Quiffen
Project description
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, QifDataType >>> 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_type=QifDataType.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(name='Personal Bank Account', desc='My personal bank account with Barclays.') >>> qif.add_account(acc) >>> groceries = quiffen.Category(name='Groceries') >>> essentials = quiffen.Category(name='Essentials') >>> groceries.add_child(essentials) >>> qif.add_category(groceries) >>> tr = quiffen.Transaction(date=datetime.now(), amount=150.0) >>> acc.add_transaction(tr, header=quiffen.AccountType.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.
Issue Tracker: https://github.com/isaacharrisholt/quiffen/issues
Source Code: https://github.com/isaacharrisholt/quiffen
Support
If you are having issues, please let me know.
License
The project is licensed under the GNU GPLv3 license.
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