nushell/crates/nu_plugin_polars/src/dataframe/eager/to_df.rs
2024-07-25 11:36:55 +08:00

281 lines
11 KiB
Rust

use crate::{
dataframe::values::NuSchema,
values::{Column, CustomValueSupport},
PolarsPlugin,
};
use super::super::values::NuDataFrame;
use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
use nu_protocol::{
Category, Example, LabeledError, PipelineData, Signature, Span,
SyntaxShape, Type, Value,
};
use polars::{
prelude::{AnyValue, DataType, Field, NamedFrom},
series::Series,
};
#[derive(Clone)]
pub struct ToDataFrame;
impl PluginCommand for ToDataFrame {
type Plugin = PolarsPlugin;
fn name(&self) -> &str {
"polars into-df"
}
fn usage(&self) -> &str {
"Converts a list, table or record into a dataframe."
}
fn signature(&self) -> Signature {
Signature::build(self.name())
.named(
"schema",
SyntaxShape::Record(vec![]),
r#"Polars Schema in format [{name: str}]. CSV, JSON, and JSONL files"#,
Some('s'),
)
.switch(
"as-columns",
r#"When input shape is record of lists, treat each list as column values."#,
Some('c'),
)
.input_output_type(Type::Any, Type::Custom("dataframe".into()))
.category(Category::Custom("dataframe".into()))
}
fn examples(&self) -> Vec<Example> {
vec![
Example {
description: "Takes a dictionary and creates a dataframe",
example: "[[a b];[1 2] [3 4]] | polars into-df",
result: Some(
NuDataFrame::try_from_columns(
vec![
Column::new(
"a".to_string(),
vec![Value::test_int(1), Value::test_int(3)],
),
Column::new(
"b".to_string(),
vec![Value::test_int(2), Value::test_int(4)],
),
],
None,
)
.expect("simple df for test should not fail")
.into_value(Span::test_data()),
),
},
Example {
description: "Takes a record of lists and creates a dataframe",
example: "{a: [1 3], b: [2 4]} | polars into-df --as-columns",
result: Some(
NuDataFrame::try_from_columns(
vec![
Column::new(
"a".to_string(),
vec![Value::test_int(1), Value::test_int(3)],
),
Column::new(
"b".to_string(),
vec![Value::test_int(2), Value::test_int(4)],
),
],
None,
)
.expect("simple df for test should not fail")
.into_value(Span::test_data()),
),
},
Example {
description: "Takes a list of tables and creates a dataframe",
example: "[[1 2 a] [3 4 b] [5 6 c]] | polars into-df",
result: Some(
NuDataFrame::try_from_columns(
vec![
Column::new(
"0".to_string(),
vec![Value::test_int(1), Value::test_int(3), Value::test_int(5)],
),
Column::new(
"1".to_string(),
vec![Value::test_int(2), Value::test_int(4), Value::test_int(6)],
),
Column::new(
"2".to_string(),
vec![
Value::test_string("a"),
Value::test_string("b"),
Value::test_string("c"),
],
),
],
None,
)
.expect("simple df for test should not fail")
.into_value(Span::test_data()),
),
},
Example {
description: "Takes a list and creates a dataframe",
example: "[a b c] | polars into-df",
result: Some(
NuDataFrame::try_from_columns(
vec![Column::new(
"0".to_string(),
vec![
Value::test_string("a"),
Value::test_string("b"),
Value::test_string("c"),
],
)],
None,
)
.expect("simple df for test should not fail")
.into_value(Span::test_data()),
),
},
Example {
description: "Takes a list of booleans and creates a dataframe",
example: "[true true false] | polars into-df",
result: Some(
NuDataFrame::try_from_columns(
vec![Column::new(
"0".to_string(),
vec![
Value::test_bool(true),
Value::test_bool(true),
Value::test_bool(false),
],
)],
None,
)
.expect("simple df for test should not fail")
.into_value(Span::test_data()),
),
},
Example {
description: "Convert to a dataframe and provide a schema",
