polars_rows_iter/lib.rs
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//! # Polars rows iterator
//!
//! Simple and convenient iteration of polars dataframe rows.
//!
//! ##### Example: Dataframe without None/null values:
//! ```rust
//!use polars::prelude::*;
//!use polars_rows_iter::*;
//!
//!fn main() {
//! #[derive(Debug, FromDataFrameRow)]
//! #[derive(PartialEq)] // for assert_eq
//! struct MyRow<'a>
//! {
//! #[column("col_a")]
//! a: i32,
//! // the column name defaults to the field name if no explicit name given
//! col_b: &'a str,
//! col_c: String,
//! #[column("col_d")]
//! optional: Option<f64>
//! }
//!
//! let df = df!(
//! "col_a" => [1i32, 2, 3, 4, 5],
//! "col_b" => ["a", "b", "c", "d", "e"],
//! "col_c" => ["A", "B", "C", "D", "E"],
//! "col_d" => [Some(1.0f64), None, None, Some(2.0), Some(3.0)]
//! ).unwrap();
//!
//! let rows_iter = df.rows_iter::<MyRow>().unwrap(); // ready to use row iterator
//! // collect to vector for assert_eq
//! let rows_vec = rows_iter.collect::<PolarsResult<Vec<MyRow>>>().unwrap();
//!
//! assert_eq!(
//! rows_vec,
//! [
//! MyRow { a: 1, col_b: "a", col_c: "A".to_string(), optional: Some(1.0) },
//! MyRow { a: 2, col_b: "b", col_c: "B".to_string(), optional: None },
//! MyRow { a: 3, col_b: "c", col_c: "C".to_string(), optional: None },
//! MyRow { a: 4, col_b: "d", col_c: "D".to_string(), optional: Some(2.0) },
//! MyRow { a: 5, col_b: "e", col_c: "E".to_string(), optional: Some(3.0) },
//! ]
//! );
//!}
//! ```
//! Every row is wrapped with a PolarsError, in case of an unexpected null value the row creation fails and the iterator
//! returns an Err(...) for the row. One can decide to cancel the iteration or to skip the affected row.
//!
//! ## Supported types
//!
//! |State|Rust Type|Supported Polars DataType|Feature Flag|
//! |--|--|--|--|
//! |✓|`bool`|`Boolean`
//! |✓|`u8`|`UInt8`
//! |✓|`u16`|`UInt16`
//! |✓|`u32`|`UInt32`
//! |✓|`u64`|`UInt64`
//! |✓|`i8`|`Int8`
//! |✓|`i16`|`Int16`
//! |✓|`i32`|`Int32`
//! |✓|`i32`|`Date`
//! |✓|`i64`|`Int64`
//! |✓|`i64`|`Datetime(..)`
//! |✓|`i64`|`Duration(..)`
//! |✓|`i64`|`Time`
//! |✓|`f32`|`Float32`
//! |✓|`f64`|`Float64`
//! |✓|`&str`|`String`
//! |✓|`&str`|`Categorical(..)`|`dtype-categorical`
//! |✓|`&str`|`Enum(..)`|`dtype-categorical`
//! |✓|`String`|`String`
//! |✓|`String`|`Categorical(..)`|`dtype-categorical`
//! |✓|`String`|`Enum(..)`|`dtype-categorical`
//! |✓|`&[u8]`|`Binary`
//! |✓|`&[u8]`|`BinaryOffset`
//! |✓|`Series`|`List(..)`
//! |✓|`chrono::NaiveDateTime`|`Datetime(..)`|`chrono`
//! |✓|`chrono::DateTime<Utc>`|`Datetime(..)`|`chrono`
//! |✓|`chrono::Date`|`Date`|`chrono`|
//! |?|?|`Array(..)`|
//! |?|?|`Decimal(..)`|
//! |?|?|`Struct(..)`|
//! |X|X|`Null`
//! |X|X|`Unknown(..)`|
//! |X|X|`Object(..)`|
//!
//! TODO: Support is planned <br>
//! ?: Support not yet certain<br>
//! X: No Support
//!
//! ## Limitations
//! * No generics in row structs supported
mod dataframe_rows_iter_ext;
mod from_dataframe_row;
mod iter_from_column;
pub use dataframe_rows_iter_ext::*;
pub use from_dataframe_row::*;
pub use iter_from_column::*;
pub use polars_rows_iter_derive::FromDataFrameRow;
#[cfg(test)]
pub mod shared_test_helpers;