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tldr: refactoring
2019-12-16 18:12:10 +01:00
# sqlite/base.py
# Copyright (C) 2005-2019 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 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 transaction 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_on_conflict_ddl:
ON CONFLICT support for constraints
-----------------------------------
SQLite supports a non-standard clause known as ON CONFLICT which can be applied
to primary key, unique, check, and not null constraints. In DDL, it is
rendered either within the "CONSTRAINT" clause or within the column definition
itself depending on the location of the target constraint. To render this
clause within DDL, the extension parameter ``sqlite_on_conflict`` can be
specified with a string conflict resolution algorithm within the
:class:`.PrimaryKeyConstraint`, :class:`.UniqueConstraint`,
:class:`.CheckConstraint` objects. Within the :class:`.Column` object, there
are individual parameters ``sqlite_on_conflict_not_null``,
``sqlite_on_conflict_primary_key``, ``sqlite_on_conflict_unique`` which each
correspond to the three types of relevant constraint types that can be
indicated from a :class:`.Column` object.
.. seealso::
`ON CONFLICT <https://www.sqlite.org/lang_conflict.html>`_ - in the SQLite
documentation
.. versionadded:: 1.3
The ``sqlite_on_conflict`` parameters accept a string argument which is just
the resolution name to be chosen, which on SQLite can be one of ROLLBACK,
ABORT, FAIL, IGNORE, and REPLACE. For example, to add a UNIQUE constraint
that specifies the IGNORE algorithm::
some_table = Table(
'some_table', metadata,
Column('id', Integer, primary_key=True),
Column('data', Integer),
UniqueConstraint('id', 'data', sqlite_on_conflict='IGNORE')
)
The above renders CREATE TABLE DDL as::
CREATE TABLE some_table (
id INTEGER NOT NULL,
data INTEGER,
PRIMARY KEY (id),
UNIQUE (id, data) ON CONFLICT IGNORE
)
When using the :paramref:`.Column.unique` flag to add a UNIQUE constraint
to a single column, the ``sqlite_on_conflict_unique`` parameter can
be added to the :class:`.Column` as well, which will be added to the
UNIQUE constraint in the DDL::
some_table = Table(
'some_table', metadata,
Column('id', Integer, primary_key=True),
Column('data', Integer, unique=True,
sqlite_on_conflict_unique='IGNORE')
)
rendering::
CREATE TABLE some_table (
id INTEGER NOT NULL,
data INTEGER,
PRIMARY KEY (id),
UNIQUE (data) ON CONFLICT IGNORE
)
To apply the FAIL algorithm for a NOT NULL constraint,
``sqlite_on_conflict_not_null`` is used::
some_table = Table(
'some_table', metadata,
Column('id', Integer, primary_key=True),
Column('data', Integer, nullable=False,
sqlite_on_conflict_not_null='FAIL')
)
this renders the column inline ON CONFLICT phrase::
CREATE TABLE some_table (
id INTEGER NOT NULL,
data INTEGER NOT NULL ON CONFLICT FAIL,
PRIMARY KEY (id)
)
Similarly, for an inline primary key, use ``sqlite_on_conflict_primary_key``::
some_table = Table(
'some_table', metadata,
Column('id', Integer, primary_key=True,
sqlite_on_conflict_primary_key='FAIL')
)
SQLAlchemy renders the PRIMARY KEY constraint separately, so the conflict
resolution algorithm is applied to the constraint itself::
CREATE TABLE some_table (
id INTEGER NOT NULL,
PRIMARY KEY (id) ON CONFLICT FAIL
)
.. _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**.
