biglm model from the small chunk with all variables that will be consdered\n> #for variable selection.\n> bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n> \n> #now run variable selection\n> FinalModel<-allanVarSelect(bigmodel,SampleData,SampleData,NumOfSteps=2,criteria=\"MSE\",silent=FALSE)\n[1] \"Total memory usage for 1000 lines:\"\n110560 bytes\n[1] \"Chunksize for dataframe after adjustment factor:\"\n[1] 429630\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n AICValue BICValue MSEValue \n \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\" \n \n \"cont3\" \"1\" \n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n AICValue BICValue MSEValue \n \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\" \n \n \"cont1\" \"2\" \n[1] \"Final Results of Variable Selection:\"\n AICValue BICValue MSEValue \nIterationSummary \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\"\nIterationSummary \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\"\n \nIterationSummary \"cont3\" \"1\"\nIterationSummary \"cont1\" \"2\"\n[1] \"Results Stored in $SelectionSummary\"\n> \n> \n> \n> \n> \n> \n> \n> cleanEx()\nWarning in .Internal(gc(verbose, reset, full)) :\n closing unused connection 3 (D:/temp/RtmpE9PIOK/RLIBS_eb3860833110/allan/extdata/SampleDataFile.csv)\nError: connections left open:\n\tD:/temp/RtmpE9PIOK/RLIBS_eb3860833110/allan/extdata/SampleDataFile.csv (file)\nExecution halted",
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cchecks::cch_pkgs_search(q = "memory")
$error
NULL
$count
[1] 1215
$returned
[1] 30
$data
# A tibble: 30 x 5
package date_updated summary$any $ok $note $warn $error $fail checks
<chr> <chr> <lgl> <int> <int> <int> <int> <int> <list>
1 cluster… 2021-02-23T15:0… TRUE 0 10 0 2 0 <df[,7]…
2 cluster… 2021-02-26T15:0… TRUE 0 10 0 2 0 <df[,7]…
3 allan 2021-02-20T15:0… TRUE 0 9 0 3 0 <df[,7]…
4 allan 2021-02-21T15:0… TRUE 0 9 0 3 0 <df[,7]…
5 allan 2021-02-22T15:0… TRUE 0 9 0 3 0 <df[,7]…
6 allan 2021-02-23T15:0… TRUE 0 9 0 3 0 <df[,7]…
7 allan 2021-02-24T15:0… TRUE 0 9 0 3 0 <df[,7]…
8 allan 2021-02-25T15:0… TRUE 0 9 0 3 0 <df[,7]…
9 allan 2021-02-26T15:0… TRUE 0 9 0 3 0 <df[,7]…
10 allan 2021-02-27T15:0… TRUE 0 9 0 3 0 <df[,7]…
# … with 20 more rows, and 1 more variable: check_details <df[,2]>
curl https://cranchecks.info/search?q=memory&one_each=true&limit=2 | jq .
HTTP/2 200
access-control-allow-methods: HEAD, GET
access-control-allow-origin: *
cache-control: public, must-revalidate, max-age=60
content-type: application/json; charset=utf8
server: Caddy
x-content-type-options: nosniff
content-length: 28475
date: Mon, 22 Mar 2021 13:01:32 GMT
{
"error": null,
"count": 61,
"returned": 2,
"data": [
{
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"output": "Running examples in 'allan-Ex.R' failed\nThe error most likely occurred in:\n\n> ### Name: allanVarSelect\n> ### Title: Memory Unlimited Forward Stepwise Variable Selection for Linear\n> ### Models\n> ### Aliases: allanVarSelect\n> ### Keywords: stepwise linear regression memory\n> \n> ### ** Examples\n> \n> #Get external data. For your own data skip this next line and replace all\n> #instance of SampleData with \"YourFile.csv\".\n> SampleData=system.file(\"extdata\",\"SampleDataFile.csv\", package = \"allan\")\n> \n> #fit smaller data to biglm object\n> columnnames<-names(read.csv(SampleData, nrows=2,header=TRUE))\n> datafeed<-readinbigdata(SampleData,chunksize=1000,col.names=columnnames)\n> datafeed(TRUE)\n> firstchunk<-datafeed(FALSE)\n> \n> #create a biglm model from the small chunk with all variables that will be consdered\n> #for variable selection.