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import _jpype
from . import _jinit
from . import _jcustomizer
from . import types as _jtypes
import typing
import _jpype
import time
import threading
import datetime
# TODO
# - Callable procedures
# - Isolation levels
# - Default adaptors
# - A complete testbench
# - Testbench with more than one DB
# - Documentation
# This a generic implementation of PEP-249
__all__ = ['ARRAY', 'ASCII_STREAM', 'BIGINT', 'BINARY', 'BINARY_STREAM', 'BIT',
'BLOB', 'BOOLEAN', 'Binary', 'CHAR', 'CHARACTER_STREAM', 'CLOB',
'Connection', 'Cursor', 'DATE', 'DATETIME', 'DECIMAL', 'DOUBLE',
'DataError', 'DatabaseError', 'Date', 'DateFromTicks', 'Error',
'FLOAT', 'GETTERS_BY_NAME', 'GETTERS_BY_TYPE', 'INTEGER',
'IntegrityError', 'InterfaceError', 'InternalError', 'JDBCType',
'LONGNVARCHAR', 'LONGVARBINARY', 'LONGVARCHAR', 'NCHAR',
'NCHARACTER_STREAM', 'NCLOB', 'NULL', 'NUMBER', 'NUMERIC', 'NVARCHAR',
'NotSupportedError', 'OBJECT', 'OTHER', 'OperationalError',
'ProgrammingError', 'REAL', 'REF', 'RESULTSET', 'ROWID',
'SETTERS_BY_META', 'SETTERS_BY_TYPE', 'SMALLINT', 'SQLXML', 'STRING',
'TEXT', 'TIME', 'TIMESTAMP', 'TIMESTAMP_WITH_TIMEZONE',
'TIME_WITH_TIMEZONE', 'TINYINT', 'Time', 'TimeFromTicks', 'Timestamp',
'TimestampFromTicks', 'URL', 'VARBINARY', 'VARCHAR', 'Warning',
'apilevel', 'connect', 'paramstyle', 'threadsafety']
apilevel = "2.0"
threadsafety = 2
paramstyle = 'qmark'
_SQLException = None
_SQLTimeoutException = None
_registry = {}
_types = []
def _nop(x):
return x
###############################################################################
# Types
class JDBCType(object):
def __init__(self, name, code=None, getter=None, setter=None):
""" (internal) Create a new JDBC type. """
if isinstance(name, (str, type(None))):
self._name = name
self._values = [name]
else:
self._name = name[0]
self._values = name
self._code = code
self._getter = getter
self._setter = setter
if code is not None:
_registry[code] = self
if name is not None:
_registry[self._name.upper()] = self
_types.append(self)
if _jpype.isStarted():
java = _jpype._JPackage("java")
self._initialize(java.sql.CallableStatement, java.sql.PreparedStatement, java.sql.ResultSet)
def _initialize(self, cs, ps, rs):
""" Called after the JVM starts initialize Java resources """
if self._getter is None:
self._getter = "getObject"
self._rsget = getattr(rs, self._getter)
self._csget = getattr(cs, self._getter, None)
if self._setter is None:
self._setter = "setObject"
self._psset = getattr(ps, self._setter)
def get(self, rs, column, st):
""" A method to retrieve a specific JDBC type.
To use a getter add the fetch method to the JDBC type matching the
column type to be pulled. For example, to set the getter for FLOAT to
use the OBJECT getter, use ``cx.getter[FLOAT] = OBJECT.get``.
Not all getters are available on all database drivers. Consult the
database driver documentation for details.
"""
try:
if st:
return self._csget(rs, column)
return self._rsget(rs, column)
except _SQLException as ex:
raise InterfaceError("Unable to get '%s' using '%s'" % (self._name, self._getter)) from ex
def set(self, ps, column, value):
""" A method used to set a parameter to a query.
To use a setter place the set method in the setter dict corresponding.
For example, if the database supports Blob types, the default handler
for BLOB can be changed from OBJECT to BLOB with
``cx.setter[BLOB] = BLOB.set``.
Not all setters are available on all database drivers. Consult the
database driver documentation for details.
