Rust in 2025: Future Directions and Predictions

// Generic Associated Types (GATs) - Stabilized in late 2025
trait StreamingIterator {
    type Item<'a> where Self: 'a;
    
    fn next<'a>(&'a mut self) -> Option<Self::Item<'a>>;
}

impl<T> StreamingIterator for VecStream<T> {
    type Item<'a> where Self: 'a = &'a T;
    
    fn next<'a>(&'a mut self) -> Option<Self::Item<'a>> {
        if self.position < self.items.len() {
            let item = &self.items[self.position];
            self.position += 1;
            Some(item)
        } else {
            None
        }
    }
}

// Const Generics Phase 2 - Expected in 2025
struct Matrix<T, const ROWS: usize, const COLS: usize> {
    data: [[T; COLS]; ROWS],
}

impl<T: Default + Copy, const ROWS: usize, const COLS: usize> Matrix<T, ROWS, COLS> {
    fn new() -> Self {
        Self {
            data: [[T::default(); COLS]; ROWS],
        }
    }
    
    // Advanced const expressions in generics
    fn transpose(&self) -> Matrix<T, COLS, ROWS> {
        let mut result = Matrix::<T, COLS, ROWS>::new();
        
        for i in 0..ROWS {
            for j in 0..COLS {
                result.data[j][i] = self.data[i][j];
            }
        }
        
        result
    }
}

// Async Functions in Traits - Expected in 2025
trait Database {
    async fn connect(&self) -> Result<Connection, Error>;
    async fn query<T: Deserialize>(&self, query: &str) -> Result<Vec<T>, Error>;
    async fn execute(&self, command: &str) -> Result<(), Error>;
}

impl Database for PostgresDatabase {
    async fn connect(&self) -> Result<Connection, Error> {
        // Implementation
    }
    
    async fn query<T: Deserialize>(&self, query: &str) -> Result<Vec<T>, Error> {
        // Implementation
    }
    
    async fn execute(&self, command: &str) -> Result<(), Error> {
        // Implementation
    }
}

// Type Alias Impl Trait (TAIT) - Expected in 2025
type Adder = impl Fn(i32, i32) -> i32;

fn get_adder() -> Adder {
    |a, b| a + b
}

// Usage
fn main() {
    let add = get_adder();
    println!("3 + 4 = {}", add(3, 4));
}

// Rust Analyzer Integration - Expected in 2025
// Rust Analyzer will be fully integrated into rustc,
// providing a unified experience for IDE support and compilation

// Example of advanced IDE features
fn example() {
    let x = 42;
    
    // Inline type hints
    let y = x.to_string(); // ^^ &str
    
    // Automatic imports
    let mut map = HashMap::new(); // Auto-import: use std::collections::HashMap;
    
    // Advanced code actions
    // - Extract function
    // - Convert to match expression
    // - Implement missing methods
    
    // Semantic highlighting
    let mut value = Some(5);
    if let Some(x) = value {
        println!("Found value: {}", x);
    }
}

// Improved Compile Times - Expected in 2025
// Incremental compilation improvements
// Parallel compilation of independent crates
// Smarter dependency tracking

// Example of build-time improvements
// Before: cargo build --release took 120 seconds
// After: cargo build --release takes 45 seconds

// Improved Error Messages - Expected in 2025
fn example_with_error() {
    let s = "hello";
    let n = s + 10; // Error: cannot add `{integer}` to `&str`
    
    // New error message will suggest:
    // - Did you mean `s.parse::<i32>()? + 10`?
    // - Did you mean `s + &10.to_string()`?
    // - Did you mean `format!("{}{}", s, 10)`?
}

// Linear Types - Research in 2025
// Linear types ensure that values are used exactly once,
// which can help with resource management

#[linear]
struct FileHandle {
    descriptor: RawFileDescriptor,
}

impl FileHandle {
    fn new(path: &str) -> Result<Self, Error> {
        let descriptor = open_file(path)?;
        Ok(FileHandle { descriptor })
    }
    
    // No explicit close method needed - the value must be consumed
}

fn process_file() -> Result<(), Error> {
    let handle = FileHandle::new("data.txt")?;
    
    // Use the handle
    let data = read_from_handle(&handle)?;
    
    // handle is consumed here, automatically closing the file
    // Forgetting to use handle would be a compile-time error
    
    Ok(())
}

// Region-based Memory Management - Research in 2025
// Regions allow for more flexible memory management patterns

#[region(r)]
fn process_data() {
    // Allocate memory in region 'r'
    let data = region_alloc::<[u8; 1024 * 1024]>();
    
    // Process data
    process(&data);
    
    // No need to explicitly free - the entire region is freed at once
    // when the region goes out of scope
}

// Leptos 1.0 - Expected in 2025
// A mature, production-ready web framework

use leptos::*;

#[component]
fn Counter(initial_value: i32) -> impl IntoView {
    let (count, set_count) = create_signal(initial_value);
    
    view! {
        <div>
            <button on:click=move |_| set_count.update(|n| *n -= 1)>"-1"</button>
            <span>"Current count: " {count}</span>
            <button on:click=move |_| set_count.update(|n| *n += 1)>"+1"</button>
        </div>
    }
}

