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@thomasaarholt
Created November 28, 2023 20:18
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Polars type serialization in a pydantic model
from typing import Any
import polars as pl
import json
from pydantic import BaseModel
original_expression = (pl.col("foo") * 2) == pl.col("bar")
class Column(BaseModel, arbitrary_types_allowed=True):
"This model won't be serializable"
name: str
expression: pl.Expr
col = Column(name="foo", expression=original_expression)
# foo.model_dump_json() # <- this will throw a serialization error
# just to demonstrate, you can use json.loads to deserialize the polars json, into a dict
expr_json = original_expression.meta.write_json() # polars json version of the expr
expr_dict = json.loads(
expr_json
) # python deserialized version of the expr. This is a dict of strings.
class TempColumn(BaseModel):
"This model WILL be serializable"
name: str
expression: dict[str, Any]
temp_col = TempColumn(
name=col.name,
expression=json.loads(
col.expression.meta.write_json()
), # notice I used the entries from the instance of Column
)
temp_col_json = temp_col.model_dump_json()
# read it back in
temp_col = TempColumn.model_validate_json(temp_col_json)
expression_read_from_pydantic = pl.Expr.from_json(json.dumps(temp_col.expression))
# expressions can't be equated, since == would compare two columns, but we can check that their string repr is the same
assert str(expression_read_from_pydantic) == str(original_expression)
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