"""
# Set the column with the specialized method
try:
if self._psset._matches(ps, column, value):
return self._psset(ps, column, value)
# Otherwise, try to set with the generic method
return ps.setObject(column, value)
except TypeError as ex:
raise InterfaceError("Unable to convert '%s' into '%s'" % (type(value).__name__, self._name)) from ex
except OverflowError as ex:
raise InterfaceError("Unable to convert '%s' into '%s' calling '%s'" % (type(value).__name__, self._name, self._setter)) from ex
def __repr__(self):
if self._name is None:
return ""
return self._name
def __eq__(self, other):
return other in self._values
def __hash__(self):
return hash(self._name)
class _JDBCTypePrimitive(JDBCType):
def get(self, rs, column, st):
try:
if st:
rc = self._csget(rs, column)
else:
rc = self._rsget(rs, column)
if rc == 0 and rs.wasNull():
return None
return rc
except _SQLException as ex:
raise InterfaceError("Unable to get '%s' using '%s'" % (self._name, self._getter)) from ex
# From https://www.cis.upenn.edu/~bcpierce/courses/629/jdkdocs/guide/jdbc/getstart/mapping.doc.html
# DATALINK = JDBCType('DATALINK',70)
# DISTINCT= JDBCType('DISTINCT',2001)
# REF_CURSOR = JDBCType('REF_CURSOR',2012)
# STRUCT = JDBCType('STRUCT',2002)
ARRAY = JDBCType('ARRAY', 2003, 'getArray', 'setArray')
BIGINT = _JDBCTypePrimitive('BIGINT', -5, 'getLong', 'setLong')
BIT = JDBCType('BIT', -7, 'getBoolean', 'setBoolean')
BLOB = JDBCType('BLOB', 2004, 'getBlob', 'setBlob')
BOOLEAN = _JDBCTypePrimitive('BOOLEAN', 16, 'getBoolean', 'setBoolean')
CHAR = JDBCType('CHAR', 1, 'getString', 'setString')
CLOB = JDBCType('CLOB', 2005, 'getClob', 'setClob')
DATE = JDBCType('DATE', 91, 'getDate', 'setDate')
DOUBLE = _JDBCTypePrimitive('DOUBLE', 8, 'getDouble', 'setDouble')
INTEGER = _JDBCTypePrimitive('INTEGER', 4, 'getInt', 'setInt')
OBJECT = JDBCType('OBJECT', 2000)
LONGNVARCHAR = JDBCType('LONGNVARCHAR', -16, 'getString', 'setString')
LONGVARBINARY = JDBCType('LONGVARBINARY', -4, 'getBytes', 'setBytes')
LONGVARCHAR = JDBCType('LONGVARCHAR', -1, 'getString', 'setString')
NCHAR = JDBCType('NCHAR', -15, 'getString', 'setString')
NCLOB = JDBCType('NCLOB', 2011, 'getNClob', 'setNClob')
NULL = JDBCType('NULL', 0)
NUMERIC = JDBCType('NUMERIC', 2, 'getBigDecimal', 'setBigDecimal')
NVARCHAR = JDBCType('NVARCHAR', -9, 'getClob', 'setClob')
OTHER = JDBCType('OTHER', 1111)
REAL = _JDBCTypePrimitive('REAL', 7, 'getFloat', 'setFloat')
REF = JDBCType('REF', 2006, 'getRef', 'setRef')
ROWID = JDBCType('ROWID', -8, 'getRowId', 'setRowId')
RESULTSET = JDBCType('RESULTSET', -10, 'getObject', 'setObject')
SMALLINT = _JDBCTypePrimitive('SMALLINT', 5, 'getShort', 'setShort')
SQLXML = JDBCType('SQLXML', 2009, 'getSQLXML', 'setSQLXML')
TIME = JDBCType('TIME', 92, 'getTime', 'setTime')
TIME_WITH_TIMEZONE = JDBCType('TIME_WITH_TIMEZONE', 2013, 'getTime', 'setTime')
TIMESTAMP = JDBCType('TIMESTAMP', 93, 'getTimestamp', 'setTimestamp')
TIMESTAMP_WITH_TIMEZONE = JDBCType('TIMESTAMP_WITH_TIMEZONE', 2014, 'getTimestamp', 'setTimestamp')
TINYINT = _JDBCTypePrimitive('TINYINT', -6, 'getShort', 'setShort')
VARBINARY = JDBCType('VARBINARY', -3, 'getBytes', 'setBytes')
VARCHAR = JDBCType('VARCHAR', 12, 'getString', 'setString')
# Aliases required by DBAPI2
STRING = JDBCType(['STRING', 'CHAR', 'NCHAR', 'NVARCHAR', 'VARCHAR', 'OTHER'], None,
'getString', 'setString')
TEXT = JDBCType(['TEXT', 'CLOB', 'LONGVARCHAR', 'LONGNVARCHAR', 'NCLOB', 'SQLXML'], None,
