Lib.rs

› Database interfaces
#polars #dataframe #plotters #egui #proc-macro #gui

macro iter-tuple

Rust iterator for tuple through proc-macro2 struct Vec AnyValue of polars DataFrame

by nomissbowling

2 releases

0.3.8 Aug 18, 2024
0.3.7 Aug 17, 2024
0.2.5 Aug 11, 2024
0.1.3 Aug 6, 2024
0.1.2 Jul 28, 2024

#2303 in Database interfaces


Used in 2 crates

MIT license

25KB
411 lines

iter-tuple

Rust iterator for tuple through proc-macro2 struct Vec AnyValue of polars DataFrame

How to use

use iter_tuple::tuple_derive;
use iter_tuple::tuple_sqlite3; // optional (must use with tuple_derive)
use iter_tuple::struct_derive; // optional (must use with tuple_sqlite3)
use polars::prelude::{DataFrame, AnyValue, Schema}; // , Field, DataType
use anyvalue_dataframe::{row_schema, named_schema, to_any};

/// auto defines struct StTpl and sqlite3 trait with struct_derive (optional)
#[struct_derive((id, string), (UInt64, Utf8))]
/// auto defines sqlite3 trait for RecTpl with tuple_sqlite3 (optional)
#[tuple_sqlite3(UInt64, Utf8)]
/// auto defines struct RecTpl with tuple_derive
#[tuple_derive(UInt64, Utf8)]
pub type Tpl<'a> = (u64, &'a str);

pub fn main() {
  let rows = [
    (0, "a"),
    (1, "b"),
    (2, "c")
  ].into_iter().map(|r|
    row_schema(RecTpl::into_iter(r).collect())
    // row_schema(RecTpl::from(r).into_iter().collect()) // same as above
  ).collect::<Vec<_>>();

  let schema = Schema::from(&rows[0]);
  let df = DataFrame::from_rows_iter_and_schema(rows.iter(), &schema);
  let mut df = df.expect("create DataFrame");
  let n = vec!["id", "string"];
  df.set_column_names(&n).expect("set column names");
  let sc = named_schema(&df, n);
  assert_eq!(df.schema(), sc); // OK all

  let df = df.select(["string", "id"]).expect("select columns");
  println!("{:?}", df.head(Some(100)));
}

Sample

Requirements

Optional

License

MIT License

Dependencies

~215–650KB
~16K SLoC