Map is a core data structure for storing key-value pairs. Explore the powerful features of Map in Topaz! 🗝️
🌱 Basic Map Concepts
What is a Map?
A Map is an associative array that stores data as key-value pairs. Each key is unique, and values can be quickly retrieved through keys.
// Basic Map creation and usage
function basicMapExample() {
// Create empty map
let mut scoreMap: Map<string, int> = Map::new()
// Insert values
scoreMap.insert("Alice", 95)
scoreMap.insert("Bob", 87)
scoreMap.insert("Charlie", 92)
// Retrieve values
match scoreMap.get("Alice") {
case Some(aliceScore) => print!("Alice's score: {}", aliceScore)
case None => {}
}
// Update values
scoreMap.insert("Alice", 98) // Overwrite existing value
// Iterate through all key-value pairs
for (name, score) in &scoreMap {
print!("{}: {}", name, score)
}
}
// Map literal creation
function mapLiteralExample() -> Map<string, int> {
map! {
"Math" => 90,
"Science" => 85,
"English" => 93,
"History" => 88
}
}
// Use composite data types as values
struct StudentInfo {
age: int,
grade: int,
major: string
}
function compositeDataMap() -> Map<string, StudentInfo> {
let mut studentMap = Map::new()
studentMap.insert("John Doe", StudentInfo {
age: 20,
grade: 2,
major: "Computer Science".to_string()
})
studentMap.insert("Jane Smith", StudentInfo {
age: 19,
grade: 1,
major: "Mathematics".to_string()
})
return studentMap
} test {
// Basic Map test
let mut testMap: Map<string, int> = Map::new()
testMap.insert("key1", 100)
testMap.insert("key2", 200)
assert testMap.get("key1") == Some(&100)
assert testMap.get("key3") == None
assert testMap.len() == 2
// Map literal test
let subjectScores = mapLiteralExample()
assert subjectScores.get("Math") == Some(&90)
assert subjectScores.len() == 4
// Composite data test
let students = compositeDataMap()
match students.get("John Doe") {
case Some(john) => {
assert john.age == 20
assert john.major == "Computer Science"
}
case None => {}
}
}
basicMapExample()
let subjectMap = mapLiteralExample()
print!("Number of subjects: {}", subjectMap.len())
let studentMap = compositeDataMap()
for (name, info) in &studentMap {
print!("{}: {} years old, grade {}, {} major", name, info.age, info.grade, info.major)
}Core Map Features
- Unique Keys: Each key must be unique in the map
- Fast Lookup: O(1) average time complexity for value retrieval
- Dynamic Size: Size can be changed at runtime
- Type Safety: Key and value types are determined at compile time
🛠️ Basic Map Operations
Creation, Insertion, and Retrieval
// Various Map creation methods
function mapCreationMethods() {
// 1. Create empty map
let mut emptyMap: Map<int, string> = Map::new()
// 2. Create with capacity
let mut capacityMap: Map<string, int> = Map::with_capacity(100)
// 3. Initialize with default values
let mut defaultMap = Map::new()
defaultMap.insert("defaultKey", "defaultValue")
// 4. Clone from another map
let clonedMap = defaultMap.clone()
print!("Empty map size: {}", emptyMap.len())
print!("Cloned map size: {}", clonedMap.len())
}
// Value insertion and updates
function valueInsertionOperations() {
let mut counterMap: Map<string, int> = Map::new()
// Insert new values
counterMap.insert("apple", 5)
counterMap.insert("banana", 3)
// Update existing values
counterMap.insert("apple", 8) // Change 5 -> 8
// Use entry API (more efficient)
counterMap.entry("orange").or_insert(0) // Insert 0 if key doesn't exist
counterMap.entry("apple").and_modify(|value| *value += 2) // Add 2 to existing value
// Utilize insert return value
match counterMap.insert("grape", 7) {
case Some(previousValue) => print!("Previous value of grape: {}", previousValue)
case None => print!("grape is a new key.")
