{
  "@context":[
    "https://www.w3.org/ns/activitystreams",
    {"Hashtag":"as:Hashtag"}
  ],
  "published":"2026-05-20T23:55:05.117Z",
  "attributedTo":"https://gopinath.org/actors/rahul",
  "replies":"https://gopinath.org/objects/Eo4QWVwlu-8/replies",
  "to":["https://www.w3.org/ns/activitystreams#Public"],
  "cc":["https://gopinath.org/actors/rahul/followers"],
  "content":"<p>A tutorial of the <a href=\"https://gopinath.org/tags/RPNI\" class=\"hashtag\" rel=\"tag\">#RPNI</a> algorithm for inferring regular input grammars when given only accepted and rejected examples (positive and negative examples). I had posted the <a href=\"https://rahul.gopinath.org/post/2024/01/04/lstar-learning-regular-languages/\">L* algorithm before</a>.</p><p>This is part of my ongoing effort to document various algorithms relating to grammars including various algorithms for parsing, random sampling of fixed size strings, and grammar fuzzing.</p><p>Note: Pyodide takes a little time to initialize, but it should be faster to initialize than spinning up the binder service from Jupyter (but slower to execute).</p><p><a href=\"https://rahul.gopinath.org/post/2025/10/24/rpni-learning-regular-languages/\">https://rahul.gopinath.org/post/2025/10/24/rpni-learning-regular-languages/</a></p>",
  "mediaType":"text/html",
  "attachment":[],
  "tag":[
      {"type":"Hashtag","name":"#RPNI","href":"https://gopinath.org/tags/RPNI"}
  ],
  "type":"Note",
  "id":"https://gopinath.org/objects/92bA9ZWsQSQ"
}