'getString', 'setString')
BINARY = JDBCType(['BINARY', 'BLOB', 'LONGVARBINARY', 'VARBINARY'], -2,
'getBytes', 'setBytes')
NUMBER = JDBCType(['NUMBER', 'BOOLEAN', 'BIGINT', 'BIT', 'INTEGER', 'SMALLINT', 'TINYINT'], None,
'getObject', 'setObject')
FLOAT = _JDBCTypePrimitive(['FLOAT', 'REAL', 'DOUBLE'], 6,
'getDouble', 'setDouble')
DECIMAL = JDBCType(['DECIMAL', 'NUMERIC'], 3,
'getBigDecimal', 'setBigDecimal')
DATETIME = TIMESTAMP
# Special types
ASCII_STREAM = JDBCType(None, None, 'getAsciiStream', 'setAsciiStream')
BINARY_STREAM = JDBCType(None, None, 'getBinaryStream', 'setBinaryStream')
CHARACTER_STREAM = JDBCType(None, None, 'getCharacterStream', 'setCharacterStream')
NCHARACTER_STREAM = JDBCType(None, None, 'getNCharacterStream', 'setNCharacterStream')
URL = JDBCType(None, None, 'getURL', 'setURL')
# The converters are defined in a customizer
def _asPython(x):
return x._py()
# This maps the types reported by the columns to the type used for the getter
# and converter
_default_map = {ARRAY: OBJECT, OBJECT: OBJECT, NULL: OBJECT,
REF: OBJECT, ROWID: OBJECT, RESULTSET: OBJECT,
TIME_WITH_TIMEZONE: OBJECT, TIMESTAMP_WITH_TIMEZONE: OBJECT,
NVARCHAR: STRING, CHAR: STRING,
NCHAR: STRING, VARCHAR: STRING, BINARY: BINARY,
BLOB: BINARY, LONGVARBINARY: BINARY, VARBINARY: BINARY,
NUMBER: NUMBER, BOOLEAN: BOOLEAN, BIGINT: BIGINT,
BIT: BIT, INTEGER: INTEGER, SMALLINT: SMALLINT,
TINYINT: TINYINT, FLOAT: FLOAT, REAL: REAL,
DECIMAL: DECIMAL, NUMERIC: NUMERIC,
DATE: DATE, TIMESTAMP: TIMESTAMP, TIME: TIME,
CLOB: STRING, NCLOB: STRING, STRING: STRING,
TEXT: STRING, SQLXML: STRING, LONGVARCHAR: STRING,
LONGNVARCHAR: STRING, DOUBLE: DOUBLE, OTHER: OBJECT
}
_default_setters = {} # type: ignore[var-annotated]
_default_converters = {} # type: ignore[var-annotated]
_default_adapters = {} # type: ignore[var-annotated]
# Setters take (connection, meta, col, type) -> JDBCTYPE
def SETTERS_BY_META(cx, meta, col, ptype):
""" Option for setters to use the metadata of the parameters.
On some databases this option is useless as they do not track parameter
types. This method can be cached for faster performance when lots of
parameters. Usually types can only be determined accurately on inserts
into defined columns.
"""
return _default_map[_registry[meta.getParameterType(col + 1)]]
SETTERS_BY_META._cachable = True # type: ignore[attr-defined]
def SETTERS_BY_TYPE(cx, meta, col, ptype):
""" Option for setters to use the type of the object passed.
This option looks at the type of the parameter being passed
from Python after adapters have been applied to determine the
best setter.
"""
return _default_setters.get(ptype, None)
# Getters take (connection, meta, col) -> JDBCTYPE
def GETTERS_BY_TYPE(cx, meta, idx):
""" Option for getters to determine column type by the JDBC type.
This option is the default option that uses the type code supplied in
the meta data. On some databases it is better to use the name.
If the type code is OTHER, it will attempt to find a type by name.
New types can be created with JDBCType for database specific types.
"""
tp = _registry[meta.getColumnType(idx + 1)]
if tp == OTHER:
# Other may be found by name
name = str(meta.getColumnTypeName(idx + 1)).upper()
return _registry.get(name, tp)
return _default_map[tp]
def GETTERS_BY_NAME(cx, meta, idx):
""" Option to getters to determine column type by the column name.
