csv format

This doc is for version 1.9.1.


CSV - how hledger reads CSV data, and the CSV rules file format


hledger can read CSV (comma-separated value) files as if they were journal files, automatically converting each CSV record into a transaction. (To learn about writing CSV, see CSV output.)

Converting CSV to transactions requires some special conversion rules. These do several things:

  • they describe the layout and format of the CSV data
  • they can customize the generated journal entries using a simple templating language
  • they can add refinements based on patterns in the CSV data, eg categorizing transactions with more detailed account names.

When reading a CSV file named FILE.csv, hledger looks for a conversion rules file named FILE.csv.rules in the same directory. You can override this with the --rules-file option. If the rules file does not exist, hledger will auto-create one with some example rules, which you'll need to adjust.

At minimum, the rules file must identify the date and amount fields. It may also be necessary to specify the date format, and the number of header lines to skip. Eg:

fields date, _, _, amount
date-format  %d/%m/%Y
skip 1

A more complete example:

# hledger CSV rules for amazon.com order history

# sample:
# "Date","Type","To/From","Name","Status","Amount","Fees","Transaction ID"
# "Jul 29, 2012","Payment","To","Adapteva, Inc.","Completed","$25.00","$0.00","17LA58JSK6PRD4HDGLNJQPI1PB9N8DKPVHL"

# skip one header line
skip 1

# name the csv fields (and assign the transaction's date, amount and code)
fields date, _, toorfrom, name, amzstatus, amount, fees, code

# how to parse the date
date-format %b %-d, %Y

# combine two fields to make the description
description %toorfrom %name

# save these fields as tags
comment     status:%amzstatus, fees:%fees

# set the base account for all transactions
account1    assets:amazon

# flip the sign on the amount
amount      -%amount

For more examples, see Convert CSV files.


The following seven kinds of rule can appear in the rules file, in any order. Blank lines and lines beginning with # or ; are ignored.



Skip this number of CSV records at the beginning. You'll need this whenever your CSV data contains header lines. Eg:

# ignore the first CSV line
skip 1



When your CSV date fields are not formatted like YYYY/MM/DD (or YYYY-MM-DD or YYYY.MM.DD), you'll need to specify the format. DATEFMT is a strptime-like date parsing pattern, which must parse the date field values completely. Examples:

# for dates like "6/11/2013":
date-format %-d/%-m/%Y
# for dates like "11/06/2013":
date-format %m/%d/%Y
# for dates like "2013-Nov-06":
date-format %Y-%h-%d
# for dates like "11/6/2013 11:32 PM":
date-format %-m/%-d/%Y %l:%M %p

field list


This (a) names the CSV fields, in order (names may not contain whitespace; uninteresting names may be left blank), and (b) assigns them to journal entry fields if you use any of these standard field names: date, date2, status, code, description, comment, account1, account2, amount, amount-in, amount-out, currency, balance. Eg:

# use the 1st, 2nd and 4th CSV fields as the entry's date, description and amount,
# and give the 7th and 8th fields meaningful names for later reference:
# CSV field:
#      1     2            3 4       5 6 7          8
# entry field:
fields date, description, , amount, , , somefield, anotherfield

field assignment


This sets a journal entry field (one of the standard names above) to the given text value, which can include CSV field values interpolated by name (%CSVFIELDNAME) or 1-based position (%N).

# set the amount to the 4th CSV field with "USD " prepended
amount USD %4
# combine three fields to make a comment (containing two tags)
comment note: %somefield - %anotherfield, date: %1

Field assignments can be used instead of or in addition to a field list.

conditional block



This applies one or more field assignments, only to those CSV records matched by one of the PATTERNs. The patterns are case-insensitive regular expressions which match anywhere within the whole CSV record (it's not yet possible to match within a specific field). When there are multiple patterns they can be written on separate lines, unindented. The field assignments are on separate lines indented by at least one space. Examples:

# if the CSV record contains "groceries", set account2 to "expenses:groceries"
if groceries
 account2 expenses:groceries
# if the CSV record contains any of these patterns, set account2 and comment as shown
monthly service fee
atm transaction fee
banking thru software
 account2 expenses:business:banking
 comment  XXX deductible ? check it



Include another rules file at this point. RULESFILE is either an absolute file path or a path relative to the current file's directory. Eg:

# rules reused with several CSV files
include common.rules



Consider adding this rule if all of the following are true: you might be processing just one day of data, your CSV records are in reverse chronological order (newest first), and you care about preserving the order of same-day transactions. It usually isn't needed, because hledger autodetects the CSV order, but when all CSV records have the same date it will assume they are oldest first.


CSV ordering

The generated journal entries will be sorted by date. The order of same-day entries will be preserved (except in the special case where you might need newest-first, see above).

CSV accounts

Each journal entry will have two postings, to account1 and account2 respectively. It's not yet possible to generate entries with more than two postings. It's conventional and recommended to use account1 for the account whose CSV we are reading.

CSV amounts

The amount field sets the amount of the account1 posting.

If the CSV has debit/credit amounts in separate fields, assign to the amount-in and amount-out pseudo fields instead. (Whichever one has a value will be used, with appropriate sign. If both contain a value, it may not work so well.)

If an amount value is parenthesised, it will be de-parenthesised and sign-flipped.

If an amount value begins with a double minus sign, those will cancel out and be removed.

If the CSV has the currency symbol in a separate field, assign that to the currency pseudo field to have it prepended to the amount. Or, you can use a field assignment to amount that interpolates both CSV fields (giving more control, eg to put the currency symbol on the right).

CSV balance assertions

If the CSV includes a running balance, you can assign that to the balance pseudo field; whenever the running balance value is non-empty, it will be asserted as the balance after the account1 posting.

Reading multiple CSV files

You can read multiple CSV files at once using multiple -f arguments on the command line, and hledger will look for a correspondingly-named rules file for each. Note if you use the --rules-file option, this one rules file will be used for all the CSV files being read.