genson-core 0.2.5

// genson-core/src/tests/schema.rs
use super::*;
use crate::debug;
use predicates::prelude::*;
use serde_json::json;

#[test]
fn test_reorder_unions_string_float_null() {
    // Unordered union: string, float, null
    let mut schema = json!({
        "type": ["string", "float", "null"]
    });

    reorder_unions(&mut schema);

    // After reordering, null should come first, then float/number, then string
    assert_eq!(
        schema,
        json!({
            "type": ["null", "float", "string"]
        })
    );
}

#[test]
fn test_basic_schema_inference() {
    let json_strings = vec![
        r#"{"name": "Alice", "age": 30}"#.to_string(),
        r#"{"name": "Bob", "age": 25, "city": "NYC"}"#.to_string(),
    ];

    let result = infer_json_schema_from_strings(&json_strings, SchemaInferenceConfig::default())
        .expect("Schema inference should succeed");

    // Test processed count
    assert_eq!(result.processed_count, 2);

    // Use predicates to test schema structure
    let schema_str = result.schema.to_string();

    predicate::str::contains("\"type\"")
        .and(predicate::str::contains("object"))
        .eval(&schema_str);

    predicate::str::contains("\"properties\"").eval(&schema_str);

    // Check that both name and age properties are present
    predicate::str::contains("\"name\"")
        .and(predicate::str::contains("\"age\""))
        .eval(&schema_str);

    println!(
        "✅ Generated schema: {}",
        serde_json::to_string_pretty(&result.schema).unwrap()
    );
}

#[test]
fn test_empty_input() {
    let json_strings = vec![];
    let result = infer_json_schema_from_strings(&json_strings, SchemaInferenceConfig::default());

    assert!(result.is_err());

    let error_msg = result.unwrap_err();
    predicate::str::contains("No JSON strings provided").eval(&error_msg);

    println!("✅ Empty input correctly rejected with: {}", error_msg);
}

#[test]
fn test_invalid_json_variants() {
    let test_cases = vec![
        (
            r#"{"name": "Alice"}"#,
            r#"{"invalid": json}"#,
            "unquoted value",
        ),
        (
            r#"{"valid": "json"}"#,
            r#"{"incomplete":"#,
            "incomplete string",
        ),
        (r#"{"good": "data"}"#, r#"{"trailing":,"#, "trailing comma"),
        (
            r#"{"working": true}"#,
            r#"{invalid: "json"}"#,
            "unquoted key",
        ),
        (
            r#"{"normal": "object"}"#,
            r#"{"nested": {"broken": json}}"#,
            "nested broken JSON",
        ),
    ];

    for (valid_json, invalid_json, description) in test_cases {
        println!("🧪 Testing: {}", description);
        println!("   Valid JSON: {}", valid_json);
        println!("   Invalid JSON: {}", invalid_json);

        let json_strings = vec![valid_json.to_string(), invalid_json.to_string()];

        let result =
            infer_json_schema_from_strings(&json_strings, SchemaInferenceConfig::default());

        // Should return an error instead of panicking
        assert!(result.is_err(), "Expected error for case: {}", description);

        let error_msg = result.unwrap_err();

        // Use predicates to verify error message content
        predicate::str::contains("Invalid JSON input at position").eval(&error_msg);

        // For short JSON strings, verify the content is included
        if invalid_json.len() <= MAX_JSON_ERROR_LENGTH {
            predicate::str::contains(invalid_json).eval(&error_msg);
        } else {
            // For long JSON, just check that truncation happened
            predicate::str::contains("truncated").eval(&error_msg);
        }

        // Ensure we don't have panic-related messages
        predicate::str::contains("panicked").not().eval(&error_msg);

        predicate::str::contains("SIGABRT").not().eval(&error_msg);

        println!("   ❌ Correctly failed with: {}", error_msg);
        println!();
    }
}

