Stable version from CRAN
install.packages("gistr")
Development version from GitHub
devtools::install_github("ropensci/gistr")
library("gistr")
There are two ways to authorise gistr to work with your GitHub account:
GITHUB_PAT envar.Using the PAT is recommended.
Using the gist_auth() function you can authenticate seperately first, or if you're not authenticated, this function will run internally with each functionn call. If you have a PAT, that will be used, if not, OAuth will be used.
gist_auth()
In gistr you can use pipes, introduced perhaps first in R in the package magrittr, to pass outputs from one function to another. If you have used dplyr with pipes you can see the difference, and perhaps the utility, of this workflow over the traditional workflow in R. You can use a non-piping or a piping workflow with gistr. Examples below use a mix of both workflows. Here is an example of a piping wofklow (with some explanation):
file <- system.file("examples", "stuff.Rmd", package = "gistr")
gists(what = "minepublic")[[1]] %>% # List my public gists, and index 1st
add_files(file) %>% # Add new file to that gist
update() # update sends a PATCH command to Gists API to add file to your gist
And a non-piping workflow that does the same exact thing:
file <- system.file("examples", "example1.md", package = "gistr")
g <- gists(what = "minepublic")[[1]]
g <- add_files(g, file)
update(g)
Or you could string them all together in one line (but it's rather difficult to follow what's going on because you have to read from the inside out)
update(add_files(gists(what = "minepublic")[[1]], file))
rate_limit()
#> Rate limit: 5000
#> Remaining: 4224
#> Resets in: 43 minutes
Limiting to a few results here to keep it brief
gists(per_page = 2)
#> [[1]]
#> <gist>4baa80440a1e0cdb4b195872762c6251
#> URL: https://gist.github.com/4baa80440a1e0cdb4b195872762c6251
#> Description: Elimination (PuzzleScript Script)
#> Public: TRUE
#> Created/Edited: 2019-07-18T17:39:06Z / 2019-07-18T17:39:06Z
#> Files: readme.txt, script.txt
#> Truncated?: FALSE, FALSE
#>
#> [[2]]
#> <gist>9f15e4d4c5f02b56cc634c31dd9f4153
#> URL: https://gist.github.com/9f15e4d4c5f02b56cc634c31dd9f4153
#> Description: rubberduck v1.4.3 - Passed - Package Tests Results
#> Public: TRUE
#> Created/Edited: 2019-07-18T17:39:05Z / 2019-07-18T17:39:06Z
#> Files: 1.RegistrySnapshot.xml, FilesSnapshot.xml, Install.txt, Uninstall.txt, _Summary.md
#> Truncated?: FALSE, FALSE, FALSE, FALSE, FALSE
Since a certain date/time
gists(since = '2014-05-26T00:00:00Z', per_page = 2)
#> [[1]]
#> <gist>4baa80440a1e0cdb4b195872762c6251
#> URL: https://gist.github.com/4baa80440a1e0cdb4b195872762c6251
#> Description: Elimination (PuzzleScript Script)
#> Public: TRUE
#> Created/Edited: 2019-07-18T17:39:06Z / 2019-07-18T17:39:06Z
#> Files: readme.txt, script.txt
#> Truncated?: FALSE, FALSE
#>
#> [[2]]
#> <gist>9f15e4d4c5f02b56cc634c31dd9f4153
#> URL: https://gist.github.com/9f15e4d4c5f02b56cc634c31dd9f4153
#> Description: rubberduck v1.4.3 - Passed - Package Tests Results
#> Public: TRUE
#> Created/Edited: 2019-07-18T17:39:05Z / 2019-07-18T17:39:06Z
#> Files: 1.RegistrySnapshot.xml, FilesSnapshot.xml, Install.txt, Uninstall.txt, _Summary.md
#> Truncated?: FALSE, FALSE, FALSE, FALSE, FALSE
Request different types of gists, one of public, minepublic, mineall, or starred.