}
for (fruit, count) in &counterMap {
print!("{}: {} pieces", fruit, count)
}
}
// Value retrieval and existence checking
function valueRetrievalOperations() {
let inventoryMap = map! {
"Apple" => 50,
"Banana" => 30,
"Orange" => 25,
"Grape" => 40
}
// Retrieve value with get
match inventoryMap.get("Apple") {
case Some(count) => print!("Apple inventory: {} pieces", count),
case None => print!("No apple inventory")
}
// Check key existence with contains_key
if inventoryMap.contains_key("Strawberry") {
print!("Strawberry available")
} else {
print!("No strawberry inventory")
}
// Get mutable reference with get_mut
let mut mutableInventoryMap = inventoryMap.clone()
match mutableInventoryMap.get_mut("Banana") {
case Some(bananaInventory) => {
*bananaInventory -= 10 // Sell 10 bananas
print!("Banana inventory after sale: {} pieces", *bananaInventory)
}
case None => {}
}
// Retrieve with default value
let kiwiInventory = mutableInventoryMap.get("Kiwi").unwrap_or(&0)
print!("Kiwi inventory: {} pieces", kiwiInventory)
}
// Value removal
function valueRemovalOperations() {
let mut tempMap = map! {
"temp1" => "value1",
"temp2" => "value2",
"temp3" => "value3",
"preserve" => "importantValue"
}
print!("Size before removal: {}", tempMap.len())
// Remove specific key
match tempMap.remove("temp1") {
case Some(removedValue) => print!("Removed value: {}", removedValue)
case None => {}
}
// Conditional removal
tempMap.retain(|key, _| !key.starts_with("temp"))
print!("Size after removal: {}", tempMap.len())
print!("Remaining keys: {:?}", tempMap.keys().collect::<Vec<_>>())
// Remove all entries
tempMap.clear()
print!("Size after clearing all: {}", tempMap.len())
} test {
// Map creation test
let mut testMap: Map<string, int> = Map::new()
assert testMap.is_empty()
// Insertion test
testMap.insert("key1", 100)
testMap.insert("key2", 200)
assert testMap.len() == 2
// Retrieval test
assert testMap.get("key1") == Some(&100)
assert testMap.contains_key("key2")
assert !testMap.contains_key("key3")
// Update test
let previousValue = testMap.insert("key1", 150)
assert previousValue == Some(100)
assert testMap.get("key1") == Some(&150)
// Removal test
let removedValue = testMap.remove("key2")
assert removedValue == Some(200)
assert testMap.len() == 1
}
mapCreationMethods()
valueInsertionOperations()
valueRetrievalOperations()
valueRemovalOperations()Iteration and Transformation
// Map iteration methods
function mapIterationMethods() {
let scoreMap = map! {
"Math" => 95,
"Science" => 88,
"English" => 92,
"History" => 85
}
// 1. Iterate through key-value pairs
print!("=== Key-Value Pair Iteration ===")
for (subject, score) in &scoreMap {
print!("{}: {} points", subject, score)
}
// 2. Iterate through keys only
print!("=== Keys Only Iteration ===")
for subject in scoreMap.keys() {
print!("Subject: {}", subject)
}
// 3. Iterate through values only
print!("=== Values Only Iteration ===")
for score in scoreMap.values() {
print!("Score: {} points", score)
}
// 4. Mutable value iteration (score adjustment)
let mut mutableScoreMap = scoreMap.clone()
for (_, score) in &mut mutableScoreMap {
*score += 5 // Add 5 points to all scores
}
print!("=== Adjusted Scores ===")
for (subject, score) in &mutableScoreMap {
print!("{}: {} points", subject, score)
}
}
// Map transformation and filtering
function mapTransformationFiltering() {
let originalMap = map! {
"apple" => 10,
"banana" => 5,
"orange" => 15,
"grape" => 8,
"kiwi" => 12
}
// Convert map to vector
let keyValueVector: Vec<(string, int)> = originalMap.iter()
.map(|(key, value)| (key.clone(), *value))
.collect()
print!("Key-value vector: {:?}", keyValueVector)
// Filter items matching condition
let expensiveFruits: Map<string, int> = originalMap.iter()
.filter(|(_, &price)| price >= 10)
.map(|(key, value)| (key.clone(), *value))
.collect()
print!("Fruits >= 10: {:?}", expensiveFruits)
// Value transformation
let discountedPrices: Map<string, int> = originalMap.iter()
.map(|(key, value)| (key.clone(), value * 90 / 100)) // 10% discount
