There have been a few discussions on IRC recently about how to scale Ledger operations, so I thought I'd start a thread here.
When I refer to scaling, I'm not only referring to increasing number of transactions and accounts, but increasing complexity. Please forgive me if this seems to ramble, or gets too detailed about my processes. My goal is to be verbose so the Ledger community can collectively grasp the problems I've encountered scaling up, and together find appropriate solutions that apply to everyone. I'd rather not reinvent the wheel or create a custom solution that only fits me, I do that enough as it is. As my Ledger solution has grown organically over four years, it's grown unwieldy. I have found myself unable to train and hand over maintenance and data entry of my Ledger data to others which is a huge bottleneck for my business. I had recently considered re-implementing my expense reporting processes as a dedicated internal application using Python/Tk (Tkinter) and PostgreSQL via SqlAlchemy. I do prefer Ledger, and would share my UI work there if we can together help address some of the following issues that have come up as my Ledger use has grown. Though the topic is broad, I've narrowed down some specific items and I am posting them as separate threads to try and make discussion easier on the ML with threading mail readers. I hope to generate constructive feedback and discussion on the ML, much like what happened on IRC. Thanks. ------------------------------------------------------------------ Russell Adams [email protected] PGP Key ID: 0x1160DCB3 http://www.adamsinfoserv.com/ Fingerprint: 1723 D8CA 4280 1EC9 557F 66E8 1154 E018 1160 DCB3
