home / twitter

tweets

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

1 row where "created_at" is on date 2021-10-08, retweeted = 1 and user = 3246815913 sorted by lang

✎ View and edit SQL

This data as json, CSV (advanced)

Suggested facets: created_at (date)

retweeted 1 ✖

  • 1 · 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
1446276421882581011 Hassan El Mghari 3246815913 2021-10-08T00:49:04+00:00 I'm using a technique called "Following the Graph" (coined by @swyx) to better understand the Next.js ecosystem. This means exploring old Next.js talks, changelogs, and RFCs to rewind to the start and understand: • What's important • Who built it & why • What influenced it       Twitter Web App 1f89d6a41b1505a3071169f8d0d028ba9ad6f952 0 [0, 279]             0 4 88 0 1   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]);
Powered by Datasette · Queries took 1110.201ms