forked from extern/nushell
9068093081
# 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>
112 lines
3.2 KiB
Rust
112 lines
3.2 KiB
Rust
use super::super::super::values::{Column, NuDataFrame};
|
|
|
|
use nu_engine::CallExt;
|
|
use nu_protocol::{
|
|
ast::Call,
|
|
engine::{Command, EngineState, Stack},
|
|
Category, Example, PipelineData, ShellError, Signature, Span, SyntaxShape, Type, Value,
|
|
};
|
|
use polars::prelude::IntoSeries;
|
|
|
|
#[derive(Clone)]
|
|
pub struct StrFTime;
|
|
|
|
impl Command for StrFTime {
|
|
fn name(&self) -> &str {
|
|
"dfr strftime"
|
|
}
|
|
|
|
fn usage(&self) -> &str {
|
|
"Formats date based on string rule."
|
|
}
|
|
|
|
fn signature(&self) -> Signature {
|
|
Signature::build(self.name())
|
|
.required("fmt", SyntaxShape::String, "Format rule")
|
|
.input_output_type(
|
|
Type::Custom("dataframe".into()),
|
|
Type::Custom("dataframe".into()),
|
|
)
|
|
.category(Category::Custom("dataframe".into()))
|
|
}
|
|
|
|
fn examples(&self) -> Vec<Example> {
|
|
vec![Example {
|
|
description: "Formats date",
|
|
example: r#"let dt = ('2020-08-04T16:39:18+00:00' | into datetime -z 'UTC');
|
|
let df = ([$dt $dt] | dfr into-df);
|
|
$df | dfr strftime "%Y/%m/%d""#,
|
|
result: Some(
|
|
NuDataFrame::try_from_columns(vec![Column::new(
|
|
"0".to_string(),
|
|
vec![
|
|
Value::test_string("2020/08/04"),
|
|
Value::test_string("2020/08/04"),
|
|
],
|
|
)])
|
|
.expect("simple df for test should not fail")
|
|
.into_value(Span::test_data()),
|
|
),
|
|
}]
|
|
}
|
|
|
|
fn run(
|
|
&self,
|
|
engine_state: &EngineState,
|
|
stack: &mut Stack,
|
|
call: &Call,
|
|
input: PipelineData,
|
|
) -> Result<PipelineData, ShellError> {
|
|
command(engine_state, stack, call, input)
|
|
}
|
|
}
|
|
|
|
fn command(
|
|
engine_state: &EngineState,
|
|
stack: &mut Stack,
|
|
call: &Call,
|
|
input: PipelineData,
|
|
) -> Result<PipelineData, ShellError> {
|
|
let fmt: String = call.req(engine_state, stack, 0)?;
|
|
|
|
let df = NuDataFrame::try_from_pipeline(input, call.head)?;
|
|
let series = df.as_series(call.head)?;
|
|
|
|
let casted = series.datetime().map_err(|e| {
|
|
ShellError::GenericError(
|
|
"Error casting to date".into(),
|
|
e.to_string(),
|
|
Some(call.head),
|
|
Some("The str-slice command can only be used with string columns".into()),
|
|
Vec::new(),
|
|
)
|
|
})?;
|
|
|
|
let res = casted
|
|
.strftime(&fmt)
|
|
.map_err(|e| {
|
|
ShellError::GenericError(
|
|
"Error formatting datetime".into(),
|
|
e.to_string(),
|
|
Some(call.head),
|
|
None,
|
|
Vec::new(),
|
|
)
|
|
})?
|
|
.into_series();
|
|
|
|
NuDataFrame::try_from_series(vec![res.into_series()], call.head)
|
|
.map(|df| PipelineData::Value(NuDataFrame::into_value(df, call.head), None))
|
|
}
|
|
|
|
#[cfg(explore_refactor_IntoDatetime)]
|
|
mod test {
|
|
use super::super::super::super::super::IntoDatetime;
|
|
use super::super::super::super::test_dataframe::test_dataframe;
|
|
use super::*;
|
|
#[test]
|
|
fn test_examples() {
|
|
test_dataframe(vec![Box::new(StrFTime {}), Box::new(IntoDatetime {})])
|
|
}
|
|
}
|