#[test]
fn test_mixed_valid_and_empty_strings() {
    let json_strings = vec![
        r#"{"name": "Alice", "age": 30}"#.to_string(),
        "".to_string(),    // Empty string should be skipped
        "   ".to_string(), // Whitespace-only should be skipped
        r#"{"name": "Bob", "age": 25}"#.to_string(),
    ];

    let result = infer_json_schema_from_strings(&json_strings, SchemaInferenceConfig::default())
        .expect("Should succeed with valid JSON, skipping empty strings");

    // Should process only the 2 valid JSON strings
    assert_eq!(result.processed_count, 2);

    let schema_str = result.schema.to_string();
    predicate::str::contains("\"name\"")
        .and(predicate::str::contains("\"age\""))
        .eval(&schema_str);

    println!(
        "✅ Processed {} valid strings, skipped empty ones",
        result.processed_count
    );
}

#[test]
fn test_schema_config_variations() {
    let json_strings = vec![r#"[{"item": "first"}, {"item": "second"}]"#.to_string()];

    // Test with ignore_outer_array = false
    let config_array = SchemaInferenceConfig {
        ignore_outer_array: false,
        ..Default::default()
    };

    let result = infer_json_schema_from_strings(&json_strings, config_array)
        .expect("Should handle array schema");

    let schema_str = result.schema.to_string();
    predicate::str::contains("\"type\"")
        .and(predicate::str::contains("array"))
        .eval(&schema_str);

    println!(
        "✅ Array schema: {}",
        serde_json::to_string_pretty(&result.schema).unwrap()
    );

    // Test with ignore_outer_array = true (default)
    let config_object = SchemaInferenceConfig {
        ignore_outer_array: true,
        ..Default::default()
    };

    let result = infer_json_schema_from_strings(&json_strings, config_object)
        .expect("Should handle object schema from array items");

    let schema_str = result.schema.to_string();
    predicate::str::contains("\"type\"")
        .and(predicate::str::contains("object"))
        .eval(&schema_str);

    predicate::str::contains("\"item\"").eval(&schema_str);

    println!(
        "✅ Object schema from array items: {}",
        serde_json::to_string_pretty(&result.schema).unwrap()
    );
}

#[test]
fn test_very_long_invalid_json() {
    // Create a very long invalid JSON string
    let long_value = "x".repeat(500); // 500 char string
    let long_invalid_json = format!(
        r#"{{"field1": "{}", "field2": "{}", "field3": "{}", "field4": "{}", "invalid_syntax": }}"#,
        long_value, long_value, long_value, long_value
    );

    let json_strings = vec![
        r#"{"valid": "json"}"#.to_string(),
        long_invalid_json.clone(),
    ];

    println!(
        "🧪 Testing very long invalid JSON ({} chars)",
        long_invalid_json.len()
    );

    let result = infer_json_schema_from_strings(&json_strings, SchemaInferenceConfig::default());

    assert!(result.is_err(), "Expected error for very long invalid JSON");

    let error_msg = result.unwrap_err();

    println!("The error message was: {}", error_msg);

    // Should contain truncation indicator
    predicate::str::contains("truncated").eval(&error_msg);

    // Should contain position information
    predicate::str::contains("Invalid JSON input at position 2").eval(&error_msg);

    // Error message should be reasonable length (much shorter than original JSON)
    assert!(
        error_msg.len() < long_invalid_json.len() / 2,
        "Error message should be much shorter than original JSON"
    );

    println!(
        "   ❌ Correctly truncated long JSON in error: {}",
        error_msg
    );

    // Verify the error message doesn't exceed a reasonable length
    assert!(
        error_msg.len() < 500,
        "Error message should be under 500 chars, got: {}",
        error_msg.len()
    );
}

