def generate_annotations_json_string(source_path):
# type: (str) -> List[FunctionData]
"""Produce annotation data JSON file from a JSON file with runtime-collected types.
Data formats:
* The source JSON is a list of pyannotate_tools.annotations.parse.RawEntry items.
* The output JSON is a list of FunctionData items.
"""
items = parse_json(source_path)
results = []
for item in items:
arg_types, return_type = infer_annotation(item.type_comments)
arg_strs = []
for arg, kind in arg_types:
arg_str = str(arg)
if kind == ARG_STAR:
arg_str = '*%s' % arg_str
elif kind == ARG_STARSTAR:
arg_str = '**%s' % arg_str
arg_strs.append(arg_str)
signature = {
'arg_types': arg_strs,
'return_type': str(return_type),
} # type: Signature
data = {
'path': item.path,
'line': item.line,
'func_name': item.func_name,
'signature': signature,
'samples': item.samples
} # type: FunctionData
results.append(data)
return results
def unify_type_comments(type_comments):
# type: (List[str]) -> Signature
arg_types, return_type = infer_annotation(type_comments)
arg_strs = []
for arg, kind in arg_types:
arg_str = str(arg)
if kind == ARG_STAR:
arg_str = '*%s' % arg_str
elif kind == ARG_STARSTAR:
arg_str = '**%s' % arg_str
arg_strs.append(arg_str)
return {
'arg_types': arg_strs,
'return_type': str(return_type),
}
def generate_annotations_json(source_path,
target_path,
source_stream=None,
target_stream=None):
# type: (str, str, Optional[IO[str]], Optional[IO[str]]) -> None
"""Produce annotation data JSON file from a JSON file with runtime-collected types.
Data formats:
* The source JSON is a list of pyannotate_tools.annotations.parse.RawEntry items.
* The output JSON is a list of FunctionData items.
"""
items = parse_json(source_path, source_stream)
results = []
for item in items:
arg_types, return_type = infer_annotation(item.type_comments)
arg_strs = []
for arg, kind in arg_types:
arg_str = str(arg)
if kind == ARG_STAR:
arg_str = '*%s' % arg_str
elif kind == ARG_STARSTAR:
arg_str = '**%s' % arg_str
arg_strs.append(arg_str)
signature = {
'arg_types': arg_strs,
'return_type': str(return_type),
} # type: Signature
data = {
'path': item.path,
'line': item.line,
'func_name': item.func_name,
'signature': signature,
'samples': item.samples
} # type: FunctionData
results.append(data)
if target_stream:
json.dump(results, target_stream, sort_keys=True, indent=4)
else:
with open(target_path, 'w') as f:
json.dump(results, f, sort_keys=True, indent=4)
def assert_infer(self, comments, expected):
# type: (List[str], Tuple[List[Tuple[AbstractType, str]], AbstractType]) -> None
actual = infer_annotation(comments)
assert actual == expected