/*!
 * Copyright (c) Microsoft. All rights reserved.
 * Licensed under the MIT license. See LICENSE file in the project.
 */
import type { DataFormat } from '../data.js';
import type { ResourceSchema } from '../datapackage/ResourceSchema.js';
import type { KnownProfile } from '../enums/index.js';
import type { DataShape } from './DataShape.js';
import type { ParserOptions } from './ParserOptions.js';
import type { TypeHints } from './TypeHints.js';
/**
 * This defines the table-containing resource type.
 * A dataset can be embedded directly using the `data` property,
 * or it can be linked to a raw file using the `path`.
 * If the latter, optional format and parsing options can be applied to aid interpreting the file contents.
 * resource profile: 'datatable'
 */
export interface DataTableSchema extends ResourceSchema {
    profile: KnownProfile.DataTable;
    /**
     * Option to embed the data directly in the JSON descriptor.
     * Valid data formats are:
     * - string: raw CSV data, parsed according to the `parser` options
     * - array: raw JSON data, parsed according to the `shape` options
     */
    data?: string | unknown[];
    /**
     * File format of the resource to inform load/parse.
     * Note that if the data property is present, this is assumed to be "JSON".
     * Default: "csv".
     */
    format?: DataFormat;
    /**
     * String encoding.
     * Default: "utf-8".
     */
    encoding?: string;
    /**
     * Defines the shape and structure of stored data.
     */
    shape?: DataShape;
    /**
     * Parser options for interpreting a CSV or other text file that needs parse instruction.
     */
    parser?: ParserOptions;
    /**
     * Options for converting string values to strict types.
     * Note that options related to data typing only apply if type detection is turned on.
     * Otherwise all cell values are treated as strings.
     * Defaults based on pandas: https://pandas.pydata.org/pandas-docs/stable/user_guide/io.html#csv-text-files
     */
    typeHints?: TypeHints;
    /**
     * Number of rows in the data.
     */
    rows?: number;
    /**
     * Number of columns in the data.
     */
    columns?: number;
}