\n> bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n> \n> #now run variable selection\n> FinalModel<-allanVarSelect(bigmodel,SampleData,SampleData,NumOfSteps=2,criteria=\"MSE\",silent=FALSE)\n[1] \"Total memory usage for 1000 lines:\"\n110560 bytes\n[1] \"Chunksize for dataframe after adjustment factor:\"\n[1] 429630\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n AICValue BICValue MSEValue \n \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\" \n \n \"cont3\" \"1\" \n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n AICValue BICValue MSEValue \n \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\" \n \n \"cont1\" \"2\" \n[1] \"Final Results of Variable Selection:\"\n AICValue BICValue MSEValue \nIterationSummary \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\"\nIterationSummary \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\"\n \nIterationSummary \"cont3\" \"1\"\nIterationSummary \"cont1\" \"2\"\n[1] \"Results Stored in $SelectionSummary\"\n> \n> \n> \n> \n> \n> \n> \n> cleanEx()\nWarning in .Internal(gc(verbose, reset, full)) :\n closing unused connection 3 (D:/temp/RtmpukHfZE/RLIBS_c44c28153910/allan/extdata/SampleDataFile.csv)\nError: connections left open:\n\tD:/temp/RtmpukHfZE/RLIBS_c44c28153910/allan/extdata/SampleDataFile.csv (file)\nExecution halted",
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"output": "Running examples in 'allan-Ex.R' failed\nThe error most likely occurred in:\n\n> ### Name: allanVarSelect\n> ### Title: Memory Unlimited Forward Stepwise Variable Selection for Linear\n> ### Models\n> ### Aliases: allanVarSelect\n> ### Keywords: stepwise linear regression memory\n> \n> ### ** Examples\n> \n> #Get external data. For your own data skip this next line and replace all\n> #instance of SampleData with \"YourFile.csv\".\n> SampleData=system.file(\"extdata\",\"SampleDataFile.csv\", package = \"allan\")\n> \n> #fit smaller data to biglm object\n> columnnames<-names(read.csv(SampleData, nrows=2,header=TRUE))\n> datafeed<-readinbigdata(SampleData,chunksize=1000,col.names=columnnames)\n> datafeed(TRUE)\n> firstchunk<-datafeed(FALSE)\n> \n> #create a biglm model from the small chunk with all variables that will be consdered\n> #for variable selection.\n> bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n> \n> #now run variable selection\n> FinalModel<-allanVarSelect(bigmodel,SampleData,SampleData,NumOfSteps=2,criteria=\"MSE\",silent=FALSE)\n[1] \"Total memory usage for 1000 lines:\"\n110560 bytes\n[1] \"Chunksize for dataframe after adjustment factor:\"\n[1] 429630\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n AICValue BICValue MSEValue \n \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\" \n \n \"cont3\" \"1\" \n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n AICValue BICValue MSEValue \n \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\" \n \n \"cont1\" \"2\" \n[1] \"Final Results of Variable Selection:\"\n AICValue BICValue MSEValue \nIterationSummary \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\"\nIterationSummary \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\"\n \nIterationSummary \"cont3\" \"1\"\nIterationSummary \"cont1\" \"2\"\n[1] \"Results Stored in $SelectionSummary\"\n> \n> \n> \n> \n> \n> \n> \n> cleanEx()\nWarning in .Internal(gc(verbose, reset, full)) :\n closing unused connection 3 (D:/temp/RtmpEHUBR4/RLIBS_12fec2e8ba2c/allan/extdata/SampleDataFile.csv)\nError: connections left open:\n\tD:/temp/RtmpEHUBR4/RLIBS_12fec2e8ba2c/allan/extdata/SampleDataFile.csv (file)\nExecution halted",
