Daily Spent(DS) is an open source software project that intends to be a simple way on counting daily spent, showing statistics, graphs, many consult options, categorization(labels), payment modes etc, with a simple web-based user interface.

The Daily Spent has an important difference characteristics from other projects: it focus only on user daily spent(all things we pay per day, like food, gifts, gas and other stuffs) and has only the minimal elements for this propose, like an simple web-based interface with users login, labels for spent and payment modes. This method bring to us a more accurate view from our spent, since we write down all things we pay, even the schedule spent. We can think on Daily Spent as a PSP(Personal Software Process) software for spent/money.

Some screenshots

Here are some screenshots detailing some Daily Spent features.

ds main page

At point 1 we can see the spent's list with the ultimate inserted spent. Note that the amount of spent items at first page can be customized. At point 2 we have a column with some kind of spent category. Point 3 show us the spent payment modes, like money, credit card, and so on.

The point 4 shows a simple menu. Through this menu we can do actions like insert spent, search for spent using a customized filter, or see the statistics for the current spent list in the screen(see the next screenshot). This menu is followed by a search field, that is a shortcut for searching spent. At point 5 we have a more elaborated menu. With that we can customize our user account or generate some backup data(database dump, CSV export/import).

ds statistics page

The statistics result is generated according to category items and payment items and the total amount of spent.

Technical aspects

The Daily Spent software is build using free/open source software. More specifically, DS uses Python as programming language, SQLAlchemy to object/relational mapping, Cherrypy to serves the web application and Cheetah as template engine. The database software, to organize the data, can any of then supported by SQLAlchemy (see the list).