tweets

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

1 row where "created_at" is on date 2021-09-09, favorite_count = 3 and source = "295366d0fb34352a1961af2413827f072adefdb9" sorted by lang

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source 1 ✖

  • Typefully · 1 ✖

in_reply_to_user_id 1 ✖

favorite_count 1 ✖

created_at (date) 1 ✖

  • 2021-09-09 · 1 ✖
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
1435801440929427456 swyx 33521530 2021-09-09T03:05:14+00:00 4/ I've enjoyed working with Chapter to set this up. @KyleLadewig and @stflory have an admirable mission to make learning more accessible...chapters are 99% cheaper than other premium online cohort based courses.       Typefully 295366d0fb34352a1961af2413827f072adefdb9 0 [0, 212] 1435801439331241987 33521530 swyx       0 0 3 0 0   en  

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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]);