db.py

from .utils import (
    chunks,
    hash_record,
    sqlite3,
    OperationalError,
    suggest_column_types,
    types_for_column_types,
    column_affinity,
    progressbar,
    find_spatialite,
)
import binascii
from collections import namedtuple
from collections.abc import Mapping
import contextlib
import datetime
import decimal
import inspect
import itertools
import json
import os
import pathlib
import re
import secrets
from sqlite_fts4 import rank_bm25  # type: ignore
import textwrap
from typing import (
    cast,
    Any,
    Callable,
    Dict,
    Generator,
    Iterable,
    Union,
    Optional,
    List,
    Tuple,
)
import uuid

SQLITE_MAX_VARS = 999

_quote_fts_re = re.compile(r'\s+|(".*?")')

_virtual_table_using_re = re.compile(
    r"""
^ # Start of string
\s*CREATE\s+VIRTUAL\s+TABLE\s+ # CREATE VIRTUAL TABLE
(
    '(?P<squoted_table>[^']*(?:''[^']*)*)' | # single quoted name
    "(?P<dquoted_table>[^"]*(?:""[^"]*)*)" | # double quoted name
    `(?P<backtick_table>[^`]+)`            | # `backtick` quoted name
    \[(?P<squarequoted_table>[^\]]+)\]     | # [...] quoted name
    (?P<identifier>                          # SQLite non-quoted identifier
        [A-Za-z_\u0080-\uffff]  # \u0080-\uffff = "any character larger than u007f"
        [A-Za-z_\u0080-\uffff0-9\$]* # zero-or-more alphanemuric or $
    )
)
\s+(IF\s+NOT\s+EXISTS\s+)?      # IF NOT EXISTS (optional)
USING\s+(?P<using>\w+)          # for example USING FTS5
""",
    re.VERBOSE | re.IGNORECASE,
)

try:
    import pandas as pd  # type: ignore
except ImportError:
    pd = None  # type: ignore

try:
    import numpy as np  # type: ignore
except ImportError:
    np = None  # type: ignore

Column = namedtuple(
    "Column", ("cid", "name", "type", "notnull", "default_value", "is_pk")
)
Column.__doc__ = """
Describes a SQLite column returned by the  :attr:`.Table.columns` property.

``cid``
    Column index

``name``
    Column name

``type``
    Column type

``notnull``
    Does the column have a ``not null`` constraint

``default_value``
    Default value for this column

``is_pk``
    Is this column part of the primary key
"""

ColumnDetails = namedtuple(
    "ColumnDetails",
    (
        "table",
        "column",
        "total_rows",
        "num_null",
        "num_blank",
        "num_distinct",
        "most_common",
        "least_common",
    ),
)
ColumnDetails.__doc__ = """
Summary information about a column, see :ref:`python_api_analyze_column`.

``table``
    The name of the table

``column``
    The name of the column

``total_rows``
    The total number of rows in the table

``num_null``
    The number of rows for which this column is null

``num_blank``
    The number of rows for which this column is blank (the empty string)

``num_distinct``
    The number of distinct values in this column

``most_common``
    The ``N`` most common values as a list of ``(value, count)`` tuples, or ``None`` if the table consists entirely of distinct values

``least_common``
    The ``N`` least common values as a list of ``(value, count)`` tuples, or ``None`` if the table is entirely distinct
    or if the number of distinct values is less than N (since they will already have been returned in ``most_common``)
"""
ForeignKey = namedtuple(
    "ForeignKey", ("table", "column", "other_table", "other_column")
)
Index = namedtuple("Index", ("seq", "name", "unique", "origin", "partial", "columns"))
XIndex = namedtuple("XIndex", ("name", "columns"))
XIndexColumn = namedtuple(
    "XIndexColumn", ("seqno", "cid", "name", "desc", "coll", "key")
)
Trigger = namedtuple("Trigger", ("name", "table", "sql"))


ForeignKeysType = Union[
    Iterable[str],
    Iterable[ForeignKey],
    Iterable[Tuple[str, str]],
    Iterable[Tuple[str, str, str]],
    Iterable[Tuple[str, str, str, str]],
]


class Default:
    pass


DEFAULT = Default()

COLUMN_TYPE_MAPPING = {
    float: "FLOAT",
    int: "INTEGER",
    bool: "INTEGER",
    str: "TEXT",
    dict: "TEXT",
    tuple: "TEXT",
    list: "TEXT",
    bytes.__class__: "BLOB",
    bytes: "BLOB",
    memoryview: "BLOB",
    datetime.datetime: "TEXT",
    datetime.date: "TEXT",
    datetime.time: "TEXT",
    decimal.Decimal: "FLOAT",
    None.__class__: "TEXT",
    uuid.UUID: "TEXT",
    # SQLite explicit types
    "TEXT": "TEXT",
    "INTEGER": "INTEGER",
    "FLOAT": "FLOAT",
    "BLOB": "BLOB",
    "text": "TEXT",
    "integer": "INTEGER",
    "float": "FLOAT",
    "blob": "BLOB",
}
# If numpy is available, add more types
if np:
    COLUMN_TYPE_MAPPING.update(
        {
            np.int8: "INTEGER",
            np.int16: "INTEGER",
            np.int32: "INTEGER",
            np.int64: "INTEGER",
            np.uint8: "INTEGER",
            np.uint16: "INTEGER",
            np.uint32: "INTEGER",
            np.uint64: "INTEGER",
            np.float16: "FLOAT",
            np.float32: "FLOAT",
            np.float64: "FLOAT",
        }
    )

# If pandas is available, add more types
if pd:
    COLUMN_TYPE_MAPPING.update({pd.Timestamp: "TEXT"})  # type: ignore


class AlterError(Exception):
    "Error altering table"
    pass


class NoObviousTable(Exception):
    "Could not tell which table this operation refers to"
    pass


class NoTable(Exception):
    "Specified table does not exist"
    pass


class BadPrimaryKey(Exception):
    "Table does not have a single obvious primary key"
    pass


class NotFoundError(Exception):
    "Record not found"
    pass


class PrimaryKeyRequired(Exception):
    "Primary key needs to be specified"
    pass


class InvalidColumns(Exception):
    "Specified columns do not exist"
    pass


class DescIndex(str):
    pass


class BadMultiValues(Exception):
    "With multi=True code must return a Python dictionary"

    def __init__(self, values):
        self.values = values


_COUNTS_TABLE_CREATE_SQL = """
CREATE TABLE IF NOT EXISTS [{}](
   [table] TEXT PRIMARY KEY,
   count INTEGER DEFAULT 0
);
""".strip()


class Database:
    """
    Wrapper for a SQLite database connection that adds a variety of useful utility methods.

    To create an instance::

        # create data.db file, or open existing:
        db = Database("data.db")
        # Create an in-memory database:
        dB = Database(memory=True)

    :param filename_or_conn: String path to a file, or a ``pathlib.Path`` object, or a
      ``sqlite3`` connection
    :param memory: set to ``True`` to create an in-memory database
    :param memory_name: creates a named in-memory database that can be shared across multiple connections
    :param recreate: set to ``True`` to delete and recreate a file database (**dangerous**)
    :param recursive_triggers: defaults to ``True``, which sets ``PRAGMA recursive_triggers=on;`` -
      set to ``False`` to avoid setting this pragma
    :param tracer: set a tracer function (``print`` works for this) which will be called with
      ``sql, parameters`` every time a SQL query is executed
    :param use_counts_table: set to ``True`` to use a cached counts table, if available. See
      :ref:`python_api_cached_table_counts`
    """

    _counts_table_name = "_counts"
    use_counts_table = False

    def __init__(
        self,
        filename_or_conn: Optional[Union[str, pathlib.Path, sqlite3.Connection]] = None,
        memory: bool = False,
        memory_name: Optional[str] = None,
        recreate: bool = False,
        recursive_triggers: bool = True,
        tracer: Optional[Callable] = None,
        use_counts_table: bool = False,
    ):
        assert (filename_or_conn is not None and (not memory and not memory_name)) or (
            filename_or_conn is None and (memory or memory_name)
        ), "Either specify a filename_or_conn or pass memory=True"
        if memory_name:
            uri = "file:{}?mode=memory&cache=shared".format(memory_name)
            self.conn = sqlite3.connect(
                uri,
                uri=True,
                check_same_thread=False,
            )
        elif memory or filename_or_conn == ":memory:":
            self.conn = sqlite3.connect(":memory:")
        elif isinstance(filename_or_conn, (str, pathlib.Path)):
            if recreate and os.path.exists(filename_or_conn):
                try:
                    os.remove(filename_or_conn)
                except OSError:
                    # Avoid mypy and __repr__ errors, see:
                    # https://github.com/simonw/sqlite-utils/issues/503
                    self.conn = sqlite3.connect(":memory:")
                    raise
            self.conn = sqlite3.connect(str(filename_or_conn))
        else:
            assert not recreate, "recreate cannot be used with connections, only paths"
            self.conn = filename_or_conn
        self._tracer = tracer
        if recursive_triggers:
            self.execute("PRAGMA recursive_triggers=on;")
        self._registered_functions: set = set()
        self.use_counts_table = use_counts_table

    def close(self):
        "Close the SQLite connection, and the underlying database file"
        self.conn.close()

    @contextlib.contextmanager
    def tracer(self, tracer: Optional[Callable] = None):
        """
        Context manager to temporarily set a tracer function - all executed SQL queries will
        be passed to this.

        The tracer function should accept two arguments: ``sql`` and ``parameters``

        Example usage::

            with db.tracer(print):
                db["creatures"].insert({"name": "Cleo"})

        See :ref:`python_api_tracing`.

        :param tracer: Callable accepting ``sql`` and ``parameters`` arguments
        """
        prev_tracer = self._tracer
        self._tracer = tracer or print
        try:
            yield self
        finally:
            self._tracer = prev_tracer

    def __getitem__(self, table_name: str) -> Union["Table", "View"]:
        """
        ``db[table_name]`` returns a :class:`.Table` object for the table with the specified name.
        If the table does not exist yet it will be created the first time data is inserted into it.

        :param table_name: The name of the table
        """
        return self.table(table_name)

    def __repr__(self) -> str:
        return "<Database {}>".format(self.conn)

    def register_function(
        self,
        fn: Optional[Callable] = None,
        deterministic: bool = False,
        replace: bool = False,
        name: Optional[str] = None,
    ):
        """
        ``fn`` will be made available as a function within SQL, with the same name and number
        of arguments. Can be used as a decorator::

            @db.register_function
            def upper(value):
                return str(value).upper()

        The decorator can take arguments::

            @db.register_function(deterministic=True, replace=True)
            def upper(value):
                return str(value).upper()

        See :ref:`python_api_register_function`.

        :param fn: Function to register
        :param deterministic: set ``True`` for functions that always returns the same output for a given input
        :param replace: set ``True`` to replace an existing function with the same name - otherwise throw an error
        :param name: name of the SQLite function - if not specified, the Python function name will be used
        """

        def register(fn):
            fn_name = name or fn.__name__
            arity = len(inspect.signature(fn).parameters)
            if not replace and (fn_name, arity) in self._registered_functions:
                return fn
            kwargs = {}
            registered = False
            if deterministic:
                # Try this, but fall back if sqlite3.NotSupportedError
                try:
                    self.conn.create_function(
                        fn_name, arity, fn, **dict(kwargs, deterministic=True)
                    )
                    registered = True
                except (sqlite3.NotSupportedError, TypeError):
                    # TypeError is Python 3.7 "function takes at most 3 arguments"
                    pass
            if not registered:
                self.conn.create_function(fn_name, arity, fn, **kwargs)
            self._registered_functions.add((fn_name, arity))
            return fn

        if fn is None:
            return register
        else:
            register(fn)

    def register_fts4_bm25(self):
        "Register the ``rank_bm25(match_info)`` function used for calculating relevance with SQLite FTS4."
        self.register_function(rank_bm25, deterministic=True)

    def attach(self, alias: str, filepath: Union[str, pathlib.Path]):
        """
        Attach another SQLite database file to this connection with the specified alias, equivalent to::

            ATTACH DATABASE 'filepath.db' AS alias

        :param alias: Alias name to use
        :param filepath: Path to SQLite database file on disk
        """
        attach_sql = """
            ATTACH DATABASE '{}' AS [{}];
        """.format(
            str(pathlib.Path(filepath).resolve()), alias
        ).strip()
        self.execute(attach_sql)

    def query(
        self, sql: str, params: Optional[Union[Iterable, dict]] = None
    ) -> Generator[dict, None, None]:
        """
        Execute ``sql`` and return an iterable of dictionaries representing each row.

        :param sql: SQL query to execute
        :param params: Parameters to use in that query - an iterable for ``where id = ?``
          parameters, or a dictionary for ``where id = :id``
        """
        cursor = self.execute(sql, params or tuple())
        keys = [d[0] for d in cursor.description]
        for row in cursor:
            yield dict(zip(keys, row))

    def execute(
        self, sql: str, parameters: Optional[Union[Iterable, dict]] = None
    ) -> sqlite3.Cursor:
        """
        Execute SQL query and return a ``sqlite3.Cursor``.

        :param sql: SQL query to execute
        :param parameters: Parameters to use in that query - an iterable for ``where id = ?``
          parameters, or a dictionary for ``where id = :id``
        """
        if self._tracer:
            self._tracer(sql, parameters)
        if parameters is not None:
            return self.conn.execute(sql, parameters)
        else:
            return self.conn.execute(sql)

    def executescript(self, sql: str) -> sqlite3.Cursor:
        """
        Execute multiple SQL statements separated by ; and return the ``sqlite3.Cursor``.

        :param sql: SQL to execute
        """
        if self._tracer:
            self._tracer(sql, None)
        return self.conn.executescript(sql)

    def table(self, table_name: str, **kwargs) -> Union["Table", "View"]:
        """
        Return a table object, optionally configured with default options.

        See :ref:`reference_db_table` for option details.

        :param table_name: Name of the table
        """
        klass = View if table_name in self.view_names() else Table
        return klass(self, table_name, **kwargs)

    def quote(self, value: str) -> str:
        """
        Apply SQLite string quoting to a value, including wrappping it in single quotes.

