- Probabilistic Data Structures for Web Analytics and Data Mining : A great overview of the space of probabilistic data structures and how they are used in approximation algorithm implementation.
- Models and Issues in Data Stream Systems
- Philippe Flajolet’s contribution to streaming algorithms : A presentation by Jérémie Lumbroso that visits some of the hostorical perspectives and how it all began with Flajolet
- Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
- [Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&rep=rep1&t
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// In a js file | |
disqus_config = function() { | |
this.callbacks.afterRender.push(function() { /* your code */ }); | |
this.callbacks.onNewComment.push(function() { /* your code */ }); | |
/* Available callbacks are afterRender, onInit, onNewComment, onPaginate, onReady, preData, preInit, preReset */ | |
} |
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/** | |
* Copyright (C) 2009-2014 Typesafe Inc. <http://www.typesafe.com> | |
*/ | |
package akka.contrib.mailbox | |
import scala.concurrent.duration._ | |
import java.util.concurrent.atomic.AtomicInteger | |
import java.util.concurrent.atomic.AtomicLong | |
import com.typesafe.config.Config | |
import akka.actor.{ ActorContext, ActorRef, ActorSystem, ExtendedActorSystem } |
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def objectReader[T1,T2,T3,T4,R](t1: String, t2: String, t3: String, t4: String)(f: (T1,T2,T3,T4) => R)(implicit readsT1:Reads[T1], readsT2:Reads[T2], readsT3:Reads[T3], readsT4:Reads[T4]): Reads[R] = { | |
def orElse[A](a:A, default: =>A) = if(a!=null) a else default | |
Reads[R]{ | |
case JsObject(fields) => | |
var t1V:JsResult[T1] = null.asInstanceOf[JsResult[T1]] | |
var t2V:JsResult[T2] = null.asInstanceOf[JsResult[T2]] |
The idea is based on a gist by @jimbojsb.
You can use Pygments or Highlight.
brew install python
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You are a powerful agentic AI coding assistant, powered by Claude 3.5 Sonnet. You operate exclusively in Cursor, the world's best IDE. | |
You are pair programming with a USER to solve their coding task. | |
The task may require creating a new codebase, modifying or debugging an existing codebase, or simply answering a question. | |
Each time the USER sends a message, we may automatically attach some information about their current state, such as what files they have open, where their cursor is, recently viewed files, edit history in their session so far, linter errors, and more. | |
This information may or may not be relevant to the coding task, it is up for you to decide. | |
Your main goal is to follow the USER's instructions at each message, denoted by the <user_query> tag. | |
<communication> | |
1. Be conversational but professional. |