use crate::{PolarsPlugin, values::CustomValueSupport};
use crate::values::{
Column, NuDataFrame, NuExpression, PolarsPluginObject, PolarsPluginType, cant_convert_err,
};
use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
use nu_protocol::{
Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, Spanned,
SyntaxShape, Value, shell_error::generic::GenericError,
};
use polars::prelude::{DataType, IntoSeries, cum_max, cum_min, cum_sum};
enum CumulativeType {
Min,
Max,
Sum,
}
impl CumulativeType {
fn from_str(roll_type: &str, span: Span) -> Result<Self, ShellError> {
match roll_type {
"min" => Ok(Self::Min),
"max" => Ok(Self::Max),
"sum" => Ok(Self::Sum),
_ => Err(ShellError::Generic(
GenericError::new(
"Wrong operation",
"Operation not valid for cumulative",
span,
)
.with_help("Allowed values: max, min, sum"),
)),
}
}
fn to_str(&self) -> &'static str {
match self {
CumulativeType::Min => "cumulative_min",
CumulativeType::Max => "cumulative_max",
CumulativeType::Sum => "cumulative_sum",
}
}
}
#[derive(Clone)]
pub struct Cumulative;
impl PluginCommand for Cumulative {
type Plugin = PolarsPlugin;
fn name(&self) -> &str {
"polars cumulative"
}
fn description(&self) -> &str {
"Cumulative calculation for a column or series."
}
fn signature(&self) -> Signature {
Signature::build(self.name())
.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![
(
PolarsPluginType::NuDataFrame.into(),
PolarsPluginType::NuDataFrame.into(),
),
(
PolarsPluginType::NuLazyFrame.into(),
PolarsPluginType::NuLazyFrame.into(),
),
(
PolarsPluginType::NuExpression.into(),
PolarsPluginType::NuExpression.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,
Span::test_data(),
)
.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",
result: Some(
NuDataFrame::try_from_columns(
vec![Column::new(
"0_cumulative_sum".to_string(),
vec![
Value::test_int(1),
Value::test_int(3),
Value::test_int(6),
Value::test_int(10),
Value::test_int(15),
],
)],
None,
Span::test_data(),
)
.expect("simple df for test should not fail")
.into_value(Span::test_data()),
),
},
Example {
description: "Cumulative sum for a series in reverse order",
example: "[1 2 3 4 5] | polars into-df | polars cumulative sum --reverse",
result: Some(
NuDataFrame::try_from_columns(
vec![Column::new(
"0_cumulative_sum".to_string(),
vec![
Value::test_int(15),
Value::test_int(14),
Value::test_int(12),
Value::test_int(9),
Value::test_int(5),
],
)],
None,
Span::test_data(),
)
.expect("simple df for test should not fail")
.into_value(Span::test_data()),
),
},
]
}
fn run(
&self,
plugin: &Self::Plugin,
engine: &EngineInterface,
call: &EvaluatedCall,
mut input: PipelineData,
) -> Result<PipelineData, LabeledError> {
let metadata = input.take_metadata();
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)
.map(|pd| pd.set_metadata(metadata))
}
}
fn command_expr(
plugin: &PolarsPlugin,
engine: &EngineInterface,
call: &EvaluatedCall,
cum_type: CumulativeType,
expr: NuExpression,
) -> Result<PipelineData, ShellError> {
let reverse = call.has_flag("reverse")?;
let polars = expr.into_polars();
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() {
return Err(ShellError::Generic(GenericError::new(
"Found object series",
"Series of type object cannot be used for cumulative operation",
call.head,
)));
}
let mut res = match cum_type {
CumulativeType::Max => cum_max(&series, reverse),
CumulativeType::Min => cum_min(&series, reverse),
CumulativeType::Sum => cum_sum(&series, reverse),
}
.map_err(|e| {
ShellError::Generic(GenericError::new(
"Error creating cumulative",
e.to_string(),
call.head,
))
})?;
let name = format!("{}_{}", series.name(), cum_type.to_str());
res.rename(name.into());
let df = NuDataFrame::try_from_series_vec(vec![res.into_series()], call.head)?;
df.to_pipeline_data(plugin, engine, call.head)
}
#[cfg(test)]
mod test {
use super::*;
use crate::test::test_polars_plugin_command;
#[test]
fn test_examples() -> Result<(), ShellError> {
test_polars_plugin_command(&Cumulative)
}
}