This option uses the column name to select the type. It looks up
the column type name, converts it to uppercase, and then searches
for a matchine type. It falls back to the type code meta information if
the typename can not be found in the registery. New types can be created
using JDBCType for database specific types such as ``JSON``.
"""
name = str(meta.getColumnTypeName(idx + 1)).upper()
tp = _registry.get(name, None)
if tp is None:
tp = _registry[meta.getColumnType(idx + 1)]
return _default_map.get(tp, tp)
###############################################################################
# Exceptions
class Warning(Exception):
"""Exception raised for important warnings like data truncations while
inserting, etc. """
pass
class Error(Exception):
"""Exception that is the base class of all other error exceptions. You can use
this to catch all errors with one single except statement. Warnings are not
considered errors and thus should not use this class as base.
"""
pass
class InterfaceError(Error, TypeError):
""" Exception raised for errors that are related to the database interface
rather than the database itself."""
pass
class DatabaseError(Error):
""" Exception raised for errors that are related to the database."""
pass
class DataError(DatabaseError):
""" Exception raised for errors that are due to problems with the processed
data like division by zero, numeric value out of range, etc."""
pass
class OperationalError(DatabaseError):
""" Exception raised for errors that are related to the database's operation
and not necessarily under the control of the programmer, e.g. an unexpected
disconnect occurs, the data source name is not found, a transaction could not
be processed, a memory allocation error occurred during processing, etc."""
pass
class IntegrityError(DatabaseError):
""" Exception raised when the relational integrity of the database is affected,
e.g. a foreign key check fails."""
pass
class InternalError(DatabaseError):
""" Exception raised when the database encounters an internal error, e.g. the
cursor is not valid anymore, the transaction is out of sync, etc."""
pass
class ProgrammingError(DatabaseError):
""" Exception raised for programming errors, e.g. table not found or already
exists, syntax error in the SQL statement, wrong number of parameters
specified, etc."""
pass
class NotSupportedError(DatabaseError):
""" Exception raised in case a method or database API was used which is not
supported by the database, e.g. requesting a .rollback() on a connection that
does not support transaction or has transactions turned off.
"""
pass
class _UnsupportedTypeError(InterfaceError, TypeError):
pass
###############################################################################
# Connection
_default = object()
def connect(dsn, *, driver=None, driver_args=None,
adapters=_default, converters=_default,
getters=GETTERS_BY_TYPE, setters=SETTERS_BY_TYPE, **kwargs):
""" Create a connection to a database.
Arguments to the driver depend on the database type.
Args:
dsn (str): The database connection string for JDBC.
driver (str, optional): A JDBC driver to load.
driver_args: Arguments to the driver. This may either be a dict,
java.util.Properties. If not supplied, kwargs are used as as the
parameters for the JDBC connection.
*kwargs: Arguments to the driver if not supplied as
driver_args.
Raises:
Error if the connection cannot be established.
Returns:
A new connection if successful.
"""
Properties = _jpype.JClass("java.util.Properties")
if driver:
_jpype.JClass('java.lang.Class').forName(driver).newInstance()
DM = _jpype.JClass('java.sql.DriverManager')
# User is supplying Java properties
if isinstance(driver_args, Properties):
connection = DM.getConnection(dsn, driver_args)
# User is supplying a mapping that can be converted Properties
elif isinstance(driver_args, typing.Mapping):
info = Properties()
for k, v in driver_args.items():
info.setProperty(k, v)
connection = DM.getConnection(dsn, info)
# User supplied nothing
elif driver_args is None:
connection = DM.getConnection(dsn)
# Otherwise use the kwargs
else:
info = Properties()
for k, v in kwargs.items():
info.setProperty(k, v)
connection = DM.getConnection(url, info)
return Connection(connection, adapters, converters, setters, getters)
class Connection(object):
""" Connection provides access to a JDBC database.
Connections are managed and can be as part of a Python with statement.
Connections close automatically when they are garbage collected, at the
end of a with statement scope, or when manually closed. Once a connection
is closed all operations using the database will raise an Error.
