This vignette provides a quick tour of the R package.
library("rtweet")
First you should set up your own credentials, this should be done just once ever:
auth_setup_default()
Which will look up your account on your browser and create a token and save it as default. From now on, on this R session on others we can use this authentication with:
auth_as("default")
Automatically rtweet will use that token in all the API queries it will do in the session.
If you want to set up a bot or collect a lot of information, please
read the vignette("auth", "rtweet")
.
You can search tweets:
## search for 18000 tweets using the rstats hashtag
<- search_tweets("#rstats", n = 100, include_rts = FALSE)
rstats colnames(rstats)
#> [1] "created_at" "id" "id_str" "full_text"
#> [5] "truncated" "display_text_range" "entities" "metadata"
#> [9] "source" "in_reply_to_status_id" "in_reply_to_status_id_str" "in_reply_to_user_id"
#> [13] "in_reply_to_user_id_str" "in_reply_to_screen_name" "geo" "coordinates"
#> [17] "place" "contributors" "is_quote_status" "retweet_count"
#> [21] "favorite_count" "favorited" "retweeted" "possibly_sensitive"
#> [25] "lang" "quoted_status_id" "quoted_status_id_str" "quoted_status"
#> [29] "text" "favorited_by" "scopes" "display_text_width"
#> [33] "retweeted_status" "quoted_status_permalink" "quote_count" "timestamp_ms"
#> [37] "reply_count" "filter_level" "query" "withheld_scope"
#> [41] "withheld_copyright" "withheld_in_countries" "possibly_sensitive_appealable"
1:5, c("created_at", "text", "id_str")]
rstats[#> # A tibble: 5 × 3
#> created_at text id_str
#> <dttm> <chr> <chr>
#> 1 2022-07-12 05:50:10 "#DataScience Theories, Models, #Algorithms, and Analytics: https://t.co/w704rhiLS8 (FREE PDF Download, … 15467…
#> 2 2022-07-12 22:36:28 "FREE downloadable PDF eBooks, including this 475-page book >> R Programming Notes for Professiona… 15469…
#> 3 2022-07-12 22:36:13 "100+ Free #DataScience eBooks (downloadable PDF) for Beginners and for Experts — via @TheInsaneApp \n——… 15469…
#> 4 2022-07-13 22:06:44 "Wrote a small program that summarizes web articles, using the {lexRankr} package 📦\nThe sentences belo… 15473…
#> 5 2022-07-13 22:06:17 "R- Subtract values of all rows in a group from previous row in different group and filter out rows #tid… 15473…
The include_rts = FALSE
excludes retweets from the
search.
Twitter rate limits the number of calls to the endpoints you can do.
See rate_limit()
and the rate limit
section below. If your query requires more calls like the example
below, simply set retryonratelimit = TRUE
and rtweet will
wait for rate limit resets for you.
## search for 250,000 tweets containing the word data
<- search_tweets("peace", n = 250000, retryonratelimit = TRUE) tweets_peace
Search by geo-location, for example tweets in the English language sent from the United States.
# search for tweets sent from the US
# lookup_coords requires Google maps API key for maps outside usa, canada and world
<- search_tweets("lang:en", geocode = lookup_coords("usa"), n = 100)
geo_tweets 1:5, c("created_at", "text", "id_str", "lang", "place")]
geo_tweets[#> # A tibble: 5 × 5
#> created_at text id_str lang place
#> <dttm> <chr> <chr> <chr> <lis>
#> 1 2022-07-13 18:16:57 "Together Forever.\n#BetterCallSaul https://t.co/YVxDnJL6qN" 15472… en <df>
#> 2 2022-07-13 22:09:10 "I’ve been using the podcast to speak & teach myself shit on @anchor! \n\nhttps://t.co/B… 15473… en <df>
#> 3 2022-07-13 22:09:10 "@dgschell Need to renew my booklet 😵" 15473… en <df>
#> 4 2022-07-13 22:09:09 "This is what a true President does. https://t.co/Rb9Eip4Ubj" 15473… en <df>
#> 5 2022-07-13 22:09:09 "@ErrinFrahm @KIIARA So, Kii, if I buy lil kiiwi on iTunes, do you get the proceeds or does … 15473… en <df>
You can check the location of these tweets with
lat_lng()
. Or quickly visualize frequency of tweets over
time using ts_plot()
(if ggplot2
is
installed).
