Mapping pandas' Series to dataclasses

Question

I've got something really simple this time where I'm mapping pandas' Series to dataclasses with a oneliner helper function (as I have several models):

import pandas as pd
from typing import Any
from dataclasses import dataclass, fields
def create_dataclass(data: pd.Series, factory: Any) -> Any:
 return factory(**{f.name: data[f.name] for f in fields(factory)})

I call it like this:

@dataclass
class Person:
 first_name: str
 last_name: str
@dataclass
class Employee(Person):
 company: str
def create_employees(data: pd.DataFrame) -> List[Employee]:
 return [create_dataclass(r, Employee) for i, r in data.iterrows()]

---

Do you think it still could be more pythonic?

Answer 1

Looks very pythonic to me.

Thumbs up, LGTM, ship it!

---

Ok, fine, I have a few minor remarks.

Maybe the Any annotations could be finessed a bit to be more informative? Or maybe just drop the -> Any:.

---

 return factory(**{f.name: data[f.name] for f in fields(factory)})

The ** double star is as pythonic as it gets. But notice that what we really care about is name. So perhaps

from operator import attrgetter
 ...
 return factory(**{name: data[name] for name in map(attrgetter('name'), fields(factory))})

Hmmm, not sure that longer works out to a win. Prolly better to keep the code as-is.

---

 ... for _, r in data.iterrows()]

nit: Prefer row over r. Whatever.

Like I said, ship it.

Answer 2

This looks great, exactly what I need, I'm stealing it. :)

I'm using this in a base class PandasClass, with the functions that create dataclass instances as classmethods. In this way, any dataclass that inherits from PandasClass gets the create_employees (and similar) "for free".

from typing import List, Self
@dataclass
class PandasClass
 @classmethod
 def create_dataclass(cls, row: pd.Series) -> Self:
 return cls(**{f.name: row[f.name] for f in fields(cls)})
 @classmethod
 def create_dataclass_list(cls, dataframe: pd.DataFrame) -> List[Self]:
 return [cls.create_dataclass(row) for _, row in dataframe.iterrows()]

So in the OP's example, if Person inherits from PandasClass

class Person(PandasClass): 
...

then we can call Employee.create_dataclass_list(df) as the original create_employees(df).