def _write(self, file, _format):
"""Internal function to dump to file in either yaml or json formats
:param file: file object to write to
:type file: file
:param _format: file format that can be "yml", "yaml", or "json
:type _ext: str
:raises ValueError: _format must be one of "yml", "yaml" or "json"
"""
if _format.lower() not in Writable._FORMATS:
raise ValueError(
"invalid _ext: {_format}, extension must be one of {formats}".
format(_format=_format, formats=Writable._FORMATS))
if _format == "yml" or _format == "yaml":
# TODO: figure out how to get yaml.dump to recurse down into nested objects
# yaml.dump(_CustomEncoder().default(self), file, sort_keys=False)
yaml.dump(
json.loads(json.dumps(self, cls=_CustomEncoder),
object_pairs_hook=OrderedDict),
file,
allow_unicode=True,
)
else:
json.dump(self,
file,
cls=_CustomEncoder,
indent=4,
ensure_ascii=False)
def test__get_braindump(self):
# create a fake temporary submit dir and braindump.yml file
with TemporaryDirectory() as td:
bd_path = Path(td) / "braindump.yml"
with bd_path.open("w+") as bd_file:
yaml.dump({
"user": "******",
"submit_dir": "/submit_dir"
}, bd_file)
bd_file.seek(0)
bd = Workflow._get_braindump(bd_path.parent)
assert bd.user == "ryan"
assert bd.submit_dir == Path("/submit_dir")
def dump(obj: Braindump, fp: TextIO, *args, **kwargs) -> None:
"""
Serialize ``obj`` as a Braindump formatted stream to ``fp`` (a ``.write()``-supporting file-like object).
[extended_summary]
:param obj: [description]
:type obj: Dict
:param fp: [description]
:type fp: TextIO
:return: [description]
:rtype: NoReturn
"""
yaml.dump(attr.asdict(obj), fp, *args, **kwargs)
def test_loads_yaml(sc1):
# dump sc1 to str, then load into new sc
new_sc = loads(yaml.dump(json.loads(json.dumps(sc1, cls=_CustomEncoder))))
# assert that what was loaded is equal to the original
result = json.loads(json.dumps(new_sc, cls=_CustomEncoder))
expected = json.loads(json.dumps(sc1, cls=_CustomEncoder))
assert result == expected
def test_loads_yaml(wf1):
# dump wf1 to str, then load into new wf
new_wf = loads(yaml.dump(json.loads(json.dumps(wf1, cls=_CustomEncoder))))
# assert that what was loaded is equal to the original
result = json.loads(json.dumps(new_wf, cls=_CustomEncoder))
expected = json.loads(json.dumps(wf1, cls=_CustomEncoder))
assert sort_parts(result) == sort_parts(expected)
def _write(self, file, _format):
"""Internal function to dump to file in either yaml or json formats
:param file: file object to write to
:type file: file
:param _format: file format that can be "yml", "yaml", or "json
:type _ext: str
:raises ValueError: _format must be one of "yml", "yaml" or "json"
"""
if _format.lower() not in Writable._FORMATS:
raise ValueError(
"invalid _ext: {_format}, extension must be one of {formats}".format(
_format=_format, formats=Writable._FORMATS
)
)
# add file info
self_as_dict = OrderedDict(
[
(
"x-pegasus",
{
"createdBy": getpass.getuser(),
"createdOn": datetime.now().strftime(r"%m-%d-%yT%H:%M:%SZ"),
"apiLang": "python",
},
)
]
)
self_as_dict.update(
json.loads(
json.dumps(self, cls=_CustomEncoder), object_pairs_hook=OrderedDict
)
)
if _format == "yml" or _format == "yaml":
# TODO: figure out how to get yaml.dump to recurse down into nested objects
# yaml.dump(_CustomEncoder().default(self), file, sort_keys=False)
yaml.dump(self_as_dict, file, allow_unicode=True)
else:
json.dump(
self_as_dict, file, cls=_CustomEncoder, indent=4, ensure_ascii=False
)