dibbler/sqlalchemy/dialects/sqlite/base.py

# sqlite/base.py
# Copyright (C) 2005-2017 the SQLAlchemy authors and contributors
# <see AUTHORS file>
#
# This module is part of SQLAlchemy and is released under
# the MIT License: http://www.opensource.org/licenses/mit-license.php

r"""
.. dialect:: sqlite
    :name: SQLite

.. _sqlite_datetime:

Date and Time Types
-------------------

SQLite does not have built-in DATE, TIME, or DATETIME types, and pysqlite does
not provide out of the box functionality for translating values between Python
`datetime` objects and a SQLite-supported format. SQLAlchemy's own
:class:`~sqlalchemy.types.DateTime` and related types provide date formatting
and parsing functionality when SQlite is used. The implementation classes are
:class:`~.sqlite.DATETIME`, :class:`~.sqlite.DATE` and :class:`~.sqlite.TIME`.
These types represent dates and times as ISO formatted strings, which also
nicely support ordering. There's no reliance on typical "libc" internals for
these functions so historical dates are fully supported.

Ensuring Text affinity
^^^^^^^^^^^^^^^^^^^^^^

The DDL rendered for these types is the standard ``DATE``, ``TIME``
and ``DATETIME`` indicators.    However, custom storage formats can also be
applied to these types.   When the
storage format is detected as containing no alpha characters, the DDL for
these types is rendered as ``DATE_CHAR``, ``TIME_CHAR``, and ``DATETIME_CHAR``,
so that the column continues to have textual affinity.

.. seealso::

    `Type Affinity <http://www.sqlite.org/datatype3.html#affinity>`_ - in the SQLite documentation

.. _sqlite_autoincrement:

SQLite Auto Incrementing Behavior
----------------------------------

Background on SQLite's autoincrement is at: http://sqlite.org/autoinc.html

Key concepts:

* SQLite has an implicit "auto increment" feature that takes place for any
  non-composite primary-key column that is specifically created using
  "INTEGER PRIMARY KEY" for the type + primary key.

* SQLite also has an explicit "AUTOINCREMENT" keyword, that is **not**
  equivalent to the implicit autoincrement feature; this keyword is not
  recommended for general use.  SQLAlchemy does not render this keyword
  unless a special SQLite-specific directive is used (see below).  However,
  it still requires that the column's type is named "INTEGER".

Using the AUTOINCREMENT Keyword
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

To specifically render the AUTOINCREMENT keyword on the primary key column
when rendering DDL, add the flag ``sqlite_autoincrement=True`` to the Table
construct::

    Table('sometable', metadata,
            Column('id', Integer, primary_key=True),
            sqlite_autoincrement=True)

Allowing autoincrement behavior SQLAlchemy types other than Integer/INTEGER
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

SQLite's typing model is based on naming conventions.  Among
other things, this means that any type name which contains the
substring ``"INT"`` will be determined to be of "integer affinity".  A
type named ``"BIGINT"``, ``"SPECIAL_INT"`` or even ``"XYZINTQPR"``, will be considered by
SQLite to be of "integer" affinity.  However, **the SQLite
autoincrement feature, whether implicitly or explicitly enabled,
requires that the name of the column's type
is exactly the string "INTEGER"**.  Therefore, if an
application uses a type like :class:`.BigInteger` for a primary key, on
SQLite this type will need to be rendered as the name ``"INTEGER"`` when
emitting the initial ``CREATE TABLE`` statement in order for the autoincrement
behavior to be available.

One approach to achieve this is to use :class:`.Integer` on SQLite
only using :meth:`.TypeEngine.with_variant`::

    table = Table(
        "my_table", metadata,
        Column("id", BigInteger().with_variant(Integer, "sqlite"), primary_key=True)
    )

Another is to use a subclass of :class:`.BigInteger` that overrides its DDL name
to be ``INTEGER`` when compiled against SQLite::

    from sqlalchemy import BigInteger
    from sqlalchemy.ext.compiler import compiles

    class SLBigInteger(BigInteger):
        pass

    @compiles(SLBigInteger, 'sqlite')
    def bi_c(element, compiler, **kw):
        return "INTEGER"

    @compiles(SLBigInteger)
    def bi_c(element, compiler, **kw):
        return compiler.visit_BIGINT(element, **kw)


    table = Table(
        "my_table", metadata,
        Column("id", SLBigInteger(), primary_key=True)
    )

.. seealso::

    :meth:`.TypeEngine.with_variant`

    :ref:`sqlalchemy.ext.compiler_toplevel`

    `Datatypes In SQLite Version 3 <http://sqlite.org/datatype3.html>`_

.. _sqlite_concurrency:

Database Locking Behavior / Concurrency
---------------------------------------

SQLite is not designed for a high level of write concurrency. The database
itself, being a file, is locked completely during write operations within
transactions, meaning exactly one "connection" (in reality a file handle)
has exclusive access to the database during this period - all other
"connections" will be blocked during this time.

The Python DBAPI specification also calls for a connection model that is
always in a transaction; there is no ``connection.begin()`` method,
only ``connection.commit()`` and ``connection.rollback()``, upon which a
new transaction is to be begun immediately.  This may seem to imply
that the SQLite driver would in theory allow only a single filehandle on a
particular database file at any time; however, there are several
factors both within SQlite itself as well as within the pysqlite driver
which loosen this restriction significantly.

However, no matter what locking modes are used, SQLite will still always
lock the database file once a transaction is started and DML (e.g. INSERT,
UPDATE, DELETE) has at least been emitted, and this will block
other transactions at least at the point that they also attempt to emit DML.
By default, the length of time on this block is very short before it times out
with an error.

This behavior becomes more critical when used in conjunction with the
SQLAlchemy ORM.  SQLAlchemy's :class:`.Session` object by default runs
within a transaction, and with its autoflush model, may emit DML preceding
any SELECT statement.   This may lead to a SQLite database that locks
more quickly than is expected.   The locking mode of SQLite and the pysqlite
driver can be manipulated to some degree, however it should be noted that
achieving a high degree of write-concurrency with SQLite is a losing battle.

For more information on SQLite's lack of write concurrency by design, please
see
`Situations Where Another RDBMS May Work Better - High Concurrency
<http://www.sqlite.org/whentouse.html>`_ near the bottom of the page.

The following subsections introduce areas that are impacted by SQLite's
file-based architecture and additionally will usually require workarounds to
work when using the pysqlite driver.

.. _sqlite_isolation_level:

Transaction Isolation Level
----------------------------

SQLite supports "transaction isolation" in a non-standard way, along two
axes.  One is that of the `PRAGMA read_uncommitted <http://www.sqlite.org/pragma.html#pragma_read_uncommitted>`_
instruction.   This setting can essentially switch SQLite between its
default mode of ``SERIALIZABLE`` isolation, and a "dirty read" isolation
mode normally referred to as ``READ UNCOMMITTED``.