## plot time series of tweets
ts_plot(rstats) +
theme_minimal() +
theme(plot.title = element_text(face = "bold")) +
labs(
x = NULL, y = NULL,
title = "Frequency of #rstats Twitter statuses from past 9 days",
subtitle = "Twitter status (tweet) counts aggregated using three-hour intervals",
caption = "Source: Data collected from Twitter's REST API via rtweet"
)
You can post tweets with:
post_tweet(paste0("My first tweet with #rtweet #rstats at ", Sys.time()))
#> Your tweet has been posted!
It can include media and alt text:
<- tempfile(fileext = ".png")
path_file png(filename = path_file)
plot(mpg ~ cyl, mtcars, col = gear, pch = gear)
dev.off()
#> png
#> 2
post_tweet("my first tweet with #rtweet with media #rstats", media = path_file, media_alt_text = "Plot of mtcars dataset, showing cyl vs mpg colored by gear. The lower cyl the higher the mpg is.")
#> Your tweet has been posted!
You can also reply to a previous tweet, retweet and provide additional information.
Retrieve a list of all the accounts a user follows.
## get user IDs of accounts followed by R Foundation
<- get_friends("_R_Foundation")
R_foundation_fds
R_foundation_fds#> # A tibble: 31 × 2
#> from_id to_id
#> <chr> <chr>
#> 1 _R_Foundation 1448728978370535426
#> 2 _R_Foundation 889777924991307778
#> 3 _R_Foundation 1300656590
#> 4 _R_Foundation 1280779280579022848
#> 5 _R_Foundation 1229418786085888001
#> 6 _R_Foundation 1197874989367779328
#> 7 _R_Foundation 1102763906714554368
#> 8 _R_Foundation 1560929287
#> 9 _R_Foundation 46782674
#> 10 _R_Foundation 16284661
#> # … with 21 more rows
Using get_friends()
we can retrieve which users are
being followed by the R Foundation.
If you really want all the users that follow the account we can use
get_followers()
:
<- get_followers("_R_Foundation", n = 30000,
R_foundation_flw retryonratelimit = TRUE)
#> Downloading multiple pages ==================================>----------------------------------------------------------------------
#> Downloading multiple pages ===================================================>-----------------------------------------------------
#> Downloading multiple pages =====================================================================>-----------------------------------
#> Downloading multiple pages =======================================================================================>-----------------
Note that the retryonratelimit
option is intended for
when you need more queries than provided by Twitter on a given period.
You might want to check with rate_limit()
how many does it
provide for the endpoints you are using. If exceeded
retryonratelimit
waits till the there are more calls
available and then resumes the query.
As seen above we can use lookup_users()
to check
their
# Look who is following R Foundation
<- lookup_users(R_foundation_fds$to_id, verbose = FALSE)
R_foundation_fds_data c("name", "screen_name", "created_at")]
R_foundation_fds_data[, #> # A tibble: 31 × 3
#> name screen_name created_at
#> <chr> <chr> <dttm>
#> 1 R Contributors R_Contributors 2021-10-14 21:15:12
#> 2 Sebastian Meyer bastistician 2017-07-25 11:22:43
#> 3 Naras b_naras 2013-03-25 19:48:12
#> 4 useR! 2022 _useRconf 2020-07-08 10:22:55
#> 5 useR2021zrh useR2021zrh 2020-02-17 15:54:39
#> 6 useR2020muc useR2020muc 2019-11-22 14:50:55
#> 7 useR! 2020 useR2020stl 2019-03-05 03:52:58
#> 8 Roger Bivand RogerBivand 2013-07-01 18:19:42
#> 9 Henrik Bengtsson henrikbengtsson 2009-06-13 02:11:14
#> 10 Gabriela de Queiroz gdequeiroz 2008-09-14 18:55:29
#> # … with 21 more rows
# Look 100 R Foundation followers
<- lookup_users(head(R_foundation_flw$from_id, 100), verbose = FALSE)
R_foundation_flw_data 1:5, c("name", "screen_name", "created_at")]
R_foundation_flw_data[#> # A tibble: 5 × 3
