More Tinkering With PyTracery

Having started to look at using pytracery for data2text transforms with pandas dataframes, I’ve been pondering how to do computational things with it, such as counts, conditional tests, and loops.

Here’s where I’m at – defining counters, a branch / conditional statement, and a conditional loop:

def inc(text, *params):
    return str(int(text)+1)

def dec(text, *params):
    return str(int(text)-1)

def branch(text, *params):
    if text==params[0].strip(): 
        ans = params[1].strip()
    else:
        ans = params[2].strip()
    return '[answer:#{}#]'.format(ans)

def whileNot0(text, *params):
    if int(text) > 0:
        return '[i:{i}]'.format(i=str(int(text)-1))
    return '[do:#{}#]'.format(params[0].strip())

pytracery_logic = {
    'inc': inc,
    'dec': dec,
    'branch':branch,
    'whileNot0': whileNot0
}

Count example:

rules = {'origin': 'Count demo - #countdemo#',
         'countdemo':'Count at [cnt:#initval#]#cnt#.\n#addone#, #addanother#, #takeone#',
         'addone': 'Add one gives [cnt:#cnt.inc#]#cnt#',
         'addanother': 'add another one gives [cnt:#cnt.inc#]#cnt#',
         'takeone':'take one gives [cnt:#cnt.dec#]#cnt.int_to_words#',
}

grammar = tracery.Grammar(rules)
grammar.add_modifiers(pytracery_logic)
grammar.add_modifiers(inflect_english)

print(grammar.flatten('[initval:1]#origin#'))
> Count demo - Count at 1.
> Add one gives 2, add another one gives 3, take one gives two

Logical test:

rules={'origin':'Logical test:[branch:#condition#]#branch# Testing #value# gives: #answer#',
       'condition': '#value.branch(VeryTrue, answer1, answer2)#',
    'answer1':'This is true...',
    'answer2':'This is false...',
    'answer3':'nope',
    'answer':'answer3'
}

grammar = tracery.Grammar(rules)
grammar.add_modifiers(pytracery_logic)

print(grammar.flatten("[value:VeryTrue]#origin#"))
> Logical test: Testing VeryTrue gives: This is true...

print(grammar.flatten("[value:notTrue]#origin#"))
> Logical test: Testing notTrue gives: This is false...

Loop test:

rules = {'origin': 'Loop test: \n#loop#',
         'loop':'[while:#i.whileNot0(end)#]#while##do#',
         'do':'#action##loop#',
         'action':'- count is at #i#\n',
         'end':'All done'
        }

grammar = tracery.Grammar(rules)
grammar.add_modifiers(pytracery_logic)
print(grammar.flatten("[i:6]#origin#"))
> Loop test: 
> - count is at 5
> - count is at 4
> - count is at 3
> - count is at 2
> - count is at 1
> - count is at 0
> All done

I’m a bit out of the way of declarative thinking (which pytracery relies on) atm, so there may be more native /idiomatic ways of doing this sort of stuff in pytracery.

I’m also a bit rusty on assembler / machine code programming, so there may be better ways of phrasing basic computational operations using pytracery using those sorts of operators.

Next step is to see whether I can start to use these reasoning steps in association with data pulled from a pandas dataframe.