#[test]
fn test_complex_nested_schema() {
    let json_strings = vec![
        json!({
            "user": {
                "id": 123,
                "profile": {
                    "name": "Alice",
                    "preferences": ["dark_mode", "notifications"]
                }
            },
            "metadata": {
                "created_at": "2024-01-01",
                "version": 1
            }
        })
        .to_string(),
        json!({
            "user": {
                "id": 456,
                "profile": {
                    "name": "Bob",
                    "preferences": ["light_mode"]
                }
            },
            "metadata": {
                "created_at": "2024-01-02",
                "version": 2
            }
        })
        .to_string(),
    ];

    let result = infer_json_schema_from_strings(&json_strings, SchemaInferenceConfig::default())
        .expect("Should handle complex nested schema");

    assert_eq!(result.processed_count, 2);

    let schema_str = result.schema.to_string();

    // Check for nested structure
    predicate::str::contains("\"user\"")
        .and(predicate::str::contains("\"metadata\""))
        .and(predicate::str::contains("\"profile\""))
        .and(predicate::str::contains("\"preferences\""))
        .eval(&schema_str);

    println!("✅ Complex nested schema generated successfully");
    println!(
        "Schema: {}",
        serde_json::to_string_pretty(&result.schema).unwrap()
    );
}

#[test]
fn test_ndjson_parsing() {
    // Two valid JSON objects separated by newlines (NDJSON format)
    let ndjson_input = r#"
{"name": "Alice", "age": 30}
{"name": "Bob", "age": 25, "city": "NYC"}
{"name": "Charlie"}
"#;

    let json_strings = vec![ndjson_input.to_string()];

    let config = SchemaInferenceConfig {
        delimiter: Some(b'\n'),
        ..Default::default()
    };

    let result = infer_json_schema_from_strings(&json_strings, config)
        .expect("NDJSON schema inference should succeed");

    // All 3 objects should be processed
    assert_eq!(result.processed_count, 1,
    "NDJSON should be counted as a single input string but parsed into multiple rows internally"
);

    let schema_str = result.schema.to_string();

    // The schema should include properties from all lines
    assert!(!schema_str.contains("Alice")); // values are not in schema
    assert!(schema_str.contains("\"name\""));
    assert!(schema_str.contains("\"age\""));
    assert!(schema_str.contains("\"city\""));

    println!(
        "✅ NDJSON schema generated: {}",
        serde_json::to_string_pretty(&result.schema).unwrap()
    );
}

#[test]
fn test_invalid_ndjson_line() {
    // Second line is malformed
    let ndjson_input = r#"
{"valid": true}
{"invalid": json}
{"also_valid": 123}
"#;

    let json_strings = vec![ndjson_input.to_string()];

    let config = SchemaInferenceConfig {
        delimiter: Some(b'\n'),
        ..Default::default()
    };

    let result = infer_json_schema_from_strings(&json_strings, config.clone());

    assert!(result.is_err(), "Expected error for malformed NDJSON line");

    let err_msg = result.unwrap_err();
    debug!(config, "Got error: {}", err_msg);
    assert!(
        err_msg.contains("Invalid JSON input at index 1: expected value at line 1 column 13"),
        "Error message should report the failing line"
    );
    println!("✅ Correctly rejected malformed NDJSON: {}", err_msg);
}

/// Two objects with varying keys and homogeneous string values (low map threshold)
#[test]
fn test_map_threshold_rewrite() {
    let json_strings = vec![
        r#"{"labels": {"en": "Hello", "fr": "Bonjour"}}"#.to_string(),
        r#"{"labels": {"de": "Hallo", "es": "Hola"}}"#.to_string(),
    ];

    let config = SchemaInferenceConfig {
        map_threshold: 2,
        ..Default::default()
    };
    let result = infer_json_schema_from_strings(&json_strings, config).unwrap();

    let labels = &result.schema["properties"]["labels"];
    assert_eq!(labels["type"], "object");
    assert!(labels.get("additionalProperties").is_some());
    assert!(labels.get("properties").is_none());
}

