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# Description This PR: - Removes the lazy_command, expr_command macros and migrates the commands that were utilizing them. - Removes the custom logic in DataFrameValues::is_equals to use the polars DataFrame version of PartialEq - Adds examples to commands that previously did not have examples or had inadequate ones. NOTE: A lot of examples now have a `polars sort` at the end. This is needed due to the comparison in the result. The new polars version of equals cares about the ordering. I removed the custom equals logic as it causes comparisons to lock up when comparing dataframes that contain a row that contains a list. I discovered this issue when adding examples to `polars implode`
177 lines
6.1 KiB
Rust
177 lines
6.1 KiB
Rust
use crate::{
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dataframe::values::{NuExpression, NuLazyFrame, NuLazyGroupBy},
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values::{Column, CustomValueSupport, NuDataFrame},
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PolarsPlugin,
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};
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use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
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use nu_protocol::{
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Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, SyntaxShape, Type,
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Value,
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};
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use polars::{datatypes::DataType, prelude::Expr};
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#[derive(Clone)]
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pub struct LazyAggregate;
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impl PluginCommand for LazyAggregate {
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type Plugin = PolarsPlugin;
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fn name(&self) -> &str {
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"polars agg"
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}
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fn description(&self) -> &str {
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"Performs a series of aggregations from a group-by."
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}
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fn signature(&self) -> Signature {
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Signature::build(self.name())
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.rest(
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"Group-by expressions",
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SyntaxShape::Any,
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"Expression(s) that define the aggregations to be applied",
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)
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.input_output_type(
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Type::Custom("dataframe".into()),
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Type::Custom("dataframe".into()),
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)
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.category(Category::Custom("lazyframe".into()))
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}
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fn examples(&self) -> Vec<Example> {
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vec![Example {
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description: "Group by and perform an aggregation",
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example: r#"[[a b]; [1 2] [1 4] [2 6] [2 4]]
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| polars into-lazy
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| polars group-by a
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| polars agg [
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(polars col b | polars min | polars as "b_min")
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(polars col b | polars max | polars as "b_max")
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(polars col b | polars sum | polars as "b_sum")
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]
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| polars collect
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| polars sort-by a"#,
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result: Some(
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NuDataFrame::try_from_columns(
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vec![
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Column::new(
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"a".to_string(),
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vec![Value::test_int(1), Value::test_int(2)],
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),
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Column::new(
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"b_min".to_string(),
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vec![Value::test_int(2), Value::test_int(4)],
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),
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Column::new(
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"b_max".to_string(),
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vec![Value::test_int(4), Value::test_int(6)],
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),
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Column::new(
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"b_sum".to_string(),
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vec![Value::test_int(6), Value::test_int(10)],
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),
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],
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None,
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)
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.expect("simple df for test should not fail")
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.into_value(Span::test_data()),
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),
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}]
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}
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fn run(
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&self,
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plugin: &Self::Plugin,
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engine: &EngineInterface,
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call: &EvaluatedCall,
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input: PipelineData,
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) -> Result<PipelineData, LabeledError> {
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let vals: Vec<Value> = call.rest(0)?;
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let value = Value::list(vals, call.head);
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let expressions = NuExpression::extract_exprs(plugin, value)?;
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let group_by = NuLazyGroupBy::try_from_pipeline(plugin, input, call.head)?;
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for expr in expressions.iter() {
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if let Some(name) = get_col_name(expr) {
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let dtype = group_by.schema.schema.get(name.as_str());
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if matches!(dtype, Some(DataType::Object(..))) {
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return Err(ShellError::GenericError {
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error: "Object type column not supported for aggregation".into(),
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msg: format!("Column '{name}' is type Object"),
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span: Some(call.head),
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help: Some("Aggregations cannot be performed on Object type columns. Use dtype command to check column types".into()),
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inner: vec![],
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}).map_err(|e| e.into());
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}
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}
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}
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let polars = group_by.to_polars();
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let lazy = NuLazyFrame::new(false, polars.agg(&expressions));
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lazy.to_pipeline_data(plugin, engine, call.head)
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.map_err(LabeledError::from)
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}
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}
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fn get_col_name(expr: &Expr) -> Option<String> {
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match expr {
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Expr::Column(column) => Some(column.to_string()),
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Expr::Agg(agg) => match agg {
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polars::prelude::AggExpr::Min { input: e, .. }
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| polars::prelude::AggExpr::Max { input: e, .. }
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| polars::prelude::AggExpr::Median(e)
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| polars::prelude::AggExpr::NUnique(e)
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| polars::prelude::AggExpr::First(e)
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| polars::prelude::AggExpr::Last(e)
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| polars::prelude::AggExpr::Mean(e)
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| polars::prelude::AggExpr::Implode(e)
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| polars::prelude::AggExpr::Count(e, _)
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| polars::prelude::AggExpr::Sum(e)
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| polars::prelude::AggExpr::AggGroups(e)
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| polars::prelude::AggExpr::Std(e, _)
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| polars::prelude::AggExpr::Var(e, _) => get_col_name(e.as_ref()),
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polars::prelude::AggExpr::Quantile { expr, .. } => get_col_name(expr.as_ref()),
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},
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Expr::Filter { input: expr, .. }
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| Expr::Slice { input: expr, .. }
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| Expr::Cast { expr, .. }
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| Expr::Sort { expr, .. }
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| Expr::Gather { expr, .. }
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| Expr::SortBy { expr, .. }
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| Expr::Exclude(expr, _)
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| Expr::Alias(expr, _)
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| Expr::KeepName(expr)
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| Expr::Explode(expr) => get_col_name(expr.as_ref()),
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Expr::Ternary { .. }
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| Expr::AnonymousFunction { .. }
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| Expr::Function { .. }
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| Expr::Columns(_)
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| Expr::DtypeColumn(_)
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| Expr::Literal(_)
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| Expr::BinaryExpr { .. }
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| Expr::Window { .. }
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| Expr::Wildcard
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| Expr::RenameAlias { .. }
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| Expr::Len
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| Expr::Nth(_)
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| Expr::SubPlan(_, _)
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| Expr::IndexColumn(_)
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| Expr::Selector(_)
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| Expr::Field(_) => None,
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}
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}
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#[cfg(test)]
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mod test {
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use super::*;
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use crate::test::test_polars_plugin_command;
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#[test]
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fn test_examples() -> Result<(), ShellError> {
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test_polars_plugin_command(&LazyAggregate)
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}
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}
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