hledger/hledger-lib/hledger_csv.m4.md

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author	monthyear	hledger_csv(5) hledger version

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NAME

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

DESCRIPTION

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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 (transactions) 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’s often necessary to specify the date format, and the number of header lines to skip, also. Eg:

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

More examples in the EXAMPLES section below.

CSV RULES

The following kinds of rule can appear in the rules file, in any order (except for end which can appear only inside a conditional block). Blank lines and lines beginning with # or ; are ignored.

skip

skip N

The word “skip” followed by a number (or no number, meaning 1) tells hledger to ignore this many non-empty lines preceding the CSV data. (Empty/blank lines are skipped automatically.) You’ll need this whenever your CSV data contains header lines.

It also has a second purpose: it can be used to ignore certain CSV records, see conditional blocks below.

fields

fields FIELDNAME1, FIELDNAME2, ...

A fields list (“fields” followed by one or more comma-separated field names) is the quick way to assign CSV field values to hledger fields. It (a) names the CSV fields, in order (names may not contain whitespace; fields you don’t care about can be left unnamed), and (b) assigns them to hledger fields if you use standard hledger field names. Here’s an example:

# use the 1st, 2nd and 4th CSV fields as the transaction's date, description and amount,
# ignore the 3rd, 5th and 6th fields,
# and name the 7th and 8th fields for later reference:
#      1     2           3  4       5 6  7          8

fields date, description, , amount1, , , somefield, anotherfield

Here are the standard hledger field names:

Transaction fields

date, date2, status, code, description, comment can be used to form the transaction’s first line. Only date is required. (See also date-format below.)

Posting fields

accountN, where N is 1 to 9, sets the Nth posting’s account name. Most often there are two postings, so you’ll want to set account1 and account2.

A number of field/pseudo-field names are available for setting posting amounts:

• amountN sets posting N’s amount
• amountN-in and amountN-out can be used instead, if the CSV has separate fields for debits and credits
• currencyN sets a currency symbol to be left-prefixed to the amount, useful if the CSV provides that as a separate field
• balanceN sets a (separate) balance assertion amount (or when no posting amount is set, a balance assignment)

If you write these with no number (amount, amount-in, amount-out, currency, balance), it means posting 1. Also, if you set an amount for posting 1 only, a second posting that balances the transaction will be generated automatically. This helps support CSV rules created before hledger 1.16.

Finally, commentN sets a comment on the Nth posting. Comments can of course contain tags.

(field assignment)

HLEDGERFIELDNAME FIELDVALUE

Instead of or in addition to a fields list, you can assign a value to a hledger field by writing its name (any of the standard names above) followed by a text value. The value may contain interpolated CSV fields (only), referenced by their 1-based position in the CSV record (%N), or by the name they were given in the fields list (%CSVFIELDNAME). Eg:

# set the amount to the 4th CSV field, with " USD" appended
amount %4 USD

# combine three fields to make a comment, containing note: and date: tags
comment note: %somefield - %anotherfield, date: %1

Interpolation strips any outer whitespace, so a CSV value like " 1 " becomes 1 when interpolated (#1051).

date-format

date-format DATEFMT

This is a helper for the date (and date2) fields. If your CSV dates are not formatted like YYYY-MM-DD, YYYY/MM/DD or YYYY.MM.DD, you’ll need to specify the format by writing “date-format” followed by a strptime-like date parsing pattern, which must parse the date field values completely. Examples:

# for dates like "11/06/2013":
date-format %m/%d/%Y

# for dates like "6/11/2013". The - allows leading zeros to be optional.
date-format %-d/%-m/%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

if

if PATTERN
 RULE

if
PATTERN
PATTERN
PATTERN
 RULE
 RULE

Conditional blocks apply one or more rules to CSV records which are matched by any of the PATTERNs. This allows transactions to be customised or categorised based on patterns in the data.

A single pattern can be written on the same line as the “if”; or multiple patterns can be written on the following lines, non-indented.

Patterns are case-insensitive regular expressions which try to match any part of the whole CSV record. It’s not yet possible to match within a specific field. Note the CSV record they see is close but not identical to the one in the CSV file; eg double quotes are removed, and the separator character becomes comma.

After the patterns, there should be one or more rules to apply, all indented by at least one space. Three kinds of rule are allowed in conditional blocks:

• field assignments (to set a field’s value)
• skip (to skip the matched CSV record)
• end (to skip all remaining CSV records).

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
if
monthly service fee
atm transaction fee
banking thru software
 account2 expenses:business:banking
 comment  XXX deductible ? check it

end

As mentioned above, this rule can be used inside conditional blocks (only) to cause hledger to stop reading CSV records and proceed with command execution. Eg:

# ignore everything following the first empty record
if ,,,,
 end

include

include RULESFILE

Include another CSV rules file at this point, as if it were written inline. RULESFILE is an absolute file path or a path relative to the current file’s directory.

