As per last week’s plan, further down in this posting is the current version of my R code to generate random hledger transactions. The program uses the function create_random_transactions to, well, generate the random transactions. If you supply no arguments, as in create_random_transactions(), the program will give you 20 transactions from random dates that fall in the last 6 months.
If you prefer a different number of transactions, you can specify the number as the first argument. For example, to create 3 random dates, run create_random_transactions(3). When I ran this in early February of 2024, I got the following output:
2023-11-17 Mom&Pop
expenses:home $16.36
liabilities:Universal Credit Card -$16.36
2023-12-05 Mom&Pop
expenses:automotive $13.34
assets:cash -$13.34
2024-01-17 Convenience
expenses:home $18.99
assets:cash -$18.99 Additionally, you can choose a beginning date instead of the default one of 6 months prior to today’s date. For example: create_random_transactions(3, as.Date(“2024-01-01”)) gives us 3 transactions dated between the first of the year and today’s date (in my case, a date in early February, when I ran the above command):
2024-01-20 BigStore
expenses:groceries $13.21
assets:cash -$13.21
2024-01-16 Sales-R-Us
expenses:automotive $7.80
assets:cash -$7.80
2024-01-12 Convenience
expenses:groceries $22.77
liabilities:Universal Credit Card -$22.77
Finally, if you need to adjust the end date, you can do so by specifying it as a third argument. For example, to create 3 random transactions in 2023, we could call create_random_transactions(3, as.Date(“2023-01-01”), as.Date(“2023-12-31”)). Output is shown below:
2023-03-04 BigStore
expenses:groceries $22.24
liabilities:Universal Credit Card -$22.24
2023-11-20 Sales-R-Us
expenses:automotive $15.12
liabilities:Universal Credit Card -$15.12
2023-06-25 Acme
expenses:automotive $17.24
liabilities:Universal Credit Card -$17.24
And here is the full R code needed for the above to work. You can easily modify the program to change the payees, expense categories, and payment categories.
It still needs some more work, as when I copy and paste the output from the R console, the line returns get changed to a single character “^M.” I had to replace all the ^Ms with an actual return so that the text appeared in proper ledger/hledger format.
However, I can now very quickly generate example transactions to use when needed for educational videos or anything else.
payees <- list("BigStore", "Acme", "Sales-R-Us", "Mom&Pop", "Convenience")
expense_categories <- list("expenses:gas", "expenses:groceries", "expenses:entertainment", "expenses:home", "expenses:automotive")
payment_categories <- list("assets:checking", "liabilities:Universal Credit Card", "assets:cash")
create_random_transactions <- function(number_of_transactions=NULL, earliest_date=NULL, latest_date=NULL) {
if(missing(number_of_transactions)) number_of_transactions <- 20
if(missing(earliest_date)) earliest_date <- Sys.Date() - 180
if(missing(latest_date)) latest_date <- Sys.Date()
for (i in 1:number_of_transactions) {
transaction_date <- get_a_date(earliest_date, latest_date)
transaction_payee <- get_a_payee()
transaction_expense_category <- get_an_expense_category()
transaction_payment_category <- get_a_payment_category()
width_expense_category <- nchar(transaction_expense_category)
width_payment_category <- nchar(transaction_payment_category)
width_difference <- width_expense_category - width_payment_category
if(width_difference > 0) {
pad_payment_string <- strrep(" ", width_difference)
pad_expense_string <- " "
}
else {
pad_expense_string <- strrep(" ", ((width_difference) * -1) + 1)
pad_payment_string <- ""
}
expense_amount <- get_an_amount()
negative_amount <- paste0("-", expense_amount)
one_transaction <- paste(transaction_date, transaction_payee, "\n ",
transaction_expense_category, pad_expense_string, expense_amount, "\n ",
transaction_payment_category, pad_payment_string, negative_amount, "\n\n"
)
cat(one_transaction)
}
}
get_a_date <- function(start_date, end_date) {
days_diff <- end_date - start_date
date_range <- 0:days_diff
random_date <- sample(date_range, 1)
new_date <- start_date + random_date
return(new_date)
}
get_a_payee <- function() {
random_payee <- sample(1:length(payees), 1)
return(payees[random_payee])
}
get_an_expense_category <- function(){
random_expense_category <- sample(1:length(expense_categories), 1)
return(expense_categories[random_expense_category])
}
get_an_amount <- function() {
dollars <- sample(5:24, 1)
cents <- sample(0:99, 1)
cents <- sprintf("%02d", cents)
amount_string <- paste0("$", dollars, ".", cents)
return(amount_string)
}
get_a_payment_category <- function() {
random_payment_category <- sample(1:length(payment_categories), 1)
return(payment_categories[random_payment_category])
}