{/* Auto-generated by scripts/mdx_snippets_gen.py. Do not edit manually. */}

export const PyAddFromDataset = "from tempfile import TemporaryDirectory\n\nimport lancedb\n\nwith TemporaryDirectory(prefix=\"lancedb-ingestion-\") as uri:\n    db = lancedb.connect(uri)\n    from pathlib import Path\n\n    import pyarrow as pa\n    import pyarrow.parquet as pq\n\n    data_path = str(Path(uri) / \"input.parquet\")\n    pq.write_table(pa.table({\"id\": [1, 2], \"name\": [\"Alice\", \"Bob\"]}), data_path)\n    import pyarrow.dataset as ds\n\n    dataset = ds.dataset(data_path, format=\"parquet\")\n    table = db.create_table(\"my_table\", schema=dataset.schema, mode=\"overwrite\")\n    table.add(dataset)\n\n    print(\"Rows:\", table.count_rows())\n";

export const PyAddProgress = "from tempfile import TemporaryDirectory\n\nimport lancedb\n\ndef report_progress(progress):\n    print(f\"Rows written: {progress['output_rows']}\")\n\nwith TemporaryDirectory(prefix=\"lancedb-ingestion-\") as uri:\n    db = lancedb.connect(uri)\n    table = db.create_table(\"users\", [{\"id\": 1, \"name\": \"Alice\"}])\n    table.add(\n        [{\"id\": 2, \"name\": \"Bob\"}, {\"id\": 3, \"name\": \"Charlie\"}],\n        progress=report_progress,\n    )\n    rows = sorted(table.search().to_list(), key=lambda row: row[\"id\"])\n    print(\"After insertion:\", rows)\n";

export const PyAppendRows = "from tempfile import TemporaryDirectory\n\nimport lancedb\n\nwith TemporaryDirectory(prefix=\"lancedb-ingestion-\") as uri:\n    db = lancedb.connect(uri)\n    table = db.create_table(\"users\", [{\"id\": 1, \"name\": \"Alice\"}])\n    table.add([{\"id\": 2, \"name\": \"Bob\"}, {\"id\": 3, \"name\": \"Charlie\"}])\n    rows = sorted(table.search().to_list(), key=lambda row: row[\"id\"])\n    print(rows)\n";

export const PyCreateEmptyTable = "from tempfile import TemporaryDirectory\n\nimport lancedb\n\nwith TemporaryDirectory(prefix=\"lancedb-ingestion-\") as uri:\n    db = lancedb.connect(uri)\n    import pyarrow as pa\n\n    schema = pa.schema(\n        [\n            pa.field(\"vector\", pa.list_(pa.float32(), 2)),\n            pa.field(\"item\", pa.string()),\n            pa.field(\"price\", pa.float32()),\n        ]\n    )\n    tbl = db.create_table(\"test_empty_table\", schema=schema, mode=\"overwrite\")\n\n    print(\"Rows:\", tbl.count_rows())\n";

export const PyCreateEmptyTablePydantic = "from tempfile import TemporaryDirectory\n\nimport lancedb\n\nwith TemporaryDirectory(prefix=\"lancedb-ingestion-\") as uri:\n    db = lancedb.connect(uri)\n    from lancedb.pydantic import LanceModel, Vector\n\n    class Item(LanceModel):\n        vector: Vector(2)\n        item: str\n        price: float\n\n    tbl = db.create_table(\n        \"test_empty_table_new\", schema=Item.to_arrow_schema(), mode=\"overwrite\"\n    )\n\n    print(\"Rows:\", tbl.count_rows())\n";