gists('minepublic', per_page = 2)
#> [[1]]
#> <gist>52f6dab219e0f2ca3f71cf70cafa11a3
#> URL: https://gist.github.com/52f6dab219e0f2ca3f71cf70cafa11a3
#> Description:
#> Public: TRUE
#> Created/Edited: 2019-04-24T16:38:20Z / 2019-04-24T16:38:43Z
#> Files: crul-eg.R
#> Truncated?: FALSE
#>
#> [[2]]
#> <gist>79507e3c5b905f605648797d849c1126
#> URL: https://gist.github.com/79507e3c5b905f605648797d849c1126
#> Description:
#> Public: TRUE
#> Created/Edited: 2019-02-22T20:31:58Z / 2019-02-22T20:31:58Z
#> Files: classification_munging.md
#> Truncated?: FALSE
gist(id = 'f1403260eb92f5dfa7e1')
#> <gist>f1403260eb92f5dfa7e1
#> URL: https://gist.github.com/f1403260eb92f5dfa7e1
#> Description: Querying bitly from R
#> Public: TRUE
#> Created/Edited: 2014-10-15T20:40:12Z / 2015-08-29T14:07:43Z
#> Files: bitly_r.md
#> Truncated?: FALSE
You can pass in files
First, get a file to work with
stuffpath <- system.file("examples", "stuff.md", package = "gistr")
gist_create(files = stuffpath, description = 'a new cool gist')
gist_create(files = stuffpath, description = 'a new cool gist', browse = FALSE)
#> <gist>9984709a30889023bd79e489a7d50860
#> URL: https://gist.github.com/9984709a30889023bd79e489a7d50860
#> Description: a new cool gist
#> Public: TRUE
#> Created/Edited: 2019-07-18T17:39:09Z / 2019-07-18T17:39:09Z
#> Files: stuff.md
#> Truncated?: FALSE
Or, wrap gist_create() around some code in your R session/IDE, like so, with just the function name, and a {' at the start and a '} at the end.
gist_create(code = {'
x <- letters
numbers <- runif(8)
numbers
[1] 0.3229318 0.5933054 0.7778408 0.3898947 0.1309717 0.7501378 0.3206379 0.3379005
'}, browse = FALSE)
#> <gist>46b8f33a29f14f7c71fc409020cd6e43
#> URL: https://gist.github.com/46b8f33a29f14f7c71fc409020cd6e43
#> Description:
#> Public: TRUE
#> Created/Edited: 2019-07-18T17:39:11Z / 2019-07-18T17:39:11Z
#> Files: code.R
#> Truncated?: FALSE
You can also knit an input file before posting as a gist:
file <- system.file("examples", "stuff.Rmd", package = "gistr")
gist_create(file, description = 'a new cool gist', knit = TRUE)
#> <gist>4162b9c53479fbc298db
#> URL: https://gist.github.com/4162b9c53479fbc298db
#> Description: a new cool gist
#> Public: TRUE
#> Created/Edited: 2014-10-27T16:07:31Z / 2014-10-27T16:07:31Z
#> Files: stuff.md
Or code blocks before (note that code blocks without knitr block demarcations will result in unexecuted code):
gist_create(code = {'
x <- letters
(numbers <- runif(8))
'}, knit = TRUE)
#> <gist>ec45c396dee4aa492139
#> URL: https://gist.github.com/ec45c396dee4aa492139
#> Description:
#> Public: TRUE
#> Created/Edited: 2014-10-27T16:09:09Z / 2014-10-27T16:09:09Z
#> Files: file81720d1ceff.md
knit a local file
file <- system.file("examples", "stuff.Rmd", package = "gistr")
run(file, knitopts = list(quiet = TRUE)) %>% gist_create(browse = FALSE)
#> <gist>43b3e21059b86fef954eb08a3d3286ee
#> URL: https://gist.github.com/43b3e21059b86fef954eb08a3d3286ee
#> Description:
#> Public: TRUE
#> Created/Edited: 2019-07-18T17:39:13Z / 2019-07-18T17:39:13Z
#> Files: stuff.md
#> Truncated?: FALSE
knit a code block (knitr code block notation missing, do add that in) (result not shown)
run({'
x <- letters
(numbers <- runif(8))
'}) %>% gist_create()
knit a file from a gist, has to get file first (result not shown)
gists('minepublic')[[1]] %>% run() %>% update()
gists()[[1]] %>% commits()
#> [[1]]
#> <commit>
#> Version: 470b3fbdf638a083ede94d7ae7fd42f0560180dd
#> User: ereastman616
#> Commited: 2019-07-18T17:39:13Z
#> Commits [total, additions, deletions]: [123,123,0]
Star
gist('b564093d359eb735138a97258d03f333') %>% star()
#> <gist>b564093d359eb735138a97258d03f333
#> URL: https://gist.github.com/b564093d359eb735138a97258d03f333
#> Description:
#> Public: TRUE
#> Created/Edited: 2018-10-03T19:07:37Z / 2018-10-03T19:07:37Z
#> Files: rcrossref-references.md
#> Truncated?: FALSE
Unstar