        :param value: String to quote
        """
        # Normally we would use .execute(sql, [params]) for escaping, but
        # occasionally that isn't available - most notable when we need
        # to include a "... DEFAULT 'value'" in a column definition.
        return self.execute(
            # Use SQLite itself to correctly escape this string:
            "SELECT quote(:value)",
            {"value": value},
        ).fetchone()[0]

    def quote_fts(self, query: str) -> str:
        """
        Escape special characters in a SQLite full-text search query.

        This works by surrounding each token within the query with double
        quotes, in order to avoid words like ``NOT`` and ``OR`` having
        special meaning as defined by the FTS query syntax here:

        https://www.sqlite.org/fts5.html#full_text_query_syntax

        If the query has unbalanced ``"`` characters, adds one at end.

        :param query: String to escape
        """
        if query.count('"') % 2:
            query += '"'
        bits = _quote_fts_re.split(query)
        bits = [b for b in bits if b and b != '""']
        return " ".join(
            '"{}"'.format(bit) if not bit.startswith('"') else bit for bit in bits
        )

    def table_names(self, fts4: bool = False, fts5: bool = False) -> List[str]:
        """
        List of string table names in this database.

        :param fts4: Only return tables that are part of FTS4 indexes
        :param fts5: Only return tables that are part of FTS5 indexes
        """
        where = ["type = 'table'"]
        if fts4:
            where.append("sql like '%USING FTS4%'")
        if fts5:
            where.append("sql like '%USING FTS5%'")
        sql = "select name from sqlite_master where {}".format(" AND ".join(where))
        return [r[0] for r in self.execute(sql).fetchall()]

    def view_names(self) -> List[str]:
        "List of string view names in this database."
        return [
            r[0]
            for r in self.execute(
                "select name from sqlite_master where type = 'view'"
            ).fetchall()
        ]

    @property
    def tables(self) -> List["Table"]:
        "List of Table objects in this database."
        return cast(List["Table"], [self[name] for name in self.table_names()])

    @property
    def views(self) -> List["View"]:
        "List of View objects in this database."
        return cast(List["View"], [self[name] for name in self.view_names()])

    @property
    def triggers(self) -> List[Trigger]:
        "List of ``(name, table_name, sql)`` tuples representing triggers in this database."
        return [
            Trigger(*r)
            for r in self.execute(
                "select name, tbl_name, sql from sqlite_master where type = 'trigger'"
            ).fetchall()
        ]

    @property
    def triggers_dict(self) -> Dict[str, str]:
        "A ``{trigger_name: sql}`` dictionary of triggers in this database."
        return {trigger.name: trigger.sql for trigger in self.triggers}

    @property
    def schema(self) -> str:
        "SQL schema for this database."
        sqls = []
        for row in self.execute(
            "select sql from sqlite_master where sql is not null"
        ).fetchall():
            sql = row[0]
            if not sql.strip().endswith(";"):
                sql += ";"
            sqls.append(sql)
        return "\n".join(sqls)

    @property
    def supports_strict(self) -> bool:
        "Does this database support STRICT mode?"
        try:
            table_name = "t{}".format(secrets.token_hex(16))
            with self.conn:
                self.conn.execute(
                    "create table {} (name text) strict".format(table_name)
                )
                self.conn.execute("drop table {}".format(table_name))
            return True
        except Exception:
            return False

    @property
    def sqlite_version(self) -> Tuple[int, ...]:
        "Version of SQLite, as a tuple of integers for example ``(3, 36, 0)``."
        row = self.execute("select sqlite_version()").fetchall()[0]
        return tuple(map(int, row[0].split(".")))

    @property
    def journal_mode(self) -> str:
        """
        Current ``journal_mode`` of this database.

        https://www.sqlite.org/pragma.html#pragma_journal_mode
        """
        return self.execute("PRAGMA journal_mode;").fetchone()[0]

    def enable_wal(self):
        """
        Sets ``journal_mode`` to ``'wal'`` to enable Write-Ahead Log mode.
        """
        if self.journal_mode != "wal":
            self.execute("PRAGMA journal_mode=wal;")

    def disable_wal(self):
        "Sets ``journal_mode`` back to ``'delete'`` to disable Write-Ahead Log mode."
        if self.journal_mode != "delete":
            self.execute("PRAGMA journal_mode=delete;")

    def _ensure_counts_table(self):
        with self.conn:
            self.execute(_COUNTS_TABLE_CREATE_SQL.format(self._counts_table_name))

    def enable_counts(self):
        """
        Enable trigger-based count caching for every table in the database, see
        :ref:`python_api_cached_table_counts`.
        """
        self._ensure_counts_table()
        for table in self.tables:
            if (
                table.virtual_table_using is None
                and table.name != self._counts_table_name
            ):
                table.enable_counts()
        self.use_counts_table = True

    def cached_counts(self, tables: Optional[Iterable[str]] = None) -> Dict[str, int]:
        """
        Return ``{table_name: count}`` dictionary of cached counts for specified tables, or
        all tables if ``tables`` not provided.

        :param tables: Subset list of tables to return counts for.
        """
        sql = "select [table], count from {}".format(self._counts_table_name)
        if tables:
            sql += " where [table] in ({})".format(", ".join("?" for table in tables))
        try:
            return {r[0]: r[1] for r in self.execute(sql, tables).fetchall()}
        except OperationalError:
            return {}

    def reset_counts(self):
        "Re-calculate cached counts for tables."
        tables = [table for table in self.tables if table.has_counts_triggers]
        with self.conn:
            self._ensure_counts_table()
            counts_table = self[self._counts_table_name]
            counts_table.delete_where()
            counts_table.insert_all(
                {"table": table.name, "count": table.execute_count()}
                for table in tables
            )

    def execute_returning_dicts(
        self, sql: str, params: Optional[Union[Iterable, dict]] = None
    ) -> List[dict]:
        return list(self.query(sql, params))

    def resolve_foreign_keys(
        self, name: str, foreign_keys: ForeignKeysType
    ) -> List[ForeignKey]:
        # foreign_keys may be a list of column names, a list of ForeignKey tuples,
        # a list of tuple-pairs or a list of tuple-triples. We want to turn
        # it into a list of ForeignKey tuples
        table = cast(Table, self[name])
        if all(isinstance(fk, ForeignKey) for fk in foreign_keys):
            return cast(List[ForeignKey], foreign_keys)
        if all(isinstance(fk, str) for fk in foreign_keys):
            # It's a list of columns
            fks = []
            for column in foreign_keys:
                column = cast(str, column)
                other_table = table.guess_foreign_table(column)
                other_column = table.guess_foreign_column(other_table)
                fks.append(ForeignKey(name, column, other_table, other_column))
            return fks
        assert all(
            isinstance(fk, (tuple, list)) for fk in foreign_keys
        ), "foreign_keys= should be a list of tuples"
        fks = []
        for tuple_or_list in foreign_keys:
            assert len(tuple_or_list) in (
                2,
                3,
            ), "foreign_keys= should be a list of tuple pairs or triples"
            if len(tuple_or_list) == 3:
                tuple_or_list = cast(Tuple[str, str, str], tuple_or_list)
                fks.append(
                    ForeignKey(
                        name, tuple_or_list[0], tuple_or_list[1], tuple_or_list[2]
                    )
                )
            else:
                # Guess the primary key
                fks.append(
                    ForeignKey(
                        name,
                        tuple_or_list[0],
                        tuple_or_list[1],
                        table.guess_foreign_column(tuple_or_list[1]),
                    )
                )
        return fks

    def create_table_sql(
        self,
        name: str,
        columns: Dict[str, Any],
        pk: Optional[Any] = None,
        foreign_keys: Optional[ForeignKeysType] = None,
        column_order: Optional[List[str]] = None,
        not_null: Optional[Iterable[str]] = None,
        defaults: Optional[Dict[str, Any]] = None,
        hash_id: Optional[str] = None,
        hash_id_columns: Optional[Iterable[str]] = None,
        extracts: Optional[Union[Dict[str, str], List[str]]] = None,
        if_not_exists: bool = False,
    ) -> str:
        """
        Returns the SQL ``CREATE TABLE`` statement for creating the specified table.

        :param name: Name of table
        :param columns: Dictionary mapping column names to their types, for example ``{"name": str, "age": int}``
        :param pk: String name of column to use as a primary key, or a tuple of strings for a compound primary key covering multiple columns
        :param foreign_keys: List of foreign key definitions for this table
        :param column_order: List specifying which columns should come first
        :param not_null: List of columns that should be created as ``NOT NULL``
        :param defaults: Dictionary specifying default values for columns
        :param hash_id: Name of column to be used as a primary key containing a hash of the other columns
        :param hash_id_columns: List of columns to be used when calculating the hash ID for a row
        :param extracts: List or dictionary of columns to be extracted during inserts, see :ref:`python_api_extracts`
        :param if_not_exists: Use ``CREATE TABLE IF NOT EXISTS``
        """
        if hash_id_columns and (hash_id is None):
            hash_id = "id"
        foreign_keys = self.resolve_foreign_keys(name, foreign_keys or [])
        foreign_keys_by_column = {fk.column: fk for fk in foreign_keys}
        # any extracts will be treated as integer columns with a foreign key
        extracts = resolve_extracts(extracts)
        for extract_column, extract_table in extracts.items():
            if isinstance(extract_column, tuple):
                assert False
            # Ensure other table exists
            if not self[extract_table].exists():
                self.create_table(extract_table, {"id": int, "value": str}, pk="id")
            columns[extract_column] = int
            foreign_keys_by_column[extract_column] = ForeignKey(
                name, extract_column, extract_table, "id"
            )
        # Soundness check not_null, and defaults if provided
        not_null = not_null or set()
        defaults = defaults or {}
        assert columns, "Tables must have at least one column"
        assert all(
            n in columns for n in not_null
        ), "not_null set {} includes items not in columns {}".format(
            repr(not_null), repr(set(columns.keys()))
        )
        assert all(
            n in columns for n in defaults
        ), "defaults set {} includes items not in columns {}".format(
            repr(set(defaults)), repr(set(columns.keys()))
        )
        validate_column_names(columns.keys())
        column_items = list(columns.items())
        if column_order is not None:

            def sort_key(p):
                return column_order.index(p[0]) if p[0] in column_order else 999

            column_items.sort(key=sort_key)
        if hash_id:
            column_items.insert(0, (hash_id, str))
            pk = hash_id
        # Soundness check foreign_keys point to existing tables
        for fk in foreign_keys:
            if not any(
                c for c in self[fk.other_table].columns if c.name == fk.other_column
            ):
                raise AlterError(
                    "No such column: {}.{}".format(fk.other_table, fk.other_column)
                )

        column_defs = []
        # ensure pk is a tuple
        single_pk = None
        if isinstance(pk, list) and len(pk) == 1 and isinstance(pk[0], str):
            pk = pk[0]
        if isinstance(pk, str):
            single_pk = pk
            if pk not in [c[0] for c in column_items]:
                column_items.insert(0, (pk, int))
        for column_name, column_type in column_items:
            column_extras = []
            if column_name == single_pk:
                column_extras.append("PRIMARY KEY")
            if column_name in not_null:
                column_extras.append("NOT NULL")
            if column_name in defaults and defaults[column_name] is not None:
                column_extras.append(
                    "DEFAULT {}".format(self.quote(defaults[column_name]))
                )
            if column_name in foreign_keys_by_column:
                column_extras.append(
                    "REFERENCES [{other_table}]([{other_column}])".format(
                        other_table=foreign_keys_by_column[column_name].other_table,
                        other_column=foreign_keys_by_column[column_name].other_column,
                    )
                )
            column_defs.append(
                "   [{column_name}] {column_type}{column_extras}".format(
                    column_name=column_name,
                    column_type=COLUMN_TYPE_MAPPING[column_type],
                    column_extras=(" " + " ".join(column_extras))
                    if column_extras
                    else "",
                )
            )
        extra_pk = ""
        if single_pk is None and pk and len(pk) > 1:
            extra_pk = ",\n   PRIMARY KEY ({pks})".format(
                pks=", ".join(["[{}]".format(p) for p in pk])
            )
        columns_sql = ",\n".join(column_defs)
        sql = """CREATE TABLE {if_not_exists}[{table}] (
{columns_sql}{extra_pk}
);
        """.format(
            if_not_exists="IF NOT EXISTS " if if_not_exists else "",
            table=name,
            columns_sql=columns_sql,
            extra_pk=extra_pk,
        )
        return sql

    def create_table(
        self,
        name: str,
        columns: Dict[str, Any],
        pk: Optional[Any] = None,
        foreign_keys: Optional[ForeignKeysType] = None,
        column_order: Optional[List[str]] = None,
        not_null: Optional[Iterable[str]] = None,
        defaults: Optional[Dict[str, Any]] = None,
        hash_id: Optional[str] = None,
        hash_id_columns: Optional[Iterable[str]] = None,
        extracts: Optional[Union[Dict[str, str], List[str]]] = None,
        if_not_exists: bool = False,
        transform: bool = False,
    ) -> "Table":
        """
        Create a table with the specified name and the specified ``{column_name: type}`` columns.

        See :ref:`python_api_explicit_create`.

