Usage
Package conventions
- Most functions begin with the prefix
drive_. Auto-completion is your friend. - Goal is to allow Drive access that feels similar to Unix file system utilities, e.g.,
find,ls,mv,cp,mkdir, andrm. - The metadata for one or more Drive files is held in a
dribble, a “Drive tibble”. This is a data frame with one row per file. A dribble is returned (and accepted) by almost every function in googledrive. Design goals:- Give humans what they want: the file name
- Track what the API wants: the file ID
- Hold on to all the other metadata sent back by the API
- googledrive is “pipe-friendly” and, in fact, re-exports
%>%, but does not require its use.
Quick demo
Here’s how to list up to n_max of the files you see in My Drive. You can expect to be sent to your browser here, to authenticate yourself and authorize the googledrive package to deal on your behalf with Google Drive.
drive_find(n_max = 30)
#> # A dribble: 16 x 3
#> name id drive_resource
#> <chr> <drv_id> <list>
#> 1 chicken_sheet 1s0kEHcqG2PyciERoGq52L_Qwzp4y3__rBVKSx7E… <named list [35…
#> 2 r_logo.jpg 1wFAZdmBiSRu4GShsqurxD7wIDSCZvPud <named list [41…
#> 3 THANKS 19URV7BT0_E1KhYdfDODszK5aiELOwTSz <named list [40…
#> 4 googledrive-NEWS.… 1h1lhFfQrDZevE2OEX10-rbi2BfvGogFm <named list [39…
#> 5 def 1ALSW_Nqs7FsPOcrJ6MqyBoRm03gansmn <named list [33…
#> 6 abc 1o89YN5n4325GbUA86Wp6pRH3dsTsE5iC <named list [33…
#> 7 BioC_mirrors.csv 13tMFbhAHoeHLFS5xu19GbDjf6GWJSxyN <named list [39…
#> 8 Rlogo.svg 1lCQGxjyoc9mQz719I8sKil_m2Nuhw0Fq <named list [41…
#> 9 DESCRIPTION 1KKYhtcdJMKh4WYeri5TOPEeAtzdN_cqV <named list [40…
#> 10 r_about.html 1mHtQhvJyDk5dX9ktKbeIoVW-wwWK0__N <named list [40…
#> 11 imdb_latin1.csv 1S5HxY7a-Jb_fV4C3T6fkGyPpXfI_yb4w <named list [39…
#> 12 chicken.txt 1xMvlJHia_qYNZmucaStDcOF9A9PD4BOT <named list [40…
#> 13 chicken.pdf 1au0aK6YCTra2sucTRus8ZaUhbaLpinTn <named list [40…
#> 14 chicken.jpg 1-BF1c4kWCkkByQbcLT-b2Hv6vnVsbqa_ <named list [41…
#> 15 chicken.csv 12212CXY_TopUMIKYu_l8hU5UXI8lrzQF <named list [39…
#> 16 chicken_doc 11GY4Q4BUG3m5U4CnZP564lYvGydvZe2XZOkwCfx… <named list [35…You can narrow the query by specifying a pattern you’d like to match names against. Or by specifying a file type: the type argument understands MIME types, file extensions, and a few human-friendly keywords.
drive_find(pattern = "chicken")
drive_find(type = "spreadsheet") ## Google Sheets!
drive_find(type = "csv") ## MIME type = "text/csv"
drive_find(type = "application/pdf") ## MIME type = "application/pdf"Alternatively, you can refine the search using the q query parameter. Accepted search clauses can be found in the Google Drive API documentation. For example, to see all files that you’ve starred and that are readable by “anyone with a link”, do this:
(files <- drive_find(q = c("starred = true", "visibility = 'anyoneWithLink'")))
#> # A dribble: 2 x 3
#> name id drive_resource
#> <chr> <drv_id> <list>
#> 1 r_logo.jpg 1wFAZdmBiSRu4GShsqurxD7wIDSCZvPud <named list [41]>
#> 2 THANKS 19URV7BT0_E1KhYdfDODszK5aiELOwTSz <named list [40]>You generally want to store the result of a googledrive call, as we do with files above. files is a dribble with info on several files and can be used as the input for downstream calls. It can also be manipulated as a regular data frame at any point.
Identify files
drive_find() searches by file properties, but you can also identify files by name (path, really) or by Drive file id using drive_get().
(x <- drive_get("~/abc/def/googledrive-NEWS.md"))
#> ✓ The input `path` resolved to exactly 1 file.
#> # A dribble: 1 x 4
#> name path id drive_resource
#> <chr> <chr> <drv_id> <list>
#> 1 googledrive-NE… ~/abc/def/googledriv… 1h1lhFfQrDZevE2OEX10-r… <named list [39…as_id() can be used to convert various inputs into a marked vector of file ids. It works on file ids (for obvious reasons!), various forms of Drive URLs, and dribbles.
x$id
#> <drive_id[1]>
#> [1] 1h1lhFfQrDZevE2OEX10-rbi2BfvGogFm
# let's retrieve same file by id (also a great way to force-refresh metadata)
drive_get(x$id)
#> # A dribble: 1 x 3
#> name id drive_resource
#> <chr> <drv_id> <list>
#> 1 googledrive-NEWS.md 1h1lhFfQrDZevE2OEX10-rbi2BfvGogFm <named list [39]>
drive_get(as_id(x))
#> # A dribble: 1 x 3
#> name id drive_resource
#> <chr> <drv_id> <list>
#> 1 googledrive-NEWS.md 1h1lhFfQrDZevE2OEX10-rbi2BfvGogFm <named list [39]>In general, googledrive functions that operate on files allow you to specify the file(s) by name/path, file id, or in a dribble. If it’s ambiguous, use as_id() to mark a character vector as holding Drive file ids as opposed to file paths. This function can also extract file ids from various URLs.