.collect()
print!("Discounted prices: {:?}", discountedPrices)
// Key transformation
let uppercaseKeyMap: Map<string, int> = originalMap.iter()
.map(|(key, value)| (key.to_uppercase(), *value))
.collect()
print!("Uppercase keys: {:?}", uppercaseKeyMap)
}
// Map aggregation and statistics
function mapAggregationStatistics() {
let salesData = map! {
"January" => 120,
"February" => 135,
"March" => 98,
"April" => 156,
"May" => 189,
"June" => 143
}
// Total sales
let totalSales: int = salesData.values().sum()
print!("Total sales: {}", totalSales)
// Average sales
let averageSales = totalSales as f64 / salesData.len() as f64
print!("Average sales: {:.2}", averageSales)
// Maximum/minimum sales
match salesData.values().max() { case Some(maxSales) => print!("Maximum sales: {}", maxSales); case None => {} }
match salesData.values().min() { case Some(minSales) => print!("Minimum sales: {}", minSales); case None => {} }
// Count meeting specific condition
let targetAchievementMonths = salesData.values()
.filter(|&&sales| sales >= 140)
.count()
print!("Months achieving target (140): {}", targetAchievementMonths)
// Find best performing month
match salesData.iter().max_by_key(|(_, &sales)| sales) { case Some((bestMonth, bestPerformance)) => print!("Best performance: {} month with {} units", bestMonth, bestPerformance), case None => {} }
} test {
// Iteration test
let testMap = map! {
"A" => 1,
"B" => 2,
"C" => 3
}
let mut keys = Vec::new()
for key in testMap.keys() {
keys.push(key.clone())
}
keys.sort()
assert keys == vec!["A", "B", "C"]
// Transformation test
let doubledMap: Map<string, int> = testMap.iter()
.map(|(key, value)| (key.clone(), value * 2))
.collect()
assert doubledMap.get("A") == Some(&2)
assert doubledMap.get("B") == Some(&4)
// Filtering test
let largeValueMap: Map<string, int> = testMap.iter()
.filter(|(_, &value)| value > 1)
.map(|(key, value)| (key.clone(), *value))
.collect()
assert largeValueMap.len() == 2
assert !largeValueMap.contains_key("A")
}
mapIterationMethods()
mapTransformationFiltering()
mapAggregationStatistics()🚀 Advanced Map Usage
Entry API and Efficient Patterns
// Entry API utilization
function entryAPIUtilization() {
let mut wordCountMap: Map<string, int> = Map::new()
let text = "hello world hello rust world rust programming"
// Count words (using Entry API)
for word in text.split_whitespace() {
*wordCountMap.entry(word.to_string()).or_insert(0) += 1
}
print!("=== Word Count ===")
for (word, count) in &wordCountMap {
print!("{}: {} times", word, count)
}
// Complex Entry patterns
let mut groupMap: Map<string, Vec<int>> = Map::new()
let data = vec![
("GroupA", 10), ("GroupB", 20), ("GroupA", 15),
("GroupC", 5), ("GroupB", 25), ("GroupA", 30)
]
for (group, value) in data {
groupMap.entry(group.to_string())
.or_insert(Vec::new())
.push(value)
}
print!("=== Group Data ===")
for (group, values) in &groupMap {
print!("{}: {:?}", group, values)
}
}
// Nested map structure
function nestedMapStructure() {
// Student -> Subject -> Score
let mut gradebook: Map<string, Map<string, int>> = Map::new()
// Grade input function
let mut inputGrade = |student: &str, subject: &str, score: int| {
gradebook.entry(student.to_string())
.or_insert(Map::new())
.insert(subject.to_string(), score)
}
// Input data
inputGrade("John Smith", "Math", 95)
inputGrade("John Smith", "Science", 88)
inputGrade("John Smith", "English", 92)
inputGrade("Jane Doe", "Math", 98)
inputGrade("Jane Doe", "Science", 94)
inputGrade("Jane Doe", "English", 89)
// Grade inquiry
for (student, subjectMap) in &gradebook {
print!("=== {} Grades ===", student)
let mut totalScore = 0
let mut subjectCount = 0
for (subject, score) in subjectMap {
print!(" {}: {} points", subject, score)
totalScore += score
subjectCount += 1
}
let average = if subjectCount > 0 { totalScore as f64 / subjectCount as f64 } else { 0.0 }
print!(" Average: {:.1} points", average)
}
}
// Map merge and combination
function mapMergeCombination() {
let inventoryA = map! {