        :param name: Name of table
        :param columns: Dictionary mapping column names to their types, for example ``{"name": str, "age": int}``
        :param pk: String name of column to use as a primary key, or a tuple of strings for a compound primary key covering multiple columns
        :param foreign_keys: List of foreign key definitions for this table
        :param column_order: List specifying which columns should come first
        :param not_null: List of columns that should be created as ``NOT NULL``
        :param defaults: Dictionary specifying default values for columns
        :param hash_id: Name of column to be used as a primary key containing a hash of the other columns
        :param hash_id_columns: List of columns to be used when calculating the hash ID for a row
        :param extracts: List or dictionary of columns to be extracted during inserts, see :ref:`python_api_extracts`
        :param if_not_exists: Use ``CREATE TABLE IF NOT EXISTS``
        :param transform: If table already exists transform it to fit the specified schema
        """
        # Transform table to match the new definition if table already exists:
        if transform and self[name].exists():
            table = cast(Table, self[name])
            should_transform = False
            # First add missing columns and figure out columns to drop
            existing_columns = table.columns_dict
            missing_columns = dict(
                (col_name, col_type)
                for col_name, col_type in columns.items()
                if col_name not in existing_columns
            )
            columns_to_drop = [
                column for column in existing_columns if column not in columns
            ]
            if missing_columns:
                for col_name, col_type in missing_columns.items():
                    table.add_column(col_name, col_type)
            if missing_columns or columns_to_drop or columns != existing_columns:
                should_transform = True
            # Do we need to change the column order?
            if (
                column_order
                and list(existing_columns)[: len(column_order)] != column_order
            ):
                should_transform = True
            # Has the primary key changed?
            current_pks = table.pks
            desired_pk = None
            if isinstance(pk, str):
                desired_pk = [pk]
            elif pk:
                desired_pk = list(pk)
            if desired_pk and current_pks != desired_pk:
                should_transform = True
            # Any not-null changes?
            current_not_null = {c.name for c in table.columns if c.notnull}
            desired_not_null = set(not_null) if not_null else set()
            if current_not_null != desired_not_null:
                should_transform = True
            # How about defaults?
            if defaults and defaults != table.default_values:
                should_transform = True
            # Only run .transform() if there is something to do
            if should_transform:
                table.transform(
                    types=columns,
                    drop=columns_to_drop,
                    column_order=column_order,
                    not_null=not_null,
                    defaults=defaults,
                    pk=pk,
                )
            return table
        sql = self.create_table_sql(
            name=name,
            columns=columns,
            pk=pk,
            foreign_keys=foreign_keys,
            column_order=column_order,
            not_null=not_null,
            defaults=defaults,
            hash_id=hash_id,
            hash_id_columns=hash_id_columns,
            extracts=extracts,
            if_not_exists=if_not_exists,
        )
        self.execute(sql)
        created_table = self.table(
            name,
            pk=pk,
            foreign_keys=foreign_keys,
            column_order=column_order,
            not_null=not_null,
            defaults=defaults,
            hash_id=hash_id,
            hash_id_columns=hash_id_columns,
        )
        return cast(Table, created_table)

    def create_view(
        self, name: str, sql: str, ignore: bool = False, replace: bool = False
    ):
        """
        Create a new SQL view with the specified name - ``sql`` should start with ``SELECT ...``.

        :param name: Name of the view
        :param sql: SQL ``SELECT`` query to use for this view.
        :param ignore: Set to ``True`` to do nothing if a view with this name already exists
        :param replace: Set to ``True`` to replace the view if one with this name already exists
        """
        assert not (
            ignore and replace
        ), "Use one or the other of ignore/replace, not both"
        create_sql = "CREATE VIEW {name} AS {sql}".format(name=name, sql=sql)
        if ignore or replace:
            # Does view exist already?
            if name in self.view_names():
                if ignore:
                    return self
                elif replace:
                    # If SQL is the same, do nothing
                    if create_sql == self[name].schema:
                        return self
                    self[name].drop()
        self.execute(create_sql)
        return self

    def m2m_table_candidates(self, table: str, other_table: str) -> List[str]:
        """
        Given two table names returns the name of tables that could define a
        many-to-many relationship between those two tables, based on having
        foreign keys to both of the provided tables.

        :param table: Table name
        :param other_table: Other table name
        """
        candidates = []
        tables = {table, other_table}
        for table_obj in self.tables:
            # Does it have foreign keys to both table and other_table?
            has_fks_to = {fk.other_table for fk in table_obj.foreign_keys}
            if has_fks_to.issuperset(tables):
                candidates.append(table_obj.name)
        return candidates

    def add_foreign_keys(self, foreign_keys: Iterable[Tuple[str, str, str, str]]):
        """
        See :ref:`python_api_add_foreign_keys`.

        :param foreign_keys: A list of  ``(table, column, other_table, other_column)``
          tuples
        """
        # foreign_keys is a list of explicit 4-tuples
        assert all(
            len(fk) == 4 and isinstance(fk, (list, tuple)) for fk in foreign_keys
        ), "foreign_keys must be a list of 4-tuples, (table, column, other_table, other_column)"

        foreign_keys_to_create = []

        # Verify that all tables and columns exist
        for table, column, other_table, other_column in foreign_keys:
            if not self[table].exists():
                raise AlterError("No such table: {}".format(table))
            table_obj = self[table]
            if not isinstance(table_obj, Table):
                raise AlterError("Must be a table, not a view: {}".format(table))
            table_obj = cast(Table, table_obj)
            if column not in table_obj.columns_dict:
                raise AlterError("No such column: {} in {}".format(column, table))
            if not self[other_table].exists():
                raise AlterError("No such other_table: {}".format(other_table))
            if (
                other_column != "rowid"
                and other_column not in self[other_table].columns_dict
            ):
                raise AlterError(
                    "No such other_column: {} in {}".format(other_column, other_table)
                )
            # We will silently skip foreign keys that exist already
            if not any(
                fk
                for fk in table_obj.foreign_keys
                if fk.column == column
                and fk.other_table == other_table
                and fk.other_column == other_column
            ):
                foreign_keys_to_create.append(
                    (table, column, other_table, other_column)
                )

        # Construct SQL for use with "UPDATE sqlite_master SET sql = ? WHERE name = ?"
        table_sql: Dict[str, str] = {}
        for table, column, other_table, other_column in foreign_keys_to_create:
            old_sql = table_sql.get(table, self[table].schema)
            extra_sql = ",\n   FOREIGN KEY([{column}]) REFERENCES [{other_table}]([{other_column}])\n".format(
                column=column, other_table=other_table, other_column=other_column
            )
            # Stick that bit in at the very end just before the closing ')'
            last_paren = old_sql.rindex(")")
            new_sql = old_sql[:last_paren].strip() + extra_sql + old_sql[last_paren:]
            table_sql[table] = new_sql

        # And execute it all within a single transaction
        with self.conn:
            cursor = self.conn.cursor()
            schema_version = cursor.execute("PRAGMA schema_version").fetchone()[0]
            cursor.execute("PRAGMA writable_schema = 1")
            for table_name, new_sql in table_sql.items():
                cursor.execute(
                    "UPDATE sqlite_master SET sql = ? WHERE name = ?",
                    (new_sql, table_name),
                )
            cursor.execute("PRAGMA schema_version = %d" % (schema_version + 1))
            cursor.execute("PRAGMA writable_schema = 0")
        # Have to VACUUM outside the transaction to ensure .foreign_keys property
        # can see the newly created foreign key.
        self.vacuum()

    def index_foreign_keys(self):
        "Create indexes for every foreign key column on every table in the database."
        for table_name in self.table_names():
            table = self[table_name]
            existing_indexes = {
                i.columns[0] for i in table.indexes if len(i.columns) == 1
            }
            for fk in table.foreign_keys:
                if fk.column not in existing_indexes:
                    table.create_index([fk.column], find_unique_name=True)

    def vacuum(self):
        "Run a SQLite ``VACUUM`` against the database."
        self.execute("VACUUM;")

    def analyze(self, name=None):
        """
        Run ``ANALYZE`` against the entire database or a named table or index.

        :param name: Run ``ANALYZE`` against this specific named table or index
        """
        sql = "ANALYZE"
        if name is not None:
            sql += " [{}]".format(name)
        self.execute(sql)

    def init_spatialite(self, path: Optional[str] = None) -> bool:
        """
        The ``init_spatialite`` method will load and initialize the SpatiaLite extension.
        The ``path`` argument should be an absolute path to the compiled extension, which
        can be found using ``find_spatialite``.

        Returns ``True`` if SpatiaLite was successfully initialized.

        .. code-block:: python

            from sqlite_utils.db import Database
            from sqlite_utils.utils import find_spatialite

            db = Database("mydb.db")
            db.init_spatialite(find_spatialite())

        If you've installed SpatiaLite somewhere unexpected (for testing an alternate version, for example)
        you can pass in an absolute path:

        .. code-block:: python

            from sqlite_utils.db import Database
            from sqlite_utils.utils import find_spatialite

            db = Database("mydb.db")
            db.init_spatialite("./local/mod_spatialite.dylib")

        :param path: Path to SpatiaLite module on disk
        """
        if path is None:
            path = find_spatialite()

        self.conn.enable_load_extension(True)
        self.conn.load_extension(path)
        # Initialize SpatiaLite if not yet initialized
        if "spatial_ref_sys" in self.table_names():
            return False
        cursor = self.execute("select InitSpatialMetadata(1)")
        result = cursor.fetchone()
        return result and bool(result[0])


class Queryable:
    def exists(self) -> bool:
        "Does this table or view exist yet?"
        return False

    def __init__(self, db, name):
        self.db = db
        self.name = name

    def count_where(
        self,
        where: Optional[str] = None,
        where_args: Optional[Union[Iterable, dict]] = None,
    ) -> int:
        """
        Executes ``SELECT count(*) FROM table WHERE ...`` and returns a count.

        :param where: SQL where fragment to use, for example ``id > ?``
        :param where_args: Parameters to use with that fragment - an iterable for ``id > ?``
          parameters, or a dictionary for ``id > :id``
        """
        sql = "select count(*) from [{}]".format(self.name)
        if where is not None:
            sql += " where " + where
        return self.db.execute(sql, where_args or []).fetchone()[0]

    def execute_count(self):
        # Backwards compatibility, see https://github.com/simonw/sqlite-utils/issues/305#issuecomment-890713185
        return self.count_where()

    @property
    def count(self) -> int:
        "A count of the rows in this table or view."
        return self.count_where()

    @property
    def rows(self) -> Generator[dict, None, None]:
        "Iterate over every dictionaries for each row in this table or view."
        return self.rows_where()

    def rows_where(
        self,
        where: Optional[str] = None,
        where_args: Optional[Union[Iterable, dict]] = None,
        order_by: Optional[str] = None,
        select: str = "*",
        limit: Optional[int] = None,
        offset: Optional[int] = None,
    ) -> Generator[dict, None, None]:
        """
        Iterate over every row in this table or view that matches the specified where clause.

        Returns each row as a dictionary. See :ref:`python_api_rows` for more details.

        :param where: SQL where fragment to use, for example ``id > ?``
        :param where_args: Parameters to use with that fragment - an iterable for ``id > ?``
          parameters, or a dictionary for ``id > :id``
        :param order_by: Column or fragment of SQL to order by
        :param select: Comma-separated list of columns to select - defaults to ``*``
        :param limit: Integer number of rows to limit to
        :param offset: Integer for SQL offset
        """
        if not self.exists():
            return
        sql = "select {} from [{}]".format(select, self.name)
        if where is not None:
            sql += " where " + where
        if order_by is not None:
            sql += " order by " + order_by
        if limit is not None:
            sql += " limit {}".format(limit)
        if offset is not None:
            sql += " offset {}".format(offset)
        cursor = self.db.execute(sql, where_args or [])
        columns = [c[0] for c in cursor.description]
        for row in cursor:
            yield dict(zip(columns, row))

    def pks_and_rows_where(
        self,
        where: Optional[str] = None,
        where_args: Optional[Union[Iterable, dict]] = None,
        order_by: Optional[str] = None,
        limit: Optional[int] = None,
        offset: Optional[int] = None,
    ) -> Generator[Tuple[Any, Dict], None, None]:
        """
        Like ``.rows_where()`` but returns ``(pk, row)`` pairs - ``pk`` can be a single value or tuple.

        :param where: SQL where fragment to use, for example ``id > ?``
        :param where_args: Parameters to use with that fragment - an iterable for ``id > ?``
          parameters, or a dictionary for ``id > :id``
        :param order_by: Column or fragment of SQL to order by
        :param select: Comma-separated list of columns to select - defaults to ``*``
        :param limit: Integer number of rows to limit to
        :param offset: Integer for SQL offset
        """
        column_names = [column.name for column in self.columns]
        pks = [column.name for column in self.columns if column.is_pk]
        if not pks:
            column_names.insert(0, "rowid")
            pks = ["rowid"]
        select = ",".join("[{}]".format(column_name) for column_name in column_names)
        for row in self.rows_where(
            select=select,
            where=where,
            where_args=where_args,
            order_by=order_by,
            limit=limit,
            offset=offset,
        ):
            row_pk = tuple(row[pk] for pk in pks)
            if len(row_pk) == 1:
                row_pk = row_pk[0]
            yield row_pk, row

    @property
    def columns(self) -> List["Column"]:
        "List of :ref:`Columns <reference_db_other_column>` representing the columns in this table or view."
        if not self.exists():
            return []
        rows = self.db.execute("PRAGMA table_info([{}])".format(self.name)).fetchall()
        return [Column(*row) for row in rows]

    @property
    def columns_dict(self) -> Dict[str, Any]:
        "``{column_name: python-type}`` dictionary representing columns in this table or view."
        return {column.name: column_affinity(column.type) for column in self.columns}

    @property
    def schema(self) -> str:
        "SQL schema for this table or view."
        return self.db.execute(
            "select sql from sqlite_master where name = ?", (self.name,)
        ).fetchone()[0]


class Table(Queryable):
    """
    Tables should usually be initialized using the ``db.table(table_name)`` or
    ``db[table_name]`` methods.

