// Copyright 2024 Lance Developers.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
//     http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.

import * as fs from "fs";
import * as path from "path";
import * as tmp from "tmp";

import * as arrow from "apache-arrow";
import * as arrowOld from "apache-arrow-old";

import { Table, connect } from "../lancedb";
import {
  Table as ArrowTable,
  Field,
  FixedSizeList,
  Float32,
  Float64,
  Int32,
  Int64,
  Schema,
  makeArrowTable,
} from "../lancedb/arrow";
import { EmbeddingFunction, LanceSchema, register } from "../lancedb/embedding";
import { Index } from "../lancedb/indices";

// biome-ignore lint/suspicious/noExplicitAny: <explanation>
describe.each([arrow, arrowOld])("Given a table", (arrow: any) => {
  let tmpDir: tmp.DirResult;
  let table: Table;

  const schema = new arrow.Schema([
    new arrow.Field("id", new arrow.Float64(), true),
  ]);

  beforeEach(async () => {
    tmpDir = tmp.dirSync({ unsafeCleanup: true });
    const conn = await connect(tmpDir.name);
    table = await conn.createEmptyTable("some_table", schema);
  });
  afterEach(() => tmpDir.removeCallback());

  it("be displayable", async () => {
    expect(table.display()).toMatch(
      /NativeTable\(some_table, uri=.*, read_consistency_interval=None\)/,
    );
    table.close();
    expect(table.display()).toBe("ClosedTable(some_table)");
  });

  it("should let me add data", async () => {
    await table.add([{ id: 1 }, { id: 2 }]);
    await table.add([{ id: 1 }]);
    await expect(table.countRows()).resolves.toBe(3);
  });

  it("should overwrite data if asked", async () => {
    await table.add([{ id: 1 }, { id: 2 }]);
    await table.add([{ id: 1 }], { mode: "overwrite" });
    await expect(table.countRows()).resolves.toBe(1);
  });

  it("should let me close the table", async () => {
    expect(table.isOpen()).toBe(true);
    table.close();
    expect(table.isOpen()).toBe(false);
    expect(table.countRows()).rejects.toThrow("Table some_table is closed");
  });

  it("should let me update values", async () => {
    await table.add([{ id: 1 }]);
    expect(await table.countRows("id == 1")).toBe(1);
    expect(await table.countRows("id == 7")).toBe(0);
    await table.update({ id: "7" });
    expect(await table.countRows("id == 1")).toBe(0);
    expect(await table.countRows("id == 7")).toBe(1);
    await table.add([{ id: 2 }]);
    // Test Map as input
    await table.update(new Map(Object.entries({ id: "10" })), {
      where: "id % 2 == 0",
    });
    expect(await table.countRows("id == 2")).toBe(0);
    expect(await table.countRows("id == 7")).toBe(1);
    expect(await table.countRows("id == 10")).toBe(1);
  });

  // https://github.com/lancedb/lancedb/issues/1293
  test.each([new arrow.Float16(), new arrow.Float32(), new arrow.Float64()])(
    "can create empty table with non default float type: %s",
    async (floatType) => {
      const db = await connect(tmpDir.name);

      const data = [
        { text: "hello", vector: Array(512).fill(1.0) },
        { text: "hello world", vector: Array(512).fill(1.0) },
      ];
      const f64Schema = new arrow.Schema([
        new arrow.Field("text", new arrow.Utf8(), true),
        new arrow.Field(
          "vector",
          new arrow.FixedSizeList(512, new arrow.Field("item", floatType)),
          true,
        ),
      ]);

      const f64Table = await db.createEmptyTable("f64", f64Schema, {
        mode: "overwrite",
      });
      try {
        await f64Table.add(data);
        const res = await f64Table.query().toArray();
        expect(res.length).toBe(2);
      } catch (e) {
        expect(e).toBeUndefined();
      }
    },
  );

  it("should return the table as an instance of an arrow table", async () => {
    const arrowTbl = await table.toArrow();
    expect(arrowTbl).toBeInstanceOf(ArrowTable);
  });
});

describe("merge insert", () => {
  let tmpDir: tmp.DirResult;
  let table: Table;

  beforeEach(async () => {
    tmpDir = tmp.dirSync({ unsafeCleanup: true });
    const conn = await connect(tmpDir.name);

    table = await conn.createTable("some_table", [
      { a: 1, b: "a" },
      { a: 2, b: "b" },
      { a: 3, b: "c" },
    ]);
  });
  afterEach(() => tmpDir.removeCallback());

