# downloads history from 2014 - today
history <- updateHistory()

# update history
history <- updateHistory(history)

# saves the history (default "history.csv")
saveHistory(history, "history.csv")

# returns latest history (default "history.csv")
history <- getLatestHistory()

# Must provide a WEEKS_ID. 
# Log in to contest and check the provided by `Export to CSV`
# (e.g. Download URL: https://www.draftkings.com/lineup/getavailableplayerscsv?contestTypeId=21&draftGroupId=21720)

WEEKS_ID = 21720

# Get latest available for weeks_id 21720
available <- getLatestAvailable(21720)

# Since your model would likely be trained on historic format, you want to convert available to historic format
availableHistory <- availableToHistory(available, 3, 2018)

# Historic format has "first last" name convention and lower-case 3 letter team abbreviations as defined by mappings.R

# Solves for optimal selection based on $prediction. Must have $prediction, $pos and $salary
# Assumes 1 qb, 2 rb, 3 wr, 1 te, 1 def and 1 flex

# Make some predictions about score for this week
availableHistory$prediction <- availableHistory$salary / 500.0 + 10.0

# Solve
results <- solve(availableHistory, budget=50000)

source("history.R")
source("solve.R")
source("available.R")

WEEKS_ID <- 21720

h <- getLatestHistory()
a <- getLatestAvailable(WEEKS_ID)
ah <- availableToHistory(a, 3, 2018)
ah$prediction <- ah$salary / 500.0 + 10
sol <- solve(ah)