"""
Error = Error
Warning = Warning
InterfaceError = InterfaceError
DatabaseError = DatabaseError
InternalError = InternalError
OperationalError = OperationalError
ProgrammingError = ProgrammingError
IntegrityError = IntegrityError
DataError = DataError
NotSupportedError = NotSupportedError
def __init__(self, jconnection, adapters, converters, setters, getters):
self._jcx = jconnection
# Required by PEP 249
# https://www.python.org/dev/peps/pep-0249/#commit
try:
# Some driver do not support this feature.
# https://github.com/jpype-project/jpype/issues/1003
self._jcx.setAutoCommit(False)
except Exception as ex:
if ex.getClass().getSimpleName() != 'SQLFeatureNotSupportedException':
raise ex
# Handle defaults
if adapters is _default:
adapters = dict(_default_adapters)
if adapters is None:
adapters = {}
if converters is _default:
converters = dict(_default_converters)
if converters is None:
converters = {}
self._closed = False
self._batch = jconnection.getMetaData().supportsBatchUpdates()
self._adapters = adapters
self._converters = converters
self._getters = getters
self._setters = setters
@property
def adapters(self):
""" Adapters are used to convert Python types into JDBC types.
Adaptors are stored in a mapping from incoming type to an adapter
function. Adapters set on a connection apply only to that connection.
Adapters can be overriden when calling the ``.execute*()`` method.
Adapters can also be set on the JDBC types directly.
"""
return self._adapters
@adapters.setter
def adapters(self, v):
if v is None:
v = {}
if not isinstance(v, typing.Mapping):
raise _UnsupportedTypeError("Mapping is required")
self._adapters = v
@property
def converters(self):
""" Converters are applied when retrieving a JDBC type from the database.
"""
return self._converters
@converters.setter
def converters(self, v):
if v is None:
v = {}
if not isinstance(v, typing.Mapping):
raise _UnsupportedTypeError("Mapping is required")
self._converters = v
@property
def getters(self):
""" Getters are used to retrieve JDBC types from the database following
a ``.fetch*()``.
Getters should be a function taking (connection, meta, col) -> JDBCTYPE
"""
return self._getters
# Setters take (connection, meta, col, type) -> JDBCTYPE
@getters.setter
def getters(self, v):
self._getters = v
@property
def setters(self):
""" Setter are used to set parameters to ``.execute*()`` methods.
Setters should be a function taking (connection, meta, col, type) -> JDBCTYPE
"""
return self._setters
@setters.setter
def setters(self, v):
self._setters = v
def __setattr__(self, name, value):
if isinstance(vars(type(self)).get(name, None), property):
return object.__setattr__(self, name, value)
if not name.startswith("_"):
raise AttributeError("'%s' cannot be set" % name)
object.__setattr__(self, name, value)
def _close(self):
if self._closed or not _jpype.isStarted():
return
if not self._jcx.isClosed():
self._jcx.close()
self._closed = True
def __enter__(self):
return self
def __exit__(self, exception_type, exception_value, traceback):
self._close()
def __del__(self):
try:
self._close()
except Exception: # pragma: no cover
pass
def close(self):
""" Close the connection immediately (rather than whenever .__del__() is called).
The connection will be unusable from this point forward; an Error (or
subclass) exception will be raised if any operation is attempted with
the connection. The same applies to all cursor objects trying to use
the connection. Note that closing a connection without committing the
changes first will cause an implicit rollback to be performed. """
self._validate()
self._close()
def commit(self):
"""Commit any pending transaction to the database.
Calling commit on a cooonection that does not support the operation
will raise NotSupportedError.
"""
self._validate()
if self._jcx.getAutoCommit():
raise NotSupportedError("Autocommit is enabled")
try:
self._jcx.commit()
except Exception as ex: # pragma: no cover
raise OperationalError(ex.message()) from ex
def rollback(self):
"""Rollback the transaction.
This method is optional since not all databases provide transaction
support. Calling rollback on a cooonection that does not support will
raise NotSupportedError.
In case a database does provide transactions this method causes the
database to roll back to the start of any pending transaction. Closing
a connection without committing the changes first will cause an
implicit rollback to be performed.
"""
self._validate()
if self._jcx.getAutoCommit():
raise NotSupportedError("Autocommit is enabled", self.autocommit)
try:
self._jcx.rollback()
except Exception as ex: # pragma: no cover
raise OperationalError(ex.message()) from ex
def cursor(self):
""" Return a new Cursor Object using the connection. """
self._validate()
return Cursor(self)
def _validate(self):
if self._closed or self._jcx.isClosed():
raise ProgrammingError
@property
def connection(self):
""" Get the JDBC connection that is backing this Python
Connection object.
This can be used to retrieve additional metadata and other features
that are outside of the scope of the DBAPI driver.
