Quiffen - A Python library to read/write Quicken Interchange Format files

Quiffen is a Python package for parsing QIF (Quicken Interchange Format) files.

The package allows users to both read QIF files and interact with the contents, and also to create a QIF structure and then output to either a QIF file, a CSV of transaction data or a pandas DataFrame.

QIF is an old file type, but has its merits because:

  • It’s standardised (apart from dates, but that can be dealt with)

    • Unlike CSVs, QIF files all follow the same format, so they don’t require special attention when they come from different sources

  • It’s written in plain text

Features

  • Import QIF files and manipulate data

  • Create QIF structures (support for Transactions, Investments, Accounts, Categories, Classes, Splits)

  • Convert Qif objects to a number of different formats and export (pandas DataFrame, CSV, QIF file)

Usage

Here’s an example parsing of a QIF file:

>>> from quiffen import Qif
>>> import decimal
>>> qif = Qif.parse('test.qif', day_first=False)
>>> qif.accounts
{'Quiffen Default Account': Account(name='Quiffen Default Account', desc='The default account created by Quiffen when no
other accounts were present')}
>>> acc = qif.accounts['Quiffen Default Account']
>>> acc.transactions
{'Bank': TransactionList(Transaction(date=datetime.datetime(2021, 2, 14, 0 , 0), amount=decimal.Decimal(150.0), ...), ...),
'Invst': TransactionList(...)}
>>> tr = acc.transactions['Bank'][0]
>>> print(tr)
Transaction:
    Date: 2020-02-14 00:00:00
    Amount: 67.5
    Payee: T-Mobile
    Category: Cell Phone
    Split Categories: ['Bills']
    Splits: 2 total split(s)
>>> qif.categories
{'Bills': Category(name='Bills), expense=True, hierarchy='Bills'}
>>> bills = qif.categories['Bills']
>>> print(bills.render_tree())
Bills (root)
└─ Cell Phone
>>> df = qif.to_dataframe(data='transactions')
>>> df.head()
        date  amount           payee  ...                           memo cleared check_number
0 2020-02-14    67.5        T-Mobile  ...                            NaN     NaN          NaN
1 2020-02-14    32.0  US Post Office  ...  money back for damaged parcel     NaN          NaN
2 2020-12-02   -10.0          Target  ...        two transactions, equal     NaN          NaN
3 2020-11-02   -25.0         Walmart  ...          non split transaction       X        123.0
4 2020-10-02  -100.0      Amazon.com  ...                   test order 1       *          NaN
...

And here’s an example of creating a QIF structure and exporting to a QIF file:

>>> import quiffen
>>> from datetime import datetime
>>> qif = quiffen.Qif()
>>> acc = quiffen.Account('Personal Bank Account', desc='My personal bank account with Barclays.')
>>> qif.add_account(acc)
>>> groceries = quiffen.Category('Groceries')
>>> essentials = quiffen.Category('Essentials')
>>> groceries.add_child(essentials)
>>> qif.add_category(groceries)
>>> tr = quiffen.Transaction(date=datetime.now(), amount=150.0)
>>> acc.add_transaction(tr, header='Bank')
>>> qif.to_qif()  # If a path is provided, this will save the file too!
'!Type:Cat\nNGroceries\nETrue\nIFalse\n^\nNGroceries:Essentials\nETrue\nIFalse\n^\n!Account\nNPersonal Bank Account\nDMy
personal bank account with Barclays.\n^\n!Type:Bank\nD02/07/2021\nT150.0\n^\n'

Documentation

Documentation can be found at: https://quiffen.readthedocs.io/en/latest/

Installation

Install Quiffen by running:

>>> pip install quiffen

Dependencies

  • pandas (optional) for exporting to DataFrames

    • The to_dataframe() method will not work without pandas installed.

To-Dos

  • Add support for the MemorizedTransaction object present in QIF files.

Contribute

GitHub pull requests welcome, though if you want to make a major change, please open an issue first for discussion.

Support

If you are having issues, please let me know.

License

The project is licensed under the GNU GPLv3 license.

Full API:

Indices and tables