2.6 KiB
2.6 KiB
Generate a roll table using weighted distributions of random options.
Given source.yaml containing options such as:
option1:
- key1: description
- key2: description
...
...
Generate a random table:
>>> print(RollTable(path='source.yaml'))
d1 option6 key3 description
d2 option2 key2 description
d3 option3 key4 description
...
You can customize the frequency distribution, headers, and table size by
defining metadata in your source file.
Using Metadata:
By default options are given uniform distribution and random keys will be
selected from each option with equal probability. This behaviour can be
changed by adding an optional metadata section to the source file:
metadata:
frequenceis:
default:
option1: 0.5
option2: 0.1
option3: 0.3
option4: 0.1
This will guarantee that random keys from option1 are selected 50% of the
time, from option 2 10% of the time, and so forth. Frequencies should add
up to 1.0.
If the metadata section includes 'frequencies', The 'default' distribution
must be defined. Additional optional distributions may also be defined, if
you want to provide alternatives for specific use cases.
metadata:
frequenceis:
default:
option1: 0.5
option2: 0.1
option3: 0.3
option4: 0.1
inverted:
option1: 0.1
option2: 0.3
option3: 0.1
option4: 0.5
A specific frequency distribution can be specifed by passing the 'frequency'
parameter at instantiation:
>>> t = RollTable('source.yaml', frequency='inverted')
The metadata section can also override the default size of die to use for
the table (a d20). For example, this creates a 100-row table:
metadata:
die: 100
This too can be overridden at instantiation:
>>> t = RollTable('source.yaml', die=64)
Finally, headers for your table columns can also be defined in metadata:
metadata:
headers:
- Roll
- Frequency
- Description
- Effect
This will yield output similar to:
>>> print(RollTable(path='source.yaml'))
Roll Category Name Effect
d1 option6 key3 description
d2 option2 key2 description
d3 option3 key4 description
...