export const PyCreateTableConflictHandling = "from tempfile import TemporaryDirectory\n\nimport lancedb\n\nwith TemporaryDirectory(prefix=\"lancedb-ingestion-\") as uri:\n    db = lancedb.connect(uri)\n    data = [{\"vector\": [1.1, 1.2], \"lat\": 45.5, \"long\": -122.7}]\n    db.create_table(\"conflict_table\", data)\n    # Idempotent open: reuse the existing table if it exists.\n    # The provided data is ignored; the schema is validated against the\n    # existing table and a mismatch raises an error.\n    tbl = db.create_table(\"conflict_table\", data, exist_ok=True)\n\n    # Overwrite: replace the contents with the provided data.\n    tbl = db.create_table(\"conflict_table\", data, mode=\"overwrite\")\n    print(\"Rows:\", tbl.count_rows())\n";

export const PyCreateTableCustomSchema = "from tempfile import TemporaryDirectory\n\nimport lancedb\n\nwith TemporaryDirectory(prefix=\"lancedb-ingestion-\") as uri:\n    db = lancedb.connect(uri)\n    import pyarrow as pa\n\n    custom_schema = pa.schema(\n        [\n            pa.field(\"vector\", pa.list_(pa.float32(), 4)),\n            pa.field(\"lat\", pa.float32()),\n            pa.field(\"long\", pa.float32()),\n        ]\n    )\n\n    data = [\n        {\"vector\": [1.1, 1.2, 1.3, 1.4], \"lat\": 45.5, \"long\": -122.7},\n        {\"vector\": [0.2, 1.8, 0.4, 3.6], \"lat\": 40.1, \"long\": -74.1},\n    ]\n    tbl = db.create_table(\n        \"my_table_custom_schema\", data, schema=custom_schema, mode=\"overwrite\"\n    )\n\n    print(\"Rows:\", tbl.count_rows())\n";

export const PyCreateTableFromArrow = "from tempfile import TemporaryDirectory\n\nimport lancedb\n\nwith TemporaryDirectory(prefix=\"lancedb-ingestion-\") as uri:\n    db = lancedb.connect(uri)\n    import numpy as np\n    import pyarrow as pa\n\n    dim = 16\n    total = 2\n    schema = pa.schema(\n        [\n            pa.field(\"vector\", pa.list_(pa.float16(), dim)),\n            pa.field(\"text\", pa.string()),\n        ]\n    )\n    data = pa.Table.from_arrays(\n        [\n            pa.array(\n                [np.random.randn(dim).astype(np.float16) for _ in range(total)],\n                pa.list_(pa.float16(), dim),\n            ),\n            pa.array([\"foo\", \"bar\"]),\n        ],\n        [\"vector\", \"text\"],\n    )\n    tbl = db.create_table(\"f16_tbl\", data, schema=schema, mode=\"overwrite\")\n\n    print(\"Rows:\", tbl.count_rows())\n";

export const PyCreateTableFromDicts = "from tempfile import TemporaryDirectory\n\nimport lancedb\n\nwith TemporaryDirectory(prefix=\"lancedb-ingestion-\") as uri:\n    db = lancedb.connect(uri)\n    data = [\n        {\"vector\": [1.1, 1.2], \"lat\": 45.5, \"long\": -122.7},\n        {\"vector\": [0.2, 1.8], \"lat\": 40.1, \"long\": -74.1},\n    ]\n    db.create_table(\"test_table\", data, mode=\"overwrite\")\n    tbl = db[\"test_table\"]\n    tbl.head()\n\n    print(\"Rows:\", tbl.count_rows())\n";

export const PyCreateTableFromIterator = "from tempfile import TemporaryDirectory\n\nimport lancedb\n\nwith TemporaryDirectory(prefix=\"lancedb-ingestion-\") as uri:\n    db = lancedb.connect(uri)\n    import pyarrow as pa\n\n    schema = pa.schema(\n        [\n            pa.field(\"vector\", pa.list_(pa.float32(), 4)),\n            pa.field(\"item\", pa.utf8()),\n            pa.field(\"price\", pa.float32()),\n        ]\n    )\n\n    def make_batches():\n        for i in range(5):\n            yield pa.RecordBatch.from_arrays(\n                [\n                    pa.array(\n                        [[3.1, 4.1, 5.1, 6.1], [5.9, 26.5, 4.7, 32.8]],\n                        pa.list_(pa.float32(), 4),\n                    ),\n                    pa.array([\"foo\", \"bar\"]),\n                    pa.array([10.0, 20.0]),\n                ],\n                [\"vector\", \"item\", \"price\"],\n            )\n\n    table = db.create_table(\"batched_table\", schema=schema)\n    table.add(make_batches())\n\n    print(\"Rows:\", table.count_rows())\n";

