df-types 0.0.1

A tool for generating dataclass type files for pandas DataFrame rows

df_types

Python tool for generating dataclass type files for pandas DataFrame rows.

Installation

pip install df-types

Usage

from df_types import DFTypes
import pandas as pd

df = pd.read_csv("dev.csv")

dft = DFTypes(df)
dft.write_types()  # creates typed_df.py in the current directory
# see df_types.config.DFTypesConfig for options

# then use the types file as a module
from typed_df import convert, iter_dataclasses

df = convert(df)

for dc in iter_dataclasses(df):
    ...  # do something with dc

In the above example, convert and iter_dataclasses are generated from typed_df.py. convert is a function that takes a DataFrame and normalizes the column names, replacing NaN values with None (by default).

iter_dataclasses is a generator that takes a DataFrame and yields a dataclass for each row.

Features

Currently, the following features are supported:

• Literal types for primitive types (e.g. Literal["some_type", "other_type"])
• Union types (e.g. int | float)
• Optional types (e.g. int | None)
• Imported/custom types (e.g. pd.Timestamp, user defined types)

In the future, I'd like to add support for typed containers (e.g. Dict[str, int], List[int]).

License

MIT