Julia and Jupyter Notebooks

import Pkg
# grab the packages not built-in to nextjournal
Pkg.add("MortalityTables") # not part of NextJournal's default packages :(
Pkg.add("ProgressMeter")
Pkg.add("Distributions")

using StatsBase, MortalityTables, Plots, ProgressMeter, Dates, BenchmarkTools, Test, CSV, DataFrames, Distributions

typeof(1), typeof(1.0), typeof(1+0im), typeof(π) # note the unicode support!

1 + π # julia usually knows how to make different types talk to each other

typeof(a), typeof([1,2,3]), typeof("I am a string"), typeof(true)

b = [2, 3, 4, 5, 6]

a .+ b # the dot syntax (aka "broadcasting")

a[1:3]

a[3:(end-1)]

d = Dict("a" => 1, "b" => 2 )

d["a"]

for (key, val) in d
    @show key,val
end

sum(val for (key, val) in d) 

# Strings are created with "
"This is a string."

# Strings are just arrays of characters, so you can do 'array type stuff' with them
"This is a string"[end-5:end]  

# String can be compared lexicographically
"good" > "bye" # => true
"good" == "good" # => true

today = Dates.today()
y = Dates.year(today)
m = Dates.month(today)
d = Dates.day(today)
file_to_export = "output data $y-$m-$d.csv"

path = "data\\input.csv"

path = raw"data\input.csv"

# basic loop that will take 5 seconds
for i in 1:5
    sleep(1)
end

using ProgressMeter
@showprogress for i in 1:5
    sleep(1)
end

using BenchmarkTools,StatsBase

# define my own mean function that will return the average of the numbers in the vector
function my_mean(vector)
    sum(vector) / length(vector)
end

# a test vector
tv = rand(1000);

@benchmark my_mean($tv)

@benchmark mean($tv)

using Test

@test 1 == 1

@testset "simple math" begin
    @test 1 == 1
    @test 1 != 2
end

struct SimpleCession # a cession object 
    face_ceded # the amount of face ceded
end

struct SimplePolicy # a simple policy object
    face # the face amount
    issue_age # the issue age
    cessions # an array of cessions
end

cessions = [SimpleCession(2.5e5),SimpleCession(2.5e5)] # two 250k cessions

pol1 = SimplePolicy(2e6,55,cessions)  # a 2m policy

#the amount that pol1 has ceded to other companies
sum(cess.face_ceded for cess in pol1.cessions)

function retained(pol::SimplePolicy)
   return pol.face - sum(cess.face_ceded for cess in pol.cessions)
end

retained(pol1)

abstract type Cession end # create the 'idea' or abstract reprsentation of a Cession

# another type of cession object 
struct Ceded <: Cession # a cession object 
    face # the amount of face ceded
end

# another type of cession object 
struct Assumed <: Cession 
    face # the amount of face assumed
end

struct Policy # a simple policy object
    face # the face amount
    issue_age # the age
    cessions # an array of cessions
end

struct Life # represents a person
    policies
end

function retained(cess::Ceded)
    return -cess.face
end

function retained(cess::Assumed)
    return cess.face
end

function retained(pol::Policy)
    return pol.face - sum(cess.face for (treaty, cess) in pol.cessions) #same as before
end

function retained(l::Life)
    return sum(retained(pol) for (id, pol) in l.policies)
end

# two 1m cessions and a 500k assumed cession
cessions1 = Dict(
    "REINS2019" => Ceded(1e6),
    "REINS2018" => Ceded(1e6), 
    "ASSUMED2015" => Assumed(5e5)
    ) 

# one 3m cession
cessions2 = Dict("REINS2019" => Ceded(3e6)) 

# one 5m policy and one 10m policy
policies = Dict( 
    "1" => Policy(5e6,30,cessions1),
    "2" => Policy(10e6,30,cessions2)
    )

# one life with the two policies
alice = Life(policies)

# how much does Alice have retained?
retained(alice) 

# how much does each policy have retained? 
Dict(pol_id => retained(pol) for (pol_id, pol) in alice.policies)

# how much have we ceded to reinsurer "REINS2019" ?

ceded = 0.0
for (p_id, pol) in alice.policies
    for (c_id, cess) in pol.cessions
        if c_id == "REINS2019"
            ceded += cess.face
        end
    end
end

ceded

function get_cession_count(l::Life)
    total = 0
    for (id,pol) in l.policies
        for (id,cess) in pol.cession # this will error because it should be `cessions` (plural)
            total += 1
        end
    end
    return total
end

get_cession_count(alice)

?mean