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Simplifying conditional Polars Expressions with Python 🐍 πŸ»β€β„οΈ

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polarIFy: Simplifying conditional Polars Expressions with Python 🐍 πŸ»β€β„οΈ

License Build Status conda-forge pypi-version python-version codecov

Welcome to polarIFy, a Python function decorator that simplifies the way you write logical statements for Polars. With polarIFy, you can use Python's language structures like if / elif / else statements and transform them into pl.when(..).then(..).otherwise(..) statements. This makes your code more readable and less cumbersome to write. πŸŽ‰

🎯 Usage

polarIFy can automatically transform Python functions using if / elif / else statements into Polars expressions.

Basic Transformation

Here's an example:

@polarify
def signum(x: pl.Expr) -> pl.Expr:
    s = 0
    if x > 0:
        s = 1
    elif x < 0:
        s = -1
    return s

This gets transformed into:

def signum(x: pl.Expr) -> pl.Expr:
    return pl.when(x > 0).then(1).otherwise(pl.when(x < 0).then(-1).otherwise(0))

Handling Multiple Statements

polarIFy can also handle multiple statements like:

@polarify
def multiple_if_statement(x: pl.Expr) -> pl.Expr:
    a = 1 if x > 0 else 5
    b = 2 if x < 0 else 2
    return a + b

which becomes:

def multiple_if_statement(x):
    return pl.when(x > 0).then(1).otherwise(5) + pl.when(x < 0).then(2).otherwise(2)

Handling Nested Statements

Additionally, it can handle nested statements:

@polarify
def nested_if_else(x: pl.Expr) -> pl.Expr:
    if x > 0:
        if x > 1:
            s = 2
        else:
            s = 1
    elif x < 0:
        s = -1
    else:
        s = 0
    return s

which becomes:

def nested_if_else(x: pl.Expr) -> pl.Expr:
    return pl.when(x > 0).then(pl.when(x > 1).then(2).otherwise(1)).otherwise(pl.when(x < 0).then(-1).otherwise(0))

So you can still write readable row-wise python code while the @polarify decorator transforms it into a function that works with efficient polars expressions.

Using a polarifyd function

import polars as pl
from polarify import polarify

@polarify
def complicated_operation(x: pl.Expr) -> pl.Expr:
    k = 0
    c = 2
    if x > 0:
        k = 1
        c = 0
        if x < 10:
            c = 1
    elif x < 0:
        k = -1
    return k * c


df = pl.DataFrame({"x": [-1, 1, 5, 10]})
result = df.select(pl.col("x"), complicated_operation(pl.col("x")))
print(result)
# shape: (4, 2)
# β”Œβ”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
# β”‚ x   ┆ literal β”‚
# β”‚ --- ┆ ---     β”‚
# β”‚ i64 ┆ i32     β”‚
# β•žβ•β•β•β•β•β•ͺ═════════║
# β”‚ -1  ┆ -2      β”‚
# β”‚ 1   ┆ 1       β”‚
# β”‚ 5   ┆ 1       β”‚
# β”‚ 10  ┆ 0       β”‚
# β””β”€β”€β”€β”€β”€β”΄β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜

Displaying the transpiled polars expression

You can also display the transpiled polars expression by calling the transform_func_to_new_source method:

from polarify import transform_func_to_new_source

def signum(x):
    s = 0
    if x > 0:
        s = 1
    elif x < 0:
        s = -1
    return s


print(f"Original function:\n{inspect.getsource(signum)}")
# Original function:
# def signum(x):
#     s = 0
#     if x > 0:
#         s = 1
#     elif x < 0:
#         s = -1
#     return s
print(f"Transformed function:\n{transform_func_to_new_source(signum)}")
# Transformed function:
# def signum_polarified(x):
#     import polars as pl
#     return pl.when(x > 0).then(1).otherwise(pl.when(x < 0).then(-1).otherwise(0))

TODO: complicated example with nested functions

βš™οΈ How It Works

polarIFy achieves this by parsing the AST (Abstract Syntax Tree) of the function and transforming the body into a Polars expression by inlining the different branches. To get a more detailed understanding of what's happening under the hood, check out our blog post explaining how polarify works!

πŸ’Ώ Installation

conda

conda install -c conda-forge polarify
# or micromamba
micromamba install -c conda-forge polarify
# or pixi
pixi add polarify

pip

pip install polarify

⚠️ Limitations

polarIFy is still in an early stage of development and doesn't support the full Python language. Here's a list of the currently supported and unsupported operations:

Supported operations

  • if / else / elif statements
  • binary operations (like +, ==, >, &, |, ...)
  • unary operations (like ~, -, not, ...) (TODO)
  • assignments (like x = 1)
  • polars expressions (like pl.col("x"), TODO)
  • side-effect free functions that return a polars expression (can be generated by @polarify) (TODO)
  • match statements

Unsupported operations

  • for loops
  • while loops
  • break statements
  • := walrus operator
  • dictionary mappings in match statements
  • list matching in match statements
  • star patterns in `match statements
  • functions with side-effects (print, pl.write_csv, ...)

πŸš€ Benchmarks

TODO: Add some benchmarks

πŸ“₯ Development installation

pixi install
pixi run postinstall
pixi run test

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