---
title: "Intro to rtweet"
output:
  rmarkdown::html_vignette:
    self_contained: false
vignette: >
  %\VignetteIndexEntry{Intro to rtweet}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---



This vignette provides a quick tour of the R package.


```r
library("rtweet")
```

## Authenticate

First you should set up your own credentials, this should be done just once ever:


```r
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:


```r
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")`.



## Search tweets

You can search tweets:


```r
## search for 18000 tweets using the rstats hashtag
rstats <- search_tweets("#rstats", n = 100, include_rts = FALSE)
colnames(rstats)
#>  [1] "created_at"                    "id"                           
#>  [3] "id_str"                        "text"                         
#>  [5] "full_text"                     "truncated"                    
#>  [7] "entities"                      "source"                       
#>  [9] "in_reply_to_status_id"         "in_reply_to_status_id_str"    
#> [11] "in_reply_to_user_id"           "in_reply_to_user_id_str"      
#> [13] "in_reply_to_screen_name"       "geo"                          
#> [15] "coordinates"                   "place"                        
#> [17] "contributors"                  "is_quote_status"              
#> [19] "retweet_count"                 "favorite_count"               
#> [21] "favorited"                     "favorited_by"                 
#> [23] "retweeted"                     "scopes"                       
#> [25] "lang"                          "possibly_sensitive"           
#> [27] "display_text_width"            "display_text_range"           
#> [29] "retweeted_status"              "quoted_status"                
#> [31] "quoted_status_id"              "quoted_status_id_str"         
#> [33] "quoted_status_permalink"       "quote_count"                  
#> [35] "timestamp_ms"                  "reply_count"                  
#> [37] "filter_level"                  "metadata"                     
#> [39] "query"                         "withheld_scope"               
#> [41] "withheld_copyright"            "withheld_in_countries"        
#> [43] "possibly_sensitive_appealable"
rstats[1:5, c("created_at", "text", "id_str")]
#> Users data at users_data()
#> # A tibble: 5 × 3
#>   created_at          text                                                                  id_str
#>   <dttm>              <chr>                                                                 <chr> 
#> 1 2022-12-20 07:00:00 "Practical Linear Algebra for #DataScience! #BigData #Analytics #Mat… 16050…
#> 2 2022-12-19 03:00:17 "#SQL Interview for #DataScientists! #BigData #Analytics #DataScienc… 16046…
#> 3 2022-12-20 00:26:01 "LSTM: Intro to Long-Short Term Memory. #BigData #Analytics #DataSci… 16049…
#> 4 2022-12-20 22:02:11 "CRAN updates: archiveRetriever #rstats"                              16053…
#> 5 2022-12-20 21:37:06 "#Python Libraries and Frameworks via @DataScienceDojo! 😄🙃😊\n\n#1… 16053…
```

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](#Rate-limit) 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.


```r
## search for 250,000 tweets containing the word data
tweets_peace <- search_tweets("peace", n = 250000, retryonratelimit = TRUE)
```

Search by geo-location, for example tweets in the English language sent from the United States.


```r
# search for tweets sent from the US
# lookup_coords requires Google maps API key for maps outside usa, canada and world
geo_tweets <- search_tweets("lang:en", geocode = lookup_coords("usa"), n = 100)
geo_tweets[1:5, c("created_at", "text", "id_str", "lang", "place")]
#> Users data at users_data()
#> # A tibble: 5 × 5
#>   created_at          text                                                     id_str lang  place 
#>   <dttm>              <chr>                                                    <chr>  <chr> <list>
#> 1 2022-12-20 13:19:26 Love being your Christmas Danny. https://t.co/XdR7Pt90at 16051… en    <df>  
#> 2 2022-12-20 22:05:45 Pedestrian Accident in #Charlotte on University City Bl… 16053… en    <df>  
#> 3 2022-12-20 22:05:45 Accident. Right Shoulder blocked in #Centreville on I-6… 16053… en    <df>  
#> 4 2022-12-20 22:05:45 Always having to pee is getting really annoying 😭😭     16053… en    <df>  
#> 5 NA                  <NA>                                                     <NA>   <NA>  <NULL>
```

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).


```r
## 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"
  )
```

![plot of chunk plot1](vignettes/files/plot1-1.png)

## Posting statuses

You can post tweets with:


```r
post_tweet(paste0("My first tweet with #rtweet #rstats at ", Sys.time()))
#> Your tweet has been posted!
```

It can include media and alt text:


```r
path_file <- tempfile(fileext = ".png")
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.

## Get friends

Retrieve a list of all the accounts a **user follows**.