SQLAlchemy ties into this PRAGMA statement using the
:paramref:`.create_engine.isolation_level` parameter of :func:`.create_engine`.
Valid values for this parameter when used with SQLite are ``"SERIALIZABLE"``
and ``"READ UNCOMMITTED"`` corresponding to a value of 0 and 1, respectively.
SQLite defaults to ``SERIALIZABLE``, however its behavior is impacted by
the pysqlite driver's default behavior.

The other axis along which SQLite's transactional locking is impacted is
via the nature of the ``BEGIN`` statement used.   The three varieties
are "deferred", "immediate", and "exclusive", as described at
`BEGIN TRANSACTION <http://sqlite.org/lang_transaction.html>`_.   A straight
``BEGIN`` statement uses the "deferred" mode, where the the database file is
not locked until the first read or write operation, and read access remains
open to other transactions until the first write operation.  But again,
it is critical to note that the pysqlite driver interferes with this behavior
by *not even emitting BEGIN* until the first write operation.

.. warning::

    SQLite's transactional scope is impacted by unresolved
    issues in the pysqlite driver, which defers BEGIN statements to a greater
    degree than is often feasible. See the section :ref:`pysqlite_serializable`
    for techniques to work around this behavior.

SAVEPOINT Support
----------------------------

SQLite supports SAVEPOINTs, which only function once a transaction is
begun.   SQLAlchemy's SAVEPOINT support is available using the
:meth:`.Connection.begin_nested` method at the Core level, and
:meth:`.Session.begin_nested` at the ORM level.   However, SAVEPOINTs
won't work at all with pysqlite unless workarounds are taken.

.. warning::

    SQLite's SAVEPOINT feature is impacted by unresolved
    issues in the pysqlite driver, which defers BEGIN statements to a greater
    degree than is often feasible. See the section :ref:`pysqlite_serializable`
    for techniques to work around this behavior.

Transactional DDL
----------------------------

The SQLite database supports transactional :term:`DDL` as well.
In this case, the pysqlite driver is not only failing to start transactions,
it also is ending any existing transction when DDL is detected, so again,
workarounds are required.

.. warning::

    SQLite's transactional DDL is impacted by unresolved issues
    in the pysqlite driver, which fails to emit BEGIN and additionally
    forces a COMMIT to cancel any transaction when DDL is encountered.
    See the section :ref:`pysqlite_serializable`
    for techniques to work around this behavior.

.. _sqlite_foreign_keys:

Foreign Key Support
-------------------

SQLite supports FOREIGN KEY syntax when emitting CREATE statements for tables,
however by default these constraints have no effect on the operation of the
table.

Constraint checking on SQLite has three prerequisites:

* At least version 3.6.19 of SQLite must be in use
* The SQLite library must be compiled *without* the SQLITE_OMIT_FOREIGN_KEY
  or SQLITE_OMIT_TRIGGER symbols enabled.
* The ``PRAGMA foreign_keys = ON`` statement must be emitted on all
  connections before use.

SQLAlchemy allows for the ``PRAGMA`` statement to be emitted automatically for
new connections through the usage of events::

    from sqlalchemy.engine import Engine
    from sqlalchemy import event

    @event.listens_for(Engine, "connect")
    def set_sqlite_pragma(dbapi_connection, connection_record):
        cursor = dbapi_connection.cursor()
        cursor.execute("PRAGMA foreign_keys=ON")
        cursor.close()

.. warning::

    When SQLite foreign keys are enabled, it is **not possible**
    to emit CREATE or DROP statements for tables that contain
    mutually-dependent foreign key constraints;
    to emit the DDL for these tables requires that ALTER TABLE be used to
    create or drop these constraints separately, for which SQLite has
    no support.

.. seealso::

    `SQLite Foreign Key Support <http://www.sqlite.org/foreignkeys.html>`_
    - on the SQLite web site.

    :ref:`event_toplevel` - SQLAlchemy event API.

    :ref:`use_alter` - more information on SQLAlchemy's facilities for handling
     mutually-dependent foreign key constraints.

.. _sqlite_type_reflection:

Type Reflection
---------------

SQLite types are unlike those of most other database backends, in that
the string name of the type usually does not correspond to a "type" in a
one-to-one fashion.  Instead, SQLite links per-column typing behavior
to one of five so-called "type affinities" based on a string matching
pattern for the type.

SQLAlchemy's reflection process, when inspecting types, uses a simple
lookup table to link the keywords returned to provided SQLAlchemy types.
This lookup table is present within the SQLite dialect as it is for all
other dialects.  However, the SQLite dialect has a different "fallback"
routine for when a particular type name is not located in the lookup map;
it instead implements the SQLite "type affinity" scheme located at
http://www.sqlite.org/datatype3.html section 2.1.

The provided typemap will make direct associations from an exact string
name match for the following types:

:class:`~.types.BIGINT`, :class:`~.types.BLOB`,
:class:`~.types.BOOLEAN`, :class:`~.types.BOOLEAN`,
:class:`~.types.CHAR`, :class:`~.types.DATE`,
:class:`~.types.DATETIME`, :class:`~.types.FLOAT`,
:class:`~.types.DECIMAL`, :class:`~.types.FLOAT`,
:class:`~.types.INTEGER`, :class:`~.types.INTEGER`,
:class:`~.types.NUMERIC`, :class:`~.types.REAL`,
:class:`~.types.SMALLINT`, :class:`~.types.TEXT`,
:class:`~.types.TIME`, :class:`~.types.TIMESTAMP`,
:class:`~.types.VARCHAR`, :class:`~.types.NVARCHAR`,
:class:`~.types.NCHAR`

When a type name does not match one of the above types, the "type affinity"
lookup is used instead:

* :class:`~.types.INTEGER` is returned if the type name includes the
  string ``INT``
* :class:`~.types.TEXT` is returned if the type name includes the
  string ``CHAR``, ``CLOB`` or ``TEXT``
* :class:`~.types.NullType` is returned if the type name includes the
  string ``BLOB``
* :class:`~.types.REAL` is returned if the type name includes the string
  ``REAL``, ``FLOA`` or ``DOUB``.
* Otherwise, the :class:`~.types.NUMERIC` type is used.

.. versionadded:: 0.9.3 Support for SQLite type affinity rules when reflecting
   columns.


.. _sqlite_partial_index:

Partial Indexes
---------------

A partial index, e.g. one which uses a WHERE clause, can be specified
with the DDL system using the argument ``sqlite_where``::

    tbl = Table('testtbl', m, Column('data', Integer))
    idx = Index('test_idx1', tbl.c.data,
                sqlite_where=and_(tbl.c.data > 5, tbl.c.data < 10))

The index will be rendered at create time as::

    CREATE INDEX test_idx1 ON testtbl (data)
    WHERE data > 5 AND data < 10

.. versionadded:: 0.9.9

.. _sqlite_dotted_column_names:

Dotted Column Names
-------------------

Using table or column names that explicitly have periods in them is
**not recommended**.   While this is generally a bad idea for relational
databases in general, as the dot is a syntactically significant character,
the SQLite driver up until version **3.10.0** of SQLite has a bug which
requires that SQLAlchemy filter out these dots in result sets.

