staltz

The introduction to Reactive Programming you've been missing

(by @andrestaltz)

---

This tutorial as a series of videos

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.

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aras-p

// Just before switching jobs:
// Add one of these.
// Preferably into the same commit where you do a large merge.
//
// This started as a tweet with a joke of "C++ pro-tip: #define private public",
// and then it quickly escalated into more and more evil suggestions.
// I've tried to capture interesting suggestions here.
//
// Contributors: @r2d2rigo, @joeldevahl, @msinilo, @_Humus_,
// @YuriyODonnell, @rygorous, @cmuratori, @mike_acton, @grumpygiant,

bishboria

These links no longer work. Springer have pulled the free plug.

Graduate texts in mathematics

duplicates = multiple editions

A Classical Introduction to Modern Number Theory, Kenneth Ireland Michael Rosen

A Classical Introduction to Modern Number Theory, Kenneth Ireland Michael Rosen

leonardofed

A curated list of AWS resources to prepare for the AWS Certifications

A curated list of awesome AWS resources you need to prepare for the all 5 AWS Certifications. This gist will include: open source repos, blogs & blogposts, ebooks, PDF, whitepapers, video courses, free lecture, slides, sample test and many other resources.

---

yossorion

What I Wish I'd Known About Equity Before Joining A Unicorn

Disclaimer: This piece is written anonymously. The names of a few particular companies are mentioned, but as common examples only.

This is a short write-up on things that I wish I'd known and considered before joining a private company (aka startup, aka unicorn in some cases). I'm not trying to make the case that you should never join a private company, but the power imbalance between founder and employee is extreme, and that potential candidates would

joepie91

Your blockchain must have all of the following properties:

• It's a merkle tree, or a construct with equivalent properties.
• There is no single point of trust or authority; nodes are operated by different parties.
• Multiple 'forks' of the blockchain may exist - that is, nodes may disagree on what the full sequence of blocks looks like.
• In the case of such a fork, there must exist a deterministic consensus algorithm of some sort to decide what the "real" blockchain looks like (ie. which fork is "correct").
• The consensus algorithm must be executable with only the information contained in the blockchain (or its forks), and no external input (eg. no decisionmaking from a centralized 'trust node').

If your blockchain is missing any of the above properties, it is not a blockchain, it is just a ledger.

dvirsky

Creating a redis Module in 15 lines of code!

A quick guide to write a very very simple "ECHO" style module to redis and load it. It's not really useful of course, but the idea is to illustrate how little boilerplate it takes.

Step 1: open your favorite editor and write/paste the following code in a file called module.c

#include "redismodule.h"
/* ECHO <string> - Echo back a string sent from the client */
int EchoCommand(RedisModuleCtx *ctx, RedisModuleString **argv, int argc) {

bearfrieze

Comprehensions in Python the Jedi way

by Bjørn Friese

Beautiful is better than ugly. Explicit is better than implicit.

-- The Zen of Python

I frequently deal with collections of things in the programs I write. Collections of droids, jedis, planets, lightsabers, starfighters, etc. When programming in Python, these collections of things are usually represented as lists, sets and dictionaries. Oftentimes, what I want to do with collections is to transform them in various ways. Comprehensions is a powerful syntax for doing just that. I use them extensively, and it's one of the things that keep me coming back to Python. Let me show you a few examples of the incredible usefulness of comprehensions.

fperez

#!/usr/bin/env python
"""
Interactive execution with automatic history, tries to mimic Mathematica's
prompt system. This environment's main features are:

- Numbered prompts (In/Out) similar to Mathematica. Only actions that produce
  output (NOT assingments, for example) affect the counter and cache.

- The following GLOBAL variables always exist (so don't overwrite them!):
  _p: stores previous result which generated printable output.

zacstewart

import os
import numpy
from pandas import DataFrame
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.naive_bayes import MultinomialNB
from sklearn.pipeline import Pipeline
from sklearn.cross_validation import KFold
from sklearn.metrics import confusion_matrix, f1_score

NEWLINE = '\n'