```r
## get user IDs of accounts followed by R Foundation
R_foundation_fds <- get_friends("_R_Foundation")
R_foundation_fds
#> # A tibble: 30 × 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 20 more rows
```

Using `get_friends()` we can retrieve which users are being followed by the R Foundation.

## Get followers

If you really want all the users that follow the account we can use `get_followers()`:

```r
R_foundation_flw <- get_followers("_R_Foundation", n = 30000,
                                  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.

## Lookup users

As seen above we can use `lookup_users()` to check their


```r
# Look who is following R Foundation
R_foundation_fds_data <- lookup_users(R_foundation_fds$to_id, verbose = FALSE)
R_foundation_fds_data[, c("name", "screen_name", "created_at")]
#> Tweets data at tweets_data()# A tibble: 30 × 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 @rsbivand@fosstodon.org           RogerBivand     2013-07-01 18:19:42
#>  9 Henrik Bengtsson                               henrikbengtsson 2009-06-13 02:11:14
#> 10 Gabriela de Queiroz ☁️ 🥑 (fosstodon.org/@kroz) gdequeiroz      2008-09-14 18:55:29
#> # … with 20 more rows

# Look 100 R Foundation followers
R_foundation_flw_data <- lookup_users(head(R_foundation_flw$from_id, 100), verbose = FALSE)
R_foundation_flw_data[1:5, c("name", "screen_name", "created_at")]
#> Tweets data at tweets_data()# A tibble: 5 × 3
#>   name           screen_name   created_at         
#>   <chr>          <chr>         <dttm>             
#> 1 N Santos       ninofss       2022-06-29 20:13:46
#> 2 KR             KuriaShiroh   2017-01-13 21:02:59
#> 3 Burak Karahan  _BurakKARAHAN 2013-06-25 14:20:58
#> 4 Fabrice Humura Fhumura       2013-06-20 09:23:07
#> 5 VictorAnsem    VictorAnsem   2013-11-18 11:03:54
```

We have now the information from those followed by the R Foundation and its followers.
We can retrieve their latest tweets from these users:


```r
tweets_data(R_foundation_fds_data)[, c("created_at", "text")]
#> # A tibble: 30 × 2
#>    created_at                     text                                                            
#>    <chr>                          <chr>                                                           
#>  1 Thu Dec 01 11:46:14 +0000 2022 "Today! EMEA/APAC office hour has just taken place. AMER office…
#>  2 Wed Sep 28 15:06:22 +0000 2022 "RT @pdalgd: #rstats 4.2.2 \"Innocent and Trusting\"  scheduled…
#>  3 Tue Nov 29 15:55:04 +0000 2022 "@stevenstrogatz Terry Tao also posted a nice note recently htt…
#>  4 Sat Nov 12 16:06:40 +0000 2022 "RT @HeathrTurnr: Wondering about setting up a data science/ope…
#>  5 Fri Jul 29 05:30:06 +0000 2022 "RT @kidssindwichtig: Wenn du in deiner Arbeitszeit noch nie ei…
#>  6 Fri Apr 16 11:03:21 +0000 2021 "RT @_useRconf: It is a good time to remember some of our keyda…
#>  7 Mon Jan 18 17:36:22 +0000 2021 "Give us a follow at @_useRconf to stay updated on *all* future…
#>  8 Sat Dec 17 13:04:43 +0000 2022 "RT @VincentAB: Want to use @jmwooldridge's Extended Two-Way Fi…
#>  9 Mon Dec 19 15:14:15 +0000 2022 "@_ColinFay @rweekly_org That was quick. Thx"                   
#> 10 Mon Dec 19 18:29:22 +0000 2022 "@thomas_mock @posit_pbc OMG! Congratulations!! (Sorry to tell …
#> # … with 20 more rows
```

