tweets

This is data scraped from swyx's timeline! See blog post

6 rows where in_reply_to_screen_name = "ejames_c" and user = 33521530 sorted by lang

✎ View and edit SQL

This data as json, CSV (advanced)

Suggested facets: source, is_quote_status, favorite_count

user 1 ✖

  • swyx · 6 ✖

in_reply_to_screen_name 1 ✖

  • ejames_c · 6 ✖
id user created_at full_text retweeted_status quoted_status place source truncated display_text_range in_reply_to_status_id in_reply_to_user_id in_reply_to_screen_name geo coordinates contributors is_quote_status retweet_count favorite_count favorited retweeted possibly_sensitive lang ▼ scopes
1422431689779802112 swyx 33521530 2021-08-03T05:38:37+00:00 @ejames_c @dimfeld @sgrove @temporalio this writeup is probably written below your level but the resources at the end may help. would love to hear your thoughts/questions! https://twitter.com/swyx/status/1417165270641045505   1417165270641045505 1417165270641045505   Twitter Web App 1f89d6a41b1505a3071169f8d0d028ba9ad6f952 0 [39, 196] 1422430127212744704 14243237 ejames_c       1 0 1 0 0 0 en  
1424606662137053184 swyx 33521530 2021-08-09T05:41:10+00:00 @ejames_c got it last week. only mild weakness on day 1. hang in there       Twitter for iPhone 95f3aaaddaa45937ac94765e0ddb68ba2be92d20 0 [10, 70] 1424382463124525071 14243237 ejames_c       0 0 2 0 0   en  
1431083176303083521 swyx 33521530 2021-08-27T02:36:32+00:00 @ejames_c i very nearly went with that title for the blogpost but felt it wouldve been too niche 😂       Twitter for iPhone 95f3aaaddaa45937ac94765e0ddb68ba2be92d20 0 [10, 98] 1431082661758394374 14243237 ejames_c       0 0 1 0 0   en  
1444551050967465986 swyx 33521530 2021-10-03T06:33:03+00:00 @ejames_c "I am a postgresql specialist because it is open source and reliable af" is a pretty good reason not to know anything else about database implementations and just spend the rest of your career knowing postgres nuances tbh. not everyone needs to be horizontally aware       Twitter Web App 1f89d6a41b1505a3071169f8d0d028ba9ad6f952 0 [10, 276] 1444549924108976130 14243237 ejames_c       0 0 1 0 0   en  
1457256545343840258 swyx 33521530 2021-11-07T08:00:09+00:00 @ejames_c i actually dont find the inability to predict a good thing. people really want predictions. personal outcomes really depend on weighting probabilities right. its not enough to sit back and say “ah look everything is so complex it all depends”. you have to *do something*.       Twitter for iPhone 95f3aaaddaa45937ac94765e0ddb68ba2be92d20 0 [10, 282] 1457002379258204165 14243237 ejames_c       0 0 1 0 0   en  
1457621152054984705 swyx 33521530 2021-11-08T08:08:58+00:00 @ejames_c this is the dankest timeline       Twitter for iPhone 95f3aaaddaa45937ac94765e0ddb68ba2be92d20 0 [10, 38] 1457584354394181635 14243237 ejames_c       0 0 3 0 0   en  

Advanced export

JSON shape: default, array, newline-delimited, object

CSV options: 

CREATE TABLE [tweets] (
   [id] INTEGER PRIMARY KEY,
   [user] INTEGER REFERENCES [users]([id]),
   [created_at] TEXT,
   [full_text] TEXT,
   [retweeted_status] INTEGER,
   [quoted_status] INTEGER,
   [place] TEXT REFERENCES [places]([id]),
   [source] TEXT REFERENCES [sources]([id]), [truncated] INTEGER, [display_text_range] TEXT, [in_reply_to_status_id] INTEGER, [in_reply_to_user_id] INTEGER, [in_reply_to_screen_name] TEXT, [geo] TEXT, [coordinates] TEXT, [contributors] TEXT, [is_quote_status] INTEGER, [retweet_count] INTEGER, [favorite_count] INTEGER, [favorited] INTEGER, [retweeted] INTEGER, [possibly_sensitive] INTEGER, [lang] TEXT, [scopes] TEXT,
   FOREIGN KEY([retweeted_status]) REFERENCES [tweets]([id]),
   FOREIGN KEY([quoted_status]) REFERENCES [tweets]([id])
);
CREATE INDEX [idx_tweets_source]
    ON [tweets] ([source]);