.. versionchanged:: 1.1

    The following SQLite issue has been resolved as of version 3.10.0
    of SQLite.  SQLAlchemy as of **1.1** automatically disables its internal
    workarounds based on detection of this version.

The bug, entirely outside of SQLAlchemy, can be illustrated thusly::

    import sqlite3

    assert sqlite3.sqlite_version_info < (3, 10, 0), "bug is fixed in this version"

    conn = sqlite3.connect(":memory:")
    cursor = conn.cursor()

    cursor.execute("create table x (a integer, b integer)")
    cursor.execute("insert into x (a, b) values (1, 1)")
    cursor.execute("insert into x (a, b) values (2, 2)")

    cursor.execute("select x.a, x.b from x")
    assert [c[0] for c in cursor.description] == ['a', 'b']

    cursor.execute('''
        select x.a, x.b from x where a=1
        union
        select x.a, x.b from x where a=2
    ''')
    assert [c[0] for c in cursor.description] == ['a', 'b'], \
        [c[0] for c in cursor.description]

The second assertion fails::

    Traceback (most recent call last):
      File "test.py", line 19, in <module>
        [c[0] for c in cursor.description]
    AssertionError: ['x.a', 'x.b']

Where above, the driver incorrectly reports the names of the columns
including the name of the table, which is entirely inconsistent vs.
when the UNION is not present.

SQLAlchemy relies upon column names being predictable in how they match
to the original statement, so the SQLAlchemy dialect has no choice but
to filter these out::


    from sqlalchemy import create_engine

    eng = create_engine("sqlite://")
    conn = eng.connect()

    conn.execute("create table x (a integer, b integer)")
    conn.execute("insert into x (a, b) values (1, 1)")
    conn.execute("insert into x (a, b) values (2, 2)")

    result = conn.execute("select x.a, x.b from x")
    assert result.keys() == ["a", "b"]

    result = conn.execute('''
        select x.a, x.b from x where a=1
        union
        select x.a, x.b from x where a=2
    ''')
    assert result.keys() == ["a", "b"]

Note that above, even though SQLAlchemy filters out the dots, *both
names are still addressable*::

    >>> row = result.first()
    >>> row["a"]
    1
    >>> row["x.a"]
    1
    >>> row["b"]
    1
    >>> row["x.b"]
    1

Therefore, the workaround applied by SQLAlchemy only impacts
:meth:`.ResultProxy.keys` and :meth:`.RowProxy.keys()` in the public API.
In the very specific case where
an application is forced to use column names that contain dots, and the
functionality of :meth:`.ResultProxy.keys` and :meth:`.RowProxy.keys()`
is required to return these dotted names unmodified, the ``sqlite_raw_colnames``
execution option may be provided, either on a per-:class:`.Connection` basis::

    result = conn.execution_options(sqlite_raw_colnames=True).execute('''
        select x.a, x.b from x where a=1
        union
        select x.a, x.b from x where a=2
    ''')
    assert result.keys() == ["x.a", "x.b"]

or on a per-:class:`.Engine` basis::

    engine = create_engine("sqlite://", execution_options={"sqlite_raw_colnames": True})

When using the per-:class:`.Engine` execution option, note that
**Core and ORM queries that use UNION may not function properly**.

"""

import datetime
import re

from ... import processors
from ... import sql, exc
from ... import types as sqltypes, schema as sa_schema
from ... import util
from ...engine import default, reflection
from ...sql import compiler

from ...types import (BLOB, BOOLEAN, CHAR, DECIMAL, FLOAT,
                      INTEGER, REAL, NUMERIC, SMALLINT, TEXT,
                      TIMESTAMP, VARCHAR)


class _DateTimeMixin(object):
    _reg = None
    _storage_format = None

    def __init__(self, storage_format=None, regexp=None, **kw):
        super(_DateTimeMixin, self).__init__(**kw)
        if regexp is not None:
            self._reg = re.compile(regexp)
        if storage_format is not None:
            self._storage_format = storage_format

    @property
    def format_is_text_affinity(self):
        """return True if the storage format will automatically imply
        a TEXT affinity.

        If the storage format contains no non-numeric characters,
        it will imply a NUMERIC storage format on SQLite; in this case,
        the type will generate its DDL as DATE_CHAR, DATETIME_CHAR,
        TIME_CHAR.

        .. versionadded:: 1.0.0

        """
        spec = self._storage_format % {
            "year": 0, "month": 0, "day": 0, "hour": 0,
            "minute": 0, "second": 0, "microsecond": 0
        }
        return bool(re.search(r'[^0-9]', spec))

    def adapt(self, cls, **kw):
        if issubclass(cls, _DateTimeMixin):
            if self._storage_format:
                kw["storage_format"] = self._storage_format
            if self._reg:
                kw["regexp"] = self._reg
        return super(_DateTimeMixin, self).adapt(cls, **kw)

    def literal_processor(self, dialect):
        bp = self.bind_processor(dialect)

        def process(value):
            return "'%s'" % bp(value)
        return process


class DATETIME(_DateTimeMixin, sqltypes.DateTime):
    r"""Represent a Python datetime object in SQLite using a string.

    The default string storage format is::

        "%(year)04d-%(month)02d-%(day)02d %(hour)02d:%(min)02d:\
%(second)02d.%(microsecond)06d"

    e.g.::

        2011-03-15 12:05:57.10558

    The storage format can be customized to some degree using the
    ``storage_format`` and ``regexp`` parameters, such as::

        import re
        from sqlalchemy.dialects.sqlite import DATETIME

        dt = DATETIME(
            storage_format="%(year)04d/%(month)02d/%(day)02d %(hour)02d:\
%(min)02d:%(second)02d",
            regexp=r"(\d+)/(\d+)/(\d+) (\d+)-(\d+)-(\d+)"
        )

    :param storage_format: format string which will be applied to the dict
     with keys year, month, day, hour, minute, second, and microsecond.