This can be useful eg for reusing common rules in several rules files:

# someaccount.csv.rules

## someaccount-specific rules
fields date,description,amount
account1 some:account
account2 some:misc

## common rules
include categorisation.rules

newest-first

hledger always sorts the generated transactions by date. Transactions on the same date should appear in the same order as their CSV records, as hledger can usually auto-detect whether the CSV’s normal order is oldest first or newest first. But if all of the following are true:

• the CSV might sometimes contain just one day of data (all records having the same date)
• the CSV records are normally in reverse chronological order (newest first)
• and you care about preserving the order of same-day transactions

you should add the newest-first rule as a hint. Eg:

# tell hledger explicitly that the CSV is normally newest-first
newest-first

EXAMPLES

A more complete example, generating three-posting transactions:

# 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, amount1, 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

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

# flip the sign on the amount
amount      -%amount

# Put fees in a separate posting
amount3     %fees
comment3    fees

For more examples, see Convert CSV files.

TIPS

Reading multiple CSV files

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

Deduplicating, importing

When you download a CSV file repeatedly, eg to get your latest bank transactions, the new file may contain some of the same records as the old one. The print –new command is one simple way to detect just the new transactions. Or better still, the import command appends those new transactions to your main journal. This is the easiest way to import CSV data. Eg, after downloading your latest CSV files:

$ hledger import *.csv [--dry]

Other import methods

A number of other tools and workflows, hledger-specific and otherwise, exist for converting, deduplicating, classifying and managing CSV data. See:

• https://hledger.org -> sidebar -> real world setups
• https://plaintextaccounting.org -> data import/conversion

Valid CSV

hledger accepts CSV conforming to RFC 4180. Some things to note when values are enclosed in quotes:

• you must use double quotes (not single quotes)
• spaces outside the quotes are not allowed

Other separator characters

With the --separator 'CHAR' option, hledger will expect the separator to be CHAR instead of a comma. Ie it will read other “Character Separated Values” formats, such as TSV (Tab Separated Values). Note: on the command line, use a real tab character in quotes, not Eg:

$ hledger -f foo.tsv --separator '	' print

(Experimental.)

Setting amounts

A posting amount can be set in one of these ways:

• by assigning (with a fields list or field assigment) to amountN (posting N’s amount) or amount (posting 1’s amount)

• by assigning to amountN-in and amountN-out (or amount-in and amount-out). For each CSV record, whichever of these has a non-zero value will be used, with appropriate sign. If both contain a non-zero value, this may not work.

• by assigning to balanceN (or balance) instead of the above, setting the amount indirectly via a balance assignment.

There is some special handling for an amount’s sign:

• 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 cancel out and are removed.
• If an amount value begins with a plus sign, that will be removed

If the currency/commodity symbol is provided as a separate CSV field, you can assign it to currency (affects all posting amounts) or currencyN (affects just posting N’s amount). The symbol will be prepended to the amount. Or for more control, you can set both currency symbol and amount with a field assignment, eg:

fields date,description,currency,amount
# add currency symbol on the right:
amount %amount %currency

Referencing other fields

In field assignments, you can interpolate only CSV fields, not hledger fields. In the example below, there’s both a CSV field and a hledger field named amount1, but %amount1 always means the CSV field, not the hledger field:

# Name the third CSV field "amount1"
fields date,description,amount1

# Set hledger's amount1 to the CSV amount1 field followed by USD
amount1 %amount1 USD

# Set comment to the CSV amount1 (not the amount1 assigned above)
comment %amount1

Here, since there’s no CSV amount1 field, %amount1 will produce a literal “amount1”:

fields date,description,csvamount
amount1 %csvamount USD
# Can't interpolate amount1 here
comment %amount1

When there are multiple field assignments to the same hledger field, only the last one takes effect. Here, comment’s value will be be B, or C if “something” is matched, but never A:

comment A
comment B
if something
 comment C

How CSV rules are evaluated

Here’s how to think of CSV rules being evaluated (if you really need to). First,

• include - all includes are inlined, from top to bottom, depth first. (At each include point the file is inlined and scanned for further includes, recursively, before proceeding.)

Then “global” rules are evaluated, top to bottom. If a rule is repeated, the last one wins:

• skip (at top level)
• date-format
• newest-first
• fields - names the CSV fields, optionally sets up initial assignments to hledger fields

Then for each CSV record in turn:

• test all if blocks. If any of them contain a end rule, skip all remaining CSV records. Otherwise if any of them contain a skip rule, skip that many CSV records. If there are multiple matched skip rules, the first one wins.
• collect all field assignments at top level and in matched if blocks. When there are multiple assignments for a field, keep only the last one.
• compute a value for each hledger field - either the one that was assigned to it (and interpolate the %CSVFIELDNAME references), or a default
• generate a synthetic hledger transaction from these values.

This is all part of the CSV reader, one of several readers hledger can use to parse input files. When all files have been read successfully, the transactions are passed as input to whichever hledger command the user specified.

Valid transactions

hledger currently does not post-process and validate transactions generated from CSV as thoroughly as transactions read from a journal file. This means that if your rules are wrong, you can generate invalid transactions. Or, amounts may not be displayed with a canonical display style.

So when setting up or adjusting CSV rules, you should check your results visually with the print command. You can also pipe the output through hledger once more to fully validate and canonicalise it:

$ hledger -f some.csv print | hledger -f- print -I

(The -I/–ignore-assertions flag disables balance assertion checks, usually needed when re-parsing print output.)