## Search users

Search for 1,000 users with the rstats hashtag in their profile bios.

```r
## search for users with #rstats in their profiles
useRs <- search_users("#rstats", n = 100, verbose = FALSE)
useRs[, c("name", "screen_name", "created_at")]
#> Tweets data at tweets_data()# 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 #RStats Question A Day       data_question  2019-10-21 19:15:24
#>  5 R Tweets                     rstats_tweets  2020-09-17 18:12:09
#>  6 Ramiro Bentes                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()`:

```r
useRs_twt <- tweets_data(useRs)
useRs_twt[1:5, c("id_str", "created_at", "text")]
#> # A tibble: 5 × 3
#>   id_str              created_at                     text                                         
#>   <chr>               <chr>                          <chr>                                        
#> 1 1605298908707508224 Tue Dec 20 20:27:39 +0000 2022 "RT @meghansharris: If you're looking for me…
#> 2 1605295768717234176 Tue Dec 20 20:15:10 +0000 2022 "RT @Highcharts: A step-by-step tutorial to …
#> 3 1593655548091797505 Fri Nov 18 17:21:06 +0000 2022 "copying @lemonwatcher's tactic of twitter b…
#> 4 1605178921355706370 Tue Dec 20 12:30:52 +0000 2022 "Options:\n(Answer at: https://t.co/luCHh1j6…
#> 5 1605298970686902294 Tue Dec 20 20:27:54 +0000 2022 "RT @meghansharris: If you're looking for me…
```

## Get timelines

Get the most recent tweets from R Foundation.

```r
## get user IDs of accounts followed by R Foundation
R_foundation_tline <- get_timeline("_R_Foundation")

## plot the frequency of tweets for each user over time
plot <- R_foundation_tline |>
  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 favorites

Get the 10 recently favorited statuses by R Foundation.


```r
R_foundation_favs <- get_favorites("_R_Foundation", n = 10)
R_foundation_favs[, c("text", "created_at", "id_str")]
#> Users data at users_data()
#> # 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 … 2020-08-03 09:51:33 12901…
#>  2 "Gret meeting of #useR2020 passing the torch to #useR2021! 🔥 \nTha… 2020-07-16 17:14:25 12837…
#>  3 "Also thanks to the @_R_Foundation, @R_Forwards, @RLadiesGlobal, Mi… 2020-05-28 08:57:24 12658…
#>  4 "Such an honour to be acknowledged this way at #useR2019. I'm happy… 2019-07-12 18:36:27 11497…
#>  5 "R-3.4.4 Windows installer is on CRAN now: https://t.co/h35EcsIEuF … 2018-03-15 18:16:13 97433…
#>  6 "Gala dinner with a table with people in cosmology, finance, psycho… 2017-07-07 09:10:41 88322…
#>  7 "AMAZING #RLadies at #useR2017 💜🌍 inspiring #rstats work around t… 2017-07-05 13:25:27 88256…
#>  8 "Fame at last: https://t.co/x4wIePKR6b -- it's always nice to get a… 2017-06-07 23:25:37 87256…
#>  9 "We are excited to let you know that the full Conference Program is… 2017-05-31 14:37:23 86989…
#> 10 ". @statsYSS and @RSSGlasgow1  to hold joint event celebrating 20 y… 2017-04-10 10:50:11 85135…
```


## Get trends

Discover what's currently trending in San Francisco.

```r
world <- get_trends("world")
world
#> # A tibble: 50 × 9
#>    trend           url   promo…¹ query tweet…² place woeid as_of               created_at         
#>    <chr>           <chr> <lgl>   <chr>   <int> <chr> <int> <dttm>              <dttm>             
#>  1 #MerciLesBleus  http… NA      %23M…      NA Worl…     1 2022-12-20 21:06:02 2022-12-18 11:01:37
#>  2 #CashAppGiftCa… http… NA      %23C…   11513 Worl…     1 2022-12-20 21:06:02 2022-12-18 11:01:37
#>  3 #PromosyonFiya… http… NA      %23P…   16068 Worl…     1 2022-12-20 21:06:02 2022-12-18 11:01:37
#>  4 Berni           http… NA      Berni   12538 Worl…     1 2022-12-20 21:06:02 2022-12-18 11:01:37
#>  5 #المتجر_الالكت… http… NA      %23%…   12029 Worl…     1 2022-12-20 21:06:02 2022-12-18 11:01:37
#>  6 #سعودي_ايدول    http… NA      %23%…      NA Worl…     1 2022-12-20 21:06:02 2022-12-18 11:01:37
#>  7 Rosada          http… NA      Rosa…  115732 Worl…     1 2022-12-20 21:06:02 2022-12-18 11:01:37
#>  8 Larreta         http… NA      Larr…   16698 Worl…     1 2022-12-20 21:06:02 2022-12-18 11:01:37
#>  9 CABA            http… NA      CABA    46767 Worl…     1 2022-12-20 21:06:02 2022-12-18 11:01:37
#> 10 Ochoa           http… NA      Ochoa   19026 Worl…     1 2022-12-20 21:06:02 2022-12-18 11:01:37
#> # … with 40 more rows, and abbreviated variable names ¹​promoted_content, ²​tweet_volume
```

