Added expression support for polars cumulative (#13799)

# Description
Provides the ability to use `polars cumulative` as an expression:

<img width="1266" alt="Screenshot 2024-09-06 at 17 47 15"
src="https://github.com/user-attachments/assets/73c11f79-598c-4efa-bfcd-755e536ead66">

# User-Facing Changes
- `polars cumulative` can now be used as an expression.
This commit is contained in:
Jack Wright 2024-09-06 20:03:51 -07:00 committed by GitHub
parent f531cc2058
commit 6c1c7f9509
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GPG key ID: B5690EEEBB952194

View file

@ -1,6 +1,8 @@
use crate::{values::CustomValueSupport, PolarsPlugin};
use crate::values::{Column, NuDataFrame};
use crate::values::{
cant_convert_err, Column, NuDataFrame, NuExpression, PolarsPluginObject, PolarsPluginType,
};
use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
use nu_protocol::{
@ -52,22 +54,53 @@ impl PluginCommand for Cumulative {
}
fn description(&self) -> &str {
"Cumulative calculation for a series."
"Cumulative calculation for a column or series."
}
fn signature(&self) -> Signature {
Signature::build(self.name())
.required("type", SyntaxShape::String, "rolling operation")
.switch("reverse", "Reverse cumulative calculation", Some('r'))
.input_output_type(
Type::Custom("dataframe".into()),
Type::Custom("dataframe".into()),
.required(
"type",
SyntaxShape::String,
"rolling operation. Values of min, max, and sum are accepted.",
)
.switch("reverse", "Reverse cumulative calculation", Some('r'))
.input_output_types(vec![
(
Type::Custom("dataframe".into()),
Type::Custom("dataframe".into()),
),
(
Type::Custom("expression".into()),
Type::Custom("expression".into()),
),
])
.category(Category::Custom("dataframe".into()))
}
fn examples(&self) -> Vec<Example> {
vec![
Example {
description: "Cumulative sum for a column",
example: "[[a]; [1] [2] [3] [4] [5]] | polars into-df | polars select (polars col a | polars cumulative sum | polars as cum_a) | polars collect",
result: Some(
NuDataFrame::try_from_columns(
vec![Column::new(
"cum_a".to_string(),
vec![
Value::test_int(1),
Value::test_int(3),
Value::test_int(6),
Value::test_int(10),
Value::test_int(15),
],
)],
None,
)
.expect("simple df for test should not fail")
.into_value(Span::test_data()),
),
},
Example {
description: "Cumulative sum for a series",
example: "[1 2 3 4 5] | polars into-df | polars cumulative sum",
@ -120,20 +153,58 @@ impl PluginCommand for Cumulative {
call: &EvaluatedCall,
input: PipelineData,
) -> Result<PipelineData, LabeledError> {
command(plugin, engine, call, input).map_err(LabeledError::from)
let value = input.into_value(call.head)?;
let cum_type: Spanned<String> = call.req(0)?;
let cum_type = CumulativeType::from_str(&cum_type.item, cum_type.span)?;
match PolarsPluginObject::try_from_value(plugin, &value)? {
PolarsPluginObject::NuDataFrame(df) => command_df(plugin, engine, call, cum_type, df),
PolarsPluginObject::NuLazyFrame(lazy) => {
command_df(plugin, engine, call, cum_type, lazy.collect(call.head)?)
}
PolarsPluginObject::NuExpression(expr) => {
command_expr(plugin, engine, call, cum_type, expr)
}
_ => Err(cant_convert_err(
&value,
&[
PolarsPluginType::NuDataFrame,
PolarsPluginType::NuLazyFrame,
PolarsPluginType::NuExpression,
],
)),
}
.map_err(LabeledError::from)
}
}
fn command(
fn command_expr(
plugin: &PolarsPlugin,
engine: &EngineInterface,
call: &EvaluatedCall,
input: PipelineData,
cum_type: CumulativeType,
expr: NuExpression,
) -> Result<PipelineData, ShellError> {
let cum_type: Spanned<String> = call.req(0)?;
let reverse = call.has_flag("reverse")?;
let polars = expr.into_polars();
let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
let res: NuExpression = match cum_type {
CumulativeType::Max => polars.cum_max(reverse),
CumulativeType::Min => polars.cum_min(reverse),
CumulativeType::Sum => polars.cum_sum(reverse),
}
.into();
res.to_pipeline_data(plugin, engine, call.head)
}
fn command_df(
plugin: &PolarsPlugin,
engine: &EngineInterface,
call: &EvaluatedCall,
cum_type: CumulativeType,
df: NuDataFrame,
) -> Result<PipelineData, ShellError> {
let reverse = call.has_flag("reverse")?;
let series = df.as_series(call.head)?;
if let DataType::Object(..) = series.dtype() {
@ -146,7 +217,6 @@ fn command(
});
}
let cum_type = CumulativeType::from_str(&cum_type.item, cum_type.span)?;
let mut res = match cum_type {
CumulativeType::Max => cum_max(&series, reverse),
CumulativeType::Min => cum_min(&series, reverse),