#[component]
fn App() -> impl IntoView {
    view! {
        <h1>"Welcome to Leptos!"</h1>
        <Counter initial_value=0 />
    }
}

// Server-side rendering with hydration
#[server(GetUsers)]
async fn get_users() -> Result<Vec<User>, ServerError> {
    // Fetch users from database
    Ok(db::get_users().await?)
}

#[component]
fn UserList() -> impl IntoView {
    let users = create_resource(|| (), |_| get_users());
    
    view! {
        <div>
            <h2>"Users"</h2>
            <Suspense fallback=move || view! { <p>"Loading..."</p> }>
                {move || {
                    users.get().map(|users| match users {
                        Ok(users) => view! {
                            <ul>
                                {users.into_iter().map(|user| view! {
                                    <li>{user.name}</li>
                                }).collect::<Vec<_>>()}
                            </ul>
                        },
                        Err(e) => view! { <p>"Error: " {e.to_string()}</p> }
                    })
                }}
            </Suspense>
        </div>
    }
}

// SeaORM 2.0 - Expected in 2025
// A mature, async ORM for Rust

use sea_orm::{entity::*, query::*, DatabaseConnection};

#[derive(Clone, Debug, PartialEq, DeriveEntityModel)]
#[sea_orm(table_name = "users")]
pub struct Model {
    #[sea_orm(primary_key)]
    pub id: i32,
    pub name: String,
    pub email: String,
    pub created_at: DateTime,
}

#[derive(Copy, Clone, Debug, EnumIter, DeriveRelation)]
pub enum Relation {
    #[sea_orm(has_many = "super::posts::Entity")]
    Posts,
}

impl Related<super::posts::Entity> for Entity {
    fn to() -> RelationDef {
        Relation::Posts.def()
    }
}

async fn example(db: &DatabaseConnection) -> Result<(), DbErr> {
    // Find all users
    let users = Users::find().all(db).await?;
    
    // Find user by ID
    let user = Users::find_by_id(1).one(db).await?;
    
    // Create a new user
    let new_user = users::ActiveModel {
        name: Set("John".to_owned()),
        email: Set("[email protected]".to_owned()),
        ..Default::default()
    };
    
    let user = new_user.insert(db).await?;
    
    // Update a user
    let mut user: users::ActiveModel = user.into();
    user.name = Set("John Doe".to_owned());
    let user = user.update(db).await?;
    
    // Delete a user
    let user: users::ActiveModel = user.into();
    user.delete(db).await?;
    
    // Advanced query with joins and conditions
    let users_with_posts = Users::find()
        .find_with_related(Posts)
        .filter(posts::Column::Published.eq(true))
        .all(db)
        .await?;
    
    Ok(())
}

// Burn 1.0 - Expected in 2025
// A mature, production-ready ML framework

use burn::tensor::Tensor;
use burn::module::Module;
use burn::nn::{
    Conv2d, Conv2dConfig,
    Linear, LinearConfig,
    BatchNorm2d, BatchNorm2dConfig,
    MaxPool2d, MaxPool2dConfig,
    Dropout, DropoutConfig,
};
use burn::optim::{AdamConfig, Adam};
use burn::data::{dataloader::DataLoaderBuilder, dataset::Dataset};
use burn::record::{CompactRecorder, Recorder};
use burn::tensor::backend::Backend;

// Define a ResNet-like model
#[derive(Module, Debug)]
struct ResNet<B: Backend> {
    conv1: Conv2d<B>,
    bn1: BatchNorm2d<B>,
    conv2: Conv2d<B>,
    bn2: BatchNorm2d<B>,
    conv3: Conv2d<B>,
    bn3: BatchNorm2d<B>,
    pool: MaxPool2d,
    fc1: Linear<B>,
    fc2: Linear<B>,
    dropout: Dropout,
}

impl<B: Backend> ResNet<B> {
    pub fn new() -> Self {
        let conv1 = Conv2dConfig::new([3, 64], [3, 3])
            .with_padding(1)
            .init();
        let bn1 = BatchNorm2dConfig::new(64).init();
        
        let conv2 = Conv2dConfig::new([64, 128], [3, 3])
            .with_padding(1)
            .init();
        let bn2 = BatchNorm2dConfig::new(128).init();
        
        let conv3 = Conv2dConfig::new([128, 256], [3, 3])
            .with_padding(1)
            .init();
        let bn3 = BatchNorm2dConfig::new(256).init();
        
        let pool = MaxPool2dConfig::new([2, 2]).init();
        
        let fc1 = LinearConfig::new(256 * 4 * 4, 512).init();
        let fc2 = LinearConfig::new(512, 10).init();
        
        let dropout = DropoutConfig::new(0.5).init();
        
