Patrikios

library(shiny)
library(quantmod)
library(VGAM)

# Define server logic for random distribution application
shinyServer(function(input, output) {
  
  # acquiring data
  dataInput <- reactive({
    if (input$get == 0)

Patrikios

package main

// Sources:
// 1. https://go.dev/tour/methods/15
// 2. https://go.dev/tour/methods/16
// 3. https://stackoverflow.com/questions/6996704/how-to-check-variable-type-at-runtime-in-go-language
// 4. https://go.dev/tour/methods/9

// Notions
// concrete types like int, float64, string etc

Patrikios

#= assignment of a function to a new name
    - is shallow copy of a function
    - in programming parlance: done by reference
=#

f(x) = 2x
g = f
g #f (generic function with 1 method)
g(2) #4
f(x) = 4x

Patrikios

using DataFrames

# create a data.frame (simple)
df = DataFrame(A=1:4, B=["M", "N", "O", "P"])
df[!, :A] # no copy
df[:, :A]  # copy is returned

# create a data.frame (row by row - not performant, as DataFrames are like in R built columnwise)
df2 = DataFrame(A=Int[], B=String[])
push!(df2, (1, "M"));

Patrikios

sync.WaitGroup

package main

import (
	"log"
	"math/rand"
	"sync"
	"time"

Patrikios

a_tuple = (1, 2)
a_pair = 1 => 2
a_tuple != a_pair
# true
# The elements are stored in the fields first and second
a_pair.first
# 1
a_pair.second
# 1
typeof(a_pair)

Patrikios

# Generator Expressions
# - comprehensions can also be written without the enclosing square brackets, producing an object known as a generator 
# - can be iterated to produce values on demand, instead of allocating an array and storing them in advance
# - Generators are implemented via inner functions.
# - simple example
(1/n^2 for n=1:1000)
# - collect
collect(1/n^2 for n=1:1000)
# - the following expression sums a series without allocating memory
map(tuple, (1/(i+j) for i=1:2, j=1:2), [1 3; 2 4])

Patrikios

# Ressources:
# - https://github.com/r-hub/r-minimal
# - https://hosting.analythium.io/best-practices-for-r-with-docker/

# NOTE
# does not support Cairo or x11 add hoc, hence renderPlot will not work, renderPlotly und JS backends are working fine

# TEST and DEBUG
# - build: sudo docker build --build-arg http_proxy=x --build-arg https_proxy=x -t shiny_app_alpine .
# - run: sudo docker run -it -p 3899:3838 -v /home/xyz/:/home/xyz/ shiny_app_alpine

Patrikios

# Multithreaded programming in Julia

#= 
    Julia supports multiple types of parallelism
    - SIMD (handled by the compiler) -> for instance the package StaticArrays.jl, short static vectors incline to encourage SIMD operations, a further reason why the package is so efficient 
    - Threads with shared memory (this documents touches upon this point)
    - Distributed (multi-mode, not sharing memory)
    - GPUs
=#

Patrikios

# DOCUMENTATION
#
# Sources: http://adv-r.had.co.nz/Exceptions-Debugging.html & https://adv-r.hadley.nz/conditions.html
#
# - all conditions inherit from abstract class 'condition'
# - conditions are being signalled from functions
# - R conditions system was inpsired by Common Lisp
#
#
# Ressources: