tweets

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

1 row where quoted_status = 1449112317917110276, retweet_count = 0 and retweeted = 0 sorted by lang

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user 1 ✖

retweeted 1 ✖

retweet_count 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
1449884413848809475 swyx 33521530 2021-10-17T23:45:56+00:00 @noseratio @jhooks our job is executing work across time and unreliable networks and machines: https://twitter.com/threepointone/status/1449112317917110276?s=21, React’s job is rendering the most current version of app state that is ready. i guess perhaps the analogy falls down there but there’s still useful things to borrow from React.   1449112317917110276 1449112317917110276   Twitter for iPhone 95f3aaaddaa45937ac94765e0ddb68ba2be92d20 0 [19, 297] 1449882287240187909 33521530 swyx       1 0 1 0 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]);