Upload files
We can upload any file type.
(chicken <- drive_upload(
drive_example_local("chicken.csv"),
"index-chicken.csv"
))
#> Local file:
#> • '/private/tmp/RtmpxrWkXq/temp_libpath16090348325b1/googledrive/extdata/example_files/chicken.csv'
#> Uploaded into Drive file:
#> • 'index-chicken.csv' <id: 14IJB7jnR-qm_-W92k_QOoobrEZJFzof9>
#> With MIME type:
#> • 'text/csv'
#> # A dribble: 1 x 3
#> name id drive_resource
#> <chr> <drv_id> <list>
#> 1 index-chicken.csv 14IJB7jnR-qm_-W92k_QOoobrEZJFzof9 <named list [39]>Notice that file was uploaded as text/csv. Since this was a .csv document, and we didn’t specify the type, googledrive guessed the MIME type. We can overrule this by using the type parameter to upload as a Google Spreadsheet. Let’s delete this file first.
drive_rm(chicken)
#> File deleted:
#> • 'index-chicken.csv' <id: 14IJB7jnR-qm_-W92k_QOoobrEZJFzof9>
# example of using a dribble as input
chicken_sheet <- drive_example_local("chicken.csv") %>%
drive_upload(
name = "index-chicken-sheet",
type = "spreadsheet"
)
#> Local file:
#> • '/private/tmp/RtmpxrWkXq/temp_libpath16090348325b1/googledrive/extdata/example_files/chicken.csv'
#> Uploaded into Drive file:
#> • 'index-chicken-sheet' <id: 1Gg5SrxCHktay1PCr7-qXNK_C_Z7ApJK8iDrQbmamh2I>
#> With MIME type:
#> • 'application/vnd.google-apps.spreadsheet'Much better!
Publish files
Versions of Google Documents, Sheets, and Presentations can be published online. You can check your publication status by running drive_reveal(..., "published"), which adds a logical column published and parks more detailed metadata in a revision_resource variable.
chicken_sheet %>%
drive_reveal("published")
#> # A dribble: 1 x 7
#> name published shared id drive_resource permissions_res… revision_resour…
#> <chr> <lgl> <lgl> <drv> <list> <list> <list>
#> 1 index… FALSE TRUE 1Gg5… <named list [… <named list [2]> <named list [7]>By default, drive_publish() will publish your most recent version.
(chicken_sheet <- drive_publish(chicken_sheet))
#> File now published:
#> • 'index-chicken-sheet' <id: 1Gg5SrxCHktay1PCr7-qXNK_C_Z7ApJK8iDrQbmamh2I>
#> # A dribble: 1 x 7
#> name published shared id drive_resource permissions_res… revision_resour…
#> <chr> <lgl> <lgl> <drv> <list> <list> <list>
#> 1 index… TRUE TRUE 1Gg5… <named list [… <named list [2]> <named list [9]>Download files
Google files
We can download files from Google Drive. Native Google file types (such as Google Documents, Google Sheets, Google Slides, etc.) need to be exported to some conventional file type. There are reasonable defaults or you can specify this explicitly via type or implicitly via the file extension in path. For example, if I would like to download the “chicken_sheet” Google Sheet as a .csv I could run the following.
drive_download("index-chicken-sheet", type = "csv")
#> File downloaded:
#> • 'index-chicken-sheet' <id: 1Gg5SrxCHktay1PCr7-qXNK_C_Z7ApJK8iDrQbmamh2I>
#> Saved locally as:
#> • 'index-chicken-sheet.csv'Alternatively, I could specify type via the path parameter.
drive_download(
"index-chicken-sheet",
path = "index-chicken-sheet.csv",
overwrite = TRUE
)
#> File downloaded:
#> • 'index-chicken-sheet' <id: 1Gg5SrxCHktay1PCr7-qXNK_C_Z7ApJK8iDrQbmamh2I>
#> Saved locally as:
#> • 'index-chicken-sheet.csv'Notice in the example above, I specified overwrite = TRUE, in order to overwrite the local csv file previously saved.
Finally, you could just allow export to the default type. In the case of Google Sheets, this is an Excel workbook:
drive_download("index-chicken-sheet")
#> File downloaded:
#> • 'index-chicken-sheet' <id: 1Gg5SrxCHktay1PCr7-qXNK_C_Z7ApJK8iDrQbmamh2I>
#> Saved locally as:
#> • 'index-chicken-sheet.xlsx'All other files
Downloading files that are not Google type files is even simpler, i.e. it does not require any conversion or type info.
# download it and prove we got it
drive_download("chicken.txt")
#> File downloaded:
#> • 'chicken.txt' <id: 1xMvlJHia_qYNZmucaStDcOF9A9PD4BOT>
#> Saved locally as:
#> • 'chicken.txt'
readLines("chicken.txt") %>% head()
#> [1] "A chicken whose name was Chantecler"
#> [2] "Clucked in iambic pentameter"
#> [3] "It sat on a shelf, reading Song of Myself"
#> [4] "And laid eggs with a perfect diameter."
#> [5] ""
#> [6] "—Richard Maxson"Clean up
file.remove(c(
"index-chicken-sheet.csv", "index-chicken-sheet.xlsx", "chicken.txt"
))
#> [1] TRUE TRUE TRUE
drive_find("index-chicken") %>% drive_rm()
#> File deleted:
#> • 'index-chicken-sheet' <id: 1Gg5SrxCHktay1PCr7-qXNK_C_Z7ApJK8iDrQbmamh2I>
