forked from extern/nushell
# Description This PR does a few things to help improve type hovers and, in the process, fixes a few outstanding issues in the type system. Here's a list of the changes: * `for` now will try to infer the type of the iteration variable based on the expression it's given. This fixes things like `for x in [1, 2, 3] { }` where `x` now properly gets the int type. * Removed old input/output type fields from the signature, focuses on the vec of signatures. Updated a bunch of dataframe commands that hadn't moved over. This helps tie things together a bit better * Fixed inference of types from subexpressions to use the last expression in the block * Fixed handling of explicit types in `let` and `mut` calls, so we now respect that as the authoritative type I also tried to add `def` input/output type inference, but unfortunately we only know the predecl types universally, which means we won't have enough information to properly know what the types of the custom commands are. # User-Facing Changes Script typechecking will get tighter in some cases Hovers should be more accurate in some cases that previously resorted to any. # Tests + Formatting <!-- Don't forget to add tests that cover your changes. Make sure you've run and fixed any issues with these commands: - `cargo fmt --all -- --check` to check standard code formatting (`cargo fmt --all` applies these changes) - `cargo clippy --workspace -- -D warnings -D clippy::unwrap_used -A clippy::needless_collect -A clippy::result_large_err` to check that you're using the standard code style - `cargo test --workspace` to check that all tests pass - `cargo run -- crates/nu-std/tests/run.nu` to run the tests for the standard library > **Note** > from `nushell` you can also use the `toolkit` as follows > ```bash > use toolkit.nu # or use an `env_change` hook to activate it automatically > toolkit check pr > ``` --> # After Submitting <!-- If your PR had any user-facing changes, update [the documentation](https://github.com/nushell/nushell.github.io) after the PR is merged, if necessary. This will help us keep the docs up to date. --> --------- Co-authored-by: Darren Schroeder <343840+fdncred@users.noreply.github.com>
154 lines
4.3 KiB
Rust
154 lines
4.3 KiB
Rust
use crate::dataframe::{utils::extract_strings, values::NuLazyFrame};
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use super::super::values::{Column, NuDataFrame};
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use nu_engine::CallExt;
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use nu_protocol::{
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ast::Call,
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engine::{Command, EngineState, Stack},
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Category, Example, PipelineData, ShellError, Signature, Span, SyntaxShape, Type, Value,
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};
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use polars::prelude::{IntoSeries, UniqueKeepStrategy};
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#[derive(Clone)]
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pub struct Unique;
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impl Command for Unique {
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fn name(&self) -> &str {
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"dfr unique"
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}
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fn usage(&self) -> &str {
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"Returns unique values from a dataframe."
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}
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fn signature(&self) -> Signature {
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Signature::build(self.name())
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.named(
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"subset",
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SyntaxShape::Any,
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"Subset of column(s) to use to maintain rows (lazy df)",
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Some('s'),
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)
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.switch(
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"last",
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"Keeps last unique value. Default keeps first value (lazy df)",
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Some('l'),
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)
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.switch(
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"maintain-order",
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"Keep the same order as the original DataFrame (lazy df)",
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Some('k'),
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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("dataframe or lazyframe".into()))
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}
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fn examples(&self) -> Vec<Example> {
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vec![
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Example {
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description: "Returns unique values from a series",
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example: "[2 2 2 2 2] | dfr into-df | dfr unique",
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result: Some(
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NuDataFrame::try_from_columns(vec![Column::new(
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"0".to_string(),
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vec![Value::test_int(2)],
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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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Example {
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description: "Creates a is unique expression from a column",
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example: "col a | unique",
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result: None,
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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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engine_state: &EngineState,
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stack: &mut Stack,
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call: &Call,
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input: PipelineData,
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) -> Result<PipelineData, ShellError> {
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let value = input.into_value(call.head);
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if NuLazyFrame::can_downcast(&value) {
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let df = NuLazyFrame::try_from_value(value)?;
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command_lazy(engine_state, stack, call, df)
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} else {
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let df = NuDataFrame::try_from_value(value)?;
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command_eager(engine_state, stack, call, df)
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}
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}
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}
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fn command_eager(
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_engine_state: &EngineState,
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_stack: &mut Stack,
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call: &Call,
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df: NuDataFrame,
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) -> Result<PipelineData, ShellError> {
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let series = df.as_series(call.head)?;
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let res = series.unique().map_err(|e| {
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ShellError::GenericError(
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"Error calculating unique values".into(),
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e.to_string(),
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Some(call.head),
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Some("The str-slice command can only be used with string columns".into()),
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Vec::new(),
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)
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})?;
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NuDataFrame::try_from_series(vec![res.into_series()], call.head)
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.map(|df| PipelineData::Value(NuDataFrame::into_value(df, call.head), None))
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}
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fn command_lazy(
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engine_state: &EngineState,
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stack: &mut Stack,
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call: &Call,
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lazy: NuLazyFrame,
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) -> Result<PipelineData, ShellError> {
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let last = call.has_flag("last");
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let maintain = call.has_flag("maintain-order");
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let subset: Option<Value> = call.get_flag(engine_state, stack, "subset")?;
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let subset = match subset {
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Some(value) => Some(extract_strings(value)?),
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None => None,
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};
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let strategy = if last {
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UniqueKeepStrategy::Last
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} else {
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UniqueKeepStrategy::First
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};
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let lazy = lazy.into_polars();
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let lazy: NuLazyFrame = if maintain {
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lazy.unique(subset, strategy).into()
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} else {
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lazy.unique_stable(subset, strategy).into()
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};
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Ok(PipelineData::Value(lazy.into_value(call.head)?, None))
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}
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#[cfg(test)]
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mod test {
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use super::super::super::test_dataframe::test_dataframe;
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use super::*;
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#[test]
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fn test_examples() {
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test_dataframe(vec![Box::new(Unique {})])
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}
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}
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