- Loi n°55-385 from 1955
- Wikipedia / Etat d'urgence en France (general structure)
import java.io.*; | |
import java.util.*; | |
public class BRC { | |
public static void main(String[] args) throws FileNotFoundException { | |
long millis = System.currentTimeMillis(); | |
System.out.println(calculateMinMeanMaxPerStation(readCSV())); | |
System.out.println("Time taken = " + (System.currentTimeMillis() - millis)); | |
} |
class Trie { | |
data class Node(var word: String? = null, val childNodes: MutableMap<Char, Node> = mutableMapOf()) | |
private val root = Node() | |
fun insert(word: String) { | |
var currentNode = root | |
for (char in word) { | |
if (currentNode.childNodes[char] == null) { |
2015-01-29 Unofficial Relay FAQ
Compilation of questions and answers about Relay from React.js Conf.
Disclaimer: I work on Relay at Facebook. Relay is a complex system on which we're iterating aggressively. I'll do my best here to provide accurate, useful answers, but the details are subject to change. I may also be wrong. Feedback and additional questions are welcome.
Relay is a new framework from Facebook that provides data-fetching functionality for React applications. It was announced at React.js Conf (January 2015).
object Maps { | |
implicit class MergableMap[K](map: Map[K, _]) { | |
/** | |
* Override values from this with values from that. | |
*/ | |
def deepMerge(that: Map[K, _]): Map[K, _] = | |
(for (k <- map.keys ++ that.keys) yield { | |
val newValue = | |
(map.get(k), that.get(k)) match { |
(by @andrestaltz)
If you prefer to watch video tutorials with live-coding, then check out this series I recorded with the same contents as in this article: Egghead.io - Introduction to Reactive Programming.
I have moved this over to the Tech Interview Cheat Sheet Repo and has been expanded and even has code challenges you can run and practice against!
\
- 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
Eric Bidelman has documented some of the common workflows possible with headless Chrome over in https://developers.google.com/web/updates/2017/04/headless-chrome.
If you're looking at this in 2016 and beyond, I strongly recommend investigating real headless Chrome: https://chromium.googlesource.com/chromium/src/+/lkgr/headless/README.md
Windows and Mac users might find using Justin Ribeiro's Docker setup useful here while full support for these platforms is being worked out.