  test("upsert", async () => {
    const newData = [
      { a: 2, b: "x" },
      { a: 3, b: "y" },
      { a: 4, b: "z" },
    ];
    await table
      .mergeInsert("a")
      .whenMatchedUpdateAll()
      .whenNotMatchedInsertAll()
      .execute(newData);
    const expected = [
      { a: 1, b: "a" },
      { a: 2, b: "x" },
      { a: 3, b: "y" },
      { a: 4, b: "z" },
    ];

    expect(
      JSON.parse(JSON.stringify((await table.toArrow()).toArray())),
    ).toEqual(expected);
  });
  test("conditional update", async () => {
    const newData = [
      { a: 2, b: "x" },
      { a: 3, b: "y" },
      { a: 4, b: "z" },
    ];
    await table
      .mergeInsert("a")
      .whenMatchedUpdateAll({ where: "target.b = 'b'" })
      .execute(newData);

    const expected = [
      { a: 1, b: "a" },
      { a: 2, b: "x" },
      { a: 3, b: "c" },
    ];
    // round trip to arrow and back to json to avoid comparing arrow objects to js object
    // biome-ignore lint/suspicious/noExplicitAny: test
    let res: any[] = JSON.parse(
      JSON.stringify((await table.toArrow()).toArray()),
    );
    res = res.sort((a, b) => a.a - b.a);

    expect(res).toEqual(expected);
  });

  test("insert if not exists", async () => {
    const newData = [
      { a: 2, b: "x" },
      { a: 3, b: "y" },
      { a: 4, b: "z" },
    ];
    await table.mergeInsert("a").whenNotMatchedInsertAll().execute(newData);
    const expected = [
      { a: 1, b: "a" },
      { a: 2, b: "b" },
      { a: 3, b: "c" },
      { a: 4, b: "z" },
    ];
    // biome-ignore lint/suspicious/noExplicitAny: <explanation>
    let res: any[] = JSON.parse(
      JSON.stringify((await table.toArrow()).toArray()),
    );
    res = res.sort((a, b) => a.a - b.a);
    expect(res).toEqual(expected);
  });
  test("replace range", async () => {
    const newData = [
      { a: 2, b: "x" },
      { a: 4, b: "z" },
    ];
    await table
      .mergeInsert("a")
      .whenMatchedUpdateAll()
      .whenNotMatchedInsertAll()
      .whenNotMatchedBySourceDelete({ where: "a > 2" })
      .execute(newData);

    const expected = [
      { a: 1, b: "a" },
      { a: 2, b: "x" },
      { a: 4, b: "z" },
    ];
    // biome-ignore lint/suspicious/noExplicitAny: <explanation>
    let res: any[] = JSON.parse(
      JSON.stringify((await table.toArrow()).toArray()),
    );
    res = res.sort((a, b) => a.a - b.a);
    expect(res).toEqual(expected);
  });
  test("replace range no condition", async () => {
    const newData = [
      { a: 2, b: "x" },
      { a: 4, b: "z" },
    ];
    await table
      .mergeInsert("a")
      .whenMatchedUpdateAll()
      .whenNotMatchedInsertAll()
      .whenNotMatchedBySourceDelete()
      .execute(newData);

    const expected = [
      { a: 2, b: "x" },
      { a: 4, b: "z" },
    ];

    // biome-ignore lint/suspicious/noExplicitAny: test
    let res: any[] = JSON.parse(
      JSON.stringify((await table.toArrow()).toArray()),
    );
    res = res.sort((a, b) => a.a - b.a);
    expect(res).toEqual(expected);
  });
});

describe("When creating an index", () => {
  let tmpDir: tmp.DirResult;
  const schema = new Schema([
    new Field("id", new Int32(), true),
    new Field("vec", new FixedSizeList(32, new Field("item", new Float32()))),
  ]);
  let tbl: Table;
  let queryVec: number[];

  beforeEach(async () => {
    tmpDir = tmp.dirSync({ unsafeCleanup: true });
    const db = await connect(tmpDir.name);
    const data = makeArrowTable(
      Array(300)
        .fill(1)
        .map((_, i) => ({
          id: i,
          vec: Array(32)
            .fill(1)
            .map(() => Math.random()),
        })),
      {
        schema,
      },
    );
    queryVec = data.toArray()[5].vec.toJSON();
    tbl = await db.createTable("test", data);
  });
  afterEach(() => tmpDir.removeCallback());

  it("should create a vector index on vector columns", async () => {
    await tbl.createIndex("vec");