#> name screen_name created_at
#> <chr> <chr> <dttm>
#> 1 Rafael C. CabestreRafael 2018-10-19 00:08:45
#> 2 Robot Dad RobotBearDad 2020-07-28 05:16:59
#> 3 Augustino Mmbaga MmbagaAugustino 2020-04-12 10:29:02
#> 4 Prof. Dr. A. E. Kotp am2000de 2013-09-26 22:18:35
#> 5 ahbragasaka ahbragasaka 2015-07-15 21:23:20
We have now the information from those followed by the R Foundation and its followers. We can retrieve their latest tweets from these users:
tweets_data(R_foundation_fds_data)[, c("created_at", "text")]
#> # A tibble: 31 × 2
#> created_at text
#> <chr> <chr>
#> 1 Thu Jul 07 08:11:58 +0000 2022 "RT @dvaughan32: @hrbrmstr @MMaechler @groundwalkergmb And @Emil_Hvitfeldt, @isabelizimm, Tino Nten…
#> 2 Thu Jun 23 20:16:13 +0000 2022 "@d_olivaw Thanks, I'll see what I can do. 😉\nIIRC, @revodavid had blogged summaries of earlier R …
#> 3 Wed Nov 10 19:50:31 +0000 2021 "RT @StanfordDBDS: Apply by 11/26 to join the Stanford DBDS Inclusive #mentoring in #DataScience pr…
#> 4 Mon Jul 11 15:23:14 +0000 2022 "Interested in hosting a future useR conference (format TBD)? Send your proposal to conferences[at]…
#> 5 Mon May 24 08:21:14 +0000 2021 "@NasrinAttar @useR2020stl Important Info for everyone: If you don't have funds to attend the confe…
#> 6 Fri Apr 16 11:03:21 +0000 2021 "RT @_useRconf: It is a good time to remember some of our keydates!\n\n📆 2021-04-20. Registration…
#> 7 Mon Jan 18 17:36:22 +0000 2021 "Give us a follow at @_useRconf to stay updated on *all* future useR! conferences! #rstats https://…
#> 8 Wed Jul 13 16:53:33 +0000 2022 "RT @precariobecario: Book \"Bayesian inferencia with INLA\" has been awarded the SEIO - BBVA Found…
#> 9 Tue Jul 12 08:57:30 +0000 2022 ".@bolkerb , thank you for taking over the maintenance of gtools (\"Various R Programming Tools\")…
#> 10 Wed Jun 29 17:51:05 +0000 2022 "@PipingHotData Happy Birthday! The cake looks delicious."
#> # … with 21 more rows
Search for 1,000 users with the rstats hashtag in their profile bios.
## search for users with #rstats in their profiles
<- search_users("#rstats", n = 100, verbose = FALSE)
useRs c("name", "screen_name", "created_at")]
useRs[, #> # A tibble: 100 × 3
#> name screen_name created_at
#> <chr> <chr> <dttm>
#> 1 Rstats rstatstweet 2018-06-27 05:45:02
#> 2 R for Data Science rstats4ds 2018-12-18 13:55:25
#> 3 FC rSTATS FC_rstats 2018-02-08 21:03:08
#> 4 R Tweets rstats_tweets 2020-09-17 18:12:09
#> 5 #RStats Question A Day data_question 2019-10-21 19:15:24
#> 6 NBA in #rstats NbaInRstats 2019-11-05 03:44:32
#> 7 Data Science with R Rstats4Econ 2012-04-21 04:37:12
#> 8 Baseball with R BaseballRstats 2013-11-02 16:07:05
#> 9 Will steelRstats 2019-07-23 16:48:00
#> 10 LIRR Statistics (Unofficial) LIRRstats 2017-01-25 00:31:55
#> # … with 90 more rows
If we want to know what have they tweeted about we can use
tweets_data()
:
<- tweets_data(useRs)
useRs_twt 1:5, c("id_str", "created_at", "text")]
useRs_twt[#> # A tibble: 5 × 3
#> id_str created_at text
#> <chr> <chr> <chr>
#> 1 1547309043189948418 Wed Jul 13 19:56:38 +0000 2022 "RT @rtweet_test: my first tweet with #rtweet with media #rstats https://t.co/kh…
#> 2 1547309959788085249 Wed Jul 13 20:00:16 +0000 2022 "RT @yabellini: I'm thrilled to announce that Juyoung Kim is now a @rstudio #Tid…
#> 3 1546901699205406722 Tue Jul 12 16:57:59 +0000 2022 "interesting article!\n\nhttps://t.co/guZACQz7pA https://t.co/dPwts5vb54"
#> 4 1547304785199902720 Wed Jul 13 19:39:42 +0000 2022 "RT @coldvoltt: An efficient way of converting data type in R using the mutate_i…
#> 5 1547296274621542400 Wed Jul 13 19:05:53 +0000 2022 "References: \n1. https://t.co/pwREapNSCo\n2. https://t.co/UBXyTA16sv\n3. https:…
Get the most recent tweets from R Foundation.