""" # noqa
import datetime
feat(HA): add cluster communication system
2019-12-31 00:52:17 +01:00
import numbers
tldr: refactoring
2019-12-16 18:12:10 +01:00
import re
from .json import JSON
from .json import JSONIndexType
from .json import JSONPathType
from ... import exc
from ... import processors
from ... import schema as sa_schema
from ... import sql
from ... import types as sqltypes
from ... import util
from ...engine import default
from ...engine import reflection
from ...sql import ColumnElement
from ...sql import compiler
from ...types import BLOB # noqa
from ...types import BOOLEAN # noqa
from ...types import CHAR # noqa
from ...types import DECIMAL # noqa
from ...types import FLOAT # noqa
from ...types import INTEGER # noqa
from ...types import NUMERIC # noqa
from ...types import REAL # noqa
from ...types import SMALLINT # noqa
from ...types import TEXT # noqa
from ...types import TIMESTAMP # noqa
from ...types import VARCHAR # noqa
feat(HA): add cluster communication system
2019-12-31 00:52:17 +01:00
class _SQliteJson(JSON):
def result_processor(self, dialect, coltype):
default_processor = super(_SQliteJson, self).result_processor(
dialect, coltype
)
def process(value):
try:
return default_processor(value)
except TypeError:
if isinstance(value, numbers.Number):
return value
else:
raise
return process
tldr: refactoring
2019-12-16 18:12:10 +01:00
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:%(minute)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:%(minute)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))``.
""" # noqa
_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,
feat(HA): add cluster communication system
2019-12-31 00:52:17 +01:00
sqltypes.JSON: _SQliteJson,
tldr: refactoring
2019-12-16 18:12:10 +01:00
sqltypes.JSON.JSONIndexType: JSONIndexType,
sqltypes.JSON.JSONPathType: JSONPathType,
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,
"JSON": JSON,
"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),
)
def visit_json_getitem_op_binary(self, binary, operator, **kw):
if binary.type._type_affinity is sqltypes.JSON:
expr = "JSON_QUOTE(JSON_EXTRACT(%s, %s))"
else:
expr = "JSON_EXTRACT(%s, %s)"
return expr % (
self.process(binary.left, **kw),
self.process(binary.right, **kw),
)
def visit_json_path_getitem_op_binary(self, binary, operator, **kw):
if binary.type._type_affinity is sqltypes.JSON:
expr = "JSON_QUOTE(JSON_EXTRACT(%s, %s))"
else:
expr = "JSON_EXTRACT(%s, %s)"
return expr % (
self.process(binary.left, **kw),
self.process(binary.right, **kw),
)
def visit_empty_set_expr(self, element_types):
return "SELECT %s FROM (SELECT %s) WHERE 1!=1" % (
", ".join("1" for type_ in element_types or [INTEGER()]),
", ".join("1" for type_ in element_types or [INTEGER()]),
)
class SQLiteDDLCompiler(compiler.DDLCompiler):
def get_column_specification(self, column, **kwargs):
if column.computed is not None:
raise exc.CompileError("SQLite does not support computed columns")
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:
if isinstance(column.server_default.arg, ColumnElement):
default = "(" + default + ")"
colspec += " DEFAULT " + default
if not column.nullable:
colspec += " NOT NULL"
on_conflict_clause = column.dialect_options["sqlite"][
"on_conflict_not_null"
]
if on_conflict_clause is not None:
colspec += " ON CONFLICT " + on_conflict_clause
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"
on_conflict_clause = column.dialect_options["sqlite"][
"on_conflict_primary_key"
]
if on_conflict_clause is not None:
colspec += " ON CONFLICT " + on_conflict_clause
colspec += " 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
text = super(SQLiteDDLCompiler, self).visit_primary_key_constraint(
constraint
)
on_conflict_clause = constraint.dialect_options["sqlite"][
"on_conflict"
]
if on_conflict_clause is None and len(constraint.columns) == 1:
on_conflict_clause = list(constraint)[0].dialect_options["sqlite"][
"on_conflict_primary_key"
]
if on_conflict_clause is not None:
text += " ON CONFLICT " + on_conflict_clause
return text
def visit_unique_constraint(self, constraint):
text = super(SQLiteDDLCompiler, self).visit_unique_constraint(
constraint
)
on_conflict_clause = constraint.dialect_options["sqlite"][
"on_conflict"
]
if on_conflict_clause is None and len(constraint.columns) == 1:
on_conflict_clause = list(constraint)[0].dialect_options["sqlite"][
"on_conflict_unique"
]
if on_conflict_clause is not None:
text += " ON CONFLICT " + on_conflict_clause
return text
def visit_check_constraint(self, constraint):
text = super(SQLiteDDLCompiler, self).visit_check_constraint(
constraint
)
on_conflict_clause = constraint.dialect_options["sqlite"][
"on_conflict"
]
if on_conflict_clause is not None:
text += " ON CONFLICT " + on_conflict_clause
return text
def visit_column_check_constraint(self, constraint):
text = super(SQLiteDDLCompiler, self).visit_column_check_constraint(
constraint
)
if constraint.dialect_options["sqlite"]["on_conflict"] is not None:
raise exc.CompileError(
"SQLite does not support on conflict clause for "
"column check constraint"
)
return text
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"
def visit_JSON(self, type_, **kw):
