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//! Testing utilities.
use crate::prelude::*;
impl Series {
/// Check if series are equal. Note that `None == None` evaluates to `false`
pub fn equals(&self, other: &Series) -> bool {
if self.null_count() > 0 || other.null_count() > 0 {
false
} else {
self.equals_missing(other)
}
}
/// Check if all values in series are equal where `None == None` evaluates to `true`.
pub fn equals_missing(&self, other: &Series) -> bool {
match (self.dtype(), other.dtype()) {
// Two [`Datetime`](DataType::Datetime) series are *not* equal if their timezones
// are different, regardless if they represent the same UTC time or not.
#[cfg(feature = "timezones")]
(DataType::Datetime(_, tz_lhs), DataType::Datetime(_, tz_rhs)) => {
if tz_lhs != tz_rhs {
return false;
}
},
_ => {},
}
// Differs from Partial::eq in that numerical dtype may be different
self.len() == other.len() && self.null_count() == other.null_count() && {
let eq = self.equal_missing(other);
match eq {
Ok(b) => b.all(),
Err(_) => false,
}
}
}
}
impl PartialEq for Series {
fn eq(&self, other: &Self) -> bool {
self.equals_missing(other)
}
}
impl DataFrame {
/// Check if [`DataFrame`]' schemas are equal.
pub fn schema_equal(&self, other: &DataFrame) -> PolarsResult<()> {
for (lhs, rhs) in self.columns().iter().zip(other.columns().iter()) {
polars_ensure!(
lhs.name() == rhs.name(),
SchemaMismatch: "column name mismatch: left-hand = '{}', right-hand = '{}'",
lhs.name(), rhs.name()
);
polars_ensure!(
lhs.dtype() == rhs.dtype(),
SchemaMismatch: "column datatype mismatch: left-hand = '{}', right-hand = '{}'",
lhs.dtype(), rhs.dtype()
);
}
Ok(())
}
/// Check if [`DataFrame`]s are equal. Note that `None == None` evaluates to `false`
///
/// # Example
///
/// ```rust
/// # use polars_core::prelude::*;
/// let df1: DataFrame = df!("Atomic number" => &[1, 51, 300],
/// "Element" => &[Some("Hydrogen"), Some("Antimony"), None])?;
/// let df2: DataFrame = df!("Atomic number" => &[1, 51, 300],
/// "Element" => &[Some("Hydrogen"), Some("Antimony"), None])?;
///
/// assert!(!df1.equals(&df2));
/// # Ok::<(), PolarsError>(())
/// ```
pub fn equals(&self, other: &DataFrame) -> bool {
if self.shape() != other.shape() {
return false;
}
for (left, right) in self.columns().iter().zip(other.columns()) {
if left.name() != right.name() || !left.equals(right) {
return false;
}
}
true
}
/// Check if all values in [`DataFrame`]s are equal where `None == None` evaluates to `true`.
///
/// # Example
///
/// ```rust
/// # use polars_core::prelude::*;
/// let df1: DataFrame = df!("Atomic number" => &[1, 51, 300],
/// "Element" => &[Some("Hydrogen"), Some("Antimony"), None])?;
/// let df2: DataFrame = df!("Atomic number" => &[1, 51, 300],
/// "Element" => &[Some("Hydrogen"), Some("Antimony"), None])?;
///
/// assert!(df1.equals_missing(&df2));
/// # Ok::<(), PolarsError>(())
/// ```
pub fn equals_missing(&self, other: &DataFrame) -> bool {
if self.shape() != other.shape() {
return false;
}
for (left, right) in self.columns().iter().zip(other.columns()) {
if left.name() != right.name() || !left.equals_missing(right) {
return false;
}
}
true
}
}
impl PartialEq for DataFrame {
fn eq(&self, other: &Self) -> bool {
self.shape() == other.shape()
&& self
.columns()
.iter()
.zip(other.columns().iter())
.all(|(s1, s2)| s1.equals_missing(s2))
}
}
/// Asserts that two expressions of type [`DataFrame`] are equal according to [`DataFrame::equals`]
/// at runtime.
///
/// If the expression are not equal, the program will panic with a message that displays
/// both dataframes.
#[macro_export]
macro_rules! assert_df_eq {
($a:expr, $b:expr $(,)?) => {
let a: &$crate::frame::DataFrame = &$a;
let b: &$crate::frame::DataFrame = &$b;
assert!(a.equals(b), "expected {:?}\nto equal {:?}", a, b);
};
}
#[cfg(test)]
mod test {
use crate::prelude::*;
#[test]
fn test_series_equals() {
let a = Series::new("a".into(), &[1_u32, 2, 3]);
let b = Series::new("a".into(), &[1_u32, 2, 3]);
assert!(a.equals(&b));
let s = Series::new("foo".into(), &[None, Some(1i64)]);
assert!(s.equals_missing(&s));
}
#[test]
fn test_series_dtype_not_equal() {
let s_i32 = Series::new("a".into(), &[1_i32, 2_i32]);
let s_i64 = Series::new("a".into(), &[1_i64, 2_i64]);
assert!(s_i32.dtype() != s_i64.dtype());
assert!(s_i32.equals(&s_i64));
}
#[test]
fn test_df_equal() {
let a = Column::new("a".into(), [1, 2, 3].as_ref());
let b = Column::new("b".into(), [1, 2, 3].as_ref());
let df1 = DataFrame::new_infer_height(vec![a, b]).unwrap();
assert!(df1.equals(&df1))
}
#[test]
fn assert_df_eq_passes() {
let df = df!("a" => [1], "b" => [2]).unwrap();
assert_df_eq!(df, df);
drop(df); // Ensure `assert_df_eq!` does not consume its arguments.
}
#[test]
#[should_panic(expected = "to equal")]
fn assert_df_eq_panics() {
assert_df_eq!(df!("a" => [1]).unwrap(), df!("a" => [2]).unwrap(),);
}
#[test]
fn test_df_partialeq() {
let df1 = df!("a" => &[1, 2, 3],
"b" => &[4, 5, 6])
.unwrap();
let df2 = df!("b" => &[4, 5, 6],
"a" => &[1, 2, 3])
.unwrap();
let df3 = df!("" => &[Some(1), None]).unwrap();
let df4 = df!("" => &[f32::NAN]).unwrap();
assert_eq!(df1, df1);
assert_ne!(df1, df2);
assert_eq!(df2, df2);
assert_ne!(df2, df3);
assert_eq!(df3, df3);
assert_eq!(df4, df4);
}
}