"Apple" => 50,
"Banana" => 30,
"Orange" => 20
}
let inventoryB = map! {
"Banana" => 25, // Duplicate key
"Grape" => 40,
"Kiwi" => 15
}
// 1. Simple merge (B takes precedence)
let mut mergedInventory = inventoryA.clone()
for (fruit, count) in inventoryB.iter() {
mergedInventory.insert(fruit.clone(), *count)
}
print!("=== Simple Merge (B Priority) ===")
for (fruit, count) in &mergedInventory {
print!("{}: {} pieces", fruit, count)
}
// 2. Value sum merge
let mut summedInventory = inventoryA.clone()
for (fruit, count) in inventoryB.iter() {
*summedInventory.entry(fruit.clone()).or_insert(0) += count
}
print!("=== Value Sum Merge ===")
for (fruit, count) in &summedInventory {
print!("{}: {} pieces", fruit, count)
}
// 3. Maximum value merge
let mut maxInventory = inventoryA.clone()
for (fruit, count) in inventoryB.iter() {
maxInventory.entry(fruit.clone())
.and_modify(|existingCount| *existingCount = (*existingCount).max(*count))
.or_insert(*count)
}
print!("=== Maximum Value Merge ===")
for (fruit, count) in &maxInventory {
print!("{}: {} pieces", fruit, count)
}
} test {
// Entry API test
let mut counter: Map<string, int> = Map::new()
// Insert new key
counter.entry("newKey".to_string()).or_insert(1)
assert counter.get("newKey") == Some(&1)
// Modify existing key
*counter.entry("newKey".to_string()).or_insert(0) += 5
assert counter.get("newKey") == Some(&6)
// Nested map test
let mut nestedMap: Map<string, Map<string, int>> = Map::new()
nestedMap.entry("outerKey".to_string())
.or_insert(Map::new())
.insert("innerKey".to_string(), 100)
assert nestedMap.get("outerKey").unwrap().get("innerKey") == Some(&100)
}
entryAPIUtilization()
nestedMapStructure()
mapMergeCombination()Performance Optimization and Memory Management
// Capacity management and performance optimization
function performanceOptimization() {
// 1. Set appropriate initial capacity
let mut largeMap: Map<int, string> = Map::with_capacity(10000)
print!("Initial capacity: {}", largeMap.capacity())
// Insert large amount of data
for i in 0..5000 {
largeMap.insert(i, format!("value{}", i))
}
print!("After insertion - length: {}, capacity: {}", largeMap.len(), largeMap.capacity())
// 2. Shrink unnecessary capacity
largeMap.shrink_to_fit()
print!("After shrinking capacity: {}", largeMap.capacity())
// 3. Reserve space
largeMap.reserve(2000)
print!("After reserving capacity: {}", largeMap.capacity())
}
// Memory-efficient key types
function efficientKeyTypes() {
// Performance comparison example for string keys vs integer keys
// Integer keys (more efficient)
let mut integerKeyMap: Map<u32, string> = Map::new()
for i in 0..1000 {
integerKeyMap.insert(i, format!("data{}", i))
}
// String keys (higher hash cost)
let mut stringKeyMap: Map<string, string> = Map::new()
for i in 0..1000 {
stringKeyMap.insert(format!("key{}", i), format!("data{}", i))
}
print!("Integer key map size: {}", integerKeyMap.len())
print!("String key map size: {}", stringKeyMap.len())
// Small strings stored on stack (efficient)
let mut fixedStringMap: Map<&'static str, int> = map! {
"Red" => 1,
"Blue" => 2,
"Green" => 3,
"Yellow" => 4
}
print!("Fixed string map: {:?}", fixedStringMap)
}
// Custom hash function usage
use std::collections::hash_map::DefaultHasher
use std::hash::{Hash, Hasher}
struct CustomKey {
id: u32,
name: string
}
impl Hash for CustomKey {
function hash<H: Hasher>(&self, state: &mut H) {
// Use only ID for hash (ignore name)
self.id.hash(state)
}
}
impl PartialEq for CustomKey {
function eq(&self, other: &Self) -> bool {
self.id == other.id // Equality based on ID only
}
}
impl Eq for CustomKey {}
function customHashExample() {
let mut customMap: Map<CustomKey, string> = Map::new()
let key1 = CustomKey { id: 1, name: "first".to_string() }
let key2 = CustomKey { id: 1, name: "different".to_string() } // Same ID
customMap.insert(key1, "value1".to_string())
// key2 is treated as the same key as key1 because they have the same ID
match customMap.get(&key2) { case Some(value) => print!("Value retrieved with custom key: {}", value), case None => {} }