    // check index directory
    const indexDir = path.join(tmpDir.name, "test.lance", "_indices");
    expect(fs.readdirSync(indexDir)).toHaveLength(1);
    const indices = await tbl.listIndices();
    expect(indices.length).toBe(1);
    expect(indices[0]).toEqual({
      name: "vec_idx",
      indexType: "IvfPq",
      columns: ["vec"],
    });

    // Search without specifying the column
    let rst = await tbl
      .query()
      .limit(2)
      .nearestTo(queryVec)
      .distanceType("DoT")
      .toArrow();
    expect(rst.numRows).toBe(2);

    // Search using `vectorSearch`
    rst = await tbl.vectorSearch(queryVec).limit(2).toArrow();
    expect(rst.numRows).toBe(2);

    // Search with specifying the column
    const rst2 = await tbl
      .query()
      .limit(2)
      .nearestTo(queryVec)
      .column("vec")
      .toArrow();
    expect(rst2.numRows).toBe(2);
    expect(rst.toString()).toEqual(rst2.toString());
  });

  it("should allow parameters to be specified", async () => {
    await tbl.createIndex("vec", {
      config: Index.ivfPq({
        numPartitions: 10,
      }),
    });

    // TODO: Verify parameters when we can load index config as part of list indices
  });

  it("should allow me to replace (or not) an existing index", async () => {
    await tbl.createIndex("id");
    // Default is replace=true
    await tbl.createIndex("id");
    await expect(tbl.createIndex("id", { replace: false })).rejects.toThrow(
      "already exists",
    );
    await tbl.createIndex("id", { replace: true });
  });

  test("should create a scalar index on scalar columns", async () => {
    await tbl.createIndex("id");
    const indexDir = path.join(tmpDir.name, "test.lance", "_indices");
    expect(fs.readdirSync(indexDir)).toHaveLength(1);

    for await (const r of tbl.query().where("id > 1").select(["id"])) {
      expect(r.numRows).toBe(298);
    }
    // should also work with 'filter' alias
    for await (const r of tbl.query().filter("id > 1").select(["id"])) {
      expect(r.numRows).toBe(298);
    }
  });

  test("should be able to get index stats", async () => {
    await tbl.createIndex("id");

    const stats = await tbl.indexStats("id_idx");
    expect(stats).toBeDefined();
    expect(stats?.numIndexedRows).toEqual(300);
    expect(stats?.numUnindexedRows).toEqual(0);
  });

  test("when getting stats on non-existent index", async () => {
    const stats = await tbl.indexStats("some non-existent index");
    expect(stats).toBeUndefined();
  });

  // TODO: Move this test to the query API test (making sure we can reject queries
  // when the dimension is incorrect)
  test("two columns with different dimensions", async () => {
    const db = await connect(tmpDir.name);
    const schema = new Schema([
      new Field("id", new Int32(), true),
      new Field("vec", new FixedSizeList(32, new Field("item", new Float32()))),
      new Field(
        "vec2",
        new FixedSizeList(64, new Field("item", new Float32())),
      ),
    ]);
    const tbl = await db.createTable(
      "two_vectors",
      makeArrowTable(
        Array(300)
          .fill(1)
          .map((_, i) => ({
            id: i,
            vec: Array(32)
              .fill(1)
              .map(() => Math.random()),
            vec2: Array(64) // different dimension
              .fill(1)
              .map(() => Math.random()),
          })),
        { schema },
      ),
    );

    // Only build index over v1
    await tbl.createIndex("vec", {
      config: Index.ivfPq({ numPartitions: 2, numSubVectors: 2 }),
    });

    const rst = await tbl
      .query()
      .limit(2)
      .nearestTo(
        Array(32)
          .fill(1)
          .map(() => Math.random()),
      )
      .toArrow();
    expect(rst.numRows).toBe(2);

    // Search with specifying the column
    await expect(
      tbl
        .query()
        .limit(2)
        .nearestTo(
          Array(64)
            .fill(1)
            .map(() => Math.random()),
        )
        .column("vec")
        .toArrow(),
    ).rejects.toThrow(/.* query dim=64, expected vector dim=32.*/);

    const query64 = Array(64)
      .fill(1)
      .map(() => Math.random());
    const rst64Query = await tbl.query().limit(2).nearestTo(query64).toArrow();
    const rst64Search = await tbl
      .query()
      .limit(2)
      .nearestTo(query64)
      .column("vec2")
      .toArrow();
    expect(rst64Query.toString()).toEqual(rst64Search.toString());
    expect(rst64Query.numRows).toBe(2);
  });
});

describe("Read consistency interval", () => {
  let tmpDir: tmp.DirResult;
  beforeEach(() => {
    tmpDir = tmp.dirSync({ unsafeCleanup: true });
  });
  afterEach(() => tmpDir.removeCallback());

