JT 1e3e034021
Spanned Value step 1: span all value cases (#10042)
# Description

This doesn't really do much that the user could see, but it helps get us
ready to do the steps of the refactor to split the span off of Value, so
that values can be spanless. This allows us to have top-level values
that can hold both a Value and a Span, without requiring that all values
have them.

We expect to see significant memory reduction by removing so many
unnecessary spans from values. For example, a table of 100,000 rows and
5 columns would have a savings of ~8megs in just spans that are almost
always duplicated.

# User-Facing Changes

Nothing yet

# Tests + Formatting
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2023-08-25 08:48:05 +12:00

120 lines
4.2 KiB
Rust

use indexmap::map::IndexMap;
use nu_protocol::ast::Call;
use nu_protocol::{IntoPipelineData, PipelineData, Record, ShellError, Span, Value};
pub fn run_with_function(
call: &Call,
input: PipelineData,
mf: impl Fn(&[Value], Span, Span) -> Result<Value, ShellError>,
) -> Result<PipelineData, ShellError> {
let name = call.head;
let res = calculate(input, name, mf);
match res {
Ok(v) => Ok(v.into_pipeline_data()),
Err(e) => Err(e),
}
}
fn helper_for_tables(
values: &[Value],
val_span: Span,
name: Span,
mf: impl Fn(&[Value], Span, Span) -> Result<Value, ShellError>,
) -> Result<Value, ShellError> {
// If we are not dealing with Primitives, then perhaps we are dealing with a table
// Create a key for each column name
let mut column_values = IndexMap::new();
for val in values {
match val {
Value::Record { val, .. } => {
for (key, value) in val {
column_values
.entry(key.clone())
.and_modify(|v: &mut Vec<Value>| v.push(value.clone()))
.or_insert_with(|| vec![value.clone()]);
}
}
Value::Error { error, .. } => return Err(*error.clone()),
_ => {
//Turns out we are not dealing with a table
return mf(values, val.span(), name);
}
}
}
// The mathematical function operates over the columns of the table
let mut column_totals = IndexMap::new();
for (col_name, col_vals) in column_values {
if let Ok(out) = mf(&col_vals, val_span, name) {
column_totals.insert(col_name, out);
}
}
if column_totals.keys().len() == 0 {
return Err(ShellError::UnsupportedInput(
"Unable to give a result with this input".to_string(),
"value originates from here".into(),
name,
val_span,
));
}
Ok(Value::record(column_totals.into_iter().collect(), name))
}
pub fn calculate(
values: PipelineData,
name: Span,
mf: impl Fn(&[Value], Span, Span) -> Result<Value, ShellError>,
) -> Result<Value, ShellError> {
// TODO implement spans for ListStream, thus negating the need for unwrap_or().
let span = values.span().unwrap_or(name);
match values {
PipelineData::ListStream(s, ..) => {
helper_for_tables(&s.collect::<Vec<Value>>(), span, name, mf)
}
PipelineData::Value(Value::List { ref vals, span }, ..) => match &vals[..] {
[Value::Record { .. }, _end @ ..] => helper_for_tables(
vals,
values.span().expect("PipelineData::Value had no span"),
name,
mf,
),
_ => mf(vals, span, name),
},
PipelineData::Value(Value::Record { val: record, span }, ..) => {
let new_vals: Result<Vec<Value>, ShellError> = record
.vals
.into_iter()
.map(|val| mf(&[val], span, name))
.collect();
match new_vals {
Ok(vec) => Ok(Value::record(
Record {
cols: record.cols,
vals: vec,
},
span,
)),
Err(err) => Err(err),
}
}
PipelineData::Value(Value::Range { val, span, .. }, ..) => {
let new_vals: Result<Vec<Value>, ShellError> = val
.into_range_iter(None)?
.map(|val| mf(&[val], span, name))
.collect();
mf(&new_vals?, span, name)
}
PipelineData::Value(val, ..) => mf(&[val], span, name),
PipelineData::Empty { .. } => Err(ShellError::PipelineEmpty { dst_span: name }),
val => Err(ShellError::UnsupportedInput(
"Only integers, floats, lists, records or ranges are supported".into(),
"value originates from here".into(),
name,
// This requires both the ListStream and Empty match arms to be above it.
val.span()
.expect("non-Empty non-ListStream PipelineData had no span"),
)),
}
}