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"output": "Running examples in 'allan-Ex.R' failed\nThe error most likely occurred in:\n\n> ### Name: allanVarSelect\n> ### Title: Memory Unlimited Forward Stepwise Variable Selection for Linear\n> ### Models\n> ### Aliases: allanVarSelect\n> ### Keywords: stepwise linear regression memory\n> \n> ### ** Examples\n> \n> #Get external data. For your own data skip this next line and replace all\n> #instance of SampleData with \"YourFile.csv\".\n> SampleData=system.file(\"extdata\",\"SampleDataFile.csv\", package = \"allan\")\n> \n> #fit smaller data to biglm object\n> columnnames<-names(read.csv(SampleData, nrows=2,header=TRUE))\n> datafeed<-readinbigdata(SampleData,chunksize=1000,col.names=columnnames)\n> datafeed(TRUE)\n> firstchunk<-datafeed(FALSE)\n> \n> #create a biglm model from the small chunk with all variables that will be consdered\n> #for variable selection.\n> bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n> \n> #now run variable selection\n> FinalModel<-allanVarSelect(bigmodel,SampleData,SampleData,NumOfSteps=2,criteria=\"MSE\",silent=FALSE)\n[1] \"Total memory usage for 1000 lines:\"\n110560 bytes\n[1] \"Chunksize for dataframe after adjustment factor:\"\n[1] 429630\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n AICValue BICValue MSEValue \n \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\" \n \n \"cont3\" \"1\" \n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n AICValue BICValue MSEValue \n \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\" \n \n \"cont1\" \"2\" \n[1] \"Final Results of Variable Selection:\"\n AICValue BICValue MSEValue \nIterationSummary \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\"\nIterationSummary \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\"\n \nIterationSummary \"cont3\" \"1\"\nIterationSummary \"cont1\" \"2\"\n[1] \"Results Stored in $SelectionSummary\"\n> \n> \n> \n> \n> \n> \n> \n> cleanEx()\nWarning in .Internal(gc(verbose, reset, full)) :\n closing unused connection 3 (D:/temp/RtmpE9PIOK/RLIBS_eb3860833110/allan/extdata/SampleDataFile.csv)\nError: connections left open:\n\tD:/temp/RtmpE9PIOK/RLIBS_eb3860833110/allan/extdata/SampleDataFile.csv (file)\nExecution halted",
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"output": "Running examples in ‘BIRDS-Ex.R’ failed\nThe error most likely occurred in:\n\n> ### Name: listSpecies\n> ### Title: Lists all species names from the data set\n> ### Aliases: listSpecies\n> \n> ### ** Examples\n> \n> OB <- organizeBirds(bombusObsShort, sppCol = \"scientificName\", simplifySppName = TRUE)\nError: Service Unavailable (HTTP 503)\nExecution halted",
"check": "examples",
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"output": "Error(s) in re-building vignettes:\n--- re-building ‘BIRDS.Rmd’ using rmarkdown\n--- finished re-building ‘BIRDS.Rmd’\n\n--- re-building ‘technical_details.Rmd’ using rmarkdown\n--- finished re-building ‘technical_details.Rmd’\n\nsh: line 1: 3806316 Segmentation fault (core dumped) R_LIBS=/tmp/RtmpJNaaDX/RLIBS_382e8337e78070 R_ENVIRON_USER='' R_LIBS_USER='' R_LIBS_SITE='no_such_dir' '/data/gannet/ripley/R/R-clang/bin/R' --vanilla --no-echo > '/tmp/RtmpJNaaDX/working_dir/RtmpQUosnL/file398f073d6e39b5' 2>&1 < '/tmp/RtmpJNaaDX/working_dir/RtmpQUosnL/file398f075951016c'\nWarning: elapsed-time limit of 30 minutes reached for sub-process\n--- re-building ‘working_with_xts_timeseries.Rmd’ using rmarkdown\nLoading required package: zoo\n\nAttaching package: 'zoo'\n\nThe following objects are masked from 'package:base':\n\n as.Date, as.Date.numeric\n\nWarning in showSRID(uprojargs, format = \"PROJ\", multiline = \"NO\", prefer_proj = prefer_proj) :\n Discarded ellps WGS 84 in Proj4 definition: +proj=merc +a=6378137 +b=6378137 +lat_ts=0 +lon_0=0 +x_0=0 +y_0=0 +k=1 +units=m +nadgrids=@null +wktext +no_defs\nWarning in showSRID(uprojargs, format = \"PROJ\", multiline = \"NO\", prefer_proj = prefer_proj) :\n Discarded datum WGS_1984 in Proj4 definition\nWarning in spTransform(polygon, CRSobj = CRS(\"+init=epsg:3857\")) :\n NULL source CRS comment, falling back to