import { DATE_FIELD_PATTERNS, NAME_FIELD_PATTERNS } from "../constants.js";
import { Field, Table as Table$1 } from "apache-arrow";

//#region src/js/arrow/arrow-client.d.ts
declare class ArrowClient {
  /**
   * Processes an Arrow IPC buffer into a Table.
   * Lazily loads the Apache Arrow library on first use.
   *
   * @param buffer - The Arrow IPC format buffer
   * @returns Promise resolving to an Arrow Table
   */
  static processArrowBuffer(buffer: Uint8Array): Promise<Table$1>;
  /**
   * Fetches Arrow data from a URL and processes it into a Table.
   * Convenience method that combines fetchArrow and processArrowBuffer.
   *
   * @param url - URL to fetch Arrow data from
   * @param headers - Optional HTTP headers to include in the request
   * @returns Promise resolving to an Arrow Table
   * @example
   * ```typescript
   * const table = await ArrowClient.fetchAndProcessArrow('/api/data/arrow');
   * console.log(`Loaded ${table.numRows} rows`);
   * ```
   */
  static fetchAndProcessArrow(url: string, headers?: Record<string, string>): Promise<Table$1>;
  /**
   * Extracts field metadata (name and type) from an Arrow Table.
   *
   * @param table - Arrow Table to extract fields from
   * @returns Array of field metadata objects
   * @example
   * ```typescript
   * const fields = ArrowClient.extractArrowFields(table);
   * // [{ name: "date", type: Date32 }, { name: "value", type: Float64 }]
   * ```
   */
  static extractArrowFields(table: Table$1): {
    name: string;
    type: any;
  }[];
  /**
   * Extracts all columns from an Arrow Table as JavaScript arrays.
   * Each column is converted to a native JavaScript array.
   *
   * @param table - Arrow Table to extract columns from
   * @returns Object mapping column names to arrays
   * @example
   * ```typescript
   * const columns = ArrowClient.extractArrowColumns(table);
   * // { date: ["2024-01-01", "2024-01-02"], value: [100, 200] }
   * ```
   */
  static extractArrowColumns(table: Table$1): Record<string, any>;
  /**
   * Extracts chart data from Arrow table.
   * Uses get(i) to properly handle complex types like Decimal128.
   * Applies decimal scaling for DECIMAL types.
   *
   * Note: This method assumes Arrow has been loaded (via processArrowBuffer).
   *
   * @returns xData for axis, yDataMap for series data
   */
  static extractChartData(table: Table$1, xKey: string, yKeys: string[]): {
    xData: (string | number)[];
    yDataMap: Record<string, (string | number)[]>;
  };
  /**
   * Automatically detect which fields to use for chart axes from an Arrow table
   * Uses the schema's type information for accurate field detection
   *
   * Note: This method assumes Arrow has been loaded (via processArrowBuffer).
   *
   * @param table - Arrow Table to analyze
   * @param orientation - Chart orientation ("vertical" for time-series, "horizontal" for categorical)
   * @returns Object containing the detected fields
   * @example
   * // Time-series data
   * detectFieldsFromArrow(timeSeriesTable)
   * // { xField: "date", yFields: ["revenue", "cost"], chartType: "timeseries" }
   *
   * // Categorical data
   * detectFieldsFromArrow(categoricalTable)
   * // { xField: "app_name", yFields: ["totalSpend"], chartType: "categorical" }
   */
  static detectFieldsFromArrow(table: Table$1, orientation?: "vertical" | "horizontal"): DetectedFields & {
    chartType: "timeseries" | "categorical";
  };
  /**
   * Fetches raw Arrow IPC data from a URL.
   *
   * @param url - URL to fetch Arrow data from
   * @param headers - Optional HTTP headers to include in the request
   * @returns Promise resolving to the raw Arrow buffer as Uint8Array
   * @example
   * ```typescript
   * const buffer = await ArrowClient.fetchArrow('/api/data/arrow');
   * const table = await ArrowClient.processArrowBuffer(buffer);
   * ```
   */
  static fetchArrow(url: string, headers?: Record<string, string>): Promise<Uint8Array>;
}
interface DetectedFields {
  /** X field */
  xField: string;
  /** Y fields */
  yFields: string[];
}
//#endregion
export { ArrowClient, DetectedFields, type Field, type Table$1 as Table };
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