You Need A Budget has been my go-to budgeting software for a long time. The software and the philosophy behind it have been really helpful in helping me navigate times of tight finances.
I donāt have anything bad to say about YNAB, but Iāve found myself with some extra time and wanted to explore alternatives. Ledger has been on my list of things to try for a long time and I decided to take the plunge, though for some reason I ended up with hledger instead of the original implementation. I donāt have a great reason for this choice, and the two appear to be largely compatible with each other so I suppose it doesnāt matter much.
NOTE: Iāve been making this switch largely out of curiosity and am still not sure if Iāll stick with hledger over YNAB. Iām documenting this out for the benefit of anyone else in a similar situation considering making the switch- hopefully you can build upon my learnings.
This page is a work in progress- Iāll try to keep it updated as I either continue or stop myself from falling down this seemingly endless rabbit hole.
A few of the reasons ledger has interested me:
I found learning the basics of ledger to be relatively straightforward. The getting started guide on hledgerās website is very approachable and the user manual + cookbook page are pretty comprehensive for everything else I needed.
After a bit of fidgeting I ended up with the following directory/file structure.
ledger/
journals/
all.dat # This file includes all of the rest, and is where LEDGER_FILE points to
accounts.dat # Used to define accounts for strict mode
budgeting.dat # Transactions which modify my envelope budgets
markets.dat # Stores latest prices for commodities/currencies
checking.dat # The rest are for transactions associated with each account
credit_card.dat
savings.dat
investments.dat
scripts/
sync.py # Auto-imports transactions from Tiller and Venmo
check.py # Run sanity checks
markets.py # Syncs latest market prices
args/
budget.args # Displays current envelope budget balances
balance.args # Displays balances of all accounts
csvs/
default.csv.rules # This file is included by each of the .rules files below
checking.csv
checking.csv.rules
savings.csv
savings.csv.rules
credit_card.csv
credit_card.csv.rules
Notable amongst the journal/ directory is all.dat. This file doesnāt actually contain any transaction data, rather, it includes in each of its sibling files so that there is a singular path that the LEDGER_FILE env variable can point at which contains all of my transaction data. It looks something like this:
include accounts.dat
include budgeting.dat
include markets.dat
include checking.dat
...
accounts.dat is likely optional depending on whether or not you want to use hledgerās strict mode. tl;dr this mode will make it so you canāt create transactions for any accounts which havenāt been explicitly declared. I made the mistake of mispelling accounts multiple times and decided this was desirable, so this file contains stuff like:
commodity $
account assets:cash:checking
account liabilities:credit:credit_card
...
account budgets:live:rent
account budgets:live:groceries
...
HLedger has a lot of options. If you donāt want to mess around with them each time you need to know if you can buy a pair of socks or not, argument files help immensely in accessing presets that give you the reports you need quickly. I have two of these so far:
budget.args shows me the current status of my envelope budgets using the balance command:
balance
budgets:*
-s # Use strict mode
--tree # Display it as a tree
--cumulative # Show running total of budgets, not just this month's allocation
balance.args shows me the balance of all of my asset accounts (ie bank accounts) + liabilities (loans, credit cards, etc.):
balancesheet
-s # Strict mode
-V # Show everything in its current market value, in $
-5 # Limit the account tree depth to 5
-E # Show empty
--tree # Display it as a tree
assets:* # The accounts to display...
liabilities:*
Obviously a large draw to YNAB is their implementation of the envelope method of budgeting. I found this guide linked from the Cookbooks page of the hledger manual which detailed how to go about implementing envelopes using sub-accounts. After giving it a shot, I found a major issue with this method is that your budgets must be sub-accounts of a physical account (ie your checking account) and canāt be mixed among them. This means that if you were to have two checking accounts for spending, your budgets would have to be split amongst the two rather than having a pool of ācash to be allocatedā that can be put in whatever budgets youād like.
This may work for some people with a single bank account but for my particular setup I found it to be limiting. I ended up venturing into my own territory by using virtual postings for my envelope budgets. This setup more closely imitates YNAB by allowing budgets to have funding that spans multiple physical accounts.
To set it up, I first made a few transactions with assertions to place the amount of money I had available in cash into an unallocated budget. For this example weāll assume we have $1000 total across all of our physical accounts:
2022-02-01 * Initial budget transfer
assets:cash ==* $1000 ; Ensure we're correct in assuming we have $1000 available
(budgets:unallocated) $1000
[budgets] ==* $1000
Next weāll take the money in the unallocated budget and assign each dollar a job:
2022-02-01 * Budget allocations
[budgets:live:rent] $500.00
[budgets:live:utilities] $100.00
[budgets:live:groceries] $150.00
[budgets:fun:restaurants] $250.00
[budgets:unallocated]
Once weāve done that we can see the current value of our budgets:
$ hledger -f ./test.dat bal budgets --tree
$1000.00 budgets
$250.00 fun:restaurants
$750.00 live
$150.00 groceries
$500.00 rent
$100.00 utilities
--------------------
$1000.00
Whenever I make a purchase itāll look something like this
2022-02-01 * Some Vendor
expenses:fun:restaurants $10.00
assets:cash:checking -$10.00
(budgets:fun:restaurants) -$10.00
Note that the expenses:* sub accounts mirror the structure of the budget accounts exactly. This allows you to pretty easily see how much you have left and how much youāve spent from each budget:
$ hledger -f ./test.dat bal budgets --tree
$990.00 budgets
$240.00 fun:restaurants
$750.00 live
$150.00 groceries
$500.00 rent
$100.00 utilities
--------------------
$990.00
$ hledger -f ./test.dat bal expenses --tree
$10.00 expenses:fun:restaurants
--------------------
$10.00
The one catch to this method is that it is critically importand that the amount of cash you have in your physical accounts exactly matches the amount of cash you have allocated in your budgets. That is, the sum of cash:* must be equal to the sum of budgets:*. Iām still not exactly sure how to do this in Ledger. It seems like there should be a way to do a balance assertion across acounts but Iāve yet to figure it out. In the interim, Iāve added a simple function in my check.py script which ensures this is true each time I run it (usually after reconciling):