    The following optional parameters can be passed to ``db.table(table_name, ...)``:

    :param db: Provided by ``db.table(table_name)``
    :param name: Provided by ``db.table(table_name)``
    :param pk: Name of the primary key column, or tuple of columns
    :param foreign_keys: List of foreign key definitions
    :param column_order: List of column names in the order they should be in the table
    :param not_null: List of columns that cannot be null
    :param defaults: Dictionary of column names and default values
    :param batch_size: Integer number of rows to insert at a time
    :param hash_id: If True, use a hash of the row values as the primary key
    :param hash_id_columns: List of columns to use for the hash_id
    :param alter: If True, automatically alter the table if it doesn't match the schema
    :param ignore: If True, ignore rows that already exist when inserting
    :param replace: If True, replace rows that already exist when inserting
    :param extracts: Dictionary or list of column names to extract into a separate table on inserts
    :param conversions: Dictionary of column names and conversion functions
    :param columns: Dictionary of column names to column types
    """

    #: The ``rowid`` of the last inserted, updated or selected row.
    last_rowid: Optional[int] = None
    #: The primary key of the last inserted, updated or selected row.
    last_pk: Optional[Any] = None

    def __init__(
        self,
        db: Database,
        name: str,
        pk: Optional[Any] = None,
        foreign_keys: Optional[ForeignKeysType] = None,
        column_order: Optional[List[str]] = None,
        not_null: Optional[Iterable[str]] = None,
        defaults: Optional[Dict[str, Any]] = None,
        batch_size: int = 100,
        hash_id: Optional[str] = None,
        hash_id_columns: Optional[Iterable[str]] = None,
        alter: bool = False,
        ignore: bool = False,
        replace: bool = False,
        extracts: Optional[Union[Dict[str, str], List[str]]] = None,
        conversions: Optional[dict] = None,
        columns: Optional[Dict[str, Any]] = None,
    ):
        super().__init__(db, name)
        self._defaults = dict(
            pk=pk,
            foreign_keys=foreign_keys,
            column_order=column_order,
            not_null=not_null,
            defaults=defaults,
            batch_size=batch_size,
            hash_id=hash_id,
            hash_id_columns=hash_id_columns,
            alter=alter,
            ignore=ignore,
            replace=replace,
            extracts=extracts,
            conversions=conversions or {},
            columns=columns,
        )

    def __repr__(self) -> str:
        return "<Table {}{}>".format(
            self.name,
            " (does not exist yet)"
            if not self.exists()
            else " ({})".format(", ".join(c.name for c in self.columns)),
        )

    @property
    def count(self) -> int:
        "Count of the rows in this table - optionally from the table count cache, if configured."
        if self.db.use_counts_table:
            counts = self.db.cached_counts([self.name])
            if counts:
                return next(iter(counts.values()))
        return self.count_where()

    def exists(self) -> bool:
        return self.name in self.db.table_names()

    @property
    def pks(self) -> List[str]:
        "Primary key columns for this table."
        names = [column.name for column in self.columns if column.is_pk]
        if not names:
            names = ["rowid"]
        return names

    @property
    def use_rowid(self) -> bool:
        "Does this table use ``rowid`` for its primary key (no other primary keys are specified)?"
        return not any(column for column in self.columns if column.is_pk)

    def get(self, pk_values: Union[list, tuple, str, int]) -> dict:
        """
        Return row (as dictionary) for the specified primary key.

        Raises ``sqlite_utils.db.NotFoundError`` if a matching row cannot be found.

        :param pk_values: A single value, or a tuple of values for tables that have a compound primary key
        """
        if not isinstance(pk_values, (list, tuple)):
            pk_values = [pk_values]
        pks = self.pks
        last_pk = pk_values[0] if len(pks) == 1 else pk_values
        if len(pks) != len(pk_values):
            raise NotFoundError(
                "Need {} primary key value{}".format(
                    len(pks), "" if len(pks) == 1 else "s"
                )
            )

        wheres = ["[{}] = ?".format(pk_name) for pk_name in pks]
        rows = self.rows_where(" and ".join(wheres), pk_values)
        try:
            row = list(rows)[0]
            self.last_pk = last_pk
            return row
        except IndexError:
            raise NotFoundError

    @property
    def foreign_keys(self) -> List["ForeignKey"]:
        "List of foreign keys defined on this table."
        fks = []
        for row in self.db.execute(
            "PRAGMA foreign_key_list([{}])".format(self.name)
        ).fetchall():
            if row is not None:
                id, seq, table_name, from_, to_, on_update, on_delete, match = row
                fks.append(
                    ForeignKey(
                        table=self.name,
                        column=from_,
                        other_table=table_name,
                        other_column=to_,
                    )
                )
        return fks

    @property
    def virtual_table_using(self) -> Optional[str]:
        "Type of virtual table, or ``None`` if this is not a virtual table."
        match = _virtual_table_using_re.match(self.schema)
        if match is None:
            return None
        return match.groupdict()["using"].upper()

    @property
    def indexes(self) -> List[Index]:
        "List of indexes defined on this table."
        sql = 'PRAGMA index_list("{}")'.format(self.name)
        indexes = []
        for row in self.db.execute_returning_dicts(sql):
            index_name = row["name"]
            index_name_quoted = (
                '"{}"'.format(index_name)
                if not index_name.startswith('"')
                else index_name
            )
            column_sql = "PRAGMA index_info({})".format(index_name_quoted)
            columns = []
            for seqno, cid, name in self.db.execute(column_sql).fetchall():
                columns.append(name)
            row["columns"] = columns
            # These columns may be missing on older SQLite versions:
            for key, default in {"origin": "c", "partial": 0}.items():
                if key not in row:
                    row[key] = default
            indexes.append(Index(**row))
        return indexes

    @property
    def xindexes(self) -> List[XIndex]:
        "List of indexes defined on this table using the more detailed ``XIndex`` format."
        sql = 'PRAGMA index_list("{}")'.format(self.name)
        indexes = []
        for row in self.db.execute_returning_dicts(sql):
            index_name = row["name"]
            index_name_quoted = (
                '"{}"'.format(index_name)
                if not index_name.startswith('"')
                else index_name
            )
            column_sql = "PRAGMA index_xinfo({})".format(index_name_quoted)
            index_columns = []
            for info in self.db.execute(column_sql).fetchall():
                index_columns.append(XIndexColumn(*info))
            indexes.append(XIndex(index_name, index_columns))
        return indexes

    @property
    def triggers(self) -> List[Trigger]:
        "List of triggers defined on this table."
        return [
            Trigger(*r)
            for r in self.db.execute(
                "select name, tbl_name, sql from sqlite_master where type = 'trigger'"
                " and tbl_name = ?",
                (self.name,),
            ).fetchall()
        ]

    @property
    def triggers_dict(self) -> Dict[str, str]:
        "``{trigger_name: sql}`` dictionary of triggers defined on this table."
        return {trigger.name: trigger.sql for trigger in self.triggers}

    @property
    def default_values(self) -> Dict[str, Any]:
        "``{column_name: default_value}`` dictionary of default values for columns in this table."
        return {
            column.name: _decode_default_value(column.default_value)
            for column in self.columns
            if column.default_value is not None
        }

    @property
    def strict(self) -> bool:
        "Is this a STRICT table?"
        table_suffix = self.schema.split(")")[-1].strip().upper()
        table_options = [bit.strip() for bit in table_suffix.split(",")]
        return "STRICT" in table_options

    def create(
        self,
        columns: Dict[str, Any],
        pk: Optional[Any] = None,
        foreign_keys: Optional[ForeignKeysType] = None,
        column_order: Optional[List[str]] = None,
        not_null: Optional[Iterable[str]] = None,
        defaults: Optional[Dict[str, Any]] = None,
        hash_id: Optional[str] = None,
        hash_id_columns: Optional[Iterable[str]] = None,
        extracts: Optional[Union[Dict[str, str], List[str]]] = None,
        if_not_exists: bool = False,
        transform: bool = False,
    ) -> "Table":
        """
        Create a table with the specified columns.

        See :ref:`python_api_explicit_create` for full details.

        :param columns: Dictionary mapping column names to their types, for example ``{"name": str, "age": int}``
        :param pk: String name of column to use as a primary key, or a tuple of strings for a compound primary key covering multiple columns
        :param foreign_keys: List of foreign key definitions for this table
        :param column_order: List specifying which columns should come first
        :param not_null: List of columns that should be created as ``NOT NULL``
        :param defaults: Dictionary specifying default values for columns
        :param hash_id: Name of column to be used as a primary key containing a hash of the other columns
        :param hash_id_columns: List of columns to be used when calculating the hash ID for a row
        :param extracts: List or dictionary of columns to be extracted during inserts, see :ref:`python_api_extracts`
        :param if_not_exists: Use ``CREATE TABLE IF NOT EXISTS``
        """
        columns = {name: value for (name, value) in columns.items()}
        with self.db.conn:
            self.db.create_table(
                self.name,
                columns,
                pk=pk,
                foreign_keys=foreign_keys,
                column_order=column_order,
                not_null=not_null,
                defaults=defaults,
                hash_id=hash_id,
                hash_id_columns=hash_id_columns,
                extracts=extracts,
                if_not_exists=if_not_exists,
                transform=transform,
            )
        return self

    def duplicate(self, new_name: str) -> "Table":
        """
        Create a duplicate of this table, copying across the schema and all row data.

        :param new_name: Name of the new table
        """
        if not self.exists():
            raise NoTable(f"Table {self.name} does not exist")
        with self.db.conn:
            sql = "CREATE TABLE [{new_table}] AS SELECT * FROM [{table}];".format(
                new_table=new_name,
                table=self.name,
            )
            self.db.execute(sql)
        return self.db[new_name]

    def transform(
        self,
        *,
        types: Optional[dict] = None,
        rename: Optional[dict] = None,
        drop: Optional[Iterable] = None,
        pk: Optional[Any] = DEFAULT,
        not_null: Optional[Iterable[str]] = None,
        defaults: Optional[Dict[str, Any]] = None,
        drop_foreign_keys: Optional[Iterable] = None,
        column_order: Optional[List[str]] = None,
    ) -> "Table":
        """
        Apply an advanced alter table, including operations that are not supported by
        ``ALTER TABLE`` in SQLite itself.

        See :ref:`python_api_transform` for full details.

        :param types: Columns that should have their type changed, for example ``{"weight": float}``
        :param rename: Columns to rename, for example ``{"headline": "title"}``
        :param drop: Columns to drop
        :param pk: New primary key for the table
        :param not_null: Columns to set as ``NOT NULL``
        :param defaults: Default values for columns
        :param drop_foreign_keys: Names of columns that should have their foreign key constraints removed
        :param column_order: List of strings specifying a full or partial column order
          to use when creating the table.
        """
        assert self.exists(), "Cannot transform a table that doesn't exist yet"
        sqls = self.transform_sql(
            types=types,
            rename=rename,
            drop=drop,
            pk=pk,
            not_null=not_null,
            defaults=defaults,
            drop_foreign_keys=drop_foreign_keys,
            column_order=column_order,
        )
        pragma_foreign_keys_was_on = self.db.execute("PRAGMA foreign_keys").fetchone()[
            0
        ]
        try:
            if pragma_foreign_keys_was_on:
                self.db.execute("PRAGMA foreign_keys=0;")
            with self.db.conn:
                for sql in sqls:
                    self.db.execute(sql)
                # Run the foreign_key_check before we commit
                if pragma_foreign_keys_was_on:
                    self.db.execute("PRAGMA foreign_key_check;")
        finally:
            if pragma_foreign_keys_was_on:
                self.db.execute("PRAGMA foreign_keys=1;")
        return self

    def transform_sql(
        self,
        *,
        types=None,
        rename=None,
        drop=None,
        pk=DEFAULT,
        not_null=None,
        defaults=None,
        drop_foreign_keys=None,
        column_order=None,
        tmp_suffix=None,
    ) -> List[str]:
        """
        Return a list of SQL statements that should be executed in order to apply this transformation.

        :param types: Columns that should have their type changed, for example ``{"weight": float}``
        :param rename: Columns to rename, for example ``{"headline": "title"}``
        :param drop: Columns to drop
        :param pk: New primary key for the table
        :param not_null: Columns to set as ``NOT NULL``
        :param defaults: Default values for columns
        :param drop_foreign_keys: Names of columns that should have their foreign key constraints removed
        :param column_order: List of strings specifying a full or partial column order
          to use when creating the table.
        """
        types = types or {}
        rename = rename or {}
        drop = drop or set()
        new_table_name = "{}_new_{}".format(
            self.name, tmp_suffix or os.urandom(6).hex()
        )
        current_column_pairs = list(self.columns_dict.items())
        new_column_pairs = []
        copy_from_to = {column: column for column, _ in current_column_pairs}
        for name, type_ in current_column_pairs:
            type_ = types.get(name) or type_
            if name in drop:
                del [copy_from_to[name]]
                continue
            new_name = rename.get(name) or name
            new_column_pairs.append((new_name, type_))
            copy_from_to[name] = new_name

        if pk is DEFAULT:
            pks_renamed = tuple(
                rename.get(p.name) or p.name for p in self.columns if p.is_pk
            )
            if len(pks_renamed) == 1:
                pk = pks_renamed[0]
            else:
                pk = pks_renamed

        # not_null may be a set or dict, need to convert to a set
        create_table_not_null = {
            rename.get(c.name) or c.name
            for c in self.columns
            if c.notnull
            if c.name not in drop
        }
        if isinstance(not_null, dict):
            # Remove any columns with a value of False
            for key, value in not_null.items():
                # Column may have been renamed
                key = rename.get(key) or key
                if value is False and key in create_table_not_null:
                    create_table_not_null.remove(key)
                else:
                    create_table_not_null.add(key)
        elif isinstance(not_null, set):
            create_table_not_null.update((rename.get(k) or k) for k in not_null)
        elif not not_null:
            pass
        else:
            assert False, "not_null must be a dict or a set or None, it was {}".format(
                repr(not_null)
            )
        # defaults=
        create_table_defaults = {
            (rename.get(c.name) or c.name): c.default_value
            for c in self.columns
            if c.default_value is not None and c.name not in drop
        }
        if defaults is not None:
            create_table_defaults.update(
                {rename.get(c) or c: v for c, v in defaults.items()}
            )

        # foreign_keys
        create_table_foreign_keys = []
        for table, column, other_table, other_column in self.foreign_keys:
            if (drop_foreign_keys is None) or (column not in drop_foreign_keys):
                create_table_foreign_keys.append(
                    (rename.get(column) or column, other_table, other_column)
                )

        if column_order is not None:
            column_order = [rename.get(col) or col for col in column_order]

        sqls = []
        sqls.append(
            self.db.create_table_sql(
                new_table_name,
                dict(new_column_pairs),
                pk=pk,
                not_null=create_table_not_null,
                defaults=create_table_defaults,
                foreign_keys=create_table_foreign_keys,
                column_order=column_order,
            ).strip()
        )

        # Copy across data, respecting any renamed columns
        new_cols = []
        old_cols = []
        for from_, to_ in copy_from_to.items():
            old_cols.append(from_)
            new_cols.append(to_)
        copy_sql = "INSERT INTO [{new_table}] ({new_cols})\n   SELECT {old_cols} FROM [{old_table}];".format(
            new_table=new_table_name,
            old_table=self.name,
            old_cols=", ".join("[{}]".format(col) for col in old_cols),
            new_cols=", ".join("[{}]".format(col) for col in new_cols),
        )
        sqls.append(copy_sql)
        # Drop the old table
        sqls.append("DROP TABLE [{}];".format(self.name))
        # Rename the new one
        sqls.append(
            "ALTER TABLE [{}] RENAME TO [{}];".format(new_table_name, self.name)
        )
        return sqls

    def extract(
        self,
        columns: Union[str, Iterable[str]],
        table: Optional[str] = None,
        fk_column: Optional[str] = None,
        rename: Optional[Dict[str, str]] = None,
    ) -> "Table":
        """
        Extract specified columns into a separate table.