        Self {
            conv1, bn1, conv2, bn2, conv3, bn3, pool, fc1, fc2, dropout,
        }
    }
    
    pub fn forward(&self, x: Tensor<B, 4>) -> Tensor<B, 2> {
        let x = self.conv1.forward(x);
        let x = self.bn1.forward(x).relu();
        let x = self.pool.forward(x);
        
        let x = self.conv2.forward(x);
        let x = self.bn2.forward(x).relu();
        let x = self.pool.forward(x);
        
        let x = self.conv3.forward(x);
        let x = self.bn3.forward(x).relu();
        let x = self.pool.forward(x);
        
        // Flatten
        let batch_size = x.shape()[0];
        let x = x.reshape([batch_size, 256 * 4 * 4]);
        
        let x = self.fc1.forward(x).relu();
        let x = self.dropout.forward(x);
        self.fc2.forward(x)
    }
}

// Training loop with advanced features
async fn train<B: Backend>(
    device: B,
    dataset: impl Dataset<Item = (Tensor<B, 4>, Tensor<B, 1>)>,
) -> ResNet<B> {
    // Initialize model
    let model = ResNet::new();
    
    // Configure optimizer
    let optimizer = AdamConfig::new()
        .with_learning_rate(0.001)
        .with_weight_decay(1e-5)
        .init();
    
    // Configure data loader
    let dataloader = DataLoaderBuilder::new()
        .with_batch_size(64)
        .with_shuffle(true)
        .build(dataset);
    
    // Configure recorder for checkpointing
    let recorder = CompactRecorder::new()
        .with_dir("checkpoints")
        .with_max_to_keep(3);
    
    // Training loop
    for epoch in 0..10 {
        let mut epoch_loss = 0.0;
        let mut batches = 0;
        
        for (inputs, targets) in dataloader.iter() {
            // Forward pass
            let outputs = model.forward(inputs);
            let loss = outputs.cross_entropy_loss(&targets);
            
            // Backward pass and optimize
            let gradients = loss.backward();
            optimizer.step(&gradients);
            
            epoch_loss += loss.into_scalar();
            batches += 1;
        }
        
        println!("Epoch {}: Loss = {}", epoch, epoch_loss / batches as f32);
        
        // Save checkpoint
        recorder.record(epoch, &model);
    }
    
    model
}

// Kube-rs 1.0 - Expected in 2025
// A mature Kubernetes client and operator framework

use kube::{
    api::{Api, DeleteParams, ListParams, PatchParams, PostParams},
    client::Client,
    core::ObjectMeta,
    CustomResource,
};
use schemars::JsonSchema;
use serde::{Deserialize, Serialize};
use k8s_openapi::api::core::v1::Pod;
use futures::StreamExt;
use std::time::Duration;

// Define a custom resource
#[derive(CustomResource, Deserialize, Serialize, Clone, Debug, JsonSchema)]
#[kube(
    group = "example.com",
    version = "v1",
    kind = "Application",
    namespaced
)]
pub struct ApplicationSpec {
    pub replicas: i32,
    pub image: String,
    pub env: Vec<EnvVar>,
}

#[derive(Deserialize, Serialize, Clone, Debug, JsonSchema)]
pub struct EnvVar {
    pub name: String,
    pub value: String,
}

#[derive(Deserialize, Serialize, Clone, Debug, JsonSchema)]
pub struct ApplicationStatus {
    pub ready_replicas: i32,
    pub phase: String,
}

// Kubernetes operator
async fn run_operator() -> Result<(), kube::Error> {
    // Initialize the Kubernetes client
    let client = Client::try_default().await?;
    
    // Create an API for our custom resource
    let applications = Api::<Application>::all(client.clone());
    
    // Watch for changes to our custom resource
    let mut application_stream = applications.watch(&ListParams::default(), "0").await?.boxed();
    
    while let Some(event) = application_stream.next().await {
        match event {
            Ok(event) => {
                match event {
                    kube::api::WatchEvent::Added(app) => {
                        reconcile_application(client.clone(), app).await?;
                    }
                    kube::api::WatchEvent::Modified(app) => {
                        reconcile_application(client.clone(), app).await?;
                    }
                    kube::api::WatchEvent::Deleted(app) => {
                        cleanup_application(client.clone(), app).await?;
                    }
                    _ => {}
                }
            }
            Err(e) => {
                eprintln!("Watch error: {}", e);
            }
        }
    }
    
    Ok(())
}

async fn reconcile_application(client: Client, app: Application) -> Result<(), kube::Error> {
    let name = app.metadata.name.as_ref().unwrap();
    let namespace = app.metadata.namespace.as_ref().unwrap();
    let spec = app.spec;
    
    // Create or update deployment
    // ...
    
    // Create or update service
    // ...
    
    // Update status
    let status = ApplicationStatus {
        ready_replicas: 0,
        phase: "Reconciling".to_string(),
    };
    
    let applications = Api::<Application>::namespaced(client, namespace);
    applications
        .patch_status(
            name,
            &PatchParams::default(),
            &serde_json::json!({
                "status": status
            }),
        )
        .await?;
    
    Ok(())
}

async fn cleanup_application(client: Client, app: Application) -> Result<(), kube::Error> {
    // Delete resources created by the application
    // ...
    
    Ok(())
}