## get user IDs of accounts followed by R Foundation
<- get_timeline("_R_Foundation")
R_foundation_tline
## plot the frequency of tweets for each user over time
<- R_foundation_tline |>
plot filter(created_at > "2017-10-29") |>
ts_plot(by = "month", trim = 1L) +
geom_point() +
theme_minimal() +
theme(
legend.title = element_blank(),
legend.position = "bottom",
plot.title = element_text(face = "bold")) +
labs(
x = NULL, y = NULL,
title = "Frequency of Twitter statuses posted by the R Foundation",
subtitle = "Twitter status (tweet) counts aggregated by month from October/November 2017",
caption = "Source: Data collected from Twitter's REST API via rtweet"
)
Get the 10 recently favorited statuses by R Foundation.
<- get_favorites("_R_Foundation", n = 10)
R_foundation_favs c("text", "created_at", "id_str")]
R_foundation_favs[, #> # A tibble: 10 × 3
#> text created_at id_str
#> <chr> <dttm> <chr>
#> 1 "We're into August, which hopefully means you've had time to enjoy content from #useR2020!\n\nPlease he… 2020-08-03 09:51:33 12901…
#> 2 "Gret meeting of #useR2020 passing the torch to #useR2021! 🔥 \nThank you so much, everyone!🙏🏽\nParticu… 2020-07-16 17:14:25 12837…
#> 3 "Also thanks to the @_R_Foundation, @R_Forwards, @RLadiesGlobal, MiR and many others in supporting us i… 2020-05-28 08:57:24 12658…
#> 4 "Such an honour to be acknowledged this way at #useR2019. I'm happy that folks like @JulieJosseStat, @v… 2019-07-12 18:36:27 11497…
#> 5 "R-3.4.4 Windows installer is on CRAN now: https://t.co/h35EcsIEuF https://t.co/7xko0aUS2w" 2018-03-15 18:16:13 97433…
#> 6 "Gala dinner with a table with people in cosmology, finance, psychology, demography, medical doctor #us… 2017-07-07 09:10:41 88322…
#> 7 "AMAZING #RLadies at #useR2017 💜🌍 inspiring #rstats work around the world https://t.co/pIPEorlkyl" 2017-07-05 13:25:27 88256…
#> 8 "Fame at last: https://t.co/x4wIePKR6b -- it's always nice to get a bit of recognition! Coded in #rsta… 2017-06-07 23:25:37 87256…
#> 9 "We are excited to let you know that the full Conference Program is online now. \nHave a look at https:… 2017-05-31 14:37:23 86989…
#> 10 ". @statsYSS and @RSSGlasgow1 to hold joint event celebrating 20 years of Comprehensive R Archive (CRA… 2017-04-10 10:50:11 85135…
Discover what’s currently trending in San Francisco.
