tweets

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

1 row where "created_at" is on date 2021-09-17, retweeted = 1 and source = "295366d0fb34352a1961af2413827f072adefdb9" sorted by lang

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source 1 ✖

  • Typefully · 1 ✖

created_at (date) 1 ✖

  • 2021-09-17 · 1 ✖

in_reply_to_user_id 0 ✖

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
1438992207344635904 procrastinator 14558882 2021-09-17T22:24:12+00:00 As lists and threads are all the rage here, this by @swyx is one of the best I read during the year...or ever 👏 Where do these people learn to write this stuff? Is there a cohort-based course for "Lessons learned in XYZ years of life"? 😕 https://www.swyx.io/35-principles/       Typefully 295366d0fb34352a1961af2413827f072adefdb9 0 [0, 263]             0 2 15 0 1 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]);