com.pulumi.azure.datafactory.kotlin.outputs.DatasetSnowflakeSchemaColumn.kt Maven / Gradle / Ivy

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Build cloud applications and infrastructure by combining the safety and reliability of infrastructure as code with the power of the Kotlin programming language.

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@file:Suppress("NAME_SHADOWING", "DEPRECATION")

package com.pulumi.azure.datafactory.kotlin.outputs

import kotlin.Int
import kotlin.String
import kotlin.Suppress

/**
 *
 * @property name The name of the column.
 * @property precision The total number of digits allowed.
 * @property scale The number of digits allowed to the right of the decimal point.
 * @property type Type of the column. Valid values are `NUMBER`, `DECIMAL`, `NUMERIC`, `INT`, `INTEGER`, `BIGINT`, `SMALLINT`, `FLOAT``FLOAT4`, `FLOAT8`, `DOUBLE`, `DOUBLE PRECISION`, `REAL`, `VARCHAR`, `CHAR`, `CHARACTER`, `STRING`, `TEXT`, `BINARY`, `VARBINARY`, `BOOLEAN`, `DATE`, `DATETIME`, `TIME`, `TIMESTAMP`, `TIMESTAMP_LTZ`, `TIMESTAMP_NTZ`, `TIMESTAMP_TZ`, `VARIANT`, `OBJECT`, `ARRAY`, `GEOGRAPHY`. Please note these values are case sensitive.
 */
public data class DatasetSnowflakeSchemaColumn(
    public val name: String,
    public val precision: Int? = null,
    public val scale: Int? = null,
    public val type: String? = null,
) {
    public companion object {
        public
        fun toKotlin(javaType: com.pulumi.azure.datafactory.outputs.DatasetSnowflakeSchemaColumn):
            DatasetSnowflakeSchemaColumn = DatasetSnowflakeSchemaColumn(
            name = javaType.name(),
            precision = javaType.precision().map({ args0 -> args0 }).orElse(null),
            scale = javaType.scale().map({ args0 -> args0 }).orElse(null),
            type = javaType.type().map({ args0 -> args0 }).orElse(null),
        )
    }
}