export const PyCreateTableFromPandas = "from tempfile import TemporaryDirectory\n\nimport lancedb\n\nwith TemporaryDirectory(prefix=\"lancedb-ingestion-\") as uri:\n    db = lancedb.connect(uri)\n    import pandas as pd\n\n    data = pd.DataFrame(\n        {\n            \"vector\": [[1.1, 1.2, 1.3, 1.4], [0.2, 1.8, 0.4, 3.6]],\n            \"lat\": [45.5, 40.1],\n            \"long\": [-122.7, -74.1],\n        }\n    )\n    db.create_table(\"my_table_pandas\", data, mode=\"overwrite\")\n    db[\"my_table_pandas\"].head()\n";

export const PyCreateTableFromPolars = "from tempfile import TemporaryDirectory\n\nimport lancedb\n\nwith TemporaryDirectory(prefix=\"lancedb-ingestion-\") as uri:\n    db = lancedb.connect(uri)\n    import polars as pl\n\n    data = pl.DataFrame(\n        {\n            \"vector\": [[3.1, 4.1], [5.9, 26.5]],\n            \"item\": [\"foo\", \"bar\"],\n            \"price\": [10.0, 20.0],\n        }\n    )\n    tbl = db.create_table(\"my_table_pl\", data, mode=\"overwrite\")\n\n    print(\"Rows:\", tbl.count_rows())\n";

export const PyCreateTableFromPydantic = "from tempfile import TemporaryDirectory\n\nimport lancedb\n\nwith TemporaryDirectory(prefix=\"lancedb-ingestion-\") as uri:\n    db = lancedb.connect(uri)\n    from lancedb.pydantic import LanceModel, Vector\n\n    class Content(LanceModel):\n        movie_id: int\n        vector: Vector(128)\n        genres: str\n        title: str\n        imdb_id: int\n\n        @property\n        def imdb_url(self) -> str:\n            return f\"https://www.imdb.com/title/tt{self.imdb_id}\"\n\n    tbl = db.create_table(\"movielens_small\", schema=Content, mode=\"overwrite\")\n\n    print(\"Rows:\", tbl.count_rows())\n";

export const PyCreateTableNestedSchema = "from tempfile import TemporaryDirectory\n\nimport lancedb\n\nwith TemporaryDirectory(prefix=\"lancedb-ingestion-\") as uri:\n    db = lancedb.connect(uri)\n    from lancedb.pydantic import LanceModel, Vector\n    from pydantic import BaseModel\n\n    class Document(BaseModel):\n        content: str\n        source: str\n\n    class NestedSchema(LanceModel):\n        id: str\n        vector: Vector(1536)\n        document: Document\n\n    tbl = db.create_table(\"nested_table\", schema=NestedSchema, mode=\"overwrite\")\n\n    print(\"Rows:\", tbl.count_rows())\n";

export const PyDeleteRows = "from tempfile import TemporaryDirectory\n\nimport lancedb\n\nwith TemporaryDirectory(prefix=\"lancedb-ingestion-\") as uri:\n    db = lancedb.connect(uri)\n    table = db.create_table(\n        \"users\",\n        [\n            {\"id\": 1, \"name\": \"Alice\"},\n            {\"id\": 2, \"name\": \"Bob\"},\n            {\"id\": 3, \"name\": \"Charlie\"},\n        ],\n    )\n    predicate = \"id = 3\"\n    print(\"Selected:\", table.search().where(predicate).to_list())\n    table.delete(predicate)\n    rows = sorted(table.search().to_list(), key=lambda row: row[\"id\"])\n    print(\"Remaining:\", rows)\n";

