I've tried to track personal finances several times, but it only started to work when I've discovered the idea (from
https://github.com/adept/full-fledged-hledger) that you need to treat the whole PTA story more like a project compilation:
- Everything is managed by build system that is able to track dependencies
- Inputs from financial institutions are kept in the repo as is
- Those inputs are converted by your scripts to .csv files that are readable by PTA import engine
- There are rules files that describe how to convert .csv lines to PTA entries
- Generated files are included from per-year PTA journals (and you can put any manual transactions in here also)
The benefit is that you can change any part of this pipeline, and just re-generate the changed parts:
- improve the program that converts to .csv - raw data immediately gets better across the whole repo
- add/customize import rules - better classification is immediately applied to all of the past data
And with this approach you can start small (like, a single month of data from your primary bank), and refine the thing in steps, like adding more historical data or adding more data sources (examples being not only bank statements, but even things like itemized Amazon orders and Paypal slips).
- Everything is managed by build system that is able to track dependencies
- Inputs from financial institutions are kept in the repo as is
- Those inputs are converted by your scripts to .csv files that are readable by PTA import engine
- There are rules files that describe how to convert .csv lines to PTA entries
- Generated files are included from per-year PTA journals (and you can put any manual transactions in here also)
The benefit is that you can change any part of this pipeline, and just re-generate the changed parts:
- improve the program that converts to .csv - raw data immediately gets better across the whole repo
- add/customize import rules - better classification is immediately applied to all of the past data
And with this approach you can start small (like, a single month of data from your primary bank), and refine the thing in steps, like adding more historical data or adding more data sources (examples being not only bank statements, but even things like itemized Amazon orders and Paypal slips).