snowflake.ml.model.batch_inference.ColumnHandlingOptions

class snowflake.ml.model.batch_inference.ColumnHandlingOptions

Bases: TypedDict

Options for handling specific columns during run_batch for file I/O.

Methods

clear()

Remove all items from the dict.

copy()

Return a shallow copy of the dict.

fromkeys(value=None, /)

Create a new dictionary with keys from iterable and values set to value.

get(key, default=None, /)

Return the value for key if key is in the dictionary, else default.

items()

Return a set-like object providing a view on the dict’s items.

keys()

Return a set-like object providing a view on the dict’s keys.

pop(k[, d]) v, remove specified key and return the corresponding value.

If the key is not found, return the default if given; otherwise, raise a KeyError.

popitem()

Remove and return a (key, value) pair as a 2-tuple.

Pairs are returned in LIFO (last-in, first-out) order. Raises KeyError if the dict is empty.

setdefault(key, default=None, /)

Insert key with a value of default if key is not in the dictionary.

Return the value for key if key is in the dictionary, else default.

update([E, ]**F) None.  Update D from mapping/iterable E and F.

If E is present and has a .keys() method, then does: for k in E.keys(): D[k] = E[k] If E is present and lacks a .keys() method, then does: for k, v in E: D[k] = v In either case, this is followed by: for k in F: D[k] = F[k]

values()

Return an object providing a view on the dict’s values.

Attributes

input_format: InputFormat
convert_to: FileEncoding