Struct Recommendation 

pub struct Recommendation {
    pub all_matches_count: i64,
    pub all_matches_sum: f64,
    pub end_time: f64,
    pub pattern: Pattern,
    pub start_time: f64,
    pub top_matches: Vec<Match>,
}

A potential improvement that was found from analyzing the profiling data.

Fields

all_matches_count: i64

How many different places in the profile graph triggered a match.

all_matches_sum: f64

How much of the total sample count is potentially affected.

end_time: f64

End time of the profile that was used by this analysis. This is specified using the ISO 8601 format. For example, 2020-06-01T13:15:02.001Z represents 1 millisecond past June 1, 2020 1:15:02 PM UTC.

pattern: Pattern

The pattern that analysis recognized in the profile to make this recommendation.

start_time: f64

The start time of the profile that was used by this analysis. This is specified using the ISO 8601 format. For example, 2020-06-01T13:15:02.001Z represents 1 millisecond past June 1, 2020 1:15:02 PM UTC.

top_matches: Vec<Match>

List of the matches with most impact.

Trait Implementations

impl Clone for Recommendation

fn clone(&self) -> Recommendation

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for Recommendation

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for Recommendation

fn default() -> Recommendation

Returns the “default value” for a type.

impl<'de> Deserialize<'de> for Recommendation

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl PartialEq for Recommendation

fn eq(&self, other: &Recommendation) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl StructuralPartialEq for Recommendation