export const PyDropTable = "from tempfile import TemporaryDirectory\n\nimport lancedb\n\nwith TemporaryDirectory(prefix=\"lancedb-ingestion-\") as uri:\n    db = lancedb.connect(uri)\n    # Create a table first\n    data = [{\"vector\": [1.1, 1.2], \"lat\": 45.5}]\n    db.create_table(\"my_table\", data, mode=\"overwrite\")\n\n    # Drop the table\n    db.drop_table(\"my_table\")\n";

export const PyInsertIfNotExists = "from tempfile import TemporaryDirectory\n\nimport lancedb\n\nwith TemporaryDirectory(prefix=\"lancedb-ingestion-\") as uri:\n    db = lancedb.connect(uri)\n    import pyarrow as pa\n\n    table = db.create_table(\n        \"users_example\",\n        data=pa.table(\n            {\n                \"id\": [1, 2],\n                \"name\": [\"Alice\", \"Bob\"],\n                \"login_count\": [10, 20],\n            }\n        ),\n        mode=\"overwrite\",\n    )\n\n    incoming_users = pa.table(\n        {\n            \"id\": [2, 3],\n            \"name\": [\"Bobby\", \"Charlie\"],\n            \"login_count\": [21, 5],\n        }\n    )\n\n    (table.merge_insert(\"id\").when_not_matched_insert_all().execute(incoming_users))\n\n    print(\"Rows:\", table.count_rows())\n";

export const PyMergeDeleteMissingBySource = "from tempfile import TemporaryDirectory\n\nimport lancedb\n\nwith TemporaryDirectory(prefix=\"lancedb-ingestion-\") as uri:\n    db = lancedb.connect(uri)\n    import pyarrow as pa\n\n    table = db.create_table(\n        \"users_example\",\n        data=pa.table(\n            {\n                \"id\": [1, 2, 3],\n                \"name\": [\"Alice\", \"Bob\", \"Charlie\"],\n                \"login_count\": [10, 20, 5],\n            }\n        ),\n        mode=\"overwrite\",\n    )\n\n    incoming_users = pa.table(\n        {\n            \"id\": [2, 3],\n            \"name\": [\"Bobby\", \"Charlie\"],\n            \"login_count\": [21, 5],\n        }\n    )\n\n    (\n        table.merge_insert(\"id\")\n        .when_matched_update_all()\n        .when_not_matched_insert_all()\n        .when_not_matched_by_source_delete()\n        .execute(incoming_users)\n    )\n\n    print(\"Rows:\", table.count_rows())\n";

export const PyMergeMatchedUpdateOnly = "from tempfile import TemporaryDirectory\n\nimport lancedb\n\nwith TemporaryDirectory(prefix=\"lancedb-ingestion-\") as uri:\n    db = lancedb.connect(uri)\n    import pyarrow as pa\n\n    table = db.create_table(\n        \"users_example\",\n        data=pa.table(\n            {\n                \"id\": [1, 2],\n                \"name\": [\"Alice\", \"Bob\"],\n                \"login_count\": [10, 20],\n            }\n        ),\n        mode=\"overwrite\",\n    )\n\n    incoming_users = pa.table(\n        {\n            \"id\": [2, 3],\n            \"name\": [\"Bobby\", \"Charlie\"],\n            \"login_count\": [21, 5],\n        }\n    )\n\n    (table.merge_insert(\"id\").when_matched_update_all().execute(incoming_users))\n\n    print(\"Rows:\", table.count_rows())\n";

export const PyMergePartialColumns = "from tempfile import TemporaryDirectory\n\nimport lancedb\n\nwith TemporaryDirectory(prefix=\"lancedb-ingestion-\") as uri:\n    db = lancedb.connect(uri)\n    import pyarrow as pa\n\n    table = db.create_table(\n        \"users_example\",\n        data=pa.table(\n            {\n                \"id\": [1, 2],\n                \"name\": [\"Alice\", \"Bob\"],\n                \"login_count\": [10, 20],\n            }\n        ),\n        mode=\"overwrite\",\n    )\n\n    incoming_users = pa.table(\n        {\n            \"id\": [2, 3],\n            \"name\": [\"Bobby\", \"Charlie\"],\n        }\n    )\n\n    (\n        table.merge_insert(\"id\")\n        .when_matched_update_all()\n        .when_not_matched_insert_all()\n        .execute(incoming_users)\n    )\n\n    print(\"Rows:\", table.count_rows())\n";

