/// Definition of multiple lazyframe commands using a macro rule /// All of these commands have an identical body and only require /// to have a change in the name, description and function use crate::dataframe::values::{Column, NuDataFrame, NuLazyFrame}; use nu_protocol::{ ast::Call, engine::{Command, EngineState, Stack}, Category, Example, PipelineData, ShellError, Signature, Span, Type, Value, }; macro_rules! lazy_command { ($command: ident, $name: expr, $desc: expr, $examples: expr, $func: ident, $test: ident) => { #[derive(Clone)] pub struct $command; impl Command for $command { fn name(&self) -> &str { $name } fn usage(&self) -> &str { $desc } fn signature(&self) -> Signature { Signature::build(self.name()).category(Category::Custom("lazyframe".into())) } fn examples(&self) -> Vec { $examples } fn input_type(&self) -> Type { Type::Custom("dataframe".into()) } fn output_type(&self) -> Type { Type::Custom("dataframe".into()) } fn run( &self, _engine_state: &EngineState, _stack: &mut Stack, call: &Call, input: PipelineData, ) -> Result { let lazy = NuLazyFrame::try_from_pipeline(input, call.head)?; let lazy = NuLazyFrame::new(lazy.from_eager, lazy.into_polars().$func()); Ok(PipelineData::Value(lazy.into_value(call.head)?, None)) } } #[cfg(test)] mod $test { use super::super::super::test_dataframe::test_dataframe; use super::*; #[test] fn test_examples() { test_dataframe(vec![Box::new($command {})]) } } }; } // LazyReverse command // Expands to a command definition for reverse lazy_command!( LazyReverse, "reverse", "Reverses the LazyFrame", vec![Example { description: "Reverses the dataframe", example: "[[a b]; [6 2] [4 2] [2 2]] | to-df | reverse", result: Some( NuDataFrame::try_from_columns(vec![ Column::new( "a".to_string(), vec![Value::test_int(2), Value::test_int(4), Value::test_int(6),], ), Column::new( "b".to_string(), vec![Value::test_int(2), Value::test_int(2), Value::test_int(2),], ), ]) .expect("simple df for test should not fail") .into_value(Span::test_data()), ), },], reverse, test_reverse ); // LazyCache command // Expands to a command definition for cache lazy_command!( LazyCache, "cache", "Caches operations in a new LazyFrame", vec![Example { description: "Caches the result into a new LazyFrame", example: "[[a b]; [6 2] [4 2] [2 2]] | to-df | reverse | cache", result: None, }], cache, test_cache ); // LazyMax command // Expands to a command definition for max aggregation lazy_command!( LazyMax, "max", "Aggregates columns to their max value", vec![Example { description: "Max value from columns in a dataframe", example: "[[a b]; [6 2] [1 4] [4 1]] | to-df | max", result: Some( NuDataFrame::try_from_columns(vec![ Column::new("a".to_string(), vec![Value::test_int(6)],), Column::new("b".to_string(), vec![Value::test_int(4)],), ]) .expect("simple df for test should not fail") .into_value(Span::test_data()), ), },], max, test_max ); // LazyMin command // Expands to a command definition for min aggregation lazy_command!( LazyMin, "min", "Aggregates columns to their min value", vec![Example { description: "Min value from columns in a dataframe", example: "[[a b]; [6 2] [1 4] [4 1]] | to-df | min", result: Some( NuDataFrame::try_from_columns(vec![ Column::new("a".to_string(), vec![Value::test_int(1)],), Column::new("b".to_string(), vec![Value::test_int(1)],), ]) .expect("simple df for test should not fail") .into_value(Span::test_data()), ), },], min, test_min ); // LazySum command // Expands to a command definition for sum aggregation lazy_command!( LazySum, "sum", "Aggregates columns to their sum value", vec![Example { description: "Sums all columns in a dataframe", example: "[[a b]; [6 2] [1 4] [4 1]] | to-df | sum", result: Some( NuDataFrame::try_from_columns(vec![ Column::new("a".to_string(), vec![Value::test_int(11)],), Column::new("b".to_string(), vec![Value::test_int(7)],), ]) .expect("simple df for test should not fail") .into_value(Span::test_data()), ), },], sum, test_sum ); // LazyMean command // Expands to a command definition for mean aggregation lazy_command!( LazyMean, "mean", "Aggregates columns to their mean value", vec![Example { description: "Mean value from columns in a dataframe", example: "[[a b]; [6 2] [4 2] [2 2]] | to-df | mean", result: Some( NuDataFrame::try_from_columns(vec![ Column::new("a".to_string(), vec![Value::test_float(4.0)],), Column::new("b".to_string(), vec![Value::test_float(2.0)],), ]) .expect("simple df for test should not fail") .into_value(Span::test_data()), ), },], mean, test_mean ); // LazyMedian command // Expands to a command definition for median aggregation lazy_command!( LazyMedian, "median", "Aggregates columns to their median value", vec![Example { description: "Median value from columns in a dataframe", example: "[[a b]; [6 2] [4 2] [2 2]] | to-df | median", result: Some( NuDataFrame::try_from_columns(vec![ Column::new("a".to_string(), vec![Value::test_float(4.0)],), Column::new("b".to_string(), vec![Value::test_float(2.0)],), ]) .expect("simple df for test should not fail") .into_value(Span::test_data()), ), },], median, test_median ); // LazyStd command // Expands to a command definition for std aggregation lazy_command!( LazyStd, "std", "Aggregates columns to their std value", vec![Example { description: "Std value from columns in a dataframe", example: "[[a b]; [6 2] [4 2] [2 2]] | to-df | std", result: Some( NuDataFrame::try_from_columns(vec![ Column::new("a".to_string(), vec![Value::test_float(2.0)],), Column::new("b".to_string(), vec![Value::test_float(0.0)],), ]) .expect("simple df for test should not fail") .into_value(Span::test_data()), ), },], std, test_std ); // LazyVar command // Expands to a command definition for var aggregation lazy_command!( LazyVar, "var", "Aggregates columns to their var value", vec![Example { description: "Var value from columns in a dataframe", example: "[[a b]; [6 2] [4 2] [2 2]] | to-df | var", result: Some( NuDataFrame::try_from_columns(vec![ Column::new("a".to_string(), vec![Value::test_float(4.0)],), Column::new("b".to_string(), vec![Value::test_float(0.0)],), ]) .expect("simple df for test should not fail") .into_value(Span::test_data()), ), },], var, test_var );