# note this name provides NUMERIC affinity, not TEXT.
# should not be an issue unless the JSON value consists of a single
# numeric value. JSONTEXT can be used if this case is required.
return "JSON"
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",
]
)
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
tuple_in_values = 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}),
(
sa_schema.Column,
{
"on_conflict_primary_key": None,
"on_conflict_not_null": None,
"on_conflict_unique": None,
},
),
(sa_schema.Constraint, {"on_conflict": None}),
]
_broken_fk_pragma_quotes = False
_broken_dotted_colnames = False
@util.deprecated_params(
_json_serializer=(
"1.3.7",
"The _json_serializer argument to the SQLite dialect has "
"been renamed to the correct name of json_serializer. The old "
"argument name will be removed in a future release.",
),
_json_deserializer=(
"1.3.7",
"The _json_deserializer argument to the SQLite dialect has "
"been renamed to the correct name of json_deserializer. The old "
"argument name will be removed in a future release.",
),
)
def __init__(
self,
isolation_level=None,
native_datetime=False,
json_serializer=None,
json_deserializer=None,
_json_serializer=None,
_json_deserializer=None,
**kwargs
):
default.DefaultDialect.__init__(self, **kwargs)
self.isolation_level = isolation_level
if _json_serializer:
json_serializer = _json_serializer
if _json_deserializer:
json_deserializer = _json_deserializer
self._json_serializer = json_serializer
self._json_deserializer = json_deserializer
# 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 not rcol:
# no referred column, which means it was not named in the
# original DDL. The referred columns of the foreign key
# constraint are therefore the primary key of the referred
# table.
referred_pk = self.get_pk_constraint(
connection, rtbl, schema=schema, **kw
)
# note that if table doesnt exist, we still get back a record,
# just it has no columns in it
referred_columns = referred_pk["constrained_columns"]
else:
# note we use this list only if this is the first column
# in the constraint. for subsequent columns we ignore the
# list and append "rcol" if present.
referred_columns = []
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": referred_columns,
"options": {},
}
fks[numerical_id] = fk
fk["constrained_columns"].append(lcol)
if rcol:
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 list(indexes):
pragma_index = self._get_table_pragma(
connection, "index_info", idx["name"]
)
for row in pragma_index:
if row[2] is None:
util.warn(
"Skipped unsupported reflection of "
"expression-based index %s" % idx["name"]
)
indexes.remove(idx)
break
else:
idx["column_names"].append(row[2])
return indexes
@reflection.cache
def _get_table_sql(self, connection, table_name, schema=None, **kw):
if schema:
schema_expr = "%s." % (
self.identifier_preparer.quote_identifier(schema)
)
else:
schema_expr = ""
try:
s = (
"SELECT sql FROM "
" (SELECT * FROM %(schema)ssqlite_master UNION ALL "
" SELECT * FROM %(schema)ssqlite_temp_master) "
"WHERE name = '%(table)s' "
"AND type = 'table'"
% {"schema": schema_expr, "table": table_name}
)
rs = connection.execute(s)
except exc.DBAPIError:
s = (
"SELECT sql FROM %(schema)ssqlite_master "
"WHERE name = '%(table)s' "
"AND type = 'table'"
% {"schema": schema_expr, "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:
statements = ["PRAGMA %s." % quote(schema)]
else:
# because PRAGMA looks in all attached databases if no schema
# given, need to specify "main" schema, however since we want
# 'temp' tables in the same namespace as 'main', need to run
# the PRAGMA twice
statements = ["PRAGMA main.", "PRAGMA temp."]
qtable = quote(table_name)
for statement in statements:
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 = []
if result:
return result
else:
return []
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