} test {
// Capacity management test
let mut testMap: Map<int, string> = Map::with_capacity(5)
assert testMap.capacity() >= 5
assert testMap.is_empty()
// Auto-expansion test when capacity exceeded
for i in 0..<10 {
testMap.insert(i, format!("value{}", i))
}
assert testMap.len() == 10
assert testMap.capacity() >= 10
}
performanceOptimization()
efficientKeyTypes()
customHashExample()🎯 Practical Map Patterns
Cache and Memoization
// Simple cache implementation
struct Cache<K, V>
where
K: Hash + Eq + Clone,
V: Clone
{
data: Map<K, V>,
maxSize: usize
}
impl<K, V> Cache<K, V>
where
K: Hash + Eq + Clone,
V: Clone
{
function new(maxSize: usize) -> Self {
Cache {
data: Map::with_capacity(maxSize),
maxSize
}
}
function get(&self, key: &K) -> Option<&V> {
self.data.get(key)
}
function put(&mut self, key: K, value: V) {
if self.data.len() >= self.maxSize {
// Simple LRU: remove first key
match self.data.keys().next().cloned() {
case Some(firstKey) => { self.data.remove(&firstKey) }
case None => {}
}
}
self.data.insert(key, value)
}
function contains_key(&self, key: &K) -> bool {
self.data.contains_key(key)
}
function clear(&mut self) {
self.data.clear()
}
}
// Memoization implementation
function memoizationExample() {
let mut fibonacciCache: Map<u32, u64> = Map::new()
function fibonacci(n: u32, cache: &mut Map<u32, u64>) -> u64 {
match cache.get(&n) { case Some(&result) => return result; case None => {} }
let result = match n {
case 0 => 0,
case 1 => 1,
case _ => fibonacci(n - 1, cache) + fibonacci(n - 2, cache)
}
cache.insert(n, result)
result
}
// Calculate Fibonacci sequence
for i in 0..15 {
let value = fibonacci(i, &mut fibonacciCache)
print!("F({}) = {}", i, value)
}
print!("Cache size: {}", fibonacciCache.len())
}
// Web request cache simulation
function webCacheSimulation() {
let mut responseCache: Cache<string, string> = Cache::new(5)
function simulateWebRequest(url: &str, cache: &mut Cache<string, string>) -> string {
match cache.get(&url.to_string()) {
case Some(cachedResponse) => {
print!("Cache hit: {}", url)
return cachedResponse.clone()
}
case None => {}
}
// Simulate actual request (with delay)
print!("Actual request: {}", url)
let response = format!("Response data from {}", url)
cache.put(url.to_string(), response.clone())
response
}
// Request simulation
let urls = vec![
"https://api.example.com/users",
"https://api.example.com/posts",
"https://api.example.com/users", // Cache hit
"https://api.example.com/comments",
"https://api.example.com/posts", // Cache hit
]
for url in urls {
let response = simulateWebRequest(url, &mut responseCache)
print!("Response: {}", response)
}
} test {
// Cache test
let mut testCache: Cache<string, int> = Cache::new(3)
testCache.put("key1".to_string(), 100)
testCache.put("key2".to_string(), 200)
testCache.put("key3".to_string(), 300)
assert testCache.get(&"key1".to_string()) == Some(&100)
assert testCache.contains_key(&"key2".to_string())
// LRU behavior test when capacity exceeded
testCache.put("key4".to_string(), 400)
// First key should be removed
assert testCache.get(&"key4".to_string()) == Some(&400)
}
memoizationExample()
webCacheSimulation()Indexing and Grouping
// Data indexing
struct User {
id: u32,
name: string,
age: u32,
department: string
}
function dataIndexing() {
let users = vec![
User { id: 1, name: "John Doe".to_string(), age: 28, department: "Development".to_string() },
User { id: 2, name: "Jane Smith".to_string(), age: 32, department: "Design".to_string() },
User { id: 3, name: "Mike Johnson".to_string(), age: 25, department: "Development".to_string() },
User { id: 4, name: "Sarah Wilson".to_string(), age: 29, department: "Marketing".to_string() },
]
// Index by ID
let idIndex: Map<u32, &User> = users.iter()
.map(|user| (user.id, user))
.collect()
// Index by name
let nameIndex: Map<string, &User> = users.iter()
.map(|user| (user.name.clone(), user))
.collect()
// Group by department
let mut departmentGroups: Map<string, Vec<&User>> = Map::new()
