sql-cli 1.73.1

SQL query tool for CSV/JSON with both interactive TUI and non-interactive CLI modes - perfect for exploration and automation
Documentation 
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use serde_json::json;
use sql_cli::data::csv_datasource::CsvApiClient;

#[test]
fn test_comparison_operators() {
    let test_data = vec![
        json!({
            "id": 1,
            "price": 100.5,
            "quantity": 10,
            "status": "active"
        }),
        json!({
            "id": 2,
            "price": 50.0,
            "quantity": 20,
            "status": "pending"
        }),
        json!({
            "id": 3,
            "price": 75.25,
            "quantity": 15,
            "status": "active"
        }),
        json!({
            "id": 4,
            "price": 100.5,
            "quantity": 5,
            "status": "cancelled"
        }),
    ];

    let mut csv_client = CsvApiClient::new();
    csv_client
        .load_from_json(test_data.clone(), "test_data")
        .unwrap();

    // Test != operator
    let result = csv_client
        .query_csv("SELECT * FROM test_data WHERE status != \"cancelled\"")
        .unwrap();
    assert_eq!(result.data.len(), 3, "Should exclude cancelled status");

    // Test >= operator
    let result = csv_client
        .query_csv("SELECT * FROM test_data WHERE price >= 75.25")
        .unwrap();
    assert_eq!(result.data.len(), 3, "Should return prices >= 75.25");

    // Test <= operator
    let result = csv_client
        .query_csv("SELECT * FROM test_data WHERE quantity <= 10")
        .unwrap();
    assert_eq!(result.data.len(), 2, "Should return quantities <= 10");

    // Test < operator
    let result = csv_client
        .query_csv("SELECT * FROM test_data WHERE price < 75.25")
        .unwrap();
    assert_eq!(result.data.len(), 1, "Should return prices < 75.25");
}

#[test]
fn test_not_in_clause() {
    let test_data = vec![
        json!({ "id": 1, "country": "US" }),
        json!({ "id": 2, "country": "FR" }),
        json!({ "id": 3, "country": "JP" }),
        json!({ "id": 4, "country": "UK" }),
        json!({ "id": 5, "country": "DE" }),
    ];

    let mut csv_client = CsvApiClient::new();
    csv_client
        .load_from_json(test_data.clone(), "countries")
        .unwrap();

    let result = csv_client
        .query_csv("SELECT * FROM countries WHERE country NOT IN (\"US\", \"UK\")")
        .unwrap();
    assert_eq!(result.data.len(), 3, "Should exclude US and UK");

    // Verify the results
    for row in &result.data {
        let country = row["country"].as_str().unwrap();
        assert!(country != "US" && country != "UK");
    }
}

#[test]
fn test_between_operator() {
    let test_data = vec![
        json!({ "id": 1, "price": 10.0, "date": "2025-01-01" }),
        json!({ "id": 2, "price": 25.0, "date": "2025-01-15" }),
        json!({ "id": 3, "price": 50.0, "date": "2025-02-01" }),
        json!({ "id": 4, "price": 75.0, "date": "2025-02-15" }),
        json!({ "id": 5, "price": 100.0, "date": "2025-03-01" }),
    ];

    let mut csv_client = CsvApiClient::new();
    csv_client
        .load_from_json(test_data.clone(), "sales")
        .unwrap();

    // Test numeric BETWEEN
    let result = csv_client
        .query_csv("SELECT * FROM sales WHERE price BETWEEN 25 AND 75")
        .unwrap();
    assert_eq!(
        result.data.len(),
        3,
        "Should return prices between 25 and 75 inclusive"
    );

    // Test date BETWEEN
    let result = csv_client
        .query_csv("SELECT * FROM sales WHERE date BETWEEN \"2025-01-15\" AND \"2025-02-15\"")
        .unwrap();
    assert_eq!(
        result.data.len(),
        3,
        "Should return dates between Jan 15 and Feb 15"
    );
}

#[test]
fn test_null_handling() {
    let test_data = vec![
        json!({ "id": 1, "name": "John", "email": "john@example.com" }),
        json!({ "id": 2, "name": "Jane", "email": null }),
        json!({ "id": 3, "name": "Bob" }), // missing email field
        json!({ "id": 4, "name": "Alice", "email": "alice@example.com" }),
    ];

    let mut csv_client = CsvApiClient::new();
    csv_client
        .load_from_json(test_data.clone(), "users")
        .unwrap();

    // Test IS NULL
    let result = csv_client
        .query_csv("SELECT * FROM users WHERE email IS NULL")
        .unwrap();
    assert_eq!(
        result.data.len(),
        2,
        "Should return rows with null or missing email"
    );