        See :ref:`python_api_extract` for details.

        :param columns: Single column or list of columns that should be extracted
        :param table: Name of table in which the new records should be created
        :param fk_column: Name of the foreign key column to populate in the original table
        :param rename: Dictionary of columns that should be renamed when populating the new table
        """
        rename = rename or {}
        if isinstance(columns, str):
            columns = [columns]
        if not set(columns).issubset(self.columns_dict.keys()):
            raise InvalidColumns(
                "Invalid columns {} for table with columns {}".format(
                    columns, list(self.columns_dict.keys())
                )
            )
        table = table or "_".join(columns)
        lookup_table = self.db[table]
        fk_column = fk_column or "{}_id".format(table)
        magic_lookup_column = "{}_{}".format(fk_column, os.urandom(6).hex())

        # Populate the lookup table with all of the extracted unique values
        lookup_columns_definition = {
            (rename.get(col) or col): typ
            for col, typ in self.columns_dict.items()
            if col in columns
        }
        if lookup_table.exists():
            if not set(lookup_columns_definition.items()).issubset(
                lookup_table.columns_dict.items()
            ):
                raise InvalidColumns(
                    "Lookup table {} already exists but does not have columns {}".format(
                        table, lookup_columns_definition
                    )
                )
        else:
            lookup_table.create(
                {
                    **{
                        "id": int,
                    },
                    **lookup_columns_definition,
                },
                pk="id",
            )
        lookup_columns = [(rename.get(col) or col) for col in columns]
        lookup_table.create_index(lookup_columns, unique=True, if_not_exists=True)
        self.db.execute(
            "INSERT OR IGNORE INTO [{lookup_table}] ({lookup_columns}) SELECT DISTINCT {table_cols} FROM [{table}]".format(
                lookup_table=table,
                lookup_columns=", ".join("[{}]".format(c) for c in lookup_columns),
                table_cols=", ".join("[{}]".format(c) for c in columns),
                table=self.name,
            )
        )

        # Now add the new fk_column
        self.add_column(magic_lookup_column, int)

        # And populate it
        self.db.execute(
            "UPDATE [{table}] SET [{magic_lookup_column}] = (SELECT id FROM [{lookup_table}] WHERE {where})".format(
                table=self.name,
                magic_lookup_column=magic_lookup_column,
                lookup_table=table,
                where=" AND ".join(
                    "[{table}].[{column}] IS [{lookup_table}].[{lookup_column}]".format(
                        table=self.name,
                        lookup_table=table,
                        column=column,
                        lookup_column=rename.get(column) or column,
                    )
                    for column in columns
                ),
            )
        )
        # Figure out the right column order
        column_order = []
        for c in self.columns:
            if c.name in columns and magic_lookup_column not in column_order:
                column_order.append(magic_lookup_column)
            elif c.name == magic_lookup_column:
                continue
            else:
                column_order.append(c.name)

        # Drop the unnecessary columns and rename lookup column
        self.transform(
            drop=set(columns),
            rename={magic_lookup_column: fk_column},
            column_order=column_order,
        )

        # And add the foreign key constraint
        self.add_foreign_key(fk_column, table, "id")
        return self

    def create_index(
        self,
        columns: Iterable[Union[str, DescIndex]],
        index_name: Optional[str] = None,
        unique: bool = False,
        if_not_exists: bool = False,
        find_unique_name: bool = False,
        analyze: bool = False,
    ):
        """
        Create an index on this table.

        :param columns: A single columns or list of columns to index. These can be strings or,
          to create an index using the column in descending order, ``db.DescIndex(column_name)`` objects.
        :param index_name: The name to use for the new index. Defaults to the column names joined on ``_``.
        :param unique: Should the index be marked as unique, forcing unique values?
        :param if_not_exists: Only create the index if one with that name does not already exist.
        :param find_unique_name: If ``index_name`` is not provided and the automatically derived name
          already exists, keep incrementing a suffix number to find an available name.
        :param analyze: Run ``ANALYZE`` against this index after creating it.

        See :ref:`python_api_create_index`.
        """
        if index_name is None:
            index_name = "idx_{}_{}".format(
                self.name.replace(" ", "_"), "_".join(columns)
            )
        columns_sql = []
        for column in columns:
            if isinstance(column, DescIndex):
                fmt = "[{}] desc"
            else:
                fmt = "[{}]"
            columns_sql.append(fmt.format(column))

        suffix = None
        created_index_name = None
        while True:
            created_index_name = (
                "{}_{}".format(index_name, suffix) if suffix else index_name
            )
            sql = (
                textwrap.dedent(
                    """
                CREATE {unique}INDEX {if_not_exists}[{index_name}]
                    ON [{table_name}] ({columns});
            """
                )
                .strip()
                .format(
                    index_name=created_index_name,
                    table_name=self.name,
                    columns=", ".join(columns_sql),
                    unique="UNIQUE " if unique else "",
                    if_not_exists="IF NOT EXISTS " if if_not_exists else "",
                )
            )
            try:
                self.db.execute(sql)
                break
            except OperationalError as e:
                # find_unique_name=True - try again if 'index ... already exists'
                arg = e.args[0]
                if (
                    find_unique_name
                    and arg.startswith("index ")
                    and arg.endswith(" already exists")
                ):
                    if suffix is None:
                        suffix = 2
                    else:
                        suffix += 1
                    continue
                else:
                    raise e
        if analyze:
            self.db.analyze(created_index_name)
        return self

    def add_column(
        self,
        col_name: str,
        col_type: Optional[Any] = None,
        fk: Optional[str] = None,
        fk_col: Optional[str] = None,
        not_null_default: Optional[Any] = None,
    ):
        """
        Add a column to this table. See :ref:`python_api_add_column`.

        :param col_name: Name of the new column
        :param col_type: Column type - a Python type such as ``str`` or a SQLite type string such as ``"BLOB"``
        :param fk: Name of a table that this column should be a foreign key reference to
        :param fk_col: Column in the foreign key table that this should reference
        :param not_null_default: Set this column to ``not null`` and give it this default value
        """
        fk_col_type = None
        if fk is not None:
            # fk must be a valid table
            if fk not in self.db.table_names():
                raise AlterError("table '{}' does not exist".format(fk))
            # if fk_col specified, must be a valid column
            if fk_col is not None:
                if fk_col not in self.db[fk].columns_dict:
                    raise AlterError("table '{}' has no column {}".format(fk, fk_col))
            else:
                # automatically set fk_col to first primary_key of fk table
                pks = [c for c in self.db[fk].columns if c.is_pk]
                if pks:
                    fk_col = pks[0].name
                    fk_col_type = pks[0].type
                else:
                    fk_col = "rowid"
                    fk_col_type = "INTEGER"
        if col_type is None:
            col_type = str
        not_null_sql = None
        if not_null_default is not None:
            not_null_sql = "NOT NULL DEFAULT {}".format(self.db.quote(not_null_default))
        sql = "ALTER TABLE [{table}] ADD COLUMN [{col_name}] {col_type}{not_null_default};".format(
            table=self.name,
            col_name=col_name,
            col_type=fk_col_type or COLUMN_TYPE_MAPPING[col_type],
            not_null_default=(" " + not_null_sql) if not_null_sql else "",
        )
        self.db.execute(sql)
        if fk is not None:
            self.add_foreign_key(col_name, fk, fk_col)
        return self

    def drop(self, ignore: bool = False):
        """
        Drop this table.

        :param ignore: Set to ``True`` to ignore the error if the table does not exist
        """
        try:
            self.db.execute("DROP TABLE [{}]".format(self.name))
        except sqlite3.OperationalError:
            if not ignore:
                raise

    def guess_foreign_table(self, column: str) -> str:
        """
        For a given column, suggest another table that might be referenced by this
        column should it be used as a foreign key.

        For example, a column called ``tag_id`` or ``tag`` or ``tags`` might suggest
        a ``tag`` table, if one exists.

        If no candidates can be found, raises a ``NoObviousTable`` exception.

        :param column: Name of column
        """
        column = column.lower()
        possibilities = [column]
        if column.endswith("_id"):
            column_without_id = column[:-3]
            possibilities.append(column_without_id)
            if not column_without_id.endswith("s"):
                possibilities.append(column_without_id + "s")
        elif not column.endswith("s"):
            possibilities.append(column + "s")
        existing_tables = {t.lower(): t for t in self.db.table_names()}
        for table in possibilities:
            if table in existing_tables:
                return existing_tables[table]
        # If we get here there's no obvious candidate - raise an error
        raise NoObviousTable(
            "No obvious foreign key table for column '{}' - tried {}".format(
                column, repr(possibilities)
            )
        )

    def guess_foreign_column(self, other_table: str):
        pks = [c for c in self.db[other_table].columns if c.is_pk]
        if len(pks) != 1:
            raise BadPrimaryKey(
                "Could not detect single primary key for table '{}'".format(other_table)
            )
        else:
            return pks[0].name

    def add_foreign_key(
        self,
        column: str,
        other_table: Optional[str] = None,
        other_column: Optional[str] = None,
        ignore: bool = False,
    ):
        """
        Alter the schema to mark the specified column as a foreign key to another table.

        :param column: The column to mark as a foreign key.
        :param other_table: The table it refers to - if omitted, will be guessed based on the column name.
        :param other_column: The column on the other table it - if omitted, will be guessed.
        :param ignore: Set this to ``True`` to ignore an existing foreign key - otherwise a ``AlterError`` will be raised.
        """
        # Ensure column exists
        if column not in self.columns_dict:
            raise AlterError("No such column: {}".format(column))
        # If other_table is not specified, attempt to guess it from the column
        if other_table is None:
            other_table = self.guess_foreign_table(column)
        # If other_column is not specified, detect the primary key on other_table
        if other_column is None:
            other_column = self.guess_foreign_column(other_table)

        # Soundness check that the other column exists
        if (
            not [c for c in self.db[other_table].columns if c.name == other_column]
            and other_column != "rowid"
        ):
            raise AlterError("No such column: {}.{}".format(other_table, other_column))
        # Check we do not already have an existing foreign key
        if any(
            fk
            for fk in self.foreign_keys
            if fk.column == column
            and fk.other_table == other_table
            and fk.other_column == other_column
        ):
            if ignore:
                return self
            else:
                raise AlterError(
                    "Foreign key already exists for {} => {}.{}".format(
                        column, other_table, other_column
                    )
                )
        self.db.add_foreign_keys([(self.name, column, other_table, other_column)])
        return self

    def enable_counts(self):
        """
        Set up triggers to update a cache of the count of rows in this table.

        See :ref:`python_api_cached_table_counts` for details.
        """
        sql = (
            textwrap.dedent(
                """
        {create_counts_table}
        CREATE TRIGGER IF NOT EXISTS [{table}{counts_table}_insert] AFTER INSERT ON [{table}]
        BEGIN
            INSERT OR REPLACE INTO [{counts_table}]
            VALUES (
                {table_quoted},
                COALESCE(
                    (SELECT count FROM [{counts_table}] WHERE [table] = {table_quoted}),
                0
                ) + 1
            );
        END;
        CREATE TRIGGER IF NOT EXISTS [{table}{counts_table}_delete] AFTER DELETE ON [{table}]
        BEGIN
            INSERT OR REPLACE INTO [{counts_table}]
            VALUES (
                {table_quoted},
                COALESCE(
                    (SELECT count FROM [{counts_table}] WHERE [table] = {table_quoted}),
                0
                ) - 1
            );
        END;
        INSERT OR REPLACE INTO _counts VALUES ({table_quoted}, (select count(*) from [{table}]));
        """
            )
            .strip()
            .format(
                create_counts_table=_COUNTS_TABLE_CREATE_SQL.format(
                    self.db._counts_table_name
                ),
                counts_table=self.db._counts_table_name,
                table=self.name,
                table_quoted=self.db.quote(self.name),
            )
        )
        with self.db.conn:
            self.db.conn.executescript(sql)
        self.db.use_counts_table = True

    @property
    def has_counts_triggers(self) -> bool:
        "Does this table have triggers setup to update cached counts?"
        trigger_names = {
            "{table}{counts_table}_{suffix}".format(
                counts_table=self.db._counts_table_name, table=self.name, suffix=suffix
            )
            for suffix in ["insert", "delete"]
        }
        return trigger_names.issubset(self.triggers_dict.keys())

    def enable_fts(
        self,
        columns: Iterable[str],
        fts_version: str = "FTS5",
        create_triggers: bool = False,
        tokenize: Optional[str] = None,
        replace: bool = False,
    ):
        """
        Enable SQLite full-text search against the specified columns.

        See :ref:`python_api_fts` for more details.