export const PyMergeUpdateInsert = "from tempfile import TemporaryDirectory\n\nimport lancedb\n\nwith TemporaryDirectory(prefix=\"lancedb-ingestion-\") as uri:\n    db = lancedb.connect(uri)\n    import pyarrow as pa\n\n    table = db.create_table(\n        \"users_example\",\n        data=pa.table(\n            {\n                \"id\": [1, 2],\n                \"name\": [\"Alice\", \"Bob\"],\n                \"login_count\": [10, 20],\n            }\n        ),\n        mode=\"overwrite\",\n    )\n\n    incoming_users = pa.table(\n        {\n            \"id\": [2, 3],\n            \"name\": [\"Bobby\", \"Charlie\"],\n            \"login_count\": [21, 5],\n        }\n    )\n\n    (\n        table.merge_insert(\"id\")\n        .when_matched_update_all()\n        .when_not_matched_insert_all()\n        .execute(incoming_users)\n    )\n\n    print(\"Rows:\", table.count_rows())\n";

export const PyOpenExistingTable = "from tempfile import TemporaryDirectory\n\nimport lancedb\n\nwith TemporaryDirectory(prefix=\"lancedb-ingestion-\") as uri:\n    db = lancedb.connect(uri)\n    # Create a table first\n    data = [{\"vector\": [1.1, 1.2], \"lat\": 45.5, \"long\": -122.7}]\n    db.create_table(\"test_table\", data, mode=\"overwrite\")\n\n    # List table names\n    print(db.list_tables().tables)\n\n    # Open existing table\n    tbl = db.open_table(\"test_table\")\n\n    print(\"Rows:\", tbl.count_rows())\n";

export const PyUpdateOperation = "from tempfile import TemporaryDirectory\n\nimport lancedb\n\nwith TemporaryDirectory(prefix=\"lancedb-ingestion-\") as uri:\n    db = lancedb.connect(uri)\n    import pyarrow as pa\n\n    table = db.create_table(\n        \"users_example\",\n        data=pa.table(\n            {\n                \"id\": [1, 2],\n                \"name\": [\"Alice\", \"Bob\"],\n                \"login_count\": [10, 20],\n            }\n        ),\n        mode=\"overwrite\",\n    )\n    table.update(where=\"id = 2\", values={\"name\": \"Bobby\"})\n\n    print(\"Rows:\", table.count_rows())\n";

export const PyUpdateUsingSql = "from tempfile import TemporaryDirectory\n\nimport lancedb\n\nwith TemporaryDirectory(prefix=\"lancedb-ingestion-\") as uri:\n    db = lancedb.connect(uri)\n    import pyarrow as pa\n\n    table = db.create_table(\n        \"users_example\",\n        data=pa.table(\n            {\n                \"id\": [1, 2],\n                \"name\": [\"Alice\", \"Bob\"],\n                \"login_count\": [10, 20],\n            }\n        ),\n        mode=\"overwrite\",\n    )\n    table.update(where=\"id = 2\", values_sql={\"login_count\": \"login_count + 1\"})\n\n    print(\"Rows:\", table.count_rows())\n";

