jdunkerley

sbt Build Commands:

• clean: flushes all the stuff and can be useful when getting new code.
• runtime/clean: flushes just the engine libs bits (so quicker).
• buildProjectManagerDistribution: builds the project manager server executable.
• buildEngineDistribution: builds the engine server and libraries distribution executable.
• buildStdLib...: builds the standard library can be All or a specific one. Tends to leave the index in a mess so often lose the dropdowns or CB.

Running Enso IDE:

• Just run the executable it will launch a GUI and a Project Manager. Opening a project opens a Language Server. IDE Dashboard <---> Project Manager --launches-> Language Server <---> IDE Graph Editor

jdunkerley

Install WinGet (https://www.microsoft.com/p/app-installer/9nblggh4nns1#activetab=pivot:overviewtab) via store

Install latest Powershell

winget install --id Microsoft.Powershell --source winget

Open Powershell 7 (or later) as admin (pwsh)

## Install Git, NVM, MSVC, Rust

jdunkerley

from Standard.Base import all
from Standard.Table import all
from Standard.Database import all
import Standard.Visualization

func1 operator11 =
    operator12 = operator11.split "-"
    operator13 = operator12.first
    operator13

jdunkerley

from Standard.Base import all
from Standard.Table import all
from Standard.Database import all
import Standard.Visualization

main =
    operator3 = enso_project.data/"Transactions.csv" . read
    operator4 = enso_project.data/"Swift Codes.csv" . read
    operator1 = operator4.use_first_row_as_names
    operator2 = operator3.join operator1 Join_Kind.Inner "Bank"

jdunkerley

from Standard.Base import all
from Standard.Table import all
from Standard.Database import all
import Standard.Visualization

func1 operator11 =
    operator12 = operator11.split "-"
    operator13 = operator12.first
    operator13

jdunkerley

#!/bin/bash
instanceid=`aws ec2 describe-instances --query 'Reservations[0].Instances[*].InstanceId' --output text`
aws ssm start-session --target $instanceid

jdunkerley

from random import random
from math import sqrt, log, exp
from numba import njit
import numpy
from numpy.random import normal

def path_final_min_max(initial, steps, sdt, volatility, drift):
    randoms = numpy.exp(normal(size=steps)*volatility*sdt) * drift
    randoms[0] = 1
    factors = numpy.cumprod(randoms) * initial

jdunkerley

from random import random
from math import sqrt, log, exp
from numba import njit, jit, prange

@njit(fastmath=True)
def box_muller_rand():
    while True:
        x = random() * 2.0 - 1
        y = random() * 2.0 - 1
        d = x * x + y * y 

jdunkerley

#include <cstdlib>
#include <random>
#include <iostream>

namespace barrierpricer {
    static std::random_device rd;
    static std::mt19937_64 rand_generator(rd());
    static std::normal_distribution<> dis;

    double box_muller_rand() {

jdunkerley

from random import random
from math import sqrt, log, exp

def box_muller_rand():
    while True:
        x = random() * 2.0 - 1
        y = random() * 2.0 - 1
        d = x * x + y * y 
        if d < 1:
            return x * sqrt(-2 * log(d) / d)