/// Two objects with varying keys and homogeneous string values (default map threshold)
#[test]
fn test_map_threshold_as_record() {
    let json_strings = vec![
        r#"{"labels": {"en": "Hello", "fr": "Bonjour"}}"#.to_string(),
        r#"{"labels": {"de": "Hallo", "es": "Hola"}}"#.to_string(),
    ];

    let result =
        infer_json_schema_from_strings(&json_strings, SchemaInferenceConfig::default()).unwrap();

    let labels = &result.schema["properties"]["labels"];
    assert!(labels.get("properties").is_some());
    assert!(labels.get("additionalProperties").is_none());
}

#[test]
fn test_wrap_root_inserts_single_required_field() {
    let json_strings = vec![
        r#"{"en":{"language":"en","value":"Hello"},"fr":{"language":"fr","value":"Bonjour"}}"#
            .to_string(),
    ];

    let cfg = SchemaInferenceConfig {
        wrap_root: Some("labels".to_string()),
        ..Default::default()
    };

    let out = infer_json_schema_from_strings(&json_strings, cfg).unwrap();
    let sch = out.schema;

    assert_eq!(sch["type"], "object");
    assert_eq!(sch["required"], serde_json::json!(["labels"]));
    assert!(sch["properties"]["labels"].is_object());
}

#[test]
fn test_rewrite_objects_map_of_records() {
    use serde_json::json;

    // Schema that genson-rs would roughly emit for {"en": {...}, "fr": {...}}
    let mut schema = json!({
        "type": "object",
        "properties": {
            "en": {
                "type": "object",
                "properties": {
                    "language": { "type": "string" },
                    "value": { "type": "string" }
                },
                "required": ["language", "value"]
            },
            "fr": {
                "type": "object",
                "properties": {
                    "language": { "type": "string" },
                    "value": { "type": "string" }
                },
                "required": ["language", "value"]
            }
        },
        "required": ["en","fr"]
    });

    let cfg = SchemaInferenceConfig {
        map_threshold: 2, // force detection at 2 keys
        ..Default::default()
    };

    rewrite_objects(&mut schema, None, &cfg);

    // After rewrite, we should have additionalProperties instead of fixed properties
    assert_eq!(schema["type"], "object");
    assert!(schema.get("properties").is_none());
    assert!(schema.get("required").is_none());

    // additionalProperties should carry the inner record shape
    let ap = schema
        .get("additionalProperties")
        .expect("should insert additionalProperties");

    assert_eq!(ap["type"], "object");
    assert_eq!(ap["properties"]["language"], json!({ "type": "string" }));
    assert_eq!(ap["properties"]["value"], json!({ "type": "string" }));
}

#[test]
fn test_map_of_strings_not_promoted_to_records() {
    let schema = json!({
        "type": "object",
        "properties": {
            "labels": {
                "type": "object",
                "properties": {
                    "en": { "type": "string" },
                    "fr": { "type": "string" }
                },
                "required": ["en", "fr"]
            }
        },
        "required": ["labels"]
    });

    let mut sch = schema.clone();
    let cfg = SchemaInferenceConfig {
        map_threshold: 2,
        ..Default::default()
    };
    rewrite_objects(&mut sch, None, &cfg);

    assert_eq!(
        sch["properties"]["labels"]["additionalProperties"]["type"],
        "string"
    );
}

#[test]
fn test_rewrite_objects_respects_map_max_required_keys() {
    let mut schema = json!({
        "type": "object",
        "properties": {
            "field1": {"type": "string"},
            "field2": {"type": "string"}
        },
        "required": ["field1", "field2"]
    });

    let config = SchemaInferenceConfig {
        map_threshold: 2,
        map_max_required_keys: Some(1), // Max 1 required key for maps
        ..Default::default()
    };

    rewrite_objects(&mut schema, None, &config);

    // Should remain as record because 2 required keys > 1
    assert_eq!(schema["type"], "object");
    assert!(schema.get("properties").is_some());
    assert!(schema.get("additionalProperties").is_none());
}