    :param regexp: regular expression which will be applied to incoming result
     rows. If the regexp contains named groups, the resulting match dict is
     applied to the Python datetime() constructor as keyword arguments.
     Otherwise, if positional groups are used, the datetime() constructor
     is called with positional arguments via
     ``*map(int, match_obj.groups(0))``.
    """

    _storage_format = (
        "%(year)04d-%(month)02d-%(day)02d "
        "%(hour)02d:%(minute)02d:%(second)02d.%(microsecond)06d"
    )

    def __init__(self, *args, **kwargs):
        truncate_microseconds = kwargs.pop('truncate_microseconds', False)
        super(DATETIME, self).__init__(*args, **kwargs)
        if truncate_microseconds:
            assert 'storage_format' not in kwargs, "You can specify only "\
                "one of truncate_microseconds or storage_format."
            assert 'regexp' not in kwargs, "You can specify only one of "\
                "truncate_microseconds or regexp."
            self._storage_format = (
                "%(year)04d-%(month)02d-%(day)02d "
                "%(hour)02d:%(minute)02d:%(second)02d"
            )

    def bind_processor(self, dialect):
        datetime_datetime = datetime.datetime
        datetime_date = datetime.date
        format = self._storage_format

        def process(value):
            if value is None:
                return None
            elif isinstance(value, datetime_datetime):
                return format % {
                    'year': value.year,
                    'month': value.month,
                    'day': value.day,
                    'hour': value.hour,
                    'minute': value.minute,
                    'second': value.second,
                    'microsecond': value.microsecond,
                }
            elif isinstance(value, datetime_date):
                return format % {
                    'year': value.year,
                    'month': value.month,
                    'day': value.day,
                    'hour': 0,
                    'minute': 0,
                    'second': 0,
                    'microsecond': 0,
                }
            else:
                raise TypeError("SQLite DateTime type only accepts Python "
                                "datetime and date objects as input.")
        return process

    def result_processor(self, dialect, coltype):
        if self._reg:
            return processors.str_to_datetime_processor_factory(
                self._reg, datetime.datetime)
        else:
            return processors.str_to_datetime


class DATE(_DateTimeMixin, sqltypes.Date):
    r"""Represent a Python date object in SQLite using a string.

    The default string storage format is::

        "%(year)04d-%(month)02d-%(day)02d"

    e.g.::

        2011-03-15

    The storage format can be customized to some degree using the
    ``storage_format`` and ``regexp`` parameters, such as::

        import re
        from sqlalchemy.dialects.sqlite import DATE

        d = DATE(
                storage_format="%(month)02d/%(day)02d/%(year)04d",
                regexp=re.compile("(?P<month>\d+)/(?P<day>\d+)/(?P<year>\d+)")
            )

    :param storage_format: format string which will be applied to the
     dict with keys year, month, and day.

    :param regexp: regular expression which will be applied to
     incoming result rows. If the regexp contains named groups, the
     resulting match dict is applied to the Python date() constructor
     as keyword arguments. Otherwise, if positional groups are used, the
     date() constructor is called with positional arguments via
     ``*map(int, match_obj.groups(0))``.
    """

    _storage_format = "%(year)04d-%(month)02d-%(day)02d"

    def bind_processor(self, dialect):
        datetime_date = datetime.date
        format = self._storage_format

        def process(value):
            if value is None:
                return None
            elif isinstance(value, datetime_date):
                return format % {
                    'year': value.year,
                    'month': value.month,
                    'day': value.day,
                }
            else:
                raise TypeError("SQLite Date type only accepts Python "
                                "date objects as input.")
        return process

    def result_processor(self, dialect, coltype):
        if self._reg:
            return processors.str_to_datetime_processor_factory(
                self._reg, datetime.date)
        else:
            return processors.str_to_date


class TIME(_DateTimeMixin, sqltypes.Time):
    r"""Represent a Python time object in SQLite using a string.

    The default string storage format is::

        "%(hour)02d:%(minute)02d:%(second)02d.%(microsecond)06d"

    e.g.::

        12:05:57.10558

    The storage format can be customized to some degree using the
    ``storage_format`` and ``regexp`` parameters, such as::

        import re
        from sqlalchemy.dialects.sqlite import TIME

        t = TIME(
            storage_format="%(hour)02d-%(minute)02d-%(second)02d-\
%(microsecond)06d",
            regexp=re.compile("(\d+)-(\d+)-(\d+)-(?:-(\d+))?")
        )

    :param storage_format: format string which will be applied to the dict
     with keys hour, minute, second, and microsecond.

    :param regexp: regular expression which will be applied to incoming result
     rows. If the regexp contains named groups, the resulting match dict is
     applied to the Python time() constructor as keyword arguments. Otherwise,
     if positional groups are used, the time() constructor is called with
     positional arguments via ``*map(int, match_obj.groups(0))``.
    """

    _storage_format = "%(hour)02d:%(minute)02d:%(second)02d.%(microsecond)06d"

    def __init__(self, *args, **kwargs):
        truncate_microseconds = kwargs.pop('truncate_microseconds', False)
        super(TIME, self).__init__(*args, **kwargs)
        if truncate_microseconds:
            assert 'storage_format' not in kwargs, "You can specify only "\
                "one of truncate_microseconds or storage_format."
            assert 'regexp' not in kwargs, "You can specify only one of "\
                "truncate_microseconds or regexp."
            self._storage_format = "%(hour)02d:%(minute)02d:%(second)02d"

    def bind_processor(self, dialect):
        datetime_time = datetime.time
        format = self._storage_format

        def process(value):
            if value is None:
                return None
            elif isinstance(value, datetime_time):
                return format % {
                    'hour': value.hour,
                    'minute': value.minute,
                    'second': value.second,
                    'microsecond': value.microsecond,
                }
            else:
                raise TypeError("SQLite Time type only accepts Python "
                                "time objects as input.")
        return process

    def result_processor(self, dialect, coltype):
        if self._reg:
            return processors.str_to_datetime_processor_factory(
                self._reg, datetime.time)
        else:
            return processors.str_to_time

colspecs = {
    sqltypes.Date: DATE,
    sqltypes.DateTime: DATETIME,
    sqltypes.Time: TIME,
}

ischema_names = {
    'BIGINT': sqltypes.BIGINT,
    'BLOB': sqltypes.BLOB,
    'BOOL': sqltypes.BOOLEAN,
    'BOOLEAN': sqltypes.BOOLEAN,
    'CHAR': sqltypes.CHAR,
    'DATE': sqltypes.DATE,
    'DATE_CHAR': sqltypes.DATE,
    'DATETIME': sqltypes.DATETIME,
    'DATETIME_CHAR': sqltypes.DATETIME,
    'DOUBLE': sqltypes.FLOAT,
    'DECIMAL': sqltypes.DECIMAL,
    'FLOAT': sqltypes.FLOAT,
    'INT': sqltypes.INTEGER,
    'INTEGER': sqltypes.INTEGER,
    'NUMERIC': sqltypes.NUMERIC,
    'REAL': sqltypes.REAL,
    'SMALLINT': sqltypes.SMALLINT,
    'TEXT': sqltypes.TEXT,
    'TIME': sqltypes.TIME,
    'TIME_CHAR': sqltypes.TIME,
    'TIMESTAMP': sqltypes.TIMESTAMP,
    'VARCHAR': sqltypes.VARCHAR,
    'NVARCHAR': sqltypes.NVARCHAR,
    'NCHAR': sqltypes.NCHAR,
}