  // const intervals = [undefined, 0, 0.1];
  const intervals = [0];
  test.each(intervals)("read consistency interval %p", async (interval) => {
    const db = await connect(tmpDir.name);
    const table = await db.createTable("my_table", [{ id: 1 }]);

    const db2 = await connect(tmpDir.name, {
      readConsistencyInterval: interval,
    });
    const table2 = await db2.openTable("my_table");
    expect(await table2.countRows()).toEqual(await table.countRows());

    await table.add([{ id: 2 }]);

    if (interval === undefined) {
      expect(await table2.countRows()).toEqual(1);
      // TODO: once we implement time travel we can uncomment this part of the test.
      // await table2.checkout_latest();
      // expect(await table2.countRows()).toEqual(2);
    } else if (interval === 0) {
      expect(await table2.countRows()).toEqual(2);
    } else {
      // interval == 0.1
      expect(await table2.countRows()).toEqual(1);
      await new Promise((r) => setTimeout(r, 100));
      expect(await table2.countRows()).toEqual(2);
    }
  });
});

describe("schema evolution", function () {
  let tmpDir: tmp.DirResult;
  beforeEach(() => {
    tmpDir = tmp.dirSync({ unsafeCleanup: true });
  });
  afterEach(() => {
    tmpDir.removeCallback();
  });

  // Create a new sample table
  it("can add a new column to the schema", async function () {
    const con = await connect(tmpDir.name);
    const table = await con.createTable("vectors", [
      { id: 1n, vector: [0.1, 0.2] },
    ]);

    await table.addColumns([
      { name: "price", valueSql: "cast(10.0 as float)" },
    ]);

    const expectedSchema = new Schema([
      new Field("id", new Int64(), true),
      new Field(
        "vector",
        new FixedSizeList(2, new Field("item", new Float32(), true)),
        true,
      ),
      new Field("price", new Float32(), false),
    ]);
    expect(await table.schema()).toEqual(expectedSchema);
  });

  it("can alter the columns in the schema", async function () {
    const con = await connect(tmpDir.name);
    const schema = new Schema([
      new Field("id", new Int64(), true),
      new Field(
        "vector",
        new FixedSizeList(2, new Field("item", new Float32(), true)),
        true,
      ),
      new Field("price", new Float64(), false),
    ]);
    const table = await con.createTable("vectors", [
      { id: 1n, vector: [0.1, 0.2] },
    ]);
    // Can create a non-nullable column only through addColumns at the moment.
    await table.addColumns([
      { name: "price", valueSql: "cast(10.0 as double)" },
    ]);
    expect(await table.schema()).toEqual(schema);

    await table.alterColumns([
      { path: "id", rename: "new_id" },
      { path: "price", nullable: true },
    ]);

    const expectedSchema = new Schema([
      new Field("new_id", new Int64(), true),
      new Field(
        "vector",
        new FixedSizeList(2, new Field("item", new Float32(), true)),
        true,
      ),
      new Field("price", new Float64(), true),
    ]);
    expect(await table.schema()).toEqual(expectedSchema);
  });

  it("can drop a column from the schema", async function () {
    const con = await connect(tmpDir.name);
    const table = await con.createTable("vectors", [
      { id: 1n, vector: [0.1, 0.2] },
    ]);
    await table.dropColumns(["vector"]);

    const expectedSchema = new Schema([new Field("id", new Int64(), true)]);
    expect(await table.schema()).toEqual(expectedSchema);
  });
});

describe("when dealing with versioning", () => {
  let tmpDir: tmp.DirResult;
  beforeEach(() => {
    tmpDir = tmp.dirSync({ unsafeCleanup: true });
  });
  afterEach(() => {
    tmpDir.removeCallback();
  });

  it("can travel in time", async () => {
    // Setup
    const con = await connect(tmpDir.name);
    const table = await con.createTable("vectors", [
      { id: 1n, vector: [0.1, 0.2] },
    ]);
    const version = await table.version();
    await table.add([{ id: 2n, vector: [0.1, 0.2] }]);
    expect(await table.countRows()).toBe(2);
    // Make sure we can rewind
    await table.checkout(version);
    expect(await table.countRows()).toBe(1);
    // Can't add data in time travel mode
    await expect(table.add([{ id: 3n, vector: [0.1, 0.2] }])).rejects.toThrow(
      "table cannot be modified when a specific version is checked out",
    );
    // Can go back to normal mode
    await table.checkoutLatest();
    expect(await table.countRows()).toBe(2);
    // Should be able to add data again
    await table.add([{ id: 2n, vector: [0.1, 0.2] }]);
    expect(await table.countRows()).toBe(3);
    // Now checkout and restore
    await table.checkout(version);
    await table.restore();
    expect(await table.countRows()).toBe(1);
    // Should be able to add data
    await table.add([{ id: 2n, vector: [0.1, 0.2] }]);
    expect(await table.countRows()).toBe(2);
    // Can't use restore if not checked out
    await expect(table.restore()).rejects.toThrow(
      "checkout before running restore",
    );
  });
});