        :param columns: List of column names to include in the search index.
        :param fts_version: FTS version to use - defaults to ``FTS5`` but you may want ``FTS4`` for older SQLite versions.
        :param create_triggers: Should triggers be created to keep the search index up-to-date? Defaults to ``False``.
        :param tokenize: Custom SQLite tokenizer to use, for example ``"porter"`` to enable Porter stemming.
        :param replace: Should any existing FTS index for this table be replaced by the new one?
        """
        create_fts_sql = (
            textwrap.dedent(
                """
            CREATE VIRTUAL TABLE [{table}_fts] USING {fts_version} (
                {columns},{tokenize}
                content=[{table}]
            )
        """
            )
            .strip()
            .format(
                table=self.name,
                columns=", ".join("[{}]".format(c) for c in columns),
                fts_version=fts_version,
                tokenize="\n    tokenize='{}',".format(tokenize) if tokenize else "",
            )
        )
        should_recreate = False
        if replace and self.db["{}_fts".format(self.name)].exists():
            # Does the table need to be recreated?
            fts_schema = self.db["{}_fts".format(self.name)].schema
            if fts_schema != create_fts_sql:
                should_recreate = True
            expected_triggers = {self.name + suffix for suffix in ("_ai", "_ad", "_au")}
            existing_triggers = {t.name for t in self.triggers}
            has_triggers = existing_triggers.issuperset(expected_triggers)
            if has_triggers != create_triggers:
                should_recreate = True
            if not should_recreate:
                # Table with correct configuration already exists
                return self

        if should_recreate:
            self.disable_fts()

        self.db.executescript(create_fts_sql)
        self.populate_fts(columns)

        if create_triggers:
            old_cols = ", ".join("old.[{}]".format(c) for c in columns)
            new_cols = ", ".join("new.[{}]".format(c) for c in columns)
            triggers = (
                textwrap.dedent(
                    """
                CREATE TRIGGER [{table}_ai] AFTER INSERT ON [{table}] BEGIN
                  INSERT INTO [{table}_fts] (rowid, {columns}) VALUES (new.rowid, {new_cols});
                END;
                CREATE TRIGGER [{table}_ad] AFTER DELETE ON [{table}] BEGIN
                  INSERT INTO [{table}_fts] ([{table}_fts], rowid, {columns}) VALUES('delete', old.rowid, {old_cols});
                END;
                CREATE TRIGGER [{table}_au] AFTER UPDATE ON [{table}] BEGIN
                  INSERT INTO [{table}_fts] ([{table}_fts], rowid, {columns}) VALUES('delete', old.rowid, {old_cols});
                  INSERT INTO [{table}_fts] (rowid, {columns}) VALUES (new.rowid, {new_cols});
                END;
            """
                )
                .strip()
                .format(
                    table=self.name,
                    columns=", ".join("[{}]".format(c) for c in columns),
                    old_cols=old_cols,
                    new_cols=new_cols,
                )
            )
            self.db.executescript(triggers)
        return self

    def populate_fts(self, columns: Iterable[str]) -> "Table":
        """
        Update the associated SQLite full-text search index with the latest data from the
        table for the specified columns.

        :param columns: Columns to populate the data for
        """
        sql = (
            textwrap.dedent(
                """
            INSERT INTO [{table}_fts] (rowid, {columns})
                SELECT rowid, {columns} FROM [{table}];
        """
            )
            .strip()
            .format(
                table=self.name, columns=", ".join("[{}]".format(c) for c in columns)
            )
        )
        self.db.executescript(sql)
        return self

    def disable_fts(self) -> "Table":
        "Remove any full-text search index and related triggers configured for this table."
        fts_table = self.detect_fts()
        if fts_table:
            self.db[fts_table].drop()
        # Now delete the triggers that related to that table
        sql = (
            textwrap.dedent(
                """
            SELECT name FROM sqlite_master
                WHERE type = 'trigger'
                AND sql LIKE '% INSERT INTO [{}]%'
        """
            )
            .strip()
            .format(fts_table)
        )
        trigger_names = []
        for row in self.db.execute(sql).fetchall():
            trigger_names.append(row[0])
        with self.db.conn:
            for trigger_name in trigger_names:
                self.db.execute("DROP TRIGGER IF EXISTS [{}]".format(trigger_name))
        return self

    def rebuild_fts(self):
        "Run the ``rebuild`` operation against the associated full-text search index table."
        fts_table = self.detect_fts()
        if fts_table is None:
            # Assume this is itself an FTS table
            fts_table = self.name
        self.db.execute(
            "INSERT INTO [{table}]([{table}]) VALUES('rebuild');".format(
                table=fts_table
            )
        )
        return self

    def detect_fts(self) -> Optional[str]:
        "Detect if table has a corresponding FTS virtual table and return it"
        sql = textwrap.dedent(
            """
            SELECT name FROM sqlite_master
                WHERE rootpage = 0
                AND (
                    sql LIKE :like
                    OR sql LIKE :like2
                    OR (
                        tbl_name = :table
                        AND sql LIKE '%VIRTUAL TABLE%USING FTS%'
                    )
                )
        """
        ).strip()
        args = {
            "like": "%VIRTUAL TABLE%USING FTS%content=[{}]%".format(self.name),
            "like2": '%VIRTUAL TABLE%USING FTS%content="{}"%'.format(self.name),
            "table": self.name,
        }
        rows = self.db.execute(sql, args).fetchall()
        if len(rows) == 0:
            return None
        else:
            return rows[0][0]

    def optimize(self) -> "Table":
        "Run the ``optimize`` operation against the associated full-text search index table."
        fts_table = self.detect_fts()
        if fts_table is not None:
            self.db.execute(
                """
                INSERT INTO [{table}] ([{table}]) VALUES ("optimize");
            """.strip().format(
                    table=fts_table
                )
            )
        return self

    def search_sql(
        self,
        columns: Optional[Iterable[str]] = None,
        order_by: Optional[str] = None,
        limit: Optional[int] = None,
        offset: Optional[int] = None,
        where: Optional[str] = None,
        include_rank: bool = False,
    ) -> str:
        """ "
        Return SQL string that can be used to execute searches against this table.

        :param columns: Columns to search against
        :param order_by: Column or SQL expression to sort by
        :param limit: SQL limit
        :param offset: SQL offset
        :param where: Extra SQL fragment for the WHERE clause
        :param include_rank: Select the search rank column in the final query
        """
        # Pick names for table and rank column that don't clash
        original = "original_" if self.name == "original" else "original"
        columns_sql = "*"
        columns_with_prefix_sql = "[{}].*".format(original)
        if columns:
            columns_sql = ",\n        ".join("[{}]".format(c) for c in columns)
            columns_with_prefix_sql = ",\n    ".join(
                "[{}].[{}]".format(original, c) for c in columns
            )
        fts_table = self.detect_fts()
        assert fts_table, "Full-text search is not configured for table '{}'".format(
            self.name
        )
        virtual_table_using = self.db[fts_table].virtual_table_using
        sql = textwrap.dedent(
            """
        with {original} as (
            select
                rowid,
                {columns}
            from [{dbtable}]{where_clause}
        )
        select
            {columns_with_prefix}
        from
            [{original}]
            join [{fts_table}] on [{original}].rowid = [{fts_table}].rowid
        where
            [{fts_table}] match :query
        order by
            {order_by}
        {limit_offset}
        """
        ).strip()
        if virtual_table_using == "FTS5":
            rank_implementation = "[{}].rank".format(fts_table)
        else:
            self.db.register_fts4_bm25()
            rank_implementation = "rank_bm25(matchinfo([{}], 'pcnalx'))".format(
                fts_table
            )
        if include_rank:
            columns_with_prefix_sql += ",\n    " + rank_implementation + " rank"
        limit_offset = ""
        if limit is not None:
            limit_offset += " limit {}".format(limit)
        if offset is not None:
            limit_offset += " offset {}".format(offset)
        return sql.format(
            dbtable=self.name,
            where_clause="\n    where {}".format(where) if where else "",
            original=original,
            columns=columns_sql,
            columns_with_prefix=columns_with_prefix_sql,
            fts_table=fts_table,
            order_by=order_by or rank_implementation,
            limit_offset=limit_offset.strip(),
        ).strip()

    def search(
        self,
        q: str,
        order_by: Optional[str] = None,
        columns: Optional[Iterable[str]] = None,
        limit: Optional[int] = None,
        offset: Optional[int] = None,
        where: Optional[str] = None,
        where_args: Optional[Union[Iterable, dict]] = None,
        quote: bool = False,
    ) -> Generator[dict, None, None]:
        """
        Execute a search against this table using SQLite full-text search, returning a sequence of
        dictionaries for each row.

        :param q: Terms to search for
        :param order_by: Defaults to order by rank, or specify a column here.
        :param columns: List of columns to return, defaults to all columns.
        :param limit: Optional integer limit for returned rows.
        :param offset: Optional integer SQL offset.
        :param where: Extra SQL fragment for the WHERE clause
        :param where_args: Arguments to use for :param placeholders in the extra WHERE clause
        :param quote: Apply quoting to disable any special characters in the search query

        See :ref:`python_api_fts_search`.
        """
        args = {"query": self.db.quote_fts(q) if quote else q}
        if where_args and "query" in where_args:
            raise ValueError(
                "'query' is a reserved key and cannot be passed to where_args for .search()"
            )
        if where_args:
            args.update(where_args)

        cursor = self.db.execute(
            self.search_sql(
                order_by=order_by,
                columns=columns,
                limit=limit,
                offset=offset,
                where=where,
            ),
            args,
        )
        columns = [c[0] for c in cursor.description]
        for row in cursor:
            yield dict(zip(columns, row))

    def value_or_default(self, key, value):
        return self._defaults[key] if value is DEFAULT else value

    def delete(self, pk_values: Union[list, tuple, str, int, float]) -> "Table":
        """
        Delete row matching the specified primary key.

        :param pk_values: A single value, or a tuple of values for tables that have a compound primary key
        """
        if not isinstance(pk_values, (list, tuple)):
            pk_values = [pk_values]
        self.get(pk_values)
        wheres = ["[{}] = ?".format(pk_name) for pk_name in self.pks]
        sql = "delete from [{table}] where {wheres}".format(
            table=self.name, wheres=" and ".join(wheres)
        )
        with self.db.conn:
            self.db.execute(sql, pk_values)
        return self

    def delete_where(
        self,
        where: Optional[str] = None,
        where_args: Optional[Union[Iterable, dict]] = None,
        analyze: bool = False,
    ) -> "Table":
        """
        Delete rows matching the specified where clause, or delete all rows in the table.

        See :ref:`python_api_delete_where`.

        :param where: SQL where fragment to use, for example ``id > ?``
        :param where_args: Parameters to use with that fragment - an iterable for ``id > ?``
          parameters, or a dictionary for ``id > :id``
        :param analyze: Set to ``True`` to run ``ANALYZE`` after the rows have been deleted.
        """
        if not self.exists():
            return self
        sql = "delete from [{}]".format(self.name)
        if where is not None:
            sql += " where " + where
        self.db.execute(sql, where_args or [])
        if analyze:
            self.analyze()
        return self

    def update(
        self,
        pk_values: Union[list, tuple, str, int, float],
        updates: Optional[dict] = None,
        alter: bool = False,
        conversions: Optional[dict] = None,
    ) -> "Table":
        """
        Execute a SQL ``UPDATE`` against the specified row.

        See :ref:`python_api_update`.

        :param pk_values: The primary key of an individual record - can be a tuple if the
          table has a compound primary key.
        :param updates: A dictionary mapping columns to their updated values.
        :param alter: Set to ``True`` to add any missing columns.
        :param conversions: Optional dictionary of SQL functions to apply during the update, for example
          ``{"mycolumn": "upper(?)"}``.
        """
        updates = updates or {}
        conversions = conversions or {}
        if not isinstance(pk_values, (list, tuple)):
            pk_values = [pk_values]
        # Soundness check that the record exists (raises error if not):
        self.get(pk_values)
        if not updates:
            return self
        args = []
        sets = []
        wheres = []
        pks = self.pks
        validate_column_names(updates.keys())
        for key, value in updates.items():
            sets.append("[{}] = {}".format(key, conversions.get(key, "?")))
            args.append(jsonify_if_needed(value))
        wheres = ["[{}] = ?".format(pk_name) for pk_name in pks]
        args.extend(pk_values)
        sql = "update [{table}] set {sets} where {wheres}".format(
            table=self.name, sets=", ".join(sets), wheres=" and ".join(wheres)
        )
        with self.db.conn:
            try:
                rowcount = self.db.execute(sql, args).rowcount
            except OperationalError as e:
                if alter and (" column" in e.args[0]):
                    # Attempt to add any missing columns, then try again
                    self.add_missing_columns([updates])
                    rowcount = self.db.execute(sql, args).rowcount
                else:
                    raise

            # TODO: Test this works (rolls back) - use better exception:
            assert rowcount == 1
        self.last_pk = pk_values[0] if len(pks) == 1 else pk_values
        return self

    def convert(
        self,
        columns: Union[str, List[str]],
        fn: Callable,
        output: Optional[str] = None,
        output_type: Optional[Any] = None,
        drop: bool = False,
        multi: bool = False,
        where: Optional[str] = None,
        where_args: Optional[Union[Iterable, dict]] = None,
        show_progress: bool = False,
    ):
        """
        Apply conversion function ``fn`` to every value in the specified columns.

        :param columns: A single column or list of string column names to convert.
        :param fn: A callable that takes a single argument, ``value``, and returns it converted.
        :param output: Optional string column name to write the results to (defaults to the input column).
        :param output_type: If the output column needs to be created, this is the type that will be used
          for the new column.
        :param drop: Should the original column be dropped once the conversion is complete?
        :param multi: If ``True`` the return value of ``fn(value)`` will be expected to be a
          dictionary, and new columns will be created for each key of that dictionary.
        :param where: SQL fragment to use as a ``WHERE`` clause to limit the rows to which the conversion
          is applied, for example ``age > ?`` or ``age > :age``.
        :param where_args: List of arguments (if using ``?``) or a dictionary (if using ``:age``).
        :param show_progress: Should a progress bar be displayed?

