This release is a pre-release and may not be stable for production use.
additory
Elegant data operations for DataFrames
A Rust-powered Python library for intuitive data transformations, lookups, synthetic data generation, and DataFrame comparison — with Polars and Pandas.
Installation
pip install additory
Requirements: Python 3.9+ · Polars (required) · pyarrow (required) · Pandas (optional)
Quick Start
import additory as add
import polars as pl
Bring data from another DataFrame
orders = pl.DataFrame({'order_id': [1, 2], 'customer_id': [101, 102], 'amount': [250, 180]})
customers = pl.DataFrame({'customer_id': [101, 102], 'name': ['Alice', 'Bob']})
result = add.to(orders, customers, 'name', 'customer_id')
Transform data
df = pl.DataFrame({'price': [100, 200, 300], 'quantity': [2, 3, 1]})
result = add.transform('@calc', df, strategy={'total': 'price * quantity', 'tax': 'total * 0.1'})
result = add.transform('@filter', df, where='price > 150')
result = add.transform('@sort', df, by='price', strategy='desc')
result = add.transform('@aggregate', df, by='category', strategy={'price': 'sum'})
Generate synthetic data
result = add.synthetic('@new', n=1000, strategy={
'age': 'normal(40, 10)',
'salary': 'normal(75000, 15000)',
})
# Augment existing data
result = add.synthetic(df, n=100)
Compare DataFrames
diff = add.scan('@diff', old=df_jan, new=df_feb)
Use dynamic expressions
patients = pl.DataFrame({'weight': [70, 85], 'height': [1.70, 1.80]})
result = add.bmi(patients)
Pipe compatibility
result = (
orders
.pipe(add.to, customers, 'name', 'customer_id')
.pipe(add.to, products, 'price', 'product_id')
)
Core Functions
| Function | Purpose | Pipe-Friendly |
|---|---|---|
add.to(bring_to, bring_from, bring, against, ...) |
Bring columns from another DataFrame | ✅ |
add.transform(mode, df, ...) |
Transform data (12 modes) | ❌ |
add.synthetic(df_or_mode, n, ...) |
Generate or augment data | ✅ |
add.scan(mode, df, ...) |
Analyze, diff, manage expressions | ❌ |
add.<dynamic>(df, ...) |
Named expression functions | ✅ |
Transform Modes
@calc · @filter · @sort · @aggregate · @harmonize · @round · @transpose · @extract · @onehot · @label · @deduce · @split
Features
- 🔗 Intuitive Lookups — bring columns from external sources with natural syntax
- ⚡ 12 Transform Modes — calculate, filter, sort, aggregate, encode, impute
- 🔍 DataFrame Diff — compare snapshots with
add.scan('@diff') - 🧮 Dynamic Expressions — 74 built-in formulas across 7 categories, extensible via
.addfiles - 🎲 Synthetic Data — generate realistic test data or augment existing datasets
- 📊 Lineage Tracking — trace data provenance with
lineage=True - 🔄 Pipe Compatibility — fluent chaining with
df.pipe() - 🚀 Rust Performance — ~95% Rust core via PyO3
- 🐼 Polars & Pandas — works with both DataFrame libraries
Documentation
📚 sekarkrishna.github.io/additory
Version
Current version: 0.1.3a11
License
MIT License — see LICENSE for details.
Author: Krishnamoorthy Sankaran
1 maintainer
Release files for additory 0.1.3a11
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| additory-0.1.3a11.tar.gz | 1.3 MB | Details |
Built distributions (wheels)
Total release size: 174.1 MB
Release files / additory-0.1.3a11.tar.gz
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