nushell/src/commands/group_by.rs
Andrés N. Robalino 392ff286b2 This commit is ongoing work for making Nu working with data processing
a joy. Fundamentally we embrace functional programming principles for
transforming the dataset from any format picked up by Nu. This table
processing "primitive" commands will build up and make pipelines
composable with data processing capabilities allowing us the valuate,
reduce, and map, the tables as far as even composing this declartively.

On this regard, `split-by` expects some table with grouped data and we
can use it further in interesting ways (Eg. collecting labels for
visualizing the data in charts and/or suit it for a particular chart
of our interest).
2019-10-29 16:04:31 -05:00

190 lines
6.8 KiB
Rust

use crate::commands::WholeStreamCommand;
use crate::data::TaggedDictBuilder;
use crate::errors::ShellError;
use crate::prelude::*;
pub struct GroupBy;
#[derive(Deserialize)]
pub struct GroupByArgs {
column_name: Tagged<String>,
}
impl WholeStreamCommand for GroupBy {
fn name(&self) -> &str {
"group-by"
}
fn signature(&self) -> Signature {
Signature::build("group-by").required(
"column_name",
SyntaxShape::String,
"the name of the column to group by",
)
}
fn usage(&self) -> &str {
"Creates a new table with the data from the table rows grouped by the column given."
}
fn run(
&self,
args: CommandArgs,
registry: &CommandRegistry,
) -> Result<OutputStream, ShellError> {
args.process(registry, group_by)?.run()
}
}
pub fn group_by(
GroupByArgs { column_name }: GroupByArgs,
RunnableContext { input, name, .. }: RunnableContext,
) -> Result<OutputStream, ShellError> {
let stream = async_stream! {
let values: Vec<Tagged<Value>> = input.values.collect().await;
if values.is_empty() {
yield Err(ShellError::labeled_error(
"Expected table from pipeline",
"requires a table input",
column_name.span()
))
} else {
match group(&column_name, values, name) {
Ok(grouped) => yield ReturnSuccess::value(grouped),
Err(err) => yield Err(err)
}
}
};
Ok(stream.to_output_stream())
}
pub fn group(
column_name: &Tagged<String>,
values: Vec<Tagged<Value>>,
tag: impl Into<Tag>,
) -> Result<Tagged<Value>, ShellError> {
let tag = tag.into();
let mut groups = indexmap::IndexMap::new();
for value in values {
let group_key = value.get_data_by_key(column_name);
if group_key.is_none() {
let possibilities = value.data_descriptors();
let mut possible_matches: Vec<_> = possibilities
.iter()
.map(|x| (natural::distance::levenshtein_distance(x, column_name), x))
.collect();
possible_matches.sort();
if possible_matches.len() > 0 {
return Err(ShellError::labeled_error(
"Unknown column",
format!("did you mean '{}'?", possible_matches[0].1),
column_name.tag(),
));
} else {
return Err(ShellError::labeled_error(
"Unknown column",
"row does not contain this column",
column_name.tag(),
));
}
}
let group_key = group_key.unwrap().as_string()?;
let group = groups.entry(group_key).or_insert(vec![]);
group.push(value);
}
let mut out = TaggedDictBuilder::new(&tag);
for (k, v) in groups.iter() {
out.insert(k, Value::table(v));
}
Ok(out.into_tagged_value())
}
#[cfg(test)]
mod tests {
use crate::commands::group_by::group;
use crate::data::meta::*;
use crate::Value;
use indexmap::IndexMap;
fn string(input: impl Into<String>) -> Tagged<Value> {
Value::string(input.into()).tagged_unknown()
}
fn row(entries: IndexMap<String, Tagged<Value>>) -> Tagged<Value> {
Value::row(entries).tagged_unknown()
}
fn table(list: &Vec<Tagged<Value>>) -> Tagged<Value> {
Value::table(list).tagged_unknown()
}
#[test]
fn groups_table_by_key() {
let for_key = String::from("date").tagged_unknown();
let nu_releases = vec![
row(
indexmap! {"name".into() => string("AR"), "country".into() => string("EC"), "date".into() => string("August 23-2019")},
),
row(
indexmap! {"name".into() => string("JT"), "country".into() => string("NZ"), "date".into() => string("August 23-2019")},
),
row(
indexmap! {"name".into() => string("YK"), "country".into() => string("US"), "date".into() => string("October 10-2019")},
),
row(
indexmap! {"name".into() => string("AR"), "country".into() => string("EC"), "date".into() => string("Sept 24-2019")},
),
row(
indexmap! {"name".into() => string("JT"), "country".into() => string("NZ"), "date".into() => string("October 10-2019")},
),
row(
indexmap! {"name".into() => string("YK"), "country".into() => string("US"), "date".into() => string("Sept 24-2019")},
),
row(
indexmap! {"name".into() => string("AR"), "country".into() => string("EC"), "date".into() => string("October 10-2019")},
),
row(
indexmap! {"name".into() => string("JT"), "country".into() => string("NZ"), "date".into() => string("Sept 24-2019")},
),
row(
indexmap! {"name".into() => string("YK"), "country".into() => string("US"), "date".into() => string("August 23-2019")},
),
];
assert_eq!(
group(&for_key, nu_releases, Tag::unknown()).unwrap(),
row(indexmap! {
"August 23-2019".into() => table(&vec![
row(indexmap!{"name".into() => string("AR"), "country".into() => string("EC"), "date".into() => string("August 23-2019")}),
row(indexmap!{"name".into() => string("JT"), "country".into() => string("NZ"), "date".into() => string("August 23-2019")}),
row(indexmap!{"name".into() => string("YK"), "country".into() => string("US"), "date".into() => string("August 23-2019")})
]),
"October 10-2019".into() => table(&vec![
row(indexmap!{"name".into() => string("YK"), "country".into() => string("US"), "date".into() => string("October 10-2019")}),
row(indexmap!{"name".into() => string("JT"), "country".into() => string("NZ"), "date".into() => string("October 10-2019")}),
row(indexmap!{"name".into() => string("AR"), "country".into() => string("EC"), "date".into() => string("October 10-2019")})
]),
"Sept 24-2019".into() => table(&vec![
row(indexmap!{"name".into() => string("AR"), "country".into() => string("EC"), "date".into() => string("Sept 24-2019")}),
row(indexmap!{"name".into() => string("YK"), "country".into() => string("US"), "date".into() => string("Sept 24-2019")}),
row(indexmap!{"name".into() => string("JT"), "country".into() => string("NZ"), "date".into() => string("Sept 24-2019")})
]),
})
);
}
}