#[test]
fn test_rewrite_objects_allows_map_with_few_required_keys() {
    let mut schema = json!({
        "type": "object",
        "properties": {
            "field1": {"type": "string"},
            "field2": {"type": "string"}
        },
        "required": ["field1"] // Only 1 required key
    });

    let config = SchemaInferenceConfig {
        map_threshold: 2,
        map_max_required_keys: Some(1), // Max 1 required key for maps
        ..Default::default()
    };

    rewrite_objects(&mut schema, None, &config);

    // Should become map because 1 required key ≤ 1
    assert_eq!(schema["type"], "object");
    assert!(schema.get("additionalProperties").is_some());
    assert!(schema.get("properties").is_none());
}

#[test]
fn test_rewrite_objects_none_max_required_keys_preserves_behavior() {
    let mut schema = json!({
        "type": "object",
        "properties": {
            "field1": {"type": "string"},
            "field2": {"type": "string"},
            "field3": {"type": "string"}
        },
        "required": ["field1", "field2", "field3"]
    });

    let config = SchemaInferenceConfig {
        map_threshold: 2,
        map_max_required_keys: None, // No gating
        ..Default::default()
    };

    rewrite_objects(&mut schema, None, &config);

    // Should become map because None means no gating (old behavior)
    assert_eq!(schema["type"], "object");
    assert!(schema.get("additionalProperties").is_some());
    assert!(schema.get("properties").is_none());
}

#[test]
fn test_rewrite_objects_zero_max_required_keys() {
    let mut schema = json!({
        "type": "object",
        "properties": {
            "field1": {"type": "string"},
            "field2": {"type": "string"}
        },
        "required": ["field1"]
    });

    let config = SchemaInferenceConfig {
        map_threshold: 2,
        map_max_required_keys: Some(0), // Only allow maps with 0 required keys
        ..Default::default()
    };

    rewrite_objects(&mut schema, None, &config);

    // Should remain as record because 1 required key > 0
    assert_eq!(schema["type"], "object");
    assert!(schema.get("properties").is_some());
    assert!(schema.get("additionalProperties").is_none());
}

#[test]
fn test_rewrite_objects_zero_required_keys_allowed() {
    let mut schema = json!({
        "type": "object",
        "properties": {
            "field1": {"type": "string"},
            "field2": {"type": "string"}
        }
        // No required array = 0 required keys
    });

    let config = SchemaInferenceConfig {
        map_threshold: 2,
        map_max_required_keys: Some(0), // Only allow maps with 0 required keys
        ..Default::default()
    };

    rewrite_objects(&mut schema, None, &config);

    // Should become map because 0 required keys ≤ 0
    assert_eq!(schema["type"], "object");
    assert!(schema.get("additionalProperties").is_some());
    assert!(schema.get("properties").is_none());
}

#[test]
fn test_rewrite_objects_force_override_wins() {
    let mut schema = json!({
        "type": "object",
        "properties": {
            "field1": {"type": "string"},
            "field2": {"type": "string"}
        },
        "required": ["field1", "field2"]
    });

    let mut force_types = std::collections::HashMap::new();
    force_types.insert("test_field".to_string(), "map".to_string());

    let config = SchemaInferenceConfig {
        map_threshold: 2,
        map_max_required_keys: Some(0), // Would normally block this
        force_field_types: force_types,
        ..Default::default()
    };

    // Apply with field name that matches force override
    rewrite_objects(&mut schema, Some("test_field"), &config);

    // Should become map despite having required keys due to force override
    assert_eq!(schema["type"], "object");
    assert!(schema.get("additionalProperties").is_some());
    assert!(schema.get("properties").is_none());
}