class SQLiteCompiler(compiler.SQLCompiler):
    extract_map = util.update_copy(
        compiler.SQLCompiler.extract_map,
        {
            'month': '%m',
            'day': '%d',
            'year': '%Y',
            'second': '%S',
            'hour': '%H',
            'doy': '%j',
            'minute': '%M',
            'epoch': '%s',
            'dow': '%w',
            'week': '%W',
        })

    def visit_now_func(self, fn, **kw):
        return "CURRENT_TIMESTAMP"

    def visit_localtimestamp_func(self, func, **kw):
        return 'DATETIME(CURRENT_TIMESTAMP, "localtime")'

    def visit_true(self, expr, **kw):
        return '1'

    def visit_false(self, expr, **kw):
        return '0'

    def visit_char_length_func(self, fn, **kw):
        return "length%s" % self.function_argspec(fn)

    def visit_cast(self, cast, **kwargs):
        if self.dialect.supports_cast:
            return super(SQLiteCompiler, self).visit_cast(cast, **kwargs)
        else:
            return self.process(cast.clause, **kwargs)

    def visit_extract(self, extract, **kw):
        try:
            return "CAST(STRFTIME('%s', %s) AS INTEGER)" % (
                self.extract_map[extract.field],
                self.process(extract.expr, **kw)
            )
        except KeyError:
            raise exc.CompileError(
                "%s is not a valid extract argument." % extract.field)

    def limit_clause(self, select, **kw):
        text = ""
        if select._limit_clause is not None:
            text += "\n LIMIT " + self.process(select._limit_clause, **kw)
        if select._offset_clause is not None:
            if select._limit_clause is None:
                text += "\n LIMIT " + self.process(sql.literal(-1))
            text += " OFFSET " + self.process(select._offset_clause, **kw)
        else:
            text += " OFFSET " + self.process(sql.literal(0), **kw)
        return text

    def for_update_clause(self, select, **kw):
        # sqlite has no "FOR UPDATE" AFAICT
        return ''

    def visit_is_distinct_from_binary(self, binary, operator, **kw):
        return "%s IS NOT %s" % (self.process(binary.left),
                                 self.process(binary.right))

    def visit_isnot_distinct_from_binary(self, binary, operator, **kw):
        return "%s IS %s" % (self.process(binary.left),
                             self.process(binary.right))


class SQLiteDDLCompiler(compiler.DDLCompiler):

    def get_column_specification(self, column, **kwargs):
        coltype = self.dialect.type_compiler.process(
            column.type, type_expression=column)
        colspec = self.preparer.format_column(column) + " " + coltype
        default = self.get_column_default_string(column)
        if default is not None:
            colspec += " DEFAULT " + default

        if not column.nullable:
            colspec += " NOT NULL"

        if column.primary_key:
            if (
                column.autoincrement is True and
                len(column.table.primary_key.columns) != 1
            ):
                raise exc.CompileError(
                    "SQLite does not support autoincrement for "
                    "composite primary keys")

            if (column.table.dialect_options['sqlite']['autoincrement'] and
                    len(column.table.primary_key.columns) == 1 and
                    issubclass(column.type._type_affinity, sqltypes.Integer) and
                    not column.foreign_keys):
                colspec += " PRIMARY KEY AUTOINCREMENT"

        return colspec

    def visit_primary_key_constraint(self, constraint):
        # for columns with sqlite_autoincrement=True,
        # the PRIMARY KEY constraint can only be inline
        # with the column itself.
        if len(constraint.columns) == 1:
            c = list(constraint)[0]
            if (c.primary_key and
                    c.table.dialect_options['sqlite']['autoincrement'] and
                    issubclass(c.type._type_affinity, sqltypes.Integer) and
                    not c.foreign_keys):
                return None

        return super(SQLiteDDLCompiler, self).visit_primary_key_constraint(
            constraint)

    def visit_foreign_key_constraint(self, constraint):

        local_table = constraint.elements[0].parent.table
        remote_table = constraint.elements[0].column.table

        if local_table.schema != remote_table.schema:
            return None
        else:
            return super(
                SQLiteDDLCompiler,
                self).visit_foreign_key_constraint(constraint)

    def define_constraint_remote_table(self, constraint, table, preparer):
        """Format the remote table clause of a CREATE CONSTRAINT clause."""

        return preparer.format_table(table, use_schema=False)

    def visit_create_index(self, create, include_schema=False,
                           include_table_schema=True):
        index = create.element
        self._verify_index_table(index)
        preparer = self.preparer
        text = "CREATE "
        if index.unique:
            text += "UNIQUE "
        text += "INDEX %s ON %s (%s)" \
            % (
                self._prepared_index_name(index,
                                          include_schema=True),
                preparer.format_table(index.table,
                                      use_schema=False),
                ', '.join(
                    self.sql_compiler.process(
                        expr, include_table=False, literal_binds=True) for
                    expr in index.expressions)
            )

        whereclause = index.dialect_options["sqlite"]["where"]
        if whereclause is not None:
            where_compiled = self.sql_compiler.process(
                whereclause, include_table=False,
                literal_binds=True)
            text += " WHERE " + where_compiled

        return text


class SQLiteTypeCompiler(compiler.GenericTypeCompiler):
    def visit_large_binary(self, type_, **kw):
        return self.visit_BLOB(type_)

    def visit_DATETIME(self, type_, **kw):
        if not isinstance(type_, _DateTimeMixin) or \
                type_.format_is_text_affinity:
            return super(SQLiteTypeCompiler, self).visit_DATETIME(type_)
        else:
            return "DATETIME_CHAR"

    def visit_DATE(self, type_, **kw):
        if not isinstance(type_, _DateTimeMixin) or \
                type_.format_is_text_affinity:
            return super(SQLiteTypeCompiler, self).visit_DATE(type_)
        else:
            return "DATE_CHAR"

    def visit_TIME(self, type_, **kw):
        if not isinstance(type_, _DateTimeMixin) or \
                type_.format_is_text_affinity:
            return super(SQLiteTypeCompiler, self).visit_TIME(type_)
        else:
            return "TIME_CHAR"


