from regparser import api_stub
from regparser.citations import internal_citations, Label
from regparser.grammar.external_citations import regtext_external_citation
from regparser.layer import key_terms
from regparser.tree import struct
def generate_key_terms_layer(xml_based_reg_json):
layer_generator = key_terms.KeyTerms(xml_based_reg_json)
return layer_generator.build()
# We're not going to use our heuristic to determine key terms for paragraphs
# this has already properly been done for.
xml_based_reg = api_stub.get_regulation_as_json('/tmp/xtree.json')
real_key_terms_layer = generate_key_terms_layer(xml_based_reg)
layer = {}
part_end = '1005.'
exclude_parser = (regtext_external_citation | Literal("U.S."))
period = re.compile(r'\.(?!,)') # Not followed by a comma
def generate_keyterm(node):
label_id = node.label_id()
if label_id in real_key_terms_layer:
layer[label_id] = real_key_terms_layer[label_id]
else:
node_text = key_terms.KeyTerms.process_node_text(node)
if not node_text:
print NodeEncoder().encode(toc)
def generate_interpretations(reg):
""" Generate the Interpretations layer """
layer_generator = interpretations.Interpretations(reg)
print NodeEncoder().encode(layer_generator.build())
def generate_terms(reg):
""" Generate the Terms layer """
layer_generator = terms.Terms(reg)
print NodeEncoder().encode(layer_generator.build())
def generate_key_terms(reg):
""" Generate the key terms layer """
layer_generator = key_terms.KeyTerms(reg)
layer_generator.build()
print NodeEncoder().encode(layer_generator.build())
if __name__ == "__main__":
reg_json = api_stub.get_regulation_as_json('/tmp/xtree.json')
# generate_table_of_contents(reg_json)
# generate_internal_citations(reg_json)
# generate_external_citations(reg_json)
# generate_interpretations(reg_json)
# generate_terms(reg_json)
generate_key_terms(reg_json)
from pyparsing import Literal
from regparser import api_stub
from regparser.citations import internal_citations, Label
from regparser.grammar.external_citations import regtext_external_citation
from regparser.layer import key_terms
from regparser.tree import struct
def generate_key_terms_layer(xml_based_reg_json):
layer_generator = key_terms.KeyTerms(xml_based_reg_json)
return layer_generator.build()
# We're not going to use our heuristic to determine key terms for paragraphs
# this has already properly been done for.
xml_based_reg = api_stub.get_regulation_as_json('/tmp/xtree.json')
real_key_terms_layer = generate_key_terms_layer(xml_based_reg)
layer = {}
part_end = '1005.'
exclude_parser = (
regtext_external_citation
| Literal("U.S.")
)
period = re.compile(r'\.(?!,)') # Not followed by a comma
def generate_keyterm(node):
label_id = node.label_id()
if label_id in real_key_terms_layer:
layer[label_id] = real_key_terms_layer[label_id]
toc = layer_generator.build()
print NodeEncoder().encode(toc)
def generate_interpretations(reg):
""" Generate the Interpretations layer """
layer_generator = interpretations.Interpretations(reg)
print NodeEncoder().encode(layer_generator.build())
def generate_terms(reg):
""" Generate the Terms layer """
layer_generator = terms.Terms(reg)
print NodeEncoder().encode(layer_generator.build())
def generate_key_terms(reg):
""" Generate the key terms layer """
layer_generator = key_terms.KeyTerms(reg)
layer_generator.build()
print NodeEncoder().encode(layer_generator.build())
if __name__ == "__main__":
reg_json = api_stub.get_regulation_as_json('/tmp/xtree.json')
# generate_table_of_contents(reg_json)
# generate_internal_citations(reg_json)
# generate_external_citations(reg_json)
# generate_interpretations(reg_json)
# generate_terms(reg_json)
generate_key_terms(reg_json)