## Following users

You can follow users and unfollow them:


```r
post_follow("_R_Foundation")
#> Response [https://api.twitter.com/1.1/friendships/create.json?notify=FALSE&screen_name=_R_Foundation]
#>   Date: 2022-12-20 21:06
#>   Status: 200
#>   Content-Type: application/json;charset=utf-8
#>   Size: 3.63 kB
post_unfollow_user("rtweet_test")
#> Response [https://api.twitter.com/1.1/friendships/destroy.json?notify=FALSE&screen_name=rtweet_test]
#>   Date: 2022-12-20 21:06
#>   Status: 200
#>   Content-Type: application/json;charset=utf-8
#>   Size: 3.3 kB
```

## Managing data

There are some functions to help analyze the data extracted from the API.

With `clean_tweets()` you can remove users mentions, hashtags, urls and media to keep only the text if you want to do sentiment analysis (you might want to remove emojis too).


```r
clean_tweets(head(R_foundation_favs), clean = c("users", "hashtags", "urls", "media"))
#> [1] "We're into August, which hopefully means you've had time to enjoy content from !\n\nPlease help us find out who participated in the conference and what you thought of it by answering our survey: ."                           
#> [2] "Gret meeting of  passing the torch to ! 🔥 \nThank you so much, everyone!🙏🏽\nParticularly,\n🌟 from  \n🌟,  chair\n🌟 &amp; ,  chairs\n🌟 &amp; , @useR2021global chairs"                                                     
#> [3] "Also thanks to the , , , MiR and many others in supporting us in this endeavour!"                                                                                                                                               
#> [4] "Such an honour to be acknowledged this way at . I'm happy that folks like , , ,  and so many others have got on board with my ideas for the  community and helped them come to fruition - even better than I could imagine. 💜 "
#> [5] "R-3.4.4 Windows installer is on CRAN now:  "                                                                                                                                                                                    
#> [6] "Gala dinner with a table with people in cosmology, finance, psychology, demography, medical doctor   😊"
```

