maryrosecook

var landscape = new Landscape(); // one actor

// make instance of Machine and get the root nodes for each actor
var machine = new Machine();
landscape.state = machine.generateTree(landscapeJson, landscape);

// every second, something happens in the ecosystem
setTimeout("step()", 1000);
var step = function() {
    // trigger the next state transition

maryrosecook

{
    identifier: "idle", strategy: "prioritised",
    children: [
        {
            identifier: "spot", strategy: "sequential",
            children: [
                { identifier: "callRange" },
                { identifier: "stopSpotting" },
            ]
        },

maryrosecook

var s = new Snowflake();
s.aSnowflakeFunc(supportingVar, actionFunc(arg) {
  // do stuff in here.
}, arg);

maryrosecook

var aliens = [{}, {}, {}];
var aliensCollidingWithPlayer = [];

for (var i = 0; i < aliens.length; i++) {
  if(colliding(alien[i], player)) { // is colliding current tick
    var collidingInPreviousTick = false;
    for (var j = 0; j < aliensCollidingWithPlayer.length; j++) {
      if (aliens[i] === aliensCollidingWithPlayer[j]) {
        collidingInPreviousTick = true;
        break;

maryrosecook

var applyFn = function(node, fn) {
  var applied = fn(node);
  return applied === undefined ? node : applied;
};

var macro = function(key, val) {
  if (key.firstBit === repeatChild) {
    repeatChild(key, val)
  }
};

maryrosecook

block_size = 16
blocks = []

a_size = 128
b_size = 32
a = [0, 1, 2]
b = [0, 1, 2]
print a == b

def memoise(fn):

maryrosecook

# A practical introduction to functional programming

Many functional programming articles teach abstract functional techniques.  That is, composition, pipelining, higher order functions.  This one is different.  It shows examples of imperative code that people write every day and translates them to a functional style.

The imperative examples are all loops.  The first section of the article takes short, data transforming loops and translates them into functional maps and reduces.  The second section takes longer loops, breaks them up into units and makes each unit functional.  The third section takes a loop that is a long series of successive data transformations and decomposes it into a functional pipeline.

The examples are in Python, because many people find Python easy to read.  A number of the examples eschew pythonicity in order to demonstrate functional techniques common to many languages: map, reduce, pipeline.

## A guide rope

maryrosecook

e

maryrosecook

### Keybase proof

I hereby claim:

  * I am maryrosecook on github.
  * I am maryrosecook (https://keybase.io/maryrosecook) on keybase.
  * I have a public key whose fingerprint is 59DB 7EF4 2BAC 5D67 22FB  F7DA 7DFF 4628 A3F1 83AF

To claim this, I am signing this object:

maryrosecook

shopping_list = ["apple", "toothbrush", "banana", "black lava"]
shopping_list.append("cheese")
shopping_list.reverse()
print("Shopping List")
for shopping_list_item in shopping_list:
    if len(shopping_list_item)<7 or shopping_list_item=="black lava":
        print("-" + shopping_list_item)