nayeemzen

// Functional programming approach to parsing query strings in Typescript/ES6.
function parseQueryString(search: string) {
  return (search.startsWith('?') ? search.substring(1) : search)
    .split('&')
    .map(str => {
      const eqIdx = str.indexOf('=');
      if (eqIdx <= 0 || eqIdx >= str.length - 1) {
        return {};
      }

rondy

FWIW: I (@rondy) am not the creator of the content shared here, which is an excerpt from Edmond Lau's book. I simply copied and pasted it from another location and saved it as a personal note, before it gained popularity on news.ycombinator.com. Unfortunately, I cannot recall the exact origin of the original source, nor was I able to find the author's name, so I am can't provide the appropriate credits.

---

Effective Engineer - Notes

• By Edmond Lau
• Highly Recommended 👍
• http://www.theeffectiveengineer.com/

What's an Effective Engineer?

CMCDragonkai

HTTP Streaming (or Chunked vs Store & Forward)

The standard way of understanding the HTTP protocol is via the request reply pattern. Each HTTP transaction consists of a finitely bounded HTTP request and a finitely bounded HTTP response.

However it's also possible for both parts of an HTTP 1.1 transaction to stream their possibly infinitely bounded data. The advantages is that the sender can send data that is beyond the sender's memory limit, and the receiver can act on

lttlrck

git branch -m old_branch new_branch         # Rename branch locally    
git push origin :old_branch                 # Delete the old branch    
git push --set-upstream origin new_branch   # Push the new branch, set local branch to track the new remote

debasishg

General Background and Overview

1. 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.
2. Models and Issues in Data Stream Systems
3. 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
4. Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
5. [Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&rep=rep1&t

livibetter

This Gist has been moved to https://github.com/lbgists/audio-spectrum-matplotlib.