    // Test IS NOT NULL
    let result = csv_client
        .query_csv("SELECT * FROM users WHERE email IS NOT NULL")
        .unwrap();
    assert_eq!(
        result.data.len(),
        2,
        "Should return rows with non-null email"
    );
}

#[test]
fn test_like_pattern_matching() {
    let test_data = vec![
        json!({ "id": 1, "name": "John Smith", "email": "john@gmail.com" }),
        json!({ "id": 2, "name": "Jane Doe", "email": "jane@yahoo.com" }),
        json!({ "id": 3, "name": "Bob Johnson", "email": "bob@gmail.com" }),
        json!({ "id": 4, "name": "Alice Brown", "email": "alice@hotmail.com" }),
    ];

    let mut csv_client = CsvApiClient::new();
    csv_client
        .load_from_json(test_data.clone(), "contacts")
        .unwrap();

    // Test LIKE with % wildcard
    let result = csv_client
        .query_csv("SELECT * FROM contacts WHERE email LIKE \"%@gmail.com\"")
        .unwrap();
    assert_eq!(result.data.len(), 2, "Should return gmail addresses");

    // Test LIKE with multiple wildcards
    let result = csv_client
        .query_csv("SELECT * FROM contacts WHERE name LIKE \"J%\"")
        .unwrap();
    assert_eq!(result.data.len(), 2, "Should return names starting with J");

    // Test LIKE with _ wildcard
    let result = csv_client
        .query_csv("SELECT * FROM contacts WHERE name LIKE \"J_ne%\"")
        .unwrap();
    assert_eq!(result.data.len(), 1, "Should return Jane");
}

#[test]
fn test_complex_combined_queries() {
    let test_data = vec![
        json!({
            "id": 1,
            "product": "Laptop",
            "price": 1200.0,
            "quantity": 5,
            "category": "Electronics",
            "discount": null
        }),
        json!({
            "id": 2,
            "product": "Mouse",
            "price": 25.0,
            "quantity": 50,
            "category": "Electronics",
            "discount": 10.0
        }),
        json!({
            "id": 3,
            "product": "Desk",
            "price": 350.0,
            "quantity": 10,
            "category": "Furniture",
            "discount": 15.0
        }),
        json!({
            "id": 4,
            "product": "Chair",
            "price": 200.0,
            "quantity": 0,
            "category": "Furniture",
            "discount": null
        }),
        json!({
            "id": 5,
            "product": "Monitor",
            "price": 400.0,
            "quantity": 8,
            "category": "Electronics",
            "discount": 20.0
        }),
    ];

    let mut csv_client = CsvApiClient::new();
    csv_client
        .load_from_json(test_data.clone(), "inventory")
        .unwrap();

    // Test BETWEEN first
    let query = "SELECT * FROM inventory WHERE price BETWEEN 100 AND 500";
    let result = csv_client.query_csv(query).unwrap();
    println!("BETWEEN test: {} results", result.data.len());
    for item in &result.data {
        println!("  {} - Price: {}", item["product"], item["price"]);
    }

    // Complex query 1: Electronics with price between 100-500 and quantity > 0
    // Expected: Monitor (400, qty 8) - Mouse is 25 (too low), Laptop is 1200 (too high)
    let query = "SELECT * FROM inventory WHERE category = \"Electronics\" AND price BETWEEN 100 AND 500 AND quantity > 0";
    let result = csv_client.query_csv(query).unwrap();
    println!("\nComplex query results:");
    for item in &result.data {
        println!(
            "  {} - Price: {}, Category: {}, Quantity: {}",
            item["product"], item["price"], item["category"], item["quantity"]
        );
    }
    assert_eq!(result.data.len(), 1, "Should return Monitor only");

    // Complex query 2: Items with discount or low quantity
    // Laptop: qty=5 (matches), Mouse: discount=10 (matches), Desk: discount=15 (matches),
    // Chair: qty=0 (matches), Monitor: discount=20 (matches) = 5 items total
    let query = "SELECT * FROM inventory WHERE discount IS NOT NULL OR quantity <= 5";
    let result = csv_client.query_csv(query).unwrap();
    assert_eq!(result.data.len(), 5, "Should return 5 items");

    // Complex query 3: Pattern matching with other conditions
    let query = "SELECT * FROM inventory WHERE product LIKE \"M%\" AND category = \"Electronics\" AND price < 500";
    let result = csv_client.query_csv(query).unwrap();
    assert_eq!(result.data.len(), 2, "Should return Mouse and Monitor");
}