export const PyWriteWorkflow = "from tempfile import TemporaryDirectory\n\nimport lancedb\n\nwith TemporaryDirectory(prefix=\"lancedb-ingestion-\") as uri:\n    db = lancedb.connect(uri)\n    table = db.create_table(\n        \"users\",\n        [\n            {\"id\": 1, \"name\": \"Alice\", \"login_count\": 10},\n            {\"id\": 2, \"name\": \"Bob\", \"login_count\": 20},\n        ],\n    )\n    table.add([{\"id\": 3, \"name\": \"Charlie\", \"login_count\": 5}])\n    table.update(where=\"id = 2\", values={\"name\": \"Bobby\"})\n    table.update(where=\"id = 2\", values_sql={\"login_count\": \"login_count + 1\"})\n    (\n        table.merge_insert(\"id\")\n        .when_matched_update_all()\n        .when_not_matched_insert_all()\n        .execute(\n            [\n                {\"id\": 3, \"name\": \"Charlie\", \"login_count\": 6},\n                {\"id\": 4, \"name\": \"Dana\", \"login_count\": 1},\n            ]\n        )\n    )\n    print(\"Rows selected for deletion:\", table.search().where(\"id = 4\").to_list())\n    table.delete(\"id = 4\")\n    rows = sorted(table.search().to_list(), key=lambda row: row[\"id\"])\n    print(rows)\n";

export const TsAddProgressBody = "const lancedb = await import(\"@lancedb/lancedb\");\nconst { mkdtemp, rm } = await import(\"node:fs/promises\");\nconst { tmpdir } = await import(\"node:os\");\nconst { join } = await import(\"node:path\");\nconst uri = await mkdtemp(join(tmpdir(), \"lancedb-ingestion-\"));\ntry {\n  const db = await lancedb.connect(uri);\n  const table = await db.createTable(\"users\", [{ id: 1, name: \"Alice\" }]);\n  await table.add(\n    [\n      { id: 2, name: \"Bob\" },\n      { id: 3, name: \"Charlie\" },\n    ],\n    {\n      progress: (progress) =>\n        console.log(`Rows written: ${progress.outputRows}`),\n    },\n  );\n  const rows = (await table.query().toArray()).sort((a, b) => a.id - b.id);\n  console.log(\"After insertion:\", rows);\n";

export const TsAddProgressTail = "} finally {\n  await rm(uri, { recursive: true, force: true });\n}\n";

export const TsDeleteRowsBody = "const lancedb = await import(\"@lancedb/lancedb\");\nconst { mkdtemp, rm } = await import(\"node:fs/promises\");\nconst { tmpdir } = await import(\"node:os\");\nconst { join } = await import(\"node:path\");\nconst uri = await mkdtemp(join(tmpdir(), \"lancedb-ingestion-\"));\ntry {\n  const db = await lancedb.connect(uri);\n  const table = await db.createTable(\"users\", [\n    { id: 1, name: \"Alice\" },\n    { id: 2, name: \"Bob\" },\n    { id: 3, name: \"Charlie\" },\n  ]);\n  const predicate = \"id = 3\";\n  console.log(\"Selected:\", await table.query().where(predicate).toArray());\n  await table.delete(predicate);\n  const rows = (await table.query().toArray()).sort((a, b) => a.id - b.id);\n  console.log(\"Remaining:\", rows);\n";

export const TsDeleteRowsTail = "} finally {\n  await rm(uri, { recursive: true, force: true });\n}\n";

export const TsWriteWorkflowBody = "const lancedb = await import(\"@lancedb/lancedb\");\nconst { mkdtemp, rm } = await import(\"node:fs/promises\");\nconst { tmpdir } = await import(\"node:os\");\nconst { join } = await import(\"node:path\");\n\nconst uri = await mkdtemp(join(tmpdir(), \"lancedb-ingestion-\"));\ntry {\n  const db = await lancedb.connect(uri);\n  const table = await db.createTable(\"users\", [\n    { id: 1, name: \"Alice\", login_count: 10 },\n    { id: 2, name: \"Bob\", login_count: 20 },\n  ]);\n  await table.add([{ id: 3, name: \"Charlie\", login_count: 5 }]);\n  await table.update({ where: \"id = 2\", values: { name: \"Bobby\" } });\n  await table.update({\n    where: \"id = 2\",\n    valuesSql: { login_count: \"login_count + 1\" },\n  });\n  await table\n    .mergeInsert(\"id\")\n    .whenMatchedUpdateAll()\n    .whenNotMatchedInsertAll()\n    .execute([\n      { id: 3, name: \"Charlie\", login_count: 6 },\n      { id: 4, name: \"Dana\", login_count: 1 },\n    ]);\n  console.log(\n    \"Rows selected for deletion:\",\n    await table.query().where(\"id = 4\").toArray(),\n  );\n  await table.delete(\"id = 4\");\n  const rows = (await table.query().toArray()).sort((a, b) => a.id - b.id);\n  console.log(rows);\n";

