The Null category represent transactions performed between banks/credit cards, that would otherwise appear in the reports and graph. This way, these transactions, while real, are shadowed from the information presented. The net effect of these transaction, if performed in the same month would be moot anyway, since they cancel each other, but could introduce visual pollution when separated for a few days, especial when spawning through different months. The Null category then present a placeholder category for these transactions, as well as a way to preserve them out of side. ToDo: As a side bonus, whenever these don't cancel eachother, a warning could be shown.

The 2 reserved groups are income and investment. The income is used for all income categories. These are the ones that will have a net effect on the overall balance of the individual, and are normally expected to be shown against expenses. The investment group is separated from the remaining expenses, has these might not only present in absolute terms much higher values than other categories, but will also be subject to a different treatment when market predictions are incorporated.

Analyze (ToDo)

Analyzes previous transaction and predicts future expenses.

Present

Create graphs and reports

Monthly spending from everyday purchases
Networth with big expenses tagged in (ToDo)
Future trajectory with predictable costs included (ToDo)

ToDo

Support regular transactions from fixed group in categories
Add one table for user inputed transactions and other for fixes
Predicting future expenses
Finish writing the README.md
Implement undo/redo feature in sqlite3 database
Allow for the possibility to create a new parser during runtime by guessing from transaction list/user input
Allow for transaction to be passed as argument to main.py