ride.utils.io
¶
Module Contents¶
Classes¶
Extensible JSON <http://json.org> encoder for Python data structures. |
Functions¶
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Bumps the version number for a path if it already exists |
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- ride.utils.io.is_nonempty_file(path: Union[str, pathlib.Path]) bool [source]¶
- ride.utils.io.bump_version(path: Union[str, pathlib.Path]) pathlib.Path [source]¶
Bumps the version number for a path if it already exists
Example:
bump_version("folder/new_file.json") == Path("folder/new_file.json) bump_version("folder/old_file.json") == Path("folder/old_file_1.json) bump_version("folder/old_file_1.json") == Path("folder/old_file_2.json)
- ride.utils.io.load_structured_data(path: pathlib.Path)[source]¶
- ride.utils.io.dump_yaml(path: pathlib.Path, data: Any)[source]¶
- ride.utils.io.load_yaml(path: pathlib.Path) Any [source]¶
- ride.utils.io.dump_json(path: pathlib.Path, data: Any)[source]¶
- ride.utils.io.load_json(path: pathlib.Path) Any [source]¶
- class ride.utils.io.NpJsonEncoder(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, sort_keys=False, indent=None, separators=None, default=None)[source]¶
Bases:
json.JSONEncoder
Extensible JSON <http://json.org> encoder for Python data structures.
Supports the following objects and types by default:
Python
JSON
dict
object
list, tuple
array
str
string
int, float
number
True
true
False
false
None
null
To extend this to recognize other objects, subclass and implement a
.default()
method with another method that returns a serializable object foro
if possible, otherwise it should call the superclass implementation (to raiseTypeError
).- default(obj)[source]¶
Implement this method in a subclass such that it returns a serializable object for
o
, or calls the base implementation (to raise aTypeError
).For example, to support arbitrary iterators, you could implement default like this:
def default(self, o): try: iterable = iter(o) except TypeError: pass else: return list(iterable) # Let the base class default method raise the TypeError return JSONEncoder.default(self, o)
- ride.utils.io.tensor_representer(dumper: yaml.Dumper, data: torch.Tensor)[source]¶