class SQLiteIdentifierPreparer(compiler.IdentifierPreparer):
    reserved_words = set([
        'add', 'after', 'all', 'alter', 'analyze', 'and', 'as', 'asc',
        'attach', 'autoincrement', 'before', 'begin', 'between', 'by',
        'cascade', 'case', 'cast', 'check', 'collate', 'column', 'commit',
        'conflict', 'constraint', 'create', 'cross', 'current_date',
        'current_time', 'current_timestamp', 'database', 'default',
        'deferrable', 'deferred', 'delete', 'desc', 'detach', 'distinct',
        'drop', 'each', 'else', 'end', 'escape', 'except', 'exclusive',
        'explain', 'false', 'fail', 'for', 'foreign', 'from', 'full', 'glob',
        'group', 'having', 'if', 'ignore', 'immediate', 'in', 'index',
        'indexed', 'initially', 'inner', 'insert', 'instead', 'intersect',
        'into', 'is', 'isnull', 'join', 'key', 'left', 'like', 'limit',
        'match', 'natural', 'not', 'notnull', 'null', 'of', 'offset', 'on',
        'or', 'order', 'outer', 'plan', 'pragma', 'primary', 'query',
        'raise', 'references', 'reindex', 'rename', 'replace', 'restrict',
        'right', 'rollback', 'row', 'select', 'set', 'table', 'temp',
        'temporary', 'then', 'to', 'transaction', 'trigger', 'true', 'union',
        'unique', 'update', 'using', 'vacuum', 'values', 'view', 'virtual',
        'when', 'where',
    ])

    def format_index(self, index, use_schema=True, name=None):
        """Prepare a quoted index and schema name."""

        if name is None:
            name = index.name
        result = self.quote(name, index.quote)
        if (not self.omit_schema and
                use_schema and
                getattr(index.table, "schema", None)):
            result = self.quote_schema(
                index.table.schema, index.table.quote_schema) + "." + result
        return result


class SQLiteExecutionContext(default.DefaultExecutionContext):
    @util.memoized_property
    def _preserve_raw_colnames(self):
        return not self.dialect._broken_dotted_colnames or \
            self.execution_options.get("sqlite_raw_colnames", False)

    def _translate_colname(self, colname):
        # TODO: detect SQLite version 3.10.0 or greater;
        # see [ticket:3633]

        # adjust for dotted column names.  SQLite
        # in the case of UNION may store col names as
        # "tablename.colname", or if using an attached database,
        # "database.tablename.colname", in cursor.description
        if not self._preserve_raw_colnames and "." in colname:
            return colname.split(".")[-1], colname
        else:
            return colname, None


class SQLiteDialect(default.DefaultDialect):
    name = 'sqlite'
    supports_alter = False
    supports_unicode_statements = True
    supports_unicode_binds = True
    supports_default_values = True
    supports_empty_insert = False
    supports_cast = True
    supports_multivalues_insert = True

    default_paramstyle = 'qmark'
    execution_ctx_cls = SQLiteExecutionContext
    statement_compiler = SQLiteCompiler
    ddl_compiler = SQLiteDDLCompiler
    type_compiler = SQLiteTypeCompiler
    preparer = SQLiteIdentifierPreparer
    ischema_names = ischema_names
    colspecs = colspecs
    isolation_level = None

    supports_cast = True
    supports_default_values = True

    construct_arguments = [
        (sa_schema.Table, {
            "autoincrement": False
        }),
        (sa_schema.Index, {
            "where": None,
        }),
    ]

    _broken_fk_pragma_quotes = False
    _broken_dotted_colnames = False

    def __init__(self, isolation_level=None, native_datetime=False, **kwargs):
        default.DefaultDialect.__init__(self, **kwargs)
        self.isolation_level = isolation_level

        # this flag used by pysqlite dialect, and perhaps others in the
        # future, to indicate the driver is handling date/timestamp
        # conversions (and perhaps datetime/time as well on some hypothetical
        # driver ?)
        self.native_datetime = native_datetime

        if self.dbapi is not None:
            self.supports_right_nested_joins = (
                self.dbapi.sqlite_version_info >= (3, 7, 16))
            self._broken_dotted_colnames = (
                self.dbapi.sqlite_version_info < (3, 10, 0)
            )
            self.supports_default_values = (
                self.dbapi.sqlite_version_info >= (3, 3, 8))
            self.supports_cast = (
                self.dbapi.sqlite_version_info >= (3, 2, 3))
            self.supports_multivalues_insert = (
                # http://www.sqlite.org/releaselog/3_7_11.html
                self.dbapi.sqlite_version_info >= (3, 7, 11))
            # see http://www.sqlalchemy.org/trac/ticket/2568
            # as well as http://www.sqlite.org/src/info/600482d161
            self._broken_fk_pragma_quotes = (
                self.dbapi.sqlite_version_info < (3, 6, 14))

    _isolation_lookup = {
        'READ UNCOMMITTED': 1,
        'SERIALIZABLE': 0,
    }

    def set_isolation_level(self, connection, level):
        try:
            isolation_level = self._isolation_lookup[level.replace('_', ' ')]
        except KeyError:
            raise exc.ArgumentError(
                "Invalid value '%s' for isolation_level. "
                "Valid isolation levels for %s are %s" %
                (level, self.name, ", ".join(self._isolation_lookup))
            )
        cursor = connection.cursor()
        cursor.execute("PRAGMA read_uncommitted = %d" % isolation_level)
        cursor.close()

    def get_isolation_level(self, connection):
        cursor = connection.cursor()
        cursor.execute('PRAGMA read_uncommitted')
        res = cursor.fetchone()
        if res:
            value = res[0]
        else:
            # http://www.sqlite.org/changes.html#version_3_3_3
            # "Optional READ UNCOMMITTED isolation (instead of the
            # default isolation level of SERIALIZABLE) and
            # table level locking when database connections
            # share a common cache.""
            # pre-SQLite 3.3.0 default to 0
            value = 0
        cursor.close()
        if value == 0:
            return "SERIALIZABLE"
        elif value == 1:
            return "READ UNCOMMITTED"
        else:
            assert False, "Unknown isolation level %s" % value

    def on_connect(self):
        if self.isolation_level is not None:
            def connect(conn):
                self.set_isolation_level(conn, self.isolation_level)
            return connect
        else:
            return None

    @reflection.cache
    def get_schema_names(self, connection, **kw):
        s = "PRAGMA database_list"
        dl = connection.execute(s)

        return [db[1] for db in dl if db[1] != "temp"]

    @reflection.cache
    def get_table_names(self, connection, schema=None, **kw):
        if schema is not None:
            qschema = self.identifier_preparer.quote_identifier(schema)
            master = '%s.sqlite_master' % qschema
        else:
            master = "sqlite_master"
        s = ("SELECT name FROM %s "
             "WHERE type='table' ORDER BY name") % (master,)
        rs = connection.execute(s)
        return [row[0] for row in rs]

    @reflection.cache
    def get_temp_table_names(self, connection, **kw):
        s = "SELECT name FROM sqlite_temp_master "\
            "WHERE type='table' ORDER BY name "
        rs = connection.execute(s)

        return [row[0] for row in rs]

    @reflection.cache
    def get_temp_view_names(self, connection, **kw):
        s = "SELECT name FROM sqlite_temp_master "\
            "WHERE type='view' ORDER BY name "
        rs = connection.execute(s)

        return [row[0] for row in rs]

    def has_table(self, connection, table_name, schema=None):
        info = self._get_table_pragma(
            connection, "table_info", table_name, schema=schema)
        return bool(info)

