Struct InMemoryRepository 

pub struct InMemoryRepository { /* private fields */ }

In-memory implementation of the MetricsRepository trait.

This implementation stores all metrics in memory and is useful for:

• Testing and development
• Small-scale applications
• Caching layers

Example

use term_guard::repository::{InMemoryRepository, ResultKey};
use term_guard::analyzers::AnalyzerContext;

let repository = InMemoryRepository::new();

// Save metrics
let key = ResultKey::now().with_tag("env", "test");
let context = AnalyzerContext::new();
repository.save(key, context).await?;

// Query metrics
let results = repository.load().await
    .with_tag("env", "test")
    .execute()
    .await?;

Implementations

impl InMemoryRepository

pub fn new() -> Self

Creates a new empty in-memory repository.

pub fn with_data(data: HashMap<ResultKey, AnalyzerContext>) -> Self

Creates a new repository with pre-populated data.

Arguments

• data - Initial metrics to populate the repository with

pub async fn size(&self) -> usize

Returns the number of stored metrics.

pub async fn clear(&mut self)

Clears all stored metrics.

impl InMemoryRepository

Override the load method to return actual stored contexts

pub async fn load_with_data(&self) -> InMemoryMetricsQuery

Loads a query that will return actual stored contexts.

pub async fn should_use_datafusion(&self) -> bool

Determines if the dataset is large enough to benefit from DataFusion.

DataFusion has overhead for small datasets, so we only use it when the performance benefits outweigh the setup costs.

impl InMemoryRepository

Custom query executor for in-memory repository with optimized filtering.

pub async fn execute_query_optimized( &self, before: Option<i64>, after: Option<i64>, tags: &HashMap<String, String>, analyzers: &Option<Vec<String>>, limit: Option<usize>, offset: Option<usize>, ascending: bool, ) -> Result<Vec<(ResultKey, AnalyzerContext)>>

Executes a query with in-memory optimizations.

Trait Implementations

impl Clone for InMemoryRepository

fn clone(&self) -> InMemoryRepository

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Default for InMemoryRepository

fn default() -> Self

Returns the “default value” for a type.

impl MetricsRepository for InMemoryRepository

fn save<'life0, 'async_trait>( &'life0 self, key: ResultKey, metrics: AnalyzerContext, ) -> Pin<Box<dyn Future<Output = Result<()>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait,

Saves metrics with the given key.

fn load<'life0, 'async_trait>( &'life0 self, ) -> Pin<Box<dyn Future<Output = MetricsQuery> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait,

Creates a query builder for retrieving metrics.

fn delete<'life0, 'async_trait>( &'life0 self, key: ResultKey, ) -> Pin<Box<dyn Future<Output = Result<()>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait,

Deletes metrics with the given key.

fn list_keys<'life0, 'async_trait>( &'life0 self, ) -> Pin<Box<dyn Future<Output = Result<Vec<ResultKey>>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait,

Lists all available keys in the repository.

fn get<'life0, 'life1, 'async_trait>( &'life0 self, key: &'life1 ResultKey, ) -> Pin<Box<dyn Future<Output = Result<Option<AnalyzerContext>>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait,

Loads a specific metric by key.

fn exists<'life0, 'life1, 'async_trait>( &'life0 self, key: &'life1 ResultKey, ) -> Pin<Box<dyn Future<Output = Result<bool>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait,

Checks if a key exists in the repository.

fn metadata<'life0, 'async_trait>( &'life0 self, ) -> Pin<Box<dyn Future<Output = Result<RepositoryMetadata>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait,

Returns metadata about the repository.