        See :ref:`python_api_convert`.
        """
        if isinstance(columns, str):
            columns = [columns]

        if multi:
            return self._convert_multi(
                columns[0],
                fn,
                drop=drop,
                where=where,
                where_args=where_args,
                show_progress=show_progress,
            )

        if output is not None:
            assert len(columns) == 1, "output= can only be used with a single column"
            if output not in self.columns_dict:
                self.add_column(output, output_type or "text")

        todo_count = self.count_where(where, where_args) * len(columns)
        with progressbar(length=todo_count, silent=not show_progress) as bar:

            def convert_value(v):
                bar.update(1)
                if not v:
                    return v
                return jsonify_if_needed(fn(v))

            self.db.register_function(convert_value)
            sql = "update [{table}] set {sets}{where};".format(
                table=self.name,
                sets=", ".join(
                    [
                        "[{output_column}] = convert_value([{column}])".format(
                            output_column=output or column, column=column
                        )
                        for column in columns
                    ]
                ),
                where=" where {}".format(where) if where is not None else "",
            )
            with self.db.conn:
                self.db.execute(sql, where_args or [])
                if drop:
                    self.transform(drop=columns)
        return self

    def _convert_multi(
        self, column, fn, drop, show_progress, where=None, where_args=None
    ):
        # First we execute the function
        pk_to_values = {}
        new_column_types = {}
        pks = [column.name for column in self.columns if column.is_pk]
        if not pks:
            pks = ["rowid"]

        with progressbar(
            length=self.count, silent=not show_progress, label="1: Evaluating"
        ) as bar:
            for row in self.rows_where(
                select=", ".join(
                    "[{}]".format(column_name) for column_name in (pks + [column])
                ),
                where=where,
                where_args=where_args,
            ):
                row_pk = tuple(row[pk] for pk in pks)
                if len(row_pk) == 1:
                    row_pk = row_pk[0]
                values = fn(row[column])
                if values is not None and not isinstance(values, dict):
                    raise BadMultiValues(values)
                if values:
                    for key, value in values.items():
                        new_column_types.setdefault(key, set()).add(type(value))
                    pk_to_values[row_pk] = values
                bar.update(1)

        # Add any new columns
        columns_to_create = types_for_column_types(new_column_types)
        for column_name, column_type in columns_to_create.items():
            if column_name not in self.columns_dict:
                self.add_column(column_name, column_type)

        # Run the updates
        with progressbar(
            length=self.count, silent=not show_progress, label="2: Updating"
        ) as bar:
            with self.db.conn:
                for pk, updates in pk_to_values.items():
                    self.update(pk, updates)
                    bar.update(1)
                if drop:
                    self.transform(drop=(column,))

    def build_insert_queries_and_params(
        self,
        extracts,
        chunk,
        all_columns,
        hash_id,
        hash_id_columns,
        upsert,
        pk,
        conversions,
        num_records_processed,
        replace,
        ignore,
    ):
        # values is the list of insert data that is passed to the
        # .execute() method - but some of them may be replaced by
        # new primary keys if we are extracting any columns.
        values = []
        if hash_id_columns and hash_id is None:
            hash_id = "id"
        extracts = resolve_extracts(extracts)
        for record in chunk:
            record_values = []
            for key in all_columns:
                value = jsonify_if_needed(
                    record.get(
                        key,
                        None
                        if key != hash_id
                        else hash_record(record, hash_id_columns),
                    )
                )
                if key in extracts:
                    extract_table = extracts[key]
                    value = self.db[extract_table].lookup({"value": value})
                record_values.append(value)
            values.append(record_values)

        queries_and_params = []
        if upsert:
            if isinstance(pk, str):
                pks = [pk]
            else:
                pks = pk
            self.last_pk = None
            for record_values in values:
                # TODO: make more efficient:
                record = dict(zip(all_columns, record_values))
                sql = "INSERT OR IGNORE INTO [{table}]({pks}) VALUES({pk_placeholders});".format(
                    table=self.name,
                    pks=", ".join(["[{}]".format(p) for p in pks]),
                    pk_placeholders=", ".join(["?" for p in pks]),
                )
                queries_and_params.append((sql, [record[col] for col in pks]))
                # UPDATE [book] SET [name] = 'Programming' WHERE [id] = 1001;
                set_cols = [col for col in all_columns if col not in pks]
                if set_cols:
                    sql2 = "UPDATE [{table}] SET {pairs} WHERE {wheres}".format(
                        table=self.name,
                        pairs=", ".join(
                            "[{}] = {}".format(col, conversions.get(col, "?"))
                            for col in set_cols
                        ),
                        wheres=" AND ".join("[{}] = ?".format(pk) for pk in pks),
                    )
                    queries_and_params.append(
                        (
                            sql2,
                            [record[col] for col in set_cols]
                            + [record[pk] for pk in pks],
                        )
                    )
                # We can populate .last_pk right here
                if num_records_processed == 1:
                    self.last_pk = tuple(record[pk] for pk in pks)
                    if len(self.last_pk) == 1:
                        self.last_pk = self.last_pk[0]

        else:
            or_what = ""
            if replace:
                or_what = "OR REPLACE "
            elif ignore:
                or_what = "OR IGNORE "
            sql = """
                INSERT {or_what}INTO [{table}] ({columns}) VALUES {rows};
            """.strip().format(
                or_what=or_what,
                table=self.name,
                columns=", ".join("[{}]".format(c) for c in all_columns),
                rows=", ".join(
                    "({placeholders})".format(
                        placeholders=", ".join(
                            [conversions.get(col, "?") for col in all_columns]
                        )
                    )
                    for record in chunk
                ),
            )
            flat_values = list(itertools.chain(*values))
            queries_and_params = [(sql, flat_values)]

        return queries_and_params

    def insert_chunk(
        self,
        alter,
        extracts,
        chunk,
        all_columns,
        hash_id,
        hash_id_columns,
        upsert,
        pk,
        conversions,
        num_records_processed,
        replace,
        ignore,
    ):
        queries_and_params = self.build_insert_queries_and_params(
            extracts,
            chunk,
            all_columns,
            hash_id,
            hash_id_columns,
            upsert,
            pk,
            conversions,
            num_records_processed,
            replace,
            ignore,
        )

        with self.db.conn:
            result = None
            for query, params in queries_and_params:
                try:
                    result = self.db.execute(query, params)
                except OperationalError as e:
                    if alter and (" column" in e.args[0]):
                        # Attempt to add any missing columns, then try again
                        self.add_missing_columns(chunk)
                        result = self.db.execute(query, params)
                    elif e.args[0] == "too many SQL variables":
                        first_half = chunk[: len(chunk) // 2]
                        second_half = chunk[len(chunk) // 2 :]

                        self.insert_chunk(
                            alter,
                            extracts,
                            first_half,
                            all_columns,
                            hash_id,
                            hash_id_columns,
                            upsert,
                            pk,
                            conversions,
                            num_records_processed,
                            replace,
                            ignore,
                        )

                        self.insert_chunk(
                            alter,
                            extracts,
                            second_half,
                            all_columns,
                            hash_id,
                            hash_id_columns,
                            upsert,
                            pk,
                            conversions,
                            num_records_processed,
                            replace,
                            ignore,
                        )

                    else:
                        raise
            if num_records_processed == 1 and not upsert:
                self.last_rowid = result.lastrowid
                self.last_pk = self.last_rowid
                # self.last_rowid will be 0 if a "INSERT OR IGNORE" happened
                if (hash_id or pk) and self.last_rowid:
                    row = list(self.rows_where("rowid = ?", [self.last_rowid]))[0]
                    if hash_id:
                        self.last_pk = row[hash_id]
                    elif isinstance(pk, str):
                        self.last_pk = row[pk]
                    else:
                        self.last_pk = tuple(row[p] for p in pk)

        return

    def insert(
        self,
        record: Dict[str, Any],
        pk=DEFAULT,
        foreign_keys=DEFAULT,
        column_order: Optional[Union[List[str], Default]] = DEFAULT,
        not_null: Optional[Union[Iterable[str], Default]] = DEFAULT,
        defaults: Optional[Union[Dict[str, Any], Default]] = DEFAULT,
        hash_id: Optional[Union[str, Default]] = DEFAULT,
        hash_id_columns: Optional[Union[Iterable[str], Default]] = DEFAULT,
        alter: Optional[Union[bool, Default]] = DEFAULT,
        ignore: Optional[Union[bool, Default]] = DEFAULT,
        replace: Optional[Union[bool, Default]] = DEFAULT,
        extracts: Optional[Union[Dict[str, str], List[str], Default]] = DEFAULT,
        conversions: Optional[Union[Dict[str, str], Default]] = DEFAULT,
        columns: Optional[Union[Dict[str, Any], Default]] = DEFAULT,
    ) -> "Table":
        """
        Insert a single record into the table. The table will be created with a schema that matches
        the inserted record if it does not already exist, see :ref:`python_api_creating_tables`.

        - ``record`` - required: a dictionary representing the record to be inserted.

        The other parameters are optional, and mostly influence how the new table will be created if
        that table does not exist yet.

        Each of them defaults to ``DEFAULT``, which indicates that the default setting for the current
        ``Table`` object (specified in the table constructor) should be used.

        :param record: Dictionary record to be inserted
        :param pk: If creating the table, which column should be the primary key.
        :param foreign_keys: See :ref:`python_api_foreign_keys`.
        :param column_order: List of strings specifying a full or partial column order
          to use when creating the table.
        :param not_null: Set of strings specifying columns that should be ``NOT NULL``.
        :param defaults: Dictionary specifying default values for specific columns.
        :param hash_id: Name of a column to create and use as a primary key, where the
          value of thet primary key will be derived as a SHA1 hash of the other column values
          in the record. ``hash_id="id"`` is a common column name used for this.
        :param alter: Boolean, should any missing columns be added automatically?
        :param ignore: Boolean, if a record already exists with this primary key, ignore this insert.
        :param replace: Boolean, if a record already exists with this primary key, replace it with this new record.
        :param extracts: A list of columns to extract to other tables, or a dictionary that maps
          ``{column_name: other_table_name}``. See :ref:`python_api_extracts`.
        :param conversions: Dictionary specifying SQL conversion functions to be applied to the data while it
          is being inserted, for example ``{"name": "upper(?)"}``. See :ref:`python_api_conversions`.
        :param columns: Dictionary over-riding the detected types used for the columns, for example
          ``{"age": int, "weight": float}``.
        """
        return self.insert_all(
            [record],
            pk=pk,
            foreign_keys=foreign_keys,
            column_order=column_order,
            not_null=not_null,
            defaults=defaults,
            hash_id=hash_id,
            hash_id_columns=hash_id_columns,
            alter=alter,
            ignore=ignore,
            replace=replace,
            extracts=extracts,
            conversions=conversions,
            columns=columns,
        )

    def insert_all(
        self,
        records,
        pk=DEFAULT,
        foreign_keys=DEFAULT,
        column_order=DEFAULT,
        not_null=DEFAULT,
        defaults=DEFAULT,
        batch_size=DEFAULT,
        hash_id=DEFAULT,
        hash_id_columns=DEFAULT,
        alter=DEFAULT,
        ignore=DEFAULT,
        replace=DEFAULT,
        truncate=False,
        extracts=DEFAULT,
        conversions=DEFAULT,
        columns=DEFAULT,
        upsert=False,
        analyze=False,
    ) -> "Table":
        """
        Like ``.insert()`` but takes a list of records and ensures that the table
        that it creates (if table does not exist) has columns for ALL of that data.

        Use ``analyze=True`` to run ``ANALYZE`` after the insert has completed.
        """
        pk = self.value_or_default("pk", pk)
        foreign_keys = self.value_or_default("foreign_keys", foreign_keys)
        column_order = self.value_or_default("column_order", column_order)
        not_null = self.value_or_default("not_null", not_null)
        defaults = self.value_or_default("defaults", defaults)
        batch_size = self.value_or_default("batch_size", batch_size)
        hash_id = self.value_or_default("hash_id", hash_id)
        hash_id_columns = self.value_or_default("hash_id_columns", hash_id_columns)
        alter = self.value_or_default("alter", alter)
        ignore = self.value_or_default("ignore", ignore)
        replace = self.value_or_default("replace", replace)
        extracts = self.value_or_default("extracts", extracts)
        conversions = self.value_or_default("conversions", conversions) or {}
        columns = self.value_or_default("columns", columns)

        if hash_id_columns and hash_id is None:
            hash_id = "id"

        if upsert and (not pk and not hash_id):
            raise PrimaryKeyRequired("upsert() requires a pk")
        assert not (hash_id and pk), "Use either pk= or hash_id="
        if hash_id_columns and (hash_id is None):
            hash_id = "id"
        if hash_id:
            pk = hash_id

        assert not (
            ignore and replace
        ), "Use either ignore=True or replace=True, not both"
        all_columns = []
        first = True
        num_records_processed = 0
        # Fix up any records with square braces in the column names
        records = fix_square_braces(records)
        # We can only handle a max of 999 variables in a SQL insert, so
        # we need to adjust the batch_size down if we have too many cols
        records = iter(records)
        # Peek at first record to count its columns:
        try:
            first_record = next(records)
        except StopIteration:
            return self  # It was an empty list
        num_columns = len(first_record.keys())
        assert (
            num_columns <= SQLITE_MAX_VARS
        ), "Rows can have a maximum of {} columns".format(SQLITE_MAX_VARS)
        batch_size = max(1, min(batch_size, SQLITE_MAX_VARS // num_columns))
        self.last_rowid = None
        self.last_pk = None
        if truncate and self.exists():
            self.db.execute("DELETE FROM [{}];".format(self.name))
        for chunk in chunks(itertools.chain([first_record], records), batch_size):
            chunk = list(chunk)
            num_records_processed += len(chunk)
            if first:
                if not self.exists():
                    # Use the first batch to derive the table names
                    column_types = suggest_column_types(chunk)
                    column_types.update(columns or {})
                    self.create(
                        column_types,
                        pk,
                        foreign_keys,
                        column_order=column_order,
                        not_null=not_null,
                        defaults=defaults,
                        hash_id=hash_id,
                        hash_id_columns=hash_id_columns,
                        extracts=extracts,
                    )
                all_columns_set = set()
                for record in chunk:
                    all_columns_set.update(record.keys())
                all_columns = list(sorted(all_columns_set))
                if hash_id:
                    all_columns.insert(0, hash_id)
            else:
                for record in chunk:
                    all_columns += [
                        column for column in record if column not in all_columns
                    ]

            first = False

            self.insert_chunk(
                alter,
                extracts,
                chunk,
                all_columns,
                hash_id,
                hash_id_columns,
                upsert,
                pk,
                conversions,
                num_records_processed,
                replace,
                ignore,
            )

        if analyze:
            self.analyze()

        return self

    def upsert(
        self,
        record,
        pk=DEFAULT,
        foreign_keys=DEFAULT,
        column_order=DEFAULT,
        not_null=DEFAULT,
        defaults=DEFAULT,
        hash_id=DEFAULT,
        hash_id_columns=DEFAULT,
        alter=DEFAULT,
        extracts=DEFAULT,
        conversions=DEFAULT,
        columns=DEFAULT,
    ) -> "Table":
        """
        Like ``.insert()`` but performs an ``UPSERT``, where records are inserted if they do
        not exist and updated if they DO exist, based on matching against their primary key.

