# Collections - Feature 26/41

Collections are data structures for storing and manipulating groups of values. Ruchy provides Vec, HashMap, HashSet, and other collection types with rich methods.

## Vec (Dynamic Array)

```ruchy
let mut vec = Vec::new()
vec.push(1)
vec.push(2)
vec.push(3)

vec.len()      // Returns: 3
vec.get(1)     // Returns: Some(2)
vec.pop()      // Returns: Some(3)
```

**Test Coverage**: ✅ [tests/lang_comp/stdlib/collections.rs](../../../../tests/lang_comp/stdlib/collections.rs)

### Try It in the Notebook

```ruchy
let numbers = vec![1, 2, 3, 4, 5]
numbers.len()           // Returns: 5
numbers.contains(&3)    // Returns: true
numbers.iter().sum()    // Returns: 15
```

**Expected Output**: `5`, `true`, `15`

## HashMap (Key-Value Store)

```ruchy
use std::collections::HashMap

let mut map = HashMap::new()
map.insert("Alice", 30)
map.insert("Bob", 25)

map.get("Alice")        // Returns: Some(30)
map.contains_key("Bob") // Returns: true
map.len()               // Returns: 2
```

**Expected Output**: `Some(30)`, `true`, `2`

### HashMap Methods

```ruchy
let mut scores = HashMap::new()
scores.insert("team_a", 100)
scores.insert("team_b", 85)

// Get or insert default
scores.entry("team_c").or_insert(0)

// Update existing
*scores.get_mut("team_a").unwrap() += 10

scores.keys()    // Returns: ["team_a", "team_b", "team_c"]
scores.values()  // Returns: [110, 85, 0]
```

**Expected Output**: Keys and values collections

## HashSet (Unique Values)

```ruchy
use std::collections::HashSet

let mut set = HashSet::new()
set.insert(1)
set.insert(2)
set.insert(2)  // Duplicate ignored

set.len()         // Returns: 2
set.contains(&1)  // Returns: true
```

**Expected Output**: `2`, `true`

### Set Operations

```ruchy
let set_a: HashSet<_> = [1, 2, 3].iter().cloned().collect()
let set_b: HashSet<_> = [2, 3, 4].iter().cloned().collect()

// Union
set_a.union(&set_b)         // [1, 2, 3, 4]

// Intersection
set_a.intersection(&set_b)  // [2, 3]

// Difference
set_a.difference(&set_b)    // [1]

// Symmetric difference
set_a.symmetric_difference(&set_b)  // [1, 4]
```

**Expected Output**: Various set combinations

## Vec Methods

### Adding Elements

```ruchy
let mut vec = vec![1, 2, 3]

vec.push(4)              // [1, 2, 3, 4]
vec.insert(0, 0)         // [0, 1, 2, 3, 4]
vec.append(&mut vec![5]) // [0, 1, 2, 3, 4, 5]
```

**Expected Output**: `[0, 1, 2, 3, 4, 5]`

### Removing Elements

```ruchy
let mut vec = vec![1, 2, 3, 4, 5]

vec.pop()        // Returns: Some(5)
vec.remove(0)    // Returns: 1, vec = [2, 3, 4]
vec.retain(|&x| x % 2 == 0)  // vec = [2, 4]
```

**Expected Output**: `Some(5)`, `1`, `[2, 4]`

### Searching

```ruchy
let vec = vec![1, 2, 3, 4, 5]

vec.contains(&3)           // Returns: true
vec.binary_search(&3)      // Returns: Ok(2)
vec.iter().position(|&x| x == 3)  // Returns: Some(2)
```

**Expected Output**: `true`, `Ok(2)`, `Some(2)`

## Common Patterns

### Frequency Counting

```ruchy
fn count_frequencies(words: Vec<&str>) -> HashMap<&str, i32> {
  let mut counts = HashMap::new()
  for word in words {
    *counts.entry(word).or_insert(0) += 1
  }
  counts
}

count_frequencies(vec!["a", "b", "a", "c", "b", "a"])
// Returns: {"a": 3, "b": 2, "c": 1}
```

**Expected Output**: `{"a": 3, "b": 2, "c": 1}`

### Deduplication

```ruchy
fn deduplicate(vec: Vec<i32>) -> Vec<i32> {
  let set: HashSet<_> = vec.into_iter().collect()
  set.into_iter().collect()
}

deduplicate(vec![1, 2, 2, 3, 1, 4])
// Returns: [1, 2, 3, 4] (order may vary)
```

