A Python library for defining and applying column functions to DuckDB tables
Project description
Deductable
de-duck-table A way to deduce new columns in your duckdb table
Description
For a client I was doing research on a collection of websites. I wanted an easy way to add a column with findings based on the previous information. For instance, I started with a list of names, for which i didn't have the URL. An agent took in the name, and found the website url.
Installation
uv pip install deductable
Requirements
- Python 3.13+
- DuckDB 1.4.1+
- Loguru 0.7.3+
- Pandas 2.3.3+
Quick Start
from typing import Optional
import duckdb
from deductable import Deductable
from my_agents import find_url
# Connect to a DuckDB database
with duckdb.connect('companies.duckdb') as con:
# Create a Deductable instance for the table
# Deductable expects at least an id column
dt = Deductable(con, table_name="companies")
@dt.column
def company_url(company_name: str) -> Optional[float]:
# company_name should be a column in the duckdb
return find_url(company_name)
# Apply the column function to populate the weight column
dt.materialize()
# View the result
print(dt.df())
Features
- Type-safe column functions: Define column functions with proper type annotations
- Automatic column creation: Columns are automatically created based on function names
- Dependency handling: Functions can depend on other columns
- Optional values: Support for nullable columns with Optional type annotations
- Pandas integration: Easy conversion to pandas DataFrames
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
License
This project is licensed under the MIT License - see the LICENSE file for details.
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