import subprocess
import pandas as pd
# This array is effectively same as YNAB's designation of an "on-budget"
# account.
BUDGETED_ACCOUNTS = [
'assets:cash:account1', 'assets:cash:account2', 'liabilities:credit:card',
]
print('--- Verifying budget totals ---')
# Fetch the amount of cash we have, stick it into a dataframe, and extract the
# total
cash = subprocess.check_output([
'hledger', 'bal', *BUDGETED_ACCOUNTS, '-O', 'csv',
]).decode('utf-8')
cash = pd\
.read_csv(io.StringIO(cash))\
.set_index('account')
cash_total = cash.iat[-1, 0].replace('$', '').replace(',', '')
# Same process but for the budget accounts
budgets = subprocess.check_output([
'hledger', 'bal', 'budgets:*', '-O', 'csv',
]).decode('utf-8')
budgets = pd\
.read_csv(io.StringIO(budgets))\
.set_index('account')
budget_total = budgets.iat[-1, 0].replace('$', '').replace(',', '')
# Verify that all looks good...
if budget_total == cash_total:
print('All good!')
else:
print('!! Budget total does not match cash total:')
print(f"\tACT: {cash_total}")
print(f"\tBUD: {budget_total}")
print(f"\t {round(float(cash_total) - float(budget_total), 2)}")The biggest hassle was setting up auto-importing from banks. This is a feature I really value from YNAB, as I donāt want to have to manually enter in transactions and I also donāt want to constantly be exporting CSVs from each financial accountās website in order to keep things up to date. I noticed that the library author had a page detailing his setup which mentions using Tiller for syncing. This seemed promising so I ended up going with that.
Tiller is a service that allows you to log into all of you bank accounts and automatically export the transaction data to a Google Sheet. This is great until you realize that Tiller has no API, so in order for the data to go from that Google Sheet to your Ledger database, youāll need to either export the sheet as a CSV or use the Google API. For the sake of automation, I opted for the latter, using the gsheets Python library to fetch the spreadsheet into a simple syncing script I wrote.
The code looks more or less like this:
import pandas as pd
import gspread
import os
# Only sync transactions that have occurred after the day we started ledger
# (ie set our initial balances)
INITIAL_LOAD_DATE = '2022-02-16'
# Tiller will likely use account names that you don't want to transfer into
# ledger. Correct for that here:
ACCOUNT_MAP = {
'Account ID in Tiller sheet': 'my_account_id',
}
# Generate some paths relative to our ledger root directory. Note that
# LEDGER_FILE points to a path within the journals/ directory
CSV_ROOT = os.path.join(os.path.dirname(os.environ['LEDGER_FILE']), '..', 'csvs')
JRN_ROOT = os.path.join(os.path.dirname(os.environ['LEDGER_FILE']), '..', 'journals')
# Fetch the current Tiller sheet and convert it to a pandas DataFrame (this
# is likely overkill but I'm more comfortable in pandas so I went with it)
gc = gspread.service_account()
sheet = gc.open('tiller')
worksheet = sheet.worksheet('Transactions')
df = pd.DataFrame(worksheet.get_all_records())
# Filter out any transactions that happened before our initial load date
df['Date'] = pd.to_datetime(df['Date'])
df = df.loc[df['Date'] >= pd.Timestamp(INITIAL_LOAD_DATE), :]
# Filter out any unwanted columns
df = df[['Date', 'Description', 'Amount', 'Account']]
# Loop through each account, saving its transactions into its own CSV file and
# then running hledger in order to display a preview of any new transactions
# that were found.
for account in df['Account'].unique():
print(f"---- {account} ----")
account_txns = df.loc[df['Account'] == account, :]
csv_path = os.path.join(CSV_ROOT, f"{ACCOUNT_MAP[account]}.csv")
print(f"Writing {len(df)} lines")
account_txns.to_csv(csv_path, index=False)
print('Preview of transactions to be imported:')
dat_path = os.path.join(JRN_ROOT, f"{ACCOUNT_MAP[account]}.dat")
subprocess.run([
'hledger', 'import', csv_path, '--dry-run', '-f', dat_path,
])After running this script each accountās CSVs will be populated with the latest transaction data. Assuming the import preview looks good, Iāll then runā¦
hledger import -f ./journals/[account].dat ./csvs/[account].csv
ā¦to import the transactions into the journal files then go in and manually edit any accounts/transaction descriptions as needed.
Once any manual touchups are done, Iāll run check.py to ensure all of the local account balances match up with the remote balances on Tiller. So far this has been a pretty reliable process, but weāll see how it fares as I encounter new financial situations.