def index_names(record: Union[List, Dict]) -> Mentioned:
"""
Call all functions to prepare "mentioned" index.
The names are sorted by length so that if one mentioned Factor's name
is a substring of another, the longest available name is expanded.
:returns:
a modified version of the dict to load, plus a dict of names
and the objects to expand them with.
"""
obj = deepcopy(record)
obj = text_expansion.expand_shorthand(obj)
obj, mentioned = collect_mentioned(obj)
sorted_mentioned = mentioned.sorted_by_length()
return obj, sorted_mentioned
def test_mentioned_context_changing(self):
"""
The "mentioned" context should not change while data
is being loaded with the schema. This is to test
that the "content" field of a value in the "mentioned"
dict isn't changed to replace the name of a Factor
with bracketed text.
"""
holdings = [
{
"inputs": {
"type": "fact",
"content": "{Bradley} lived at Bradley's house",
},
"outputs": {
"type": "evidence",
"exhibit": {
"offered_by": {
"type": "entity",
"name": "the People"
}
},
"to_effect": {
"type": "fact",
"name": "fact that Bradley committed a crime",
"content": "Bradley committed a crime",
},
"name": "evidence of Bradley's guilt",
"absent": True,
},
},
{
"inputs": "fact that Bradley committed a crime",
"outputs": {
"type": "fact",
"content": "Bradley committed a tort"
},
},
]
expanded = text_expansion.expand_shorthand(holdings)
built = readers.read_holdings(expanded)
new_factor = built[0].outputs[0].to_effect.terms[0]
assert new_factor.name == "Bradley"
def test_make_fact_from_string(self, watt_factor):
fact_float_data = {
"content":
"the distance between $person0 and $person1 was >= 20.1",
"terms": [
{
"type": "Entity",
"name": "Ann"
},
{
"type": "Entity",
"name": "Lee"
},
],
}
record = expand_shorthand(fact_float_data)
record, mentioned = index_names(record)
expanded = readers.expand_factor(record, mentioned)
fact_float_more = Fact(**expanded)
fact_float_less = watt_factor["f8_int"]
assert fact_float_more >= fact_float_less
def test_mentioned_ordered_by_length(self, raw_factor):
obj = text_expansion.expand_shorthand(raw_factor["relevant"])
obj, mentioned = name_index.index_names(obj)
shortest = mentioned.popitem()
assert shortest[0] == "Short Name"
def test_mentioned_from_fact_and_entities(self, raw_factor):
obj = text_expansion.expand_shorthand(raw_factor["relevant"])
obj, mentioned = name_index.collect_mentioned(obj)
assert mentioned["relevant fact"]["type"] == "Fact"
shooting = mentioned["relevant fact"]["context_factors"][0]
assert mentioned[shooting]["context_factors"][0] == "Short Name"
def test_holdings_with_allegation_and_exhibit(self):
"""
Testing the error message:
The number of items in 'context_factors' must be 1,
to match predicate.context_slots for '{} committed
an attempted robbery' for 'fact that defendant
committed an attempted robbery'
This was another bug involving mutation of the "mentioned" context object
during deserialization.
Fixed by having FactSchema.get_references_from_mentioned call
add_found_context with deepcopy(obj) instead of obj for the
"factor" parameter
"""
holdings = [
{
"inputs": [
{
"type": "Exhibit",
"name": "officer's testimony that defendant was addicted to heroin",
"form": "testimony",
"statement": {
"type": "Fact",
"name": "fact that defendant was addicted to heroin",
"content": "the {defendant} was addicted to heroin",
},
"statement_attribution": {
"type": "entity",
"name": "parole officer",
},
},
{
"type": "Allegation",
"name": "the attempted robbery charge",
"pleading": {
"type": "Pleading",
"filer": {
"type": "Entity",
"name": "The People of California",
},
},
"statement": {
"type": "Fact",
"name": "fact that defendant committed an attempted robbery",
"content": "defendant committed an attempted robbery",
},
},
],
"despite": [
{
"type": "Fact",
"content": "officer's testimony that defendant was addicted to heroin, was relevant to show the defendant had a motive to commit an attempted robbery",
}
],
"outputs": [
{
"type": "Fact",
"content": "the probative value of officer's testimony that defendant was addicted to heroin, in showing fact that defendant committed an attempted robbery, was outweighed by unfair prejudice to defendant",
}
],
"mandatory": True,
},
{
"inputs": [
{
"type": "Fact",
"content": "the probative value of officer's testimony that defendant was addicted to heroin, in indicating fact that defendant committed an attempted robbery, was outweighed by unfair prejudice to defendant",
}
],
"despite": [
{
"type": "Fact",
"content": "officer's testimony that defendant was addicted to heroin was relevant to show defendant had a motive to commit an attempted robbery",
}
],
"outputs": [
{
"type": "Evidence",
"name": "evidence of officer's testimony that defendant was addicted to heroin",
"exhibit": "officer's testimony that defendant was addicted to heroin",
"to_effect": "fact that defendant committed an attempted robbery",
"absent": True,
}
],
"mandatory": True,
},
]
expanded = text_expansion.expand_shorthand(holdings)
built = readers.read_holdings(expanded)
allegation = built[0].inputs[1]
assert allegation.statement.context_factors[0].name == "defendant"
def test_holding_without_enactments_or_regime(self, raw_holding):
expanded = text_expansion.expand_shorthand(raw_holding["bradley_house"])
built = readers.read_holding(expanded)
new_factor = built.outputs[0].to_effect.context_factors[0]
assert new_factor.name == "Bradley"
def test_load_example(self):
procedure = text_expansion.expand_shorthand(self.example)
procedure = readers.read_procedure(procedure)
factor = procedure.outputs[0].context_factors[0]
assert factor.name == "the Java API"
def test_import_fact_with_entity_name_containing_another(self):
expanded = expand_shorthand(self.house_data)
record, mentioned = index_names(expanded)
assert mentioned["Alice's house"]["type"] == "Entity"