feathertail 0.2.0

A tiny, fast, Rust-backed transformation core for Python table data

🪶 feathertail

A high-performance Python DataFrame library powered by Rust — designed for flexibility, blazing speed, and intelligent type handling.

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✨ Features

• ✅ Build TinyFrame from Python dict records (from_dicts)
• ✅ Automatic type inference, including mixed-type and optional columns
• ✅ Intelligent fallback to Python objects when Rust-native types aren’t possible
• ✅ Flexible fillna to handle missing data
• ✅ Powerful cast_column to convert columns between types
• ✅ Smart edit_column: edits that automatically adjust column type if needed
• ✅ Drop or rename columns easily
• ✅ Group-by aggregations via TinyGroupBy
• ✅ Export back to Python dicts (to_dicts)
• ✅ Rust-backed core: lightweight, fast, and dependency-light

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📦 Installation

pip install feathertail

Or, from local source:

pip install -e .

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🧑‍💻 Quickstart

import feathertail as ft

records = [
    {"name": "Alice", "age": 30, "city": "New York", "score": 95.5},
    {"name": "Bob", "age": None, "city": "Paris", "score": 85.0},
    {"name": "Charlie", "age": 25, "city": "New York", "score": None},
]

frame = ft.TinyFrame.from_dicts(records)
print(frame)
print(frame.to_dicts())

Output:

TinyFrame(rows=3, columns=4, cols={ 'name': 'Str', 'age': 'OptInt', 'city': 'Str', 'score': 'OptFloat' })
[{'name': 'Alice', 'age': 30, 'city': 'New York', 'score': 95.5}, ...]

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Fill missing values

frame.fillna({"age": 20, "score": 0.0})
print(frame.to_dicts())

[{'name': 'Alice', 'age': 30, 'city': 'New York', 'score': 95.5},
 {'name': 'Bob', 'age': 20, 'city': 'Paris', 'score': 85.0},
 {'name': 'Charlie', 'age': 25, 'city': 'New York', 'score': 0.0}]

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Cast and edit columns

frame.cast_column("score", float)
frame.edit_column("city", lambda x: x.upper() if x else x)
print(frame.to_dicts())

[{'name': 'Alice', 'age': 30, 'city': 'NEW YORK', 'score': 95.5},
 {'name': 'Bob', 'age': 20, 'city': 'PARIS', 'score': 85.0},
 {'name': 'Charlie', 'age': 25, 'city': 'NEW YORK', 'score': 0.0}]

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Drop and rename columns

frame.drop_columns(["score"])
frame.rename_column("name", "full_name")
print(frame.to_dicts())

[{'full_name': 'Alice', 'age': 30, 'city': 'NEW YORK'},
 {'full_name': 'Bob', 'age': 20, 'city': 'PARIS'},
 {'full_name': 'Charlie', 'age': 25, 'city': 'NEW YORK'}]

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Group by columns

groupby = ft.TinyGroupBy(frame, keys=["city"])
count_frame = groupby.count(frame)
print(count_frame.to_dicts())

[{'city': 'NEW YORK', 'count': 2},
 {'city': 'PARIS', 'count': 1}]

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⚙️ Supported Types

Type	Column variants
int	Int, OptInt
float	Float, OptFloat
bool	Bool, OptBool
str	Str, OptStr
mixed & fallback	Mixed, OptMixed (includes Python fallback objects automatically)

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🐉 Why "feathertail"?

In Fourth Wing, a "feathertail" is a juvenile dragon — small, golden, and nonviolent, known for grace rather than brute force.

This library follows the same spirit: gentle on dependencies, elegant in design, and capable of handling complex data types with ease.

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❤️ Contributing

Contributions, ideas, and feedback are always welcome! Please open an issue or pull request.

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📄 License

MIT