    @reflection.cache
    def get_view_names(self, connection, schema=None, **kw):
        if schema is not None:
            qschema = self.identifier_preparer.quote_identifier(schema)
            master = '%s.sqlite_master' % qschema
        else:
            master = "sqlite_master"
        s = ("SELECT name FROM %s "
             "WHERE type='view' ORDER BY name") % (master,)
        rs = connection.execute(s)

        return [row[0] for row in rs]

    @reflection.cache
    def get_view_definition(self, connection, view_name, schema=None, **kw):
        if schema is not None:
            qschema = self.identifier_preparer.quote_identifier(schema)
            master = '%s.sqlite_master' % qschema
            s = ("SELECT sql FROM %s WHERE name = '%s'"
                 "AND type='view'") % (master, view_name)
            rs = connection.execute(s)
        else:
            try:
                s = ("SELECT sql FROM "
                     " (SELECT * FROM sqlite_master UNION ALL "
                     "  SELECT * FROM sqlite_temp_master) "
                     "WHERE name = '%s' "
                     "AND type='view'") % view_name
                rs = connection.execute(s)
            except exc.DBAPIError:
                s = ("SELECT sql FROM sqlite_master WHERE name = '%s' "
                     "AND type='view'") % view_name
                rs = connection.execute(s)

        result = rs.fetchall()
        if result:
            return result[0].sql

    @reflection.cache
    def get_columns(self, connection, table_name, schema=None, **kw):
        info = self._get_table_pragma(
            connection, "table_info", table_name, schema=schema)

        columns = []
        for row in info:
            (name, type_, nullable, default, primary_key) = (
                row[1], row[2].upper(), not row[3], row[4], row[5])

            columns.append(self._get_column_info(name, type_, nullable,
                                                 default, primary_key))
        return columns

    def _get_column_info(self, name, type_, nullable, default, primary_key):
        coltype = self._resolve_type_affinity(type_)

        if default is not None:
            default = util.text_type(default)

        return {
            'name': name,
            'type': coltype,
            'nullable': nullable,
            'default': default,
            'autoincrement': 'auto',
            'primary_key': primary_key,
        }

    def _resolve_type_affinity(self, type_):
        """Return a data type from a reflected column, using affinity tules.

        SQLite's goal for universal compatibility introduces some complexity
        during reflection, as a column's defined type might not actually be a
        type that SQLite understands - or indeed, my not be defined *at all*.
        Internally, SQLite handles this with a 'data type affinity' for each
        column definition, mapping to one of 'TEXT', 'NUMERIC', 'INTEGER',
        'REAL', or 'NONE' (raw bits). The algorithm that determines this is
        listed in http://www.sqlite.org/datatype3.html section 2.1.

        This method allows SQLAlchemy to support that algorithm, while still
        providing access to smarter reflection utilities by regcognizing
        column definitions that SQLite only supports through affinity (like
        DATE and DOUBLE).

        """
        match = re.match(r'([\w ]+)(\(.*?\))?', type_)
        if match:
            coltype = match.group(1)
            args = match.group(2)
        else:
            coltype = ''
            args = ''

        if coltype in self.ischema_names:
            coltype = self.ischema_names[coltype]
        elif 'INT' in coltype:
            coltype = sqltypes.INTEGER
        elif 'CHAR' in coltype or 'CLOB' in coltype or 'TEXT' in coltype:
            coltype = sqltypes.TEXT
        elif 'BLOB' in coltype or not coltype:
            coltype = sqltypes.NullType
        elif 'REAL' in coltype or 'FLOA' in coltype or 'DOUB' in coltype:
            coltype = sqltypes.REAL
        else:
            coltype = sqltypes.NUMERIC

        if args is not None:
            args = re.findall(r'(\d+)', args)
            try:
                coltype = coltype(*[int(a) for a in args])
            except TypeError:
                util.warn(
                    "Could not instantiate type %s with "
                    "reflected arguments %s; using no arguments." %
                    (coltype, args))
                coltype = coltype()
        else:
            coltype = coltype()

        return coltype

    @reflection.cache
    def get_pk_constraint(self, connection, table_name, schema=None, **kw):
        constraint_name = None
        table_data = self._get_table_sql(connection, table_name, schema=schema)
        if table_data:
            PK_PATTERN = r'CONSTRAINT (\w+) PRIMARY KEY'
            result = re.search(PK_PATTERN, table_data, re.I)
            constraint_name = result.group(1) if result else None

        cols = self.get_columns(connection, table_name, schema, **kw)
        pkeys = []
        for col in cols:
            if col['primary_key']:
                pkeys.append(col['name'])

        return {'constrained_columns': pkeys, 'name': constraint_name}

    @reflection.cache
    def get_foreign_keys(self, connection, table_name, schema=None, **kw):
        # sqlite makes this *extremely difficult*.
        # First, use the pragma to get the actual FKs.
        pragma_fks = self._get_table_pragma(
            connection, "foreign_key_list",
            table_name, schema=schema
        )

        fks = {}

        for row in pragma_fks:
            (numerical_id, rtbl, lcol, rcol) = (
                row[0], row[2], row[3], row[4])

            if rcol is None:
                rcol = lcol

            if self._broken_fk_pragma_quotes:
                rtbl = re.sub(r'^[\"\[`\']|[\"\]`\']$', '', rtbl)

            if numerical_id in fks:
                fk = fks[numerical_id]
            else:
                fk = fks[numerical_id] = {
                    'name': None,
                    'constrained_columns': [],
                    'referred_schema': schema,
                    'referred_table': rtbl,
                    'referred_columns': [],
                    'options': {}
                }
                fks[numerical_id] = fk

            fk['constrained_columns'].append(lcol)
            fk['referred_columns'].append(rcol)

        def fk_sig(constrained_columns, referred_table, referred_columns):
            return tuple(constrained_columns) + (referred_table,) + \
                tuple(referred_columns)

        # then, parse the actual SQL and attempt to find DDL that matches
        # the names as well.   SQLite saves the DDL in whatever format
        # it was typed in as, so need to be liberal here.