PROJ string\nWarning in spTransform(polygon, CRSobj = CRS(\"+init=epsg:3857\")) :\n +init dropped in PROJ string\nWarning in wkt(obj) : CRS object has no comment\nWarning in proj4string(obj) :\n CRS object has comment, which is lost in output\n\nQuitting from lines 26-43 (working_with_xts_timeseries.Rmd) \n\n *** caught segfault ***\naddress 0x44c6, cause 'memory not mapped'\n\nTraceback:\n 1: dev.off(dv)\n 2: block_exec(params)\n 3: call_block(x)\n 4: process_group.block(group)\n 5: process_group(group)\n 6: withCallingHandlers(if (tangle) process_tangle(group) else process_group(group), error = function(e) { setwd(wd) cat(res, sep = \"\\n\", file = output %n% \"\") message(\"Quitting from lines \", paste(current_lines(i), collapse = \"-\"), \" (\", knit_concord$get(\"infile\"), \") \") })\n 7: process_file(text, output)\n 8: knitr::knit(knit_input, knit_output, envir = envir, quiet = quiet)\n 9: rmarkdown::render(file, encoding = encoding, quiet = quiet, envir = globalenv(), output_dir = getwd(), ...)\n10: vweave_rmarkdown(...)\n11: engine$weave(file, quiet = quiet, encoding = enc)\n12: doTryCatch(return(expr), name, parentenv, handler)\n13: tryCatchOne(expr, names, parentenv, handlers[[1L]])\n14: tryCatchList(expr, classes, parentenv, handlers)\n15: tryCatch({ engine$weave(file, quiet = quiet, encoding = enc) setwd(startdir) output <- find_vignette_product(name, by = \"weave\", engine = engine) if (!have.makefile && vignette_is_tex(output)) { texi2pdf(file = output, clean = FALSE, quiet = quiet) output <- find_vignette_product(name, by = \"texi2pdf\", engine = engine) }}, error = function(e) { OK <<- FALSE message(gettextf(\"Error: processing vignette '%s' failed with diagnostics:\\n%s\", file, conditionMessage(e)))})\n16: tools:::.buildOneVignette(\"working_with_xts_timeseries.Rmd\", \"/data/gannet/ripley/R/packages/tests-clang/BIRDS.Rcheck/vign_test/BIRDS\", TRUE, FALSE, \"working_with_xts_timeseries\", \"UTF-8\", \"/tmp/RtmpJNaaDX/working_dir/RtmpQUosnL/file398f07526f457e.rds\")\nAn irrecoverable exception occurred. R is aborting now ...\nSUMMARY: processing the following file failed:\n ‘working_with_xts_timeseries.Rmd’\n\nError: Vignette re-building failed.\nExecution halted",
"check": "re-building of vignette outputs",
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cchecks::cch_pkgs_search(q = "memory", one_each = TRUE, limit = 2)
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NULL
$count
[1] 61
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[1] 2
$data
# A tibble: 2 x 5
package date_updated summary$any $ok $note $warn $error $fail checks
<chr> <chr> <lgl> <int> <int> <int> <int> <int> <list>
1 allan 2021-02-20T15:03… TRUE 0 9 0 3 0 <df[,7] …
2 BIRDS 2021-02-20T15:03… TRUE 3 8 0 1 0 <df[,7] …
# … with 1 more variable: check_details <df[,2]>
curl https://cranchecks.info/search?q=memory&one_each=true&fields=package | jq .
HTTP/2 200
access-control-allow-methods: HEAD, GET
access-control-allow-origin: *
cache-control: public, must-revalidate, max-age=60
content-type: application/json; charset=utf8
server: Caddy
x-content-type-options: nosniff
content-length: 1186
date: Mon, 22 Mar 2021 13:01:54 GMT
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cchecks::cch_pkgs_search(q = "memory", one_each = TRUE, fields = "package")
$error
NULL
$count
[1] 61
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# A tibble: 30 x 5
package date_updated summary checks check_details
<chr> <chr> <lgl> <lgl> <lgl>
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6 cairoDevice 2021-02-22T15:03:45.000Z NA NA NA
7 cecs 2021-02-20T15:03:50.000Z NA NA NA
8 ChoR 2021-03-06T15:03:46.000Z NA NA NA
9 clusternor 2021-02-23T15:03:48.000Z NA NA NA
10 compboost 2021-02-20T15:03:50.000Z NA NA NA
# … with 20 more rows