        See :ref:`python_api_upsert`.
        """
        return self.upsert_all(
            [record],
            pk=pk,
            foreign_keys=foreign_keys,
            column_order=column_order,
            not_null=not_null,
            defaults=defaults,
            hash_id=hash_id,
            hash_id_columns=hash_id_columns,
            alter=alter,
            extracts=extracts,
            conversions=conversions,
            columns=columns,
        )

    def upsert_all(
        self,
        records,
        pk=DEFAULT,
        foreign_keys=DEFAULT,
        column_order=DEFAULT,
        not_null=DEFAULT,
        defaults=DEFAULT,
        batch_size=DEFAULT,
        hash_id=DEFAULT,
        hash_id_columns=DEFAULT,
        alter=DEFAULT,
        extracts=DEFAULT,
        conversions=DEFAULT,
        columns=DEFAULT,
        analyze=False,
    ) -> "Table":
        """
        Like ``.upsert()`` but can be applied to a list of records.
        """
        return self.insert_all(
            records,
            pk=pk,
            foreign_keys=foreign_keys,
            column_order=column_order,
            not_null=not_null,
            defaults=defaults,
            batch_size=batch_size,
            hash_id=hash_id,
            hash_id_columns=hash_id_columns,
            alter=alter,
            extracts=extracts,
            conversions=conversions,
            columns=columns,
            upsert=True,
            analyze=analyze,
        )

    def add_missing_columns(self, records: Iterable[Dict[str, Any]]) -> "Table":
        needed_columns = suggest_column_types(records)
        current_columns = {c.lower() for c in self.columns_dict}
        for col_name, col_type in needed_columns.items():
            if col_name.lower() not in current_columns:
                self.add_column(col_name, col_type)
        return self

    def lookup(
        self,
        lookup_values: Dict[str, Any],
        extra_values: Optional[Dict[str, Any]] = None,
        pk: Optional[str] = "id",
        foreign_keys: Optional[ForeignKeysType] = None,
        column_order: Optional[List[str]] = None,
        not_null: Optional[Iterable[str]] = None,
        defaults: Optional[Dict[str, Any]] = None,
        extracts: Optional[Union[Dict[str, str], List[str]]] = None,
        conversions: Optional[Dict[str, str]] = None,
        columns: Optional[Dict[str, Any]] = None,
    ):
        """
        Create or populate a lookup table with the specified values.

        ``db["Species"].lookup({"name": "Palm"})`` will create a table called ``Species``
        (if one does not already exist) with two columns: ``id`` and ``name``. It will
        set up a unique constraint on the ``name`` column to guarantee it will not
        contain duplicate rows.

        It will then insert a new row with the ``name`` set to ``Palm`` and return the
        new integer primary key value.

        An optional second argument can be provided with more ``name: value`` pairs to
        be included only if the record is being created for the first time. These will
        be ignored on subsequent lookup calls for records that already exist.

        All other keyword arguments are passed through to ``.insert()``.

        See :ref:`python_api_lookup_tables` for more details.

        :param lookup_values: Dictionary specifying column names and values to use for the lookup
        :param extra_values: Additional column values to be used only if creating a new record
        """
        assert isinstance(lookup_values, dict)
        if extra_values is not None:
            assert isinstance(extra_values, dict)
        combined_values = dict(lookup_values)
        if extra_values is not None:
            combined_values.update(extra_values)
        if self.exists():
            self.add_missing_columns([combined_values])
            unique_column_sets = [set(i.columns) for i in self.indexes]
            if set(lookup_values.keys()) not in unique_column_sets:
                self.create_index(lookup_values.keys(), unique=True)
            wheres = ["[{}] = ?".format(column) for column in lookup_values]
            rows = list(
                self.rows_where(
                    " and ".join(wheres), [value for _, value in lookup_values.items()]
                )
            )
            try:
                return rows[0][pk]
            except IndexError:
                return self.insert(
                    combined_values,
                    pk=pk,
                    foreign_keys=foreign_keys,
                    column_order=column_order,
                    not_null=not_null,
                    defaults=defaults,
                    extracts=extracts,
                    conversions=conversions,
                    columns=columns,
                ).last_pk
        else:
            pk = self.insert(
                combined_values,
                pk=pk,
                foreign_keys=foreign_keys,
                column_order=column_order,
                not_null=not_null,
                defaults=defaults,
                extracts=extracts,
                conversions=conversions,
                columns=columns,
            ).last_pk
            self.create_index(lookup_values.keys(), unique=True)
            return pk

    def m2m(
        self,
        other_table: Union[str, "Table"],
        record_or_iterable: Optional[
            Union[Iterable[Dict[str, Any]], Dict[str, Any]]
        ] = None,
        pk: Optional[Union[Any, Default]] = DEFAULT,
        lookup: Optional[Dict[str, Any]] = None,
        m2m_table: Optional[str] = None,
        alter: bool = False,
    ):
        """
        After inserting a record in a table, create one or more records in some other
        table and then create many-to-many records linking the original record and the
        newly created records together.

        For example::

            db["dogs"].insert({"id": 1, "name": "Cleo"}, pk="id").m2m(
                "humans", {"id": 1, "name": "Natalie"}, pk="id"
            )

        See :ref:`python_api_m2m` for details.

        :param other_table: The name of the table to insert the new records into.
        :param record_or_iterable: A single dictionary record to insert, or a list of records.
        :param pk: The primary key to use if creating ``other_table``.
        :param lookup: Same dictionary as for ``.lookup()``, to create a many-to-many lookup table.
        :param m2m_table: The string name to use for the many-to-many table, defaults to creating
          this automatically based on the names of the two tables.
        :param alter: Set to ``True`` to add any missing columns on ``other_table`` if that table
          already exists.
        """
        if isinstance(other_table, str):
            other_table = cast(Table, self.db.table(other_table, pk=pk))
        our_id = self.last_pk
        if lookup is not None:
            assert record_or_iterable is None, "Provide lookup= or record, not both"
        else:
            assert record_or_iterable is not None, "Provide lookup= or record, not both"
        tables = list(sorted([self.name, other_table.name]))
        columns = ["{}_id".format(t) for t in tables]
        if m2m_table is not None:
            m2m_table_name = m2m_table
        else:
            # Detect if there is a single, unambiguous option
            candidates = self.db.m2m_table_candidates(self.name, other_table.name)
            if len(candidates) == 1:
                m2m_table_name = candidates[0]
            elif len(candidates) > 1:
                raise NoObviousTable(
                    "No single obvious m2m table for {}, {} - use m2m_table= parameter".format(
                        self.name, other_table.name
                    )
                )
            else:
                # If not, create a new table
                m2m_table_name = m2m_table or "{}_{}".format(*tables)
        m2m_table_obj = self.db.table(m2m_table_name, pk=columns, foreign_keys=columns)
        if lookup is None:
            # if records is only one record, put the record in a list
            if isinstance(record_or_iterable, Mapping):
                records = [record_or_iterable]
            else:
                records = cast(List, record_or_iterable)
            # Ensure each record exists in other table
            for record in records:
                id = other_table.insert(
                    cast(dict, record), pk=pk, replace=True, alter=alter
                ).last_pk
                m2m_table_obj.insert(
                    {
                        "{}_id".format(other_table.name): id,
                        "{}_id".format(self.name): our_id,
                    },
                    replace=True,
                )
        else:
            id = other_table.lookup(lookup)
            m2m_table_obj.insert(
                {
                    "{}_id".format(other_table.name): id,
                    "{}_id".format(self.name): our_id,
                },
                replace=True,
            )
        return self

    def analyze(self):
        "Run ANALYZE against this table"
        self.db.analyze(self.name)

    def analyze_column(
        self, column: str, common_limit: int = 10, value_truncate=None, total_rows=None
    ) -> "ColumnDetails":
        """
        Return statistics about the specified column.

        See :ref:`python_api_analyze_column`.

        :param column: Column to analyze
        :param common_limit: Show this many column values
        :param value_truncate: Truncate display of common values to this many characters
        :param total_rows: Optimization - pass the total number of rows in the table to save running a fresh ``count(*)`` query
        """
        db = self.db
        table = self.name
        if total_rows is None:
            total_rows = db[table].count

        def truncate(value):
            if value_truncate is None or isinstance(value, (float, int)):
                return value
            value = str(value)
            if len(value) > value_truncate:
                value = value[:value_truncate] + "..."
            return value

        num_null = db.execute(
            "select count(*) from [{}] where [{}] is null".format(table, column)
        ).fetchone()[0]
        num_blank = db.execute(
            "select count(*) from [{}] where [{}] = ''".format(table, column)
        ).fetchone()[0]
        num_distinct = db.execute(
            "select count(distinct [{}]) from [{}]".format(column, table)
        ).fetchone()[0]
        most_common = None
        least_common = None
        if num_distinct == 1:
            value = db.execute(
                "select [{}] from [{}] limit 1".format(column, table)
            ).fetchone()[0]
            most_common = [(truncate(value), total_rows)]
        elif num_distinct != total_rows:
            most_common = [
                (truncate(r[0]), r[1])
                for r in db.execute(
                    "select [{}], count(*) from [{}] group by [{}] order by count(*) desc, [{}] limit {}".format(
                        column, table, column, column, common_limit
                    )
                ).fetchall()
            ]
            most_common.sort(key=lambda p: (p[1], p[0]), reverse=True)
            if num_distinct <= common_limit:
                # No need to run the query if it will just return the results in revers order
                least_common = None
            else:
                least_common = [
                    (truncate(r[0]), r[1])
                    for r in db.execute(
                        "select [{}], count(*) from [{}] group by [{}] order by count(*), [{}] desc limit {}".format(
                            column, table, column, column, common_limit
                        )
                    ).fetchall()
                ]
                least_common.sort(key=lambda p: (p[1], p[0]))
        return ColumnDetails(
            self.name,
            column,
            total_rows,
            num_null,
            num_blank,
            num_distinct,
            most_common,
            least_common,
        )

    def add_geometry_column(
        self,
        column_name: str,
        geometry_type: str,
        srid: int = 4326,
        coord_dimension: str = "XY",
        not_null: bool = False,
    ) -> bool:
        """
        In SpatiaLite, a geometry column can only be added to an existing table.
        To do so, use ``table.add_geometry_column``, passing in a geometry type.

        By default, this will add a nullable column using
        `SRID 4326 <https://spatialreference.org/ref/epsg/wgs-84/>`__. This can
        be customized using the ``column_name``, ``srid`` and ``not_null`` arguments.

        Returns ``True`` if the column was successfully added, ``False`` if not.

        .. code-block:: python

            from sqlite_utils.db import Database
            from sqlite_utils.utils import find_spatialite

            db = Database("mydb.db")
            db.init_spatialite(find_spatialite())

            # the table must exist before adding a geometry column
            table = db["locations"].create({"name": str})
            table.add_geometry_column("geometry", "POINT")

        :param column_name: Name of column to add
        :param geometry_type: Type of geometry column, for example ``"GEOMETRY"`` or ``"POINT" or ``"POLYGON"``
        :param srid: Integer SRID, defaults to 4326 for WGS84
        :param coord_dimension: Dimensions to use, defaults to ``"XY"`` - set to ``"XYZ"`` to work in three dimensions
        :param not_null: Should the column be ``NOT NULL``
        """
        cursor = self.db.execute(
            "SELECT AddGeometryColumn(?, ?, ?, ?, ?, ?);",
            [
                self.name,
                column_name,
                srid,
                geometry_type,
                coord_dimension,
                int(not_null),
            ],
        )

        result = cursor.fetchone()
        return result and bool(result[0])

    def create_spatial_index(self, column_name) -> bool:
        """
        A spatial index allows for significantly faster bounding box queries.
        To create one, use ``create_spatial_index`` with the name of an existing geometry column.

        Returns ``True`` if the index was successfully created, ``False`` if not. Calling this
        function if an index already exists is a no-op.

        .. code-block:: python

            # assuming SpatiaLite is loaded, create the table, add the column
            table = db["locations"].create({"name": str})
            table.add_geometry_column("geometry", "POINT")

            # now we can index it
            table.create_spatial_index("geometry")

            # the spatial index is a virtual table, which we can inspect
            print(db["idx_locations_geometry"].schema)
            # outputs:
            # CREATE VIRTUAL TABLE "idx_locations_geometry" USING rtree(pkid, xmin, xmax, ymin, ymax)

        :param column_name: Geometry column to create the spatial index against
        """
        if f"idx_{self.name}_{column_name}" in self.db.table_names():
            return False

        cursor = self.db.execute(
            "select CreateSpatialIndex(?, ?)", [self.name, column_name]
        )
        result = cursor.fetchone()
        return result and bool(result[0])


class View(Queryable):
    def exists(self):
        return True

    def __repr__(self) -> str:
        return "<View {} ({})>".format(
            self.name, ", ".join(c.name for c in self.columns)
        )

    def drop(self, ignore=False):
        """
        Drop this view.

        :param ignore: Set to ``True`` to ignore the error if the view does not exist
        """

        try:
            self.db.execute("DROP VIEW [{}]".format(self.name))
        except sqlite3.OperationalError:
            if not ignore:
                raise

    def enable_fts(self, *args, **kwargs):
        "``enable_fts()`` is supported on tables but not on views."
        raise NotImplementedError(
            "enable_fts() is supported on tables but not on views"
        )


def jsonify_if_needed(value):
    if isinstance(value, decimal.Decimal):
        return float(value)
    if isinstance(value, (dict, list, tuple)):
        return json.dumps(value, default=repr, ensure_ascii=False)
    elif isinstance(value, (datetime.time, datetime.date, datetime.datetime)):
        return value.isoformat()
    elif isinstance(value, uuid.UUID):
        return str(value)
    else:
        return value


def resolve_extracts(
    extracts: Optional[Union[Dict[str, str], List[str], Tuple[str]]]
) -> dict:
    if extracts is None:
        extracts = {}
    if isinstance(extracts, (list, tuple)):
        extracts = {item: item for item in extracts}
    return extracts


def validate_column_names(columns):
    # Validate no columns contain '[' or ']' - #86
    for column in columns:
        assert (
            "[" not in column and "]" not in column
        ), "'[' and ']' cannot be used in column names"


def fix_square_braces(records: Iterable[Dict[str, Any]]):
    for record in records:
        if any("[" in key or "]" in key for key in record.keys()):
            yield {
                key.replace("[", "_").replace("]", "_"): value
                for key, value in record.items()
            }
        else:
            yield record


def _decode_default_value(value):
    if value.startswith("'") and value.endswith("'"):
        # It's a string
        return value[1:-1]
    if value.isdigit():
        # It's an integer
        return int(value)
    if value.startswith("X'") and value.endswith("'"):
        # It's a binary string, stored as hex
        to_decode = value[2:-1]
        return binascii.unhexlify(to_decode)
    # If it is a string containing a floating point number:
    try:
        return float(value)
    except ValueError:
        pass
    return value