polars.Expr.str.json_decode#

Expr.str.json_decode( dtype: PolarsDataType | None = None, *, infer_schema_length: int | None = 100, ) → Expr[source]#

Parse string values as JSON.

Throws an error if invalid JSON strings are encountered.

Parameters:

dtype: The dtype to cast the extracted value to. If None, the dtype will be inferred from the JSON value.
infer_schema_length: The maximum number of rows to scan for schema inference. If set to None, the full data may be scanned (this is slow).

See also

json_path_match: Extract the first match of json string with provided JSONPath expression.

Examples

>>> df = pl.DataFrame(
...     {"json": ['{"a":1, "b": true}', None, '{"a":2, "b": false}']}
... )
>>> dtype = pl.Struct([pl.Field("a", pl.Int64), pl.Field("b", pl.Boolean)])
>>> df.with_columns(decoded=pl.col("json").str.json_decode(dtype))
shape: (3, 2)
┌─────────────────────┬─────────────┐
│ json                ┆ decoded     │
│ ---                 ┆ ---         │
│ str                 ┆ struct[2]   │
╞═════════════════════╪═════════════╡
│ {"a":1, "b": true}  ┆ {1,true}    │
│ null                ┆ {null,null} │
│ {"a":2, "b": false} ┆ {2,false}   │
└─────────────────────┴─────────────┘