#[test]
fn test_rewrite_objects_non_homogeneous_values_not_rewritten() {
    let mut schema = json!({
        "type": "object",
        "properties": {
            "field1": {"type": "string"},
            "field2": {"type": "integer"} // Non-homogeneous
        },
        "required": []
    });

    let config = SchemaInferenceConfig {
        map_threshold: 2,
        map_max_required_keys: Some(5), // Would allow this
        ..Default::default()
    };

    rewrite_objects(&mut schema, None, &config);

    // Should remain as record because values are not homogeneous
    assert_eq!(schema["type"], "object");
    assert!(schema.get("properties").is_some());
    assert!(schema.get("additionalProperties").is_none());
}

#[test]
fn test_rewrite_objects_below_threshold_not_rewritten() {
    let mut schema = json!({
        "type": "object",
        "properties": {
            "field1": {"type": "string"}
        },
        "required": []
    });

    let config = SchemaInferenceConfig {
        map_threshold: 5,               // Above the key count
        map_max_required_keys: Some(5), // Would allow this
        ..Default::default()
    };

    rewrite_objects(&mut schema, None, &config);

    // Should remain as record because below threshold
    assert_eq!(schema["type"], "object");
    assert!(schema.get("properties").is_some());
    assert!(schema.get("additionalProperties").is_none());
}

#[test]
fn test_map_max_required_keys_with_wrap_root() {
    let json_strings = vec![
        r#"{"en":{"language":"en","value":"Hello"},"fr":{"language":"fr","value":"Bonjour"}}"#
            .to_string(),
    ];

    let cfg = SchemaInferenceConfig {
        wrap_root: Some("labels".to_string()),
        map_threshold: 2,
        map_max_required_keys: Some(1), // Should allow the wrapped content
        ..Default::default()
    };

    let out = infer_json_schema_from_strings(&json_strings, cfg).unwrap();
    let sch = out.schema;

    assert_eq!(sch["type"], "object");
    assert_eq!(sch["required"], serde_json::json!(["labels"]));

    // The wrapped labels should have the map logic applied
    let labels_content = &sch["properties"]["labels"];
    assert!(labels_content.is_object());

    println!("✅ map_max_required_keys works with wrap_root");
}

#[test]
fn test_wrap_scalars_in_map_of_records() {
    let json_strings = vec![
        // "root" field is a map, all map keys have a record{id,value},
        // for map keys A/B value is a record{hello} and for map key C value is a string
        // Row 1: value is an object
        r#"{"root": {"A": {"id": 1, "value": {"hello": "world"}}}}"#.to_string(),
        // Row 2: value is an object, again
        r#"{"root": {"B": {"id": 2, "value": {"hello": "foo"}}}}"#.to_string(),
        // Row 3: value is just a string
        r#"{"root": {"C": {"id": 3, "value": "bar"}}}"#.to_string(),
    ];

    let cfg = SchemaInferenceConfig {
        map_threshold: 3,
        map_max_required_keys: Some(0),
        unify_maps: true,
        wrap_scalars: true,
        ..Default::default()
    };

    let result = infer_json_schema_from_strings(&json_strings, cfg)
        .expect("Schema inference should succeed with wrap_scalars");

    let sch = result.schema;

    // Navigate to root map’s value type
    let root_additional = &sch["properties"]["root"]["additionalProperties"];
    assert_eq!(root_additional["type"], "object");

    // The "value" field should be promoted and contain both object and scalar string form
    let value_schema = &root_additional["properties"]["value"];
    assert!(value_schema.is_object());

    // Should contain the synthetic key for the wrapped scalar
    assert!(
        value_schema["properties"]
            .as_object()
            .unwrap()
            .keys()
            .any(|k| k.contains("__string")),
        "Expected synthetic scalar wrapper key inside value schema, got: {}",
        serde_json::to_string_pretty(value_schema).unwrap()
    );

    println!(
        "✅ wrap_scalars promoted scalar inside map-of-records: {}",
        serde_json::to_string_pretty(value_schema).unwrap()
    );
}