Inputs and Outputs¶
With rare exception, all data handled by the system is processed functionally. That is, every operation applied to an input must create a new input, without exception. The program follows this principle for two reasons:
- branching. Since one input can produce multiple outputs, it’s easier to just create new outputs and ensure that no implicit information can be propagated.
- basic sanity. This makes the system easier to model mentally.
Terms¶
A rule accepts a list of terms as input and returns the same as output. A term is an arbitrary piece of sound and usually represents a morphere, but that’s not always the case.
In the Ashtadhyayi, these terms are usually called upadeśa, since
the grammar is taught (upadiśyate) by means of these terms, And in the
program, these terms are usually represented by instances of the
Upadesha class. These classes provide some nice
methods for accessing and modifying various parts of the term. For details,
see the documentation on the Upadesha class.
Data spaces¶
As mentioned earlier, terms in the Ashtadhyayi often contain multiple values at once. Within the program, these are modeled by data spaces, which make it easier to access and manipulate these values. These data spaces are basically just tuples; instead of containing a single data value, each term contains a variety of values that are valid simultaneously.
TODO