Data Transform

Source: examples/data_transform.ion in the repo.

// Data transformation pipeline

let users = [
    #{name: "Alice", age: 30, role: "admin"},
    #{name: "Bob", age: 25, role: "user"},
    #{name: "Charlie", age: 35, role: "admin"},
    #{name: "Diana", age: 28, role: "user"},
    #{name: "Eve", age: 22, role: "admin"},
];

// Filter admins and format their names
let admin_names = users
    .filter(|u| u.role == "admin")
    .map(|u| u.name);
io::println(f"Admins: {admin_names}");

// Average age using reduce
let total_age = users.map(|u| u.age).reduce(|a, b| a + b);
let avg_age = total_age / users.len();
io::println(f"Average age: {avg_age}");

// Unique roles using set
let unique_roles = set(users.map(|u| u.role));
io::println(f"Roles: {unique_roles}");

// Age statistics using min/max/sum
let ages = users.map(|u| u.age);
io::println(f"Youngest: {ages.min()}");
io::println(f"Oldest: {ages.max()}");
io::println(f"Total age: {ages.sum()}");

// Chunk users into groups of 2
let groups = users.chunk(2);
for (i, group) in enumerate(groups) {
    let names = group.map(|u| u.name).join(", ");
    io::println(f"Group {i + 1}: {names}");
}

// Sort by age
let by_age = users
    .sort_by(|a, b| a.age - b.age)
    .map(|u| f"{u.name} ({u.age})");
io::println(f"By age: {by_age.join(", ")}");

// Create summary report
let report = #{
    total_users: users.len(),
    admin_count: users.filter(|u| u.role == "admin").len(),
    average_age: avg_age,
    oldest: ages.max(),
    youngest: ages.min(),
};
io::println(f"Report: {json::pretty(report)}");