With `entity()` you can access any entity of the tweets.
It returns the id of the tweet and the corresponding data field in the selected entity.


```r
head(entity(R_foundation_favs, "urls"))
#>                id_str                     url
#> 1 1290193576169803776 https://t.co/HYLl6rMySc
#> 2 1283782043021774850                    <NA>
#> 3 1265899960228360195                    <NA>
#> 4 1149719180314316800 https://t.co/dg2Dh49tug
#> 5  974333459085672448 https://t.co/h35EcsIEuF
#> 6  974333459085672448 https://t.co/7xko0aUS2w
#>                                                expanded_url                        display_url
#> 1                              http://bit.ly/useR2020survey              bit.ly/useR2020survey
#> 2                                                      <NA>                               <NA>
#> 3                                                      <NA>                               <NA>
#> 4 https://twitter.com/alice_data/status/1149680375817494529        twitter.com/alice_data/sta…
#> 5              https://cran.r-project.org/bin/windows/base/ cran.r-project.org/bin/windows/ba…
#> 6      https://twitter.com/pdalgd/status/974214402097508353        twitter.com/pdalgd/status/…
#>   unwound
#> 1      NA
#> 2      NA
#> 3      NA
#> 4      NA
#> 5      NA
#> 6      NA
head(entity(R_foundation_favs, "hashtags"))
#>                id_str     text
#> 1 1290193576169803776 useR2020
#> 2 1283782043021774850 useR2020
#> 3 1283782043021774850 useR2021
#> 4 1265899960228360195     <NA>
#> 5 1149719180314316800 useR2019
#> 6 1149719180314316800   rstats
head(entity(R_foundation_favs, "symbols"))
#>                id_str text
#> 1 1290193576169803776   NA
#> 2 1283782043021774850   NA
#> 3 1265899960228360195   NA
#> 4 1149719180314316800   NA
#> 5  974333459085672448   NA
#> 6  883221715777720320   NA
head(entity(R_foundation_favs, "user_mentions"))
#>                id_str   screen_name                                         name      user_id
#> 1 1290193576169803776          <NA>                                         <NA>           NA
#> 2 1283782043021774850   HeathrTurnr                  Heather Turner is on strike 3.367337e+09
#> 3 1283782043021774850 _R_Foundation The R Foundation @R_Foundation@fosstodon.org 7.944582e+17
#> 4 1283782043021774850     HeidiBaya    Heidi Seibold @HeidiSeibold@fosstodon.org 5.321151e+08
#> 5 1283782043021774850   useR2020muc                                  useR2020muc 1.197875e+18
#> 6 1283782043021774850   chrisprener                                 Chris Prener 5.075829e+08
#>           user_id_str
#> 1                <NA>
#> 2          3367336625
#> 3  794458165987438592
#> 4           532115122
#> 5 1197874989367779328
#> 6           507582860
head(entity(R_foundation_favs, "media"))
#>                id_str id id_str media_url media_url_https  url display_url expanded_url type
#> 1 1290193576169803776 NA   <NA>      <NA>            <NA> <NA>        <NA>         <NA> <NA>
#> 2 1283782043021774850 NA   <NA>      <NA>            <NA> <NA>        <NA>         <NA> <NA>
#> 3 1265899960228360195 NA   <NA>      <NA>            <NA> <NA>        <NA>         <NA> <NA>
#> 4 1149719180314316800 NA   <NA>      <NA>            <NA> <NA>        <NA>         <NA> <NA>
#> 5  974333459085672448 NA   <NA>      <NA>            <NA> <NA>        <NA>         <NA> <NA>
#> 6  883221715777720320 NA   <NA>      <NA>            <NA> <NA>        <NA>         <NA> <NA>
#>   sizes ext_alt_text
#> 1    NA           NA
#> 2    NA           NA
#> 3    NA           NA
#> 4    NA           NA
#> 5    NA           NA
#> 6    NA           NA
```

To avoid having two columns with the same name, `user_mentions()` renames to  the ids  from "id" and "id_str" to "user_id" and "user_id_str".

[1]: Also applies to users ids

## Muting users

You can mute and unmute users:


```r
post_follow("rtweet_test", mute = TRUE)
post_follow("rtweet_test", mute = FALSE)
```


## Blocking users

You can block users and unblock them:


```r
user_block("RTweetTest1")
#> Response [https://api.twitter.com/1.1/blocks/create.json?screen_name=RTweetTest1]
#>   Date: 2022-12-20 21:06
#>   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: 2022-12-20 21:06
#>   Status: 200
#>   Content-Type: application/json;charset=utf-8
#>   Size: 1.35 kB
```



## Rate limits

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()`


```r
rate_limit()
#> # A tibble: 263 × 5
#>    resource                 limit remaining reset_at            reset  
#>    <chr>                    <int>     <int> <dttm>              <drtn> 
#>  1 /lists/list                 15        15 2022-12-20 22:21:03 15 mins
#>  2 /lists/:id/tweets&GET      900       900 2022-12-20 22:21:03 15 mins
#>  3 /lists/:id/followers&GET   180       180 2022-12-20 22:21:03 15 mins
#>  4 /lists/memberships          75        75 2022-12-20 22:21:03 15 mins
#>  5 /lists/:id&DELETE          300       300 2022-12-20 22:21:03 15 mins
#>  6 /lists/subscriptions        15        15 2022-12-20 22:21:03 15 mins
#>  7 /lists/members             900       900 2022-12-20 22:21:03 15 mins
#>  8 /lists/:id&GET              75        75 2022-12-20 22:21:03 15 mins
#>  9 /lists/subscribers/show     15        15 2022-12-20 22:21:03 15 mins
#> 10 /lists/:id&PUT             300       300 2022-12-20 22:21:03 15 mins
#> # … with 253 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 2022-12-20 22:21:04 15 mins
#> 2 /users/:id/followers                      15        15 2022-12-20 22:21:04 15 mins
#> 3 /users/by/username/:username/followers    15        15 2022-12-20 22:21:04 15 mins
#> 4 /followers/ids                            15         9 2022-12-20 22:20:50 15 mins
#> 5 /followers/list                           15        15 2022-12-20 22:21:04 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".

## Stream tweets

Please, see the vignette on `vignette("stream", "rtweet")` for more information.

## SessionInfo

To provide real examples the vignette is precomputed before submission.
Also note that results returned by the API will change.