for user in &users {
departmentGroups.entry(user.department.clone())
.or_insert(Vec::new())
.push(user)
}
// Index usage examples
match idIndex.get(&2) { case Some(user) => print!("User with ID 2: {}", user.name), case None => {} }
match nameIndex.get("Mike Johnson") { case Some(user) => print!("Mike Johnson's department: {}", user.department), case None => {} }
// Grouping results output
for (department, members) in &departmentGroups {
print!("=== {} ===", department)
for user in members {
print!(" {} ({} years old)", user.name, user.age)
}
}
}
// Multi-index system
struct MultiIndex<T> {
data: Vec<T>
}
impl MultiIndex<User> {
function new(data: Vec<User>) -> Self {
MultiIndex { data }
}
function findById(&self, id: u32) -> Option<&User> {
self.data.iter().find(|user| user.id == id)
}
function findByDepartment(&self, department: &str) -> Vec<&User> {
self.data.iter()
.filter(|user| user.department == department)
.collect()
}
function findByAgeRange(&self, minAge: u32, maxAge: u32) -> Vec<&User> {
self.data.iter()
.filter(|user| user.age >= minAge && user.age <= maxAge)
.collect()
}
function statistics(&self) -> Map<string, u32> {
let mut statsMap = Map::new()
// Department member count
let mut departmentCount: Map<string, u32> = Map::new()
for user in &self.data {
*departmentCount.entry(user.department.clone()).or_insert(0) += 1
}
// Average age
let totalAge: u32 = self.data.iter().map(|user| user.age).sum()
let averageAge = if !self.data.is_empty() {
totalAge / self.data.len() as u32
} else { 0 }
statsMap.insert("totalMembers".to_string(), self.data.len() as u32)
statsMap.insert("averageAge".to_string(), averageAge)
for (department, count) in departmentCount {
statsMap.insert(format!("{}_members", department), count)
}
statsMap
}
}
function multiIndexExample() {
let userData = vec![
User { id: 1, name: "John Doe".to_string(), age: 28, department: "Development".to_string() },
User { id: 2, name: "Jane Smith".to_string(), age: 32, department: "Design".to_string() },
User { id: 3, name: "Mike Johnson".to_string(), age: 25, department: "Development".to_string() },
User { id: 4, name: "Sarah Wilson".to_string(), age: 29, department: "Marketing".to_string() },
]
let index = MultiIndex::new(userData)
// Various searches
match index.findById(3) { case Some(user) => print!("ID 3: {}", user.name), case None => {} }
let devMembers = index.findByDepartment("Development")
print!("Development members: {:?}", devMembers.iter().map(|u| &u.name).collect::<Vec<_>>())
let youngEmployees = index.findByAgeRange(25, 30)
print!("25-30 years old: {:?}", youngEmployees.iter().map(|u| &u.name).collect::<Vec<_>>())
// Statistics output
let stats = index.statistics()
for (item, value) in &stats {
print!("{}: {}", item, value)
}
} test {
// Indexing test
let testUsers = vec![
User { id: 1, name: "Test1".to_string(), age: 25, department: "TeamA".to_string() },
User { id: 2, name: "Test2".to_string(), age: 30, department: "TeamB".to_string() },
]
let idMap: Map<u32, &User> = testUsers.iter()
.map(|u| (u.id, u))
.collect()
assert idMap.get(&1).unwrap().name == "Test1"
assert idMap.get(&2).unwrap().department == "TeamB"
// Multi-index test
let index = MultiIndex::new(testUsers)
assert index.findById(1).is_some()
assert index.findByDepartment("TeamA").len() == 1
assert index.findByAgeRange(25, 35).len() == 2
}
dataIndexing()
multiIndexExample()🎯 Mastering Map
Map is one of the most useful data structures in Topaz:
✅ When to Use Map:
- Key-value pair data storage
- When fast lookup is needed
- Data indexing and grouping
- Cache and memoization implementation
⚠️ Considerations:
- Choose appropriate key types (consider hash performance)
- Manage memory usage (for large datasets)
- Consider concurrency (in multi-threaded environments)
- Ensure key immutability
🚀 Topaz Map Advantages:
- Type safety guarantee
- Efficient hashing algorithms
- Flexible Entry API
- Memory-safe management
Experience efficient data management with Map! 🗝️✨