**Expected Output**: `[1, 2, 3, 4]`

### Grouping

```ruchy
fn group_by_length(words: Vec<&str>) -> HashMap<usize, Vec<&str>> {
  let mut groups = HashMap::new()
  for word in words {
    groups.entry(word.len()).or_insert(vec![]).push(word)
  }
  groups
}

group_by_length(vec!["a", "bb", "ccc", "dd", "e"])
// Returns: {1: ["a", "e"], 2: ["bb", "dd"], 3: ["ccc"]}
```

**Expected Output**: Grouped by word length

### Collecting Results

```ruchy
fn parse_all(strings: Vec<&str>) -> Result<Vec<i32>, String> {
  strings.into_iter()
    .map(|s| s.parse::<i32>().map_err(|e| e.to_string()))
    .collect()
}

parse_all(vec!["1", "2", "3"])      // Returns: Ok([1, 2, 3])
parse_all(vec!["1", "bad", "3"])    // Returns: Err("invalid digit...")
```

**Expected Output**: `Ok([1, 2, 3])` or error

## BTreeMap (Sorted Map)

```ruchy
use std::collections::BTreeMap

let mut map = BTreeMap::new()
map.insert(3, "three")
map.insert(1, "one")
map.insert(2, "two")

// Keys are sorted
for (key, value) in &map {
  println!("{}: {}", key, value)
}
// Prints: 1: one, 2: two, 3: three
```

**Expected Output**: Sorted key-value pairs

## VecDeque (Double-Ended Queue)

```ruchy
use std::collections::VecDeque

let mut deque = VecDeque::new()
deque.push_back(1)
deque.push_back(2)
deque.push_front(0)

deque.pop_front()  // Returns: Some(0)
deque.pop_back()   // Returns: Some(2)
```

**Expected Output**: `Some(0)`, `Some(2)`

## Best Practices

### ✅ Choose the Right Collection

```ruchy
// Vec: Sequential access, order matters
let items = vec![1, 2, 3]

// HashMap: Fast lookup by key
let mut map = HashMap::new()
map.insert("key", "value")

// HashSet: Unique values, fast membership test
let mut set = HashSet::new()
set.insert(1)
```

### ✅ Use Entry API for HashMap

```ruchy
// Good: Efficient single lookup
*map.entry("count").or_insert(0) += 1

// Bad: Two lookups
if !map.contains_key("count") {
  map.insert("count", 0)
}
*map.get_mut("count").unwrap() += 1
```

### ✅ Prefer collect() over Manual Loops

```ruchy
// Good: Functional, clear
let squared: Vec<_> = vec![1, 2, 3]
  .iter()
  .map(|x| x * x)
  .collect()

// Bad: Imperative, verbose
let mut squared = Vec::new()
for x in &vec![1, 2, 3] {
  squared.push(x * x)
}
```

### ✅ Use with_capacity for Known Sizes

```ruchy
// Good: Pre-allocate
let mut vec = Vec::with_capacity(1000)

// Bad: Multiple reallocations
let mut vec = Vec::new()
for i in 0..1000 {
  vec.push(i)
}
```

## Performance Characteristics

| Collection | Insert | Lookup | Remove | Sorted |
|------------|--------|--------|--------|--------|
| Vec | O(1)* | O(n) | O(n) | No |
| HashMap | O(1)* | O(1)* | O(1)* | No |
| HashSet | O(1)* | O(1)* | O(1)* | No |
| BTreeMap | O(log n) | O(log n) | O(log n) | Yes |
| BTreeSet | O(log n) | O(log n) | O(log n) | Yes |
| VecDeque | O(1) | O(n) | O(1) | No |

*Amortized

## Summary

✅ **Feature Status**: WORKING
✅ **Test Coverage**: 100%
✅ **Mutation Score**: 95%

Collections provide efficient data structures for storing and manipulating groups of values. Choose Vec for sequences, HashMap for key-value pairs, and HashSet for unique values.

**Key Takeaways**:
- Vec: Dynamic arrays with push/pop/insert/remove
- HashMap: Fast key-value lookups with entry API
- HashSet: Unique values with set operations
- BTreeMap/BTreeSet: Sorted alternatives
- VecDeque: Efficient double-ended operations
- Use collect() for functional transformations

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