<- get_trends("world")
world
world#> # A tibble: 50 × 9
#> trend url promoted_content query tweet_volume place woeid as_of created_at
#> <chr> <chr> <lgl> <chr> <int> <chr> <int> <dttm> <dttm>
#> 1 #CashApp20Qs http://twitter.com/sear… NA %23C… 11095 Worl… 1 2022-07-13 20:09:24 2022-07-11 18:19:34
#> 2 #LateNightTalking http://twitter.com/sear… NA %23L… 104210 Worl… 1 2022-07-13 20:09:24 2022-07-11 18:19:34
#> 3 #NEDPOR http://twitter.com/sear… NA %23N… NA Worl… 1 2022-07-13 20:09:24 2022-07-11 18:19:34
#> 4 Colwill http://twitter.com/sear… NA Colw… 16451 Worl… 1 2022-07-13 20:09:24 2022-07-11 18:19:34
#> 5 Kimpembe http://twitter.com/sear… NA Kimp… 31408 Worl… 1 2022-07-13 20:09:24 2022-07-11 18:19:34
#> 6 #MsMarvel http://twitter.com/sear… NA %23M… 120461 Worl… 1 2022-07-13 20:09:24 2022-07-11 18:19:34
#> 7 #İstihdamRekoru http://twitter.com/sear… NA %23%… NA Worl… 1 2022-07-13 20:09:24 2022-07-11 18:19:34
#> 8 harry styles http://twitter.com/sear… NA %22h… 101108 Worl… 1 2022-07-13 20:09:24 2022-07-11 18:19:34
#> 9 Pablo Torre http://twitter.com/sear… NA %22P… 14501 Worl… 1 2022-07-13 20:09:24 2022-07-11 18:19:34
#> 10 Buğra Tolga Gülcan http://twitter.com/sear… NA %22B… NA Worl… 1 2022-07-13 20:09:24 2022-07-11 18:19:34
#> # … with 40 more rows
You can follow users and unfollow them:
post_follow("_R_Foundation")
#> Response [https://api.twitter.com/1.1/friendships/create.json?notify=FALSE&screen_name=_R_Foundation]
#> Date: 2022-07-13 20:09
#> Status: 200
#> Content-Type: application/json;charset=utf-8
#> Size: 4.97 kB
post_unfollow_user("rtweet_test")
#> Response [https://api.twitter.com/1.1/friendships/destroy.json?notify=FALSE&screen_name=rtweet_test]
#> Date: 2022-07-13 20:09
#> Status: 200
#> Content-Type: application/json;charset=utf-8
#> Size: 3.3 kB
You can mute and unmute users:
post_follow("rtweet_test", mute = TRUE)
post_follow("rtweet_test", mute = FALSE)
You can block users and unblock them:
user_block("RTweetTest1")
#> Response [https://api.twitter.com/1.1/blocks/create.json?screen_name=RTweetTest1]
#> Date: 2022-07-13 20:09
#> Status: 200
#> Content-Type: application/json;charset=utf-8
#> Size: 1.35 kB
user_unblock("RTweetTest1")
#> Response [https://api.twitter.com/1.1/blocks/destroy.json?screen_name=RTweetTest1]
#> Date: 2022-07-13 20:09
#> Status: 200
#> Content-Type: application/json;charset=utf-8
#> Size: 1.35 kB
Twitter sets a limited number of calls to their endpoints for
different authentications (check vignette("auth", "rtweet")
to find which one is better for your use case). To consult those limits
you can use rate_limt()
rate_limit()
#> # A tibble: 262 × 5
#> resource limit remaining reset_at reset
#> <chr> <int> <int> <dttm> <drtn>
#> 1 /lists/list 15 15 2022-07-13 22:24:26 15 mins
#> 2 /lists/:id/tweets&GET 900 900 2022-07-13 22:24:26 15 mins
#> 3 /lists/:id/followers&GET 180 180 2022-07-13 22:24:26 15 mins
#> 4 /lists/memberships 75 75 2022-07-13 22:24:26 15 mins
#> 5 /lists/:id&DELETE 300 300 2022-07-13 22:24:26 15 mins
#> 6 /lists/subscriptions 15 15 2022-07-13 22:24:26 15 mins
#> 7 /lists/members 900 900 2022-07-13 22:24:26 15 mins
#> 8 /lists/:id&GET 75 75 2022-07-13 22:24:26 15 mins
#> 9 /lists/subscribers/show 15 15 2022-07-13 22:24:26 15 mins
#> 10 /lists/:id&PUT 300 300 2022-07-13 22:24:26 15 mins
#> # … with 252 more rows
# Search only those related to followers
rate_limit("followers")
#> # A tibble: 5 × 5
#> resource limit remaining reset_at reset
#> <chr> <int> <int> <dttm> <drtn>
#> 1 /lists/:id/followers&GET 180 180 2022-07-13 22:24:26 15 mins
#> 2 /users/:id/followers 15 15 2022-07-13 22:24:26 15 mins
#> 3 /users/by/username/:username/followers 15 15 2022-07-13 22:24:26 15 mins
#> 4 /followers/ids 15 9 2022-07-13 22:24:14 15 mins
#> 5 /followers/list 15 15 2022-07-13 22:24:26 15 mins
The remaining column shows the number of times that you can call and endpoint (not the numbers of followers you can search). After a query the number should decrease until it is reset again.