        keys_by_signature = dict(
            (
                fk_sig(
                    fk['constrained_columns'],
                    fk['referred_table'], fk['referred_columns']),
                fk
            ) for fk in fks.values()
        )

        table_data = self._get_table_sql(connection, table_name, schema=schema)
        if table_data is None:
            # system tables, etc.
            return []

        def parse_fks():
            FK_PATTERN = (
                r'(?:CONSTRAINT (\w+) +)?'
                r'FOREIGN KEY *\( *(.+?) *\) +'
                r'REFERENCES +(?:(?:"(.+?)")|([a-z0-9_]+)) *\((.+?)\) *'
                r'((?:ON (?:DELETE|UPDATE) '
                r'(?:SET NULL|SET DEFAULT|CASCADE|RESTRICT|NO ACTION) *)*)'
            )
            for match in re.finditer(FK_PATTERN, table_data, re.I):
                (
                    constraint_name, constrained_columns,
                    referred_quoted_name, referred_name,
                    referred_columns, onupdatedelete) = \
                    match.group(1, 2, 3, 4, 5, 6)
                constrained_columns = list(
                    self._find_cols_in_sig(constrained_columns))
                if not referred_columns:
                    referred_columns = constrained_columns
                else:
                    referred_columns = list(
                        self._find_cols_in_sig(referred_columns))
                referred_name = referred_quoted_name or referred_name
                options = {}

                for token in re.split(r" *\bON\b *", onupdatedelete.upper()):
                    if token.startswith("DELETE"):
                        options['ondelete'] = token[6:].strip()
                    elif token.startswith("UPDATE"):
                        options["onupdate"] = token[6:].strip()
                yield (
                    constraint_name, constrained_columns,
                    referred_name, referred_columns, options)
        fkeys = []

        for (
            constraint_name, constrained_columns,
                referred_name, referred_columns, options) in parse_fks():
            sig = fk_sig(
                constrained_columns, referred_name, referred_columns)
            if sig not in keys_by_signature:
                util.warn(
                    "WARNING: SQL-parsed foreign key constraint "
                    "'%s' could not be located in PRAGMA "
                    "foreign_keys for table %s" % (
                        sig,
                        table_name
                    ))
                continue
            key = keys_by_signature.pop(sig)
            key['name'] = constraint_name
            key['options'] = options
            fkeys.append(key)
        # assume the remainders are the unnamed, inline constraints, just
        # use them as is as it's extremely difficult to parse inline
        # constraints
        fkeys.extend(keys_by_signature.values())
        return fkeys

    def _find_cols_in_sig(self, sig):
        for match in re.finditer(r'(?:"(.+?)")|([a-z0-9_]+)', sig, re.I):
            yield match.group(1) or match.group(2)

    @reflection.cache
    def get_unique_constraints(self, connection, table_name,
                               schema=None, **kw):

        auto_index_by_sig = {}
        for idx in self.get_indexes(
                connection, table_name, schema=schema,
                include_auto_indexes=True, **kw):
            if not idx['name'].startswith("sqlite_autoindex"):
                continue
            sig = tuple(idx['column_names'])
            auto_index_by_sig[sig] = idx

        table_data = self._get_table_sql(
            connection, table_name, schema=schema, **kw)
        if not table_data:
            return []

        unique_constraints = []

        def parse_uqs():
            UNIQUE_PATTERN = r'(?:CONSTRAINT "?(.+?)"? +)?UNIQUE *\((.+?)\)'
            INLINE_UNIQUE_PATTERN = (
                r'(?:(".+?")|([a-z0-9]+)) '
                r'+[a-z0-9_ ]+? +UNIQUE')

            for match in re.finditer(UNIQUE_PATTERN, table_data, re.I):
                name, cols = match.group(1, 2)
                yield name, list(self._find_cols_in_sig(cols))

            # we need to match inlines as well, as we seek to differentiate
            # a UNIQUE constraint from a UNIQUE INDEX, even though these
            # are kind of the same thing :)
            for match in re.finditer(INLINE_UNIQUE_PATTERN, table_data, re.I):
                cols = list(
                    self._find_cols_in_sig(match.group(1) or match.group(2)))
                yield None, cols

        for name, cols in parse_uqs():
            sig = tuple(cols)
            if sig in auto_index_by_sig:
                auto_index_by_sig.pop(sig)
                parsed_constraint = {
                    'name': name,
                    'column_names': cols
                }
                unique_constraints.append(parsed_constraint)
        # NOTE: auto_index_by_sig might not be empty here,
        # the PRIMARY KEY may have an entry.
        return unique_constraints

    @reflection.cache
    def get_check_constraints(self, connection, table_name,
                              schema=None, **kw):
        table_data = self._get_table_sql(
            connection, table_name, schema=schema, **kw)
        if not table_data:
            return []

        CHECK_PATTERN = (
            r'(?:CONSTRAINT (\w+) +)?'
            r'CHECK *\( *(.+) *\),? *'
        )
        check_constraints = []
        # NOTE: we aren't using re.S here because we actually are
        # taking advantage of each CHECK constraint being all on one
        # line in the table definition in order to delineate.  This
        # necessarily makes assumptions as to how the CREATE TABLE
        # was emitted.
        for match in re.finditer(CHECK_PATTERN, table_data, re.I):
            check_constraints.append({
                'sqltext': match.group(2),
                'name': match.group(1)
            })

        return check_constraints

    @reflection.cache
    def get_indexes(self, connection, table_name, schema=None, **kw):
        pragma_indexes = self._get_table_pragma(
            connection, "index_list", table_name, schema=schema)
        indexes = []

        include_auto_indexes = kw.pop('include_auto_indexes', False)
        for row in pragma_indexes:
            # ignore implicit primary key index.
            # http://www.mail-archive.com/sqlite-users@sqlite.org/msg30517.html
            if (not include_auto_indexes and
                    row[1].startswith('sqlite_autoindex')):
                continue

            indexes.append(dict(name=row[1], column_names=[], unique=row[2]))

        # loop thru unique indexes to get the column names.
        for idx in indexes:
            pragma_index = self._get_table_pragma(
                connection, "index_info", idx['name'])

            for row in pragma_index:
                idx['column_names'].append(row[2])
        return indexes

    @reflection.cache
    def _get_table_sql(self, connection, table_name, schema=None, **kw):
        try:
            s = ("SELECT sql FROM "
                 " (SELECT * FROM sqlite_master UNION ALL "
                 "  SELECT * FROM sqlite_temp_master) "
                 "WHERE name = '%s' "
                 "AND type = 'table'") % table_name
            rs = connection.execute(s)
        except exc.DBAPIError:
            s = ("SELECT sql FROM sqlite_master WHERE name = '%s' "
                 "AND type = 'table'") % table_name
            rs = connection.execute(s)
        return rs.scalar()

    def _get_table_pragma(self, connection, pragma, table_name, schema=None):
        quote = self.identifier_preparer.quote_identifier
        if schema is not None:
            statement = "PRAGMA %s." % quote(schema)
        else:
            statement = "PRAGMA "
        qtable = quote(table_name)
        statement = "%s%s(%s)" % (statement, pragma, qtable)
        cursor = connection.execute(statement)
        if not cursor._soft_closed:
            # work around SQLite issue whereby cursor.description
            # is blank when PRAGMA returns no rows:
            # http://www.sqlite.org/cvstrac/tktview?tn=1884
            result = cursor.fetchall()
        else:
            result = []
        return result