export const TsWriteWorkflowTail = "} finally {\n  await rm(uri, { recursive: true, force: true });\n}\n";

export const RsWriteWorkflow = "use std::sync::Arc;\n\nuse arrow_array::{Int64Array, RecordBatch, RecordBatchIterator, RecordBatchReader, StringArray};\nuse arrow_schema::{DataType, Field, Schema};\nuse futures::TryStreamExt;\nuse lancedb::query::{ExecutableQuery, QueryBase};\n\nfn make_users_reader(rows: &[(i64, &str, i64)]) -> Box<dyn RecordBatchReader + Send> {\n    let schema = Arc::new(Schema::new(vec![\n        Field::new(\"id\", DataType::Int64, false),\n        Field::new(\"name\", DataType::Utf8, false),\n        Field::new(\"login_count\", DataType::Int64, false),\n    ]));\n    let batch = RecordBatch::try_new(\n        schema.clone(),\n        vec![\n            Arc::new(Int64Array::from_iter_values(rows.iter().map(|r| r.0))),\n            Arc::new(StringArray::from_iter_values(rows.iter().map(|r| r.1))),\n            Arc::new(Int64Array::from_iter_values(rows.iter().map(|r| r.2))),\n        ],\n    )\n    .unwrap();\n    Box::new(RecordBatchIterator::new(\n        vec![Ok(batch)].into_iter(),\n        schema,\n    ))\n}\n\n#[tokio::main]\nasync fn main() -> Result<(), Box<dyn std::error::Error>> {\n    let directory = tempfile::tempdir()?;\n    let db = lancedb::connect(directory.path().to_str().unwrap())\n        .execute()\n        .await?;\n    let table = db\n        .create_table(\n            \"users\",\n            make_users_reader(&[(1, \"Alice\", 10), (2, \"Bob\", 20)]),\n        )\n        .execute()\n        .await?;\n    table\n        .add(make_users_reader(&[(3, \"Charlie\", 5)]))\n        .execute()\n        .await?;\n    table\n        .update()\n        .only_if(\"id = 2\")\n        .column(\"name\", \"'Bobby'\")\n        .execute()\n        .await?;\n    table\n        .update()\n        .only_if(\"id = 2\")\n        .column(\"login_count\", \"login_count + 1\")\n        .execute()\n        .await?;\n    let mut merge = table.merge_insert(&[\"id\"]);\n    merge\n        .when_matched_update_all(None)\n        .when_not_matched_insert_all();\n    merge\n        .execute(make_users_reader(&[(3, \"Charlie\", 6), (4, \"Dana\", 1)]))\n        .await?;\n    let selected: Vec<RecordBatch> = table\n        .query()\n        .only_if(\"id = 4\")\n        .execute()\n        .await?\n        .try_collect()\n        .await?;\n    println!(\"Rows selected for deletion: {selected:?}\");\n    table.delete(\"id = 4\").await?;\n    let rows: Vec<RecordBatch> = table.query().execute().await?.try_collect().await?;\n    println!(\"Remaining rows: {rows:?}\");\n    assert_eq!(table.count_rows(None).await?, 3);\n    assert_eq!(\n        table\n            .count_rows(Some(\n                \"id = 2 AND name = 'Bobby' AND login_count = 21\".into()\n            ))\n            .await?,\n        1\n    );\n    assert_eq!(\n        table\n            .count_rows(Some(\"id = 3 AND login_count = 6\".into()))\n            .await?,\n        1\n    );\n    Ok(())\n}\n";