```{.r .fold-hide}
sessionInfo()
#> R version 4.2.2 (2022-10-31)
#> Platform: x86_64-pc-linux-gnu (64-bit)
#> Running under: Ubuntu 22.04.1 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/libopenblasp-r0.3.20.so
#> 
#> locale:
#>  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C               LC_TIME=es_ES.UTF-8       
#>  [4] LC_COLLATE=en_US.UTF-8     LC_MONETARY=es_ES.UTF-8    LC_MESSAGES=en_US.UTF-8   
#>  [7] LC_PAPER=es_ES.UTF-8       LC_NAME=C                  LC_ADDRESS=C              
#> [10] 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] dplyr_1.0.10        ggplot2_3.4.0       knitr_1.41          rtweet_1.0.2.9018  
#> [5] BiocManager_1.30.19 cyclocomp_1.1.0     testthat_3.1.5      devtools_2.4.5     
#> [9] usethis_2.1.6      
#> 
#> loaded via a namespace (and not attached):
#>  [1] fs_1.5.2          bit64_4.0.5       progress_1.2.2    httr_1.4.4        rprojroot_2.0.3  
#>  [6] tools_4.2.2       profvis_0.3.7     utf8_1.2.2        R6_2.5.1          DBI_1.1.3        
#> [11] colorspace_2.0-3  urlchecker_1.0.1  withr_2.5.0       tidyselect_1.2.0  prettyunits_1.1.1
#> [16] processx_3.8.0    bit_4.0.5         curl_4.3.3        compiler_4.2.2    httr2_0.2.2      
#> [21] cli_3.4.1         webmockr_0.8.2    xml2_1.3.3        desc_1.4.2        labeling_0.4.2   
#> [26] triebeard_0.3.0   scales_1.2.1      callr_3.7.3       askpass_1.1       rappdirs_0.3.3   
#> [31] commonmark_1.8.1  stringr_1.5.0     digest_0.6.30     rmarkdown_2.18    base64enc_0.1-3  
#> [36] pkgconfig_2.0.3   htmltools_0.5.3   sessioninfo_1.2.2 highr_0.9         fastmap_1.1.0    
#> [41] htmlwidgets_1.5.4 rlang_1.0.6       rstudioapi_0.14   httpcode_0.3.0    shiny_1.7.3      
#> [46] farver_2.1.1      generics_0.1.3    jsonlite_1.8.4    magrittr_2.0.3    fauxpas_0.5.0    
#> [51] Rcpp_1.0.9        munsell_0.5.0     fansi_1.0.3       lifecycle_1.0.3   stringi_1.7.8    
#> [56] whisker_0.4.1     yaml_2.3.6        brio_1.1.3        pkgbuild_1.4.0    grid_4.2.2       
#> [61] promises_1.2.0.1  crayon_1.5.2      miniUI_0.1.1.1    hms_1.1.2         ps_1.7.2         
#> [66] pillar_1.8.1      pkgload_1.3.2     crul_1.3          glue_1.6.2        evaluate_0.18    
#> [71] remotes_2.4.2     vctrs_0.5.1       httpuv_1.6.6      urltools_1.7.3    gtable_0.3.1     
#> [76] openssl_2.0.5     purrr_0.3.5       assertthat_0.2.1  cachem_1.0.6      xfun_0.35        
#> [81] mime_0.12         xtable_1.8-4      roxygen2_7.2.2    later_1.3.0       vcr_1.2.0        
#> [86] tibble_3.1.8      memoise_2.0.1     ellipsis_0.3.2
```