"""
return self._jcx
@property
def autocommit(self):
""" bool: Property controlling autocommit behavior.
By default connects are not autocommit. Setting autocommit
will result in commit and rollback producing a ProgrammingError.
"""
self._validate()
return self._jcx.getAutoCommit()
@autocommit.setter
def autocommit(self, enabled):
self._validate()
self._jcx.setAutoCommit(enabled)
@property
def typeinfo(self):
""" list: The list of types that are supported by this driver.
This is useful to find out the capabilities of the driver.
"""
self._validate()
out = {}
metadata = self._jcx.getMetaData()
with metadata.getTypeInfo() as resultSet:
while (resultSet.next()):
try:
key = str(resultSet.getString("TYPE_NAME"))
out[key] = _registry[resultSet.getInt("DATA_TYPE")]
except KeyError as ex: # pragma: no cover
raise DatabaseError("Unknown data type '%s'" % key) from ex
return out
###############################################################################
# Cursor
class Cursor(object):
""" Cursors are used to execute queries and retrieve results.
Part PreparedStatement, part ResultSet, Cursors are a mixture of
both. The native resultSet can be accessed with ``resultSet``.
Cursors are managed and can be as part of a Python with statement.
Cursors close automatically when they are garbage collected, at the
end of a with statement scope, or when manually closed. Once a cursor
is closed all operations using the database will raise an Error.
"""
def __init__(self, connection):
if not isinstance(connection, Connection):
raise TypeError
self._connection = connection
self._jcx = connection._jcx
self._resultSet = None
self._statement = None
self._rowcount = -1
self._arraysize = 1
self._description = None
self._closed = False
self._resultGetters = None
self._thread = threading.get_ident()
self._last = None
def _close(self):
if self._closed or not _jpype.isStarted():
return
self._finish()
self._closed = True
def _setParams(self, params):
cx = self._connection
meta = self._statement.getParameterMetaData()
count = meta.getParameterCount()
types = self._parameterTypes
if types is None:
types = [None] * count
if isinstance(params, str):
raise _UnsupportedTypeError("parameters must be a sequence of values")
if isinstance(params, typing.Sequence):
if count != len(params):
raise ProgrammingError("incorrect number of parameters (%d!=%d)"
% (count, len(params)))
for i in range(len(params)):
p = params[i]
# Find and apply the adapter
a = cx._adapters.get(type(p), None)
if a is not None:
p = a(p)
# Find the setter
if types[i] is None:
s = cx._setters(cx, meta, i, type(p))
types[i] = s
if s is None:
raise _UnsupportedTypeError("no setter found for '%s'" % type(p).__name__)
s.set(self._statement, i + 1, p)
# Cache
if hasattr(cx._setters, "_cachable"):
self._parameterTypes = types
elif isinstance(params, typing.Mapping):
raise _UnsupportedTypeError("mapping parameters not supported")
elif isinstance(params, typing.Iterable):
for i, p in enumerate(params):
if i >= count:
raise ProgrammingError("incorrect number of parameters (%d!=%d)" % (count, i + 1))
# Find and apply the adapter
a = cx._adapters.get(type(p), None)
if a is not None:
p = a(p)
# Find the setter
if types[i] is None:
s = cx._setters(cx, meta, i, type(p))
types[i] = s
if s is None:
raise _UnsupportedTypeError("no setter found for '%s'" % type(p).__name__)
s.set(self._statement, i + 1, p)
if count != i + 1:
raise ProgrammingError("incorrect number of parameters (%d!=%d)" % (count, i + 1))
# Cache
if hasattr(cx._setters, "_cachable"):
self._parameterTypes = types
else:
raise _UnsupportedTypeError("'%s' parameters not supported" % (type(params).__name__)) # pragma: no cover
def _onResultSet(self, rs):
meta = rs.getMetaData()
self._resultSet = rs
self._resultSetMeta = meta
self._resultSetCount = meta.getColumnCount()
self._columnTypes = None
def _fetchRow(self, converters):
cx = self._connection
count = self._resultSetCount
meta = self._resultSetMeta
byPosition = False
if converters is _default:
converters = cx._converters
if isinstance(converters, typing.Sequence):
if len(converters) != count:
raise ProgrammingError("converter list size incorrect")
byPosition = True
# Get all the column types
if self._columnTypes is None:
gk = cx._getters
# We need the type information for the columns
self._columnTypes = [gk(cx, meta, i) for i in range(count)]
if len(self._columnTypes) != count:
raise ProgrammingError("incorrect number of columns")
try:
row = []
for idx in range(count):
tp = self._columnTypes[idx]