example: "{a: 1, b: {a: [1 2 3]}, c: [a b c]}| polars into-df -s {a: u8, b: {a: list<u64>}, c: list<str>}",
result: Some(
NuDataFrame::try_from_series_vec(vec![
Series::new("a", &[1u8]),
{
let dtype = DataType::Struct(vec![Field::new("a", DataType::List(Box::new(DataType::UInt64)))]);
let vals = vec![AnyValue::StructOwned(
Box::new((vec![AnyValue::List(Series::new("a", &[1u64, 2, 3]))], vec![Field::new("a", DataType::String)]))); 1];
Series::from_any_values_and_dtype("b", &vals, &dtype, false)
.expect("Struct series should not fail")
},
{
let dtype = DataType::List(Box::new(DataType::String));
let vals = vec![AnyValue::List(Series::new("c", &["a", "b", "c"]))];
Series::from_any_values_and_dtype("c", &vals, &dtype, false)
.expect("List series should not fail")
}
], Span::test_data())
.expect("simple df for test should not fail")
.into_value(Span::test_data()),
),
},
Example {
description: "Convert to a dataframe and provide a schema that adds a new column",
example: r#"[[a b]; [1 "foo"] [2 "bar"]] | polars into-df -s {a: u8, b:str, c:i64} | polars fill-null 3"#,
result: Some(NuDataFrame::try_from_series_vec(vec![
Series::new("a", [1u8, 2]),
Series::new("b", ["foo", "bar"]),
Series::new("c", [3i64, 3]),
], Span::test_data())
.expect("simple df for test should not fail")
.into_value(Span::test_data()),
),
}
]
}
fn run(
&self,
plugin: &Self::Plugin,
engine: &EngineInterface,
call: &EvaluatedCall,
input: PipelineData,
) -> Result<PipelineData, LabeledError> {
let maybe_schema = call
.get_flag("schema")?
.map(|schema| NuSchema::try_from(&schema))
.transpose()?;
let maybe_as_columns = call.has_flag("as-columns")?;
let df = if !maybe_as_columns {
NuDataFrame::try_from_iter(plugin, input.into_iter(), maybe_schema.clone())?
} else {
match &input {
PipelineData::Value(Value::Record { val, .. }, _) => {
let items: Result<Vec<(String, Vec<Value>)>, &str> = val
.iter()
.map(|(k, v)| match v.to_owned().into_list() {
Ok(v) => Ok((k.to_owned(), v)),
_ => Err("error"),
})
.collect();
match items {
Ok(items) => {
let columns = items
.iter()
.map(|(k, v)| Column::new(k.to_owned(), v.to_owned()))
.collect::<Vec<Column>>();
NuDataFrame::try_from_columns(columns, maybe_schema)?
}
Err(_) => NuDataFrame::try_from_iter(
plugin,
input.into_iter(),
maybe_schema.clone(),
)?,
}
}
_ => NuDataFrame::try_from_iter(plugin, input.into_iter(), maybe_schema.clone())?,
}
};
// let df = match &input {
// PipelineData::Value(Value::Record {val, ..}, _) => {
// let items: Result<Vec<(String, Vec<Value>)>,&str> = val.iter().map(
// |(k, v)| match v.to_owned().into_list() {
// Ok(v) => Ok((k.to_owned(), v)),
// _ => Err("error")
// }
// ).collect();
// match items {
// Ok(items) => {
// let columns = items.iter().map(|(k, v)| Column::new(k.to_owned(), v.to_owned())).collect::<Vec<Column>>();
// NuDataFrame::try_from_columns(columns, maybe_schema)?
// },
// Err(_) => NuDataFrame::try_from_iter(plugin, input.into_iter(), maybe_schema.clone())?
// }
// },
// _ => NuDataFrame::try_from_iter(plugin, input.into_iter(), maybe_schema.clone())?
// };
// let df = NuDataFrame::try_from_iter(plugin, input.into_iter(), maybe_schema.clone())?;
df.to_pipeline_data(plugin, engine, call.head)
.map_err(LabeledError::from)
}
}
#[cfg(test)]
mod test {
use crate::test::test_polars_plugin_command;
use super::*;
use nu_protocol::ShellError;
#[test]
fn test_into_df() -> Result<(), ShellError> {
test_polars_plugin_command(&ToDataFrame)
}
}