imjacobclark

(defun pad(thing) 
  (concatenate 'string "0" thing))

(defun pad-if-length-not-same(thing length)
  (cond
    ((not 
      (= (length thing) length)) 
        (pad thing))
    (t thing)))

imjacobclark

(defun pad(num)
  (concatenate 'string "0" num))

(defun should-pad(num)
  (= (length num) 1))

(defun apply-padding(num) 
    (cond
        ((should-pad num) (pad num))
        (t num))) 

imjacobclark

module DFASpec (spec) where

import Test.Hspec

data State = S1 | S2 deriving (Eq, Show)

data Symbols = Zero | One deriving (Eq, Show)
data Alphabet = Alphabet [Symbols]  deriving (Eq, Show)
data FiniteStates = FiniteStates [State] deriving (Eq, Show)
 

imjacobclark

#[derive(Debug, PartialEq)] 
enum Token {
    Symbol(Symbol),
    Type(Type),
    Keyword(Keyword),
    Word(Word),
    Char(char),
}

#[derive(Debug, PartialEq)] 

imjacobclark

package xyz.jacobclark.day3;


import org.junit.Test;

import java.util.ArrayList;
import java.util.List;

import static org.junit.Assert.assertEquals;

imjacobclark

const query = require('./query.js');

require('es6-promise').polyfill();

exports.handler = function(event, context, callback) {
    query(event["queryStringParameters"]['username']).then(function(data){

        var resp = {
            "isBase64Encoded": false,
            "statusCode": 200,

imjacobclark

module Main where
    
import Network.HTTP.Conduit
import qualified Data.ByteString.Lazy as L
import Text.Regex.PCRE

findNewsroundLinks ::  String -> [String]
findNewsroundLinks = map read . getAllTextMatches . (=~ "href=\"/newsround([^\"#]+)")

bytestringToString :: L.ByteString ->  [String]

imjacobclark

package xyz.jacobclark;

import java.util.List;
import java.util.stream.Collectors;
import java.util.stream.IntStream;

import static java.util.Arrays.asList;

public class LinearRegression {
    private static final List<Integer> x = asList(2, 3, 5, 7, 9, 11, 14); // Consecutive hours developer codes

imjacobclark

def nn(input1, input2):
    bias    = 1

    weight0 = -1 
    weight1 = 0.5
    weight2 = 0.5

    net = (bias*weight0)+(input1*weight1)+(input2*weight2)

    return "1" if net >= 0 else "0"

imjacobclark

Association Lisps 💥

Running:

$ brew install sbcl
$ sbcl --script association.cl