nushell/crates/nu-command/src/dataframe/eager/list.rs
Leon 220b105efb
Reduced LOC by replacing several instances of Value::Int {}, Value::Float{}, Value::Bool {}, and Value::String {} with Value::int(), Value::float(), Value::boolean() and Value::string() (#7412)
# Description

While perusing Value.rs, I noticed the `Value::int()`, `Value::float()`,
`Value::boolean()` and `Value::string()` constructors, which seem
designed to make it easier to construct various Values, but which aren't
used often at all in the codebase. So, using a few find-replaces
regexes, I increased their usage. This reduces overall LOC because
structures like this:
```
Value::Int {
  val: a,
  span: head
}
```
are changed into
```
Value::int(a, head)
```
and are respected as such by the project's formatter.
There are little readability concerns because the second argument to all
of these is `span`, and it's almost always extremely obvious which is
the span at every callsite.

# User-Facing Changes

None.

# 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` to check that you're using the standard code
style
- `cargo test --workspace` to check that all tests pass

# 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.
2022-12-09 11:37:51 -05:00

91 lines
2.4 KiB
Rust

use nu_protocol::{
ast::Call,
engine::{Command, EngineState, Stack},
Category, Example, IntoPipelineData, PipelineData, ShellError, Signature, Value,
};
use crate::dataframe::values::NuDataFrame;
#[derive(Clone)]
pub struct ListDF;
impl Command for ListDF {
fn name(&self) -> &str {
"ls-df"
}
fn usage(&self) -> &str {
"Lists stored dataframes"
}
fn signature(&self) -> Signature {
Signature::build(self.name()).category(Category::Custom("dataframe".into()))
}
fn examples(&self) -> Vec<Example> {
vec![Example {
description: "Creates a new dataframe and shows it in the dataframe list",
example: r#"let test = ([[a b];[1 2] [3 4]] | into df);
ls-df"#,
result: None,
}]
}
fn run(
&self,
engine_state: &EngineState,
stack: &mut Stack,
call: &Call,
_input: PipelineData,
) -> Result<PipelineData, ShellError> {
let mut vals: Vec<(String, Value)> = vec![];
for overlay_frame in engine_state.active_overlays(&[]) {
for var in &overlay_frame.vars {
if let Ok(value) = stack.get_var(*var.1, call.head) {
let name = String::from_utf8_lossy(var.0).to_string();
vals.push((name, value));
}
}
}
let vals = vals
.into_iter()
.filter_map(|(name, value)| match NuDataFrame::try_from_value(value) {
Ok(df) => Some((name, df)),
Err(_) => None,
})
.map(|(name, df)| {
let name = Value::String {
val: name,
span: call.head,
};
let columns = Value::int(df.as_ref().width() as i64, call.head);
let rows = Value::int(df.as_ref().height() as i64, call.head);
let cols = vec![
"name".to_string(),
"columns".to_string(),
"rows".to_string(),
];
let vals = vec![name, columns, rows];
Value::Record {
cols,
vals,
span: call.head,
}
})
.collect::<Vec<Value>>();
let list = Value::List {
vals,
span: call.head,
};
Ok(list.into_pipeline_data())
}
}