gist('b564093d359eb735138a97258d03f333') %>% unstar()
#> <gist>b564093d359eb735138a97258d03f333
#> URL: https://gist.github.com/b564093d359eb735138a97258d03f333
#> Description:
#> Public: TRUE
#> Created/Edited: 2018-10-03T19:07:37Z / 2019-07-18T17:39:15Z
#> Files: rcrossref-references.md
#> Truncated?: FALSE
Add files
First, path to file
file <- system.file("examples", "alm.md", package = "gistr")
gists(what = "minepublic")[[1]] %>%
add_files(file) %>%
update()
#> <gist>46b8f33a29f14f7c71fc409020cd6e43
#> URL: https://gist.github.com/46b8f33a29f14f7c71fc409020cd6e43
#> Description:
#> Public: TRUE
#> Created/Edited: 2019-07-18T17:39:11Z / 2019-07-18T17:39:16Z
#> Files: alm.md, code.R
#> Truncated?: FALSE, FALSE
Delete files
gists(what = "minepublic")[[1]] %>%
delete_files(file) %>%
update()
#> <gist>46b8f33a29f14f7c71fc409020cd6e43
#> URL: https://gist.github.com/46b8f33a29f14f7c71fc409020cd6e43
#> Description:
#> Public: TRUE
#> Created/Edited: 2019-07-18T17:39:11Z / 2019-07-18T17:39:18Z
#> Files: code.R
#> Truncated?: FALSE
gists()[[1]] %>% browse()
Opens the gist in your default browser
gists()[[1]] %>% embed()
#> [1] "<script src=\"https://gist.github.com/ereastman616/edbc570a99738505d4eef196e4ae7cba.js\"></script>"
Returns a list of gist objects, just like gists()
gist(id = '1642874') %>% forks(per_page = 2)
#> [[1]]
#> <gist>1642989
#> URL: https://gist.github.com/1642989
#> Description: Spline Transition
#> Public: TRUE
#> Created/Edited: 2012-01-19T21:45:20Z / 2019-04-30T00:23:48Z
#> Files:
#> Truncated?:
#>
#> [[2]]
#> <gist>1643051
#> URL: https://gist.github.com/1643051
#> Description: Line Transition (Broken)
#> Public: TRUE
#> Created/Edited: 2012-01-19T21:51:30Z / 2018-09-29T06:16:06Z
#> Files:
#> Truncated?:
Returns a gist object
g <- gists()
(forked <- g[[ sample(seq_along(g), 1) ]] %>% fork())
#> <gist>8f9f96b67c67fd4a3a6b352674f95602
#> URL: https://gist.github.com/8f9f96b67c67fd4a3a6b352674f95602
#> Description:
#> Public: TRUE
#> Created/Edited: 2019-07-18T17:39:22Z / 2019-07-18T17:39:22Z
#> Files: gistfile1.txt
#> Truncated?: FALSE
Working with the Mapzen Pelias geocoding API
The API is described at https://github.com/pelias/pelias, and is still in alpha they say. The steps: get data, make a gist. The data is returned from Mapzen as geojson, so all we have to do is literally push it up to GitHub gists and we're done b/c GitHub renders the map.
library('httr')
base <- "http://pelias.mapzen.com/search"
res <- httr::GET(base, query = list(input = 'coffee shop', lat = 45.5, lon = -122.6))
json <- httr::content(res, "text")
gist_create(code = json, filename = "pelias_test.geojson")
#> <gist>017214637bcfeb198070
#> URL: https://gist.github.com/017214637bcfeb198070
#> Description:
#> Public: TRUE
#> Created/Edited: 2014-10-28T14:42:36Z / 2014-10-28T14:42:36Z
#> Files: pelias_test.geojson
And here's that gist: https://gist.github.com/sckott/017214637bcfeb198070
Round-trip storage of a data frame
Maybe you want to use a gist to share some data as an alternative to dput? We can do this by writing our data.frame to a temporary buffer and passing it to gist_create. We can read the data back from the gist by passing its content to read.csv.
data(iris)
str <- ''
tc <- textConnection('str', 'w', local = TRUE)
write.csv(iris, file = tc, row.names = FALSE)
close(tc)
content <- list(content=paste(as.character(str), collapse='\n'))
gistr::gist_create(code = {
content$content
}, description = "using a gist as a data store",
filename = "iris.csv")
#> <gist>c7dfe593f4944df4818df884689734f9
#> URL: https://gist.github.com/c7dfe593f4944df4818df884689734f9
#> Description: using a gist as a data store
#> Public: TRUE
#> Created/Edited: 2019-07-18T14:23:23Z / 2019-07-18T14:23:23Z
#> Files: iris.csv
#> Truncated?: FALSE
output <- read.csv(
text = gist(gists(what = "minepublic", per_page = 1)[[1]]$id)$
files$iris.csv$content)
identical(output, iris)
#> TRUE