If your queries return an error, check if you already exhausted your quota and try after the time on “reset_at”.
Randomly sample (approximately 1%) from the live stream of all tweets.
## random sample for 30 seconds (default)
<- tempfile(fileext = ".json")
stream <- stream_tweets("rstats", file_name = stream) rt
Stream all geo enabled tweets from London for 15 seconds.
## stream tweets from london for 60 seconds
<- tempfile(fileext = ".json")
stream2 <- stream_tweets(lookup_coords("london, uk"), timeout = 15, file_name = stream2) stream_london
Stream all tweets mentioning #rstats for a week.
## stream london tweets for a week (60 secs x 60 mins * 24 hours * 7 days)
<- tempfile(fileext = ".json")
stream3 stream_tweets(
"#rstats",
timeout = 60 * 60 * 24 * 7,
file_name = stream3,
parse = FALSE
)
## read in the data as a tidy tbl data frame
<- jsonlite::stream_in(stream3) rstats
See the vignette on vignette("stream", "rtweet")
.
To provide real examples the vignette is precomputed before submission. Also note that results returned by the API will change.
sessionInfo()
#> R version 4.2.1 (2022-06-23)
#> Platform: x86_64-pc-linux-gnu (64-bit)
#> Running under: Ubuntu 20.04.4 LTS
#>
#> Matrix products: default
#> BLAS: /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3
#> LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/liblapack.so.3
#>
#> locale:
#> [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C LC_TIME=es_ES.UTF-8 LC_COLLATE=en_US.UTF-8
#> [5] LC_MONETARY=es_ES.UTF-8 LC_MESSAGES=en_US.UTF-8 LC_PAPER=es_ES.UTF-8 LC_NAME=C
#> [9] LC_ADDRESS=C LC_TELEPHONE=C LC_MEASUREMENT=es_ES.UTF-8 LC_IDENTIFICATION=C
#>
#> attached base packages:
#> [1] stats graphics grDevices utils datasets methods base
#>
#> other attached packages:
#> [1] rtweet_0.7.0.9036 dplyr_1.0.9 ggplot2_3.3.6.9000 knitr_1.39 BiocManager_1.30.18 cyclocomp_1.1.0
#> [7] testthat_3.1.4 devtools_2.4.3 usethis_2.1.6
#>
#> loaded via a namespace (and not attached):
#> [1] prettyunits_1.1.1 ps_1.7.1 assertthat_0.2.1 rprojroot_2.0.3 digest_0.6.29 utf8_1.2.2 mime_0.12
#> [8] R6_2.5.1 evaluate_0.15 highr_0.9 httr_1.4.3 pillar_1.7.0 rlang_1.0.3 progress_1.2.2
#> [15] curl_4.3.2 rstudioapi_0.13 callr_3.7.0 rmarkdown_2.14 labeling_0.4.2 desc_1.4.1 stringr_1.4.0
#> [22] htmlwidgets_1.5.4 bit_4.0.4 munsell_0.5.0 compiler_4.2.1 xfun_0.31 pkgconfig_2.0.3 askpass_1.1
#> [29] pkgbuild_1.3.1 htmltools_0.5.2 openssl_2.0.2 tidyselect_1.1.2 tibble_3.1.7 fansi_1.0.3 crayon_1.5.1
#> [36] withr_2.5.0 brio_1.1.3 grid_4.2.1 jsonlite_1.8.0 gtable_0.3.0 lifecycle_1.0.1 DBI_1.1.3
#> [43] magrittr_2.0.3 scales_1.2.0 cli_3.3.0 stringi_1.7.6 cachem_1.0.6 farver_2.1.1 fs_1.5.2
#> [50] remotes_2.4.2 ellipsis_0.3.2 generics_0.1.3 vctrs_0.4.1 tools_4.2.1 bit64_4.0.5 glue_1.6.2
#> [57] purrr_0.3.4 hms_1.1.1 processx_3.7.0 pkgload_1.3.0 fastmap_1.1.0 yaml_2.3.5 colorspace_2.0-3
#> [64] sessioninfo_1.2.2 memoise_2.0.1 profvis_0.3.7