describe("when optimizing a dataset", () => {
  let tmpDir: tmp.DirResult;
  let table: Table;
  beforeEach(async () => {
    tmpDir = tmp.dirSync({ unsafeCleanup: true });
    const con = await connect(tmpDir.name);
    table = await con.createTable("vectors", [{ id: 1 }]);
    await table.add([{ id: 2 }]);
  });
  afterEach(() => {
    tmpDir.removeCallback();
  });

  it("compacts files", async () => {
    const stats = await table.optimize();
    expect(stats.compaction.filesAdded).toBe(1);
    expect(stats.compaction.filesRemoved).toBe(2);
    expect(stats.compaction.fragmentsAdded).toBe(1);
    expect(stats.compaction.fragmentsRemoved).toBe(2);
  });

  it("cleanups old versions", async () => {
    const stats = await table.optimize({ cleanupOlderThan: new Date() });
    expect(stats.prune.bytesRemoved).toBeGreaterThan(0);
    expect(stats.prune.oldVersionsRemoved).toBe(3);
  });
});

describe("table.search", () => {
  let tmpDir: tmp.DirResult;
  beforeEach(() => {
    tmpDir = tmp.dirSync({ unsafeCleanup: true });
  });
  afterEach(() => tmpDir.removeCallback());

  test("can search using a string", async () => {
    @register()
    class MockEmbeddingFunction extends EmbeddingFunction<string> {
      toJSON(): object {
        return {};
      }
      ndims() {
        return 1;
      }
      embeddingDataType(): arrow.Float {
        return new Float32();
      }

      // Hardcoded embeddings for the sake of testing
      async computeQueryEmbeddings(_data: string) {
        switch (_data) {
          case "greetings":
            return [0.1];
          case "farewell":
            return [0.2];
          default:
            return null as never;
        }
      }

      // Hardcoded embeddings for the sake of testing
      async computeSourceEmbeddings(data: string[]) {
        return data.map((s) => {
          switch (s) {
            case "hello world":
              return [0.1];
            case "goodbye world":
              return [0.2];
            default:
              return null as never;
          }
        });
      }
    }

    const func = new MockEmbeddingFunction();
    const schema = LanceSchema({
      text: func.sourceField(new arrow.Utf8()),
      vector: func.vectorField(),
    });
    const db = await connect(tmpDir.name);
    const data = [{ text: "hello world" }, { text: "goodbye world" }];
    const table = await db.createTable("test", data, { schema });

    const results = await table.search("greetings").then((r) => r.toArray());
    expect(results[0].text).toBe(data[0].text);

    const results2 = await table.search("farewell").then((r) => r.toArray());
    expect(results2[0].text).toBe(data[1].text);
  });

  test("rejects if no embedding function provided", async () => {
    const db = await connect(tmpDir.name);
    const data = [
      { text: "hello world", vector: [0.1, 0.2, 0.3] },
      { text: "goodbye world", vector: [0.4, 0.5, 0.6] },
    ];
    const table = await db.createTable("test", data);

    expect(table.search("hello")).rejects.toThrow(
      "No embedding functions are defined in the table",
    );
  });

  test.each([
    [0.4, 0.5, 0.599], // number[]
    Float32Array.of(0.4, 0.5, 0.599), // Float32Array
    Float64Array.of(0.4, 0.5, 0.599), // Float64Array
  ])("can search using vectorlike datatypes", async (vectorlike) => {
    const db = await connect(tmpDir.name);
    const data = [
      { text: "hello world", vector: [0.1, 0.2, 0.3] },
      { text: "goodbye world", vector: [0.4, 0.5, 0.6] },
    ];
    const table = await db.createTable("test", data);

    // biome-ignore lint/suspicious/noExplicitAny: test
    const results: any[] = await table.search(vectorlike).toArray();

    expect(results.length).toBe(2);
    expect(results[0].text).toBe(data[1].text);
  });
});