Abstract out Polars expressions with user-defined chainable functions on the `DataFrame` - node.js

Question

Motivation
Abstract out parametrized (via custom function parameters) chainable (preferably via the DataFrame.prototype) Polars expressions to provide user-defined, higher-level, reusable and chainable data analysis functions on the DataFrame
Desired behavior and failed intent
import pl from "nodejs-polars"
const { DataFrame, col } = pl
// user-defined, higher-level, reusable and chainable data analysis function
// with arbitrary complex parametrized Polars expressions
DataFrame.prototype.inc = function inc(column, x = 1, alias = `${column}Inc`) {
return this.withColumn(col(column).add(x).alias(alias))
}
const df = new DataFrame({ a: [1, 2, 3] })
// works, but implies code duplication on reuse
console.log(df.withColumn(col("a").add(1).alias("aInc")))
// desiged behavior gives TypeError: df.inc is not a function
console.log(df.inc("a").inc("a", 2, "aInc2"))
What it the recommended way to define custom functions that encapsulate Polars expressions in nodejs-polars?

Answer 1

a functional approach that does not require additional libraries would be to create a simple wrapper function & reexport polars with an overridden DataFrame method within your own package.
// polars_extension.js
import pl from 'nodejs-polars'
const customMethods = {
sumAlias() {
return this.sum();
},
};
export default {
...pl,
DataFrame(...args) {
return Object.assign(pl.DataFrame(...args), customMethods);
}
}
// another_file.js
import pl from './polars_extension'
pl.DataFrame({num: [1, 2, 3]}).sumAlias()

Answer 2

Prototype-based solution
function DF(df) { this.df = df }
DF.prototype.inc = function inc(column, x = 1, alias = `${column}Inc`) {
this.df = this.df.withColumn(col(column).add(x).alias(alias))
return this
}
const df = new DF(new DataFrame({ a: [1, 2, 3] }))
console.log(df.inc("a").inc("a", 2, "aInc2"))
Functional programming solution (preferred)
import { curry, pipe } from "rambda"
function inc(column, x, alias, df) {
return df.withColumn(col(column).add(x).alias(alias))
}
const makeInc = curry(inc)
const df = new DataFrame({ a: [1, 2, 3] })
console.log(pipe(makeInc("a", 1, "aInc"), makeInc("a", 2, "aInc2"))(df))
Output
shape: (3, 3)
┌─────┬──────┬───────┐
│ a ┆ aInc ┆ aInc2 │
│ --- ┆ --- ┆ --- │
│ f64 ┆ f64 ┆ f64 │
╞═════╪══════╪═══════╡
│ 1.0 ┆ 2.0 ┆ 3.0 │
├╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌╌╌┤
│ 2.0 ┆ 3.0 ┆ 4.0 │
├╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌╌╌┤
│ 3.0 ┆ 4.0 ┆ 5.0 │
└─────┴──────┴───────┘```