Python terminal application for tracking expenses and providing analytics with an emphasis on extensibility, usability, future proof-ness, simplicity, and user control. PR's encouraged to support more accounts, see below.

Commercial expense trackers have their limitations, such as:

• Unable to map and categorize expenses sourced in outside accounts. For example, Amazon purchases are often grouped and just appear as "AMZN MKTP XXXX-XXXXX-XXXX" on your Credit Card. Was that purchase Electronics/Clothing/Groceries? Was it a single or multiple items? Finding out involves much manual work...
• Unable to use powerful Regular Expressions to auto-categorize transactions using user defined patterns.
• Sharing finances with 3rd party who may not have strong privacy protections.
• Getting locked to one particular vendor. Hard to switch and keep your data.
• Paid

This application offers an intuitive terminal user interface that allows for fast categorization and analytics of all your expenses, without any of these limitations.

• Amazon (Purchases & Refunds)
• Citi Double Cash Card
• Citi Custom Cash Card
• Chase Freedom Unlimited Card
• Chase Debit Card
• American Express Blue Cash Preferred Card

To support more accounts, please submit a PR with these changes:

1. Add the account name and columns of the raw downloaded csv to spending_tracker/config.yml
2. Add method with the same name in spending_tracker/engines/raw_data_processing_engine.py for that account.

Python >=3.11 required.

1. Clone repo.
2. Create and activate virtual environment python3 -m venv .spending_tracker, . ./.spending_tracker/bin/activate.
3. pip3 install -r requirements.txt
4. Create directory for your raw data files: mkdir -p <path>/spending_tracker_data/raw
5. Run export SPENDING_TRACKER_DATA_PATH=<path>/spending_tracker_data or add to profile.
6. Download CSV's for your accounts into the raw folder. CSV's should be named with this format: YYYY-MM-DD_to_YYYY-MM-DD*<account_name>*.csv. For example 2022-09-01_to_2022-12-31_citi_double_cash_2022_1_lastyear2022.csv. The citi_double_cash_2022_1 is the account name as specified in spending_tracker/config.yaml. As long as the institution doesn't change their csv export format from 2022 onwards, it should keep working.
7. Run python3 -m spending_tracker.main

Once done, a new file, <path>/data/categorized_transactions.csv will store your categorized transactions. The next time you run the app with new files in the raw folder, it will remember and apply all the Regular Expression patterns created in previous runs on the new transactions (of course, you can override these auto-categorizations).