# Fetch the value
value = tp.get(self._resultSet, idx + 1, False)
if value is None or converters is None:
row.append(value)
elif byPosition:
# find the column converter by type
converter = converters[idx]
row.append(converter(value))
else:
# find the column converter by type
converter = cx._converters.get(type(value), _nop)
row.append(converter(value))
return row
except TypeError as ex:
raise _UnsupportedTypeError(str(ex)) from ex
def _validate(self):
""" Called before any method that requires the statement to be open. """
if self._closed or self._jcx.isClosed():
raise ProgrammingError("Cursor is closed")
if threading.get_ident() != self._thread:
raise ProgrammingError("Threading error")
def _check_executed(self):
""" Called before any method that requires the resultSet to be open. """
if self._closed or self._jcx.isClosed() or threading.get_ident() != self._thread:
raise ProgrammingError("Cursor is closed")
if self._resultSet is None:
raise ProgrammingError("execute() first")
def _finish(self):
if self._resultSet is not None:
self._resultSet.close()
self._resultSet = None
if self._statement is not None:
self._statement.close()
self._statement = None
self._rowcount = -1
self._description = None
self._last = None
@property
def resultSet(self):
""" Get the Java result set if available.
The object will be closed on the next call to ``.execute*()``.
"""
return self._resultSet
@property
def parameters(self):
""" (extension) Parameters is read-only attribute is a sequence of
6-item sequences.
Each of these sequences contains information describing one result
column:
- type_name
- jdbc_type
- parameter_mode (1=in, 2=in/out, 4=out)
- precision
- scale
- null_ok
This can only be used after execute or callproc.
"""
desc = []
if not self._statement:
raise ProgrammingError("No statement")
meta = self._statement.getParameterMetaData()
for i in range(1, meta.getParameterCount() + 1):
desc.append((str(meta.getParameterTypeName(i)),
_registry[meta.getParameterType(i)],
meta.getParameterMode(i),
meta.getPrecision(i),
meta.getScale(i),
meta.isNullable(i),))
return desc
@property
def description(self):
""" Description is read-only attribute is a sequence of 7-item
sequences.
Each of these sequences contains information describing one result
column:
- name
- type_code
- display_size
- internal_size
- precision
- scale
- null_ok
This can only be used if the last query produced a result set.
"""
if self._description is not None:
return self._description
desc = []
if not self._resultSet:
return None
meta = self._resultSet.getMetaData()
for i in range(1, meta.getColumnCount() + 1):
size = meta.getColumnDisplaySize(i)
desc.append((str(meta.getColumnName(i)),
str(meta.getColumnTypeName(i)),
size,
size,
meta.getPrecision(i),
meta.getScale(i),
meta.isNullable(i),))
self._description = desc
return desc
@property
def rowcount(self):
""" This read-only attribute specifies the number of rows that the last
.execute*() affected (for DML statements like UPDATE or INSERT).
The attribute is -1 in case no .execute*() has been performed on the
cursor or the rowcount of the last operation is cannot be determined by
the interface. JDBC does not support getting the number of rows
returned from SELECT, so for most drivers rowcount will be -1 after a
SELECT statement.
"""
return self._rowcount
def close(self):
""" Close the cursor now (rather than whenever __del__ is called).
The cursor will be unusable from this point forward; an Error (or
subclass) exception will be raised if any operation is attempted with
the cursor.
"""
self._validate()
self._close()
def callproc(self, procname, parameters=(), *, types=None):
""" Call a stored procedure.
(Not all JDBC drivers support this method)
Call a stored database procedure with the given name. The sequence of
parameters must contain one entry for each argument that the procedure
expects. The result of the call is returned as modified copy of the
input sequence. Input parameters are left untouched, output and
input/output parameters replaced with possibly new values.
For type output and input/output arguments, it is best to use
types keyword argument to select the appropriate getters for the
returned arguments. Converters are applied to output parameters.
The procedure may also provide a result set as output. This must then
be made available through the standard .fetch*() methods.
"""
try:
self._validate()
self._finish()
if not isinstance(procname, str):
raise _UnsupportedTypeError("procname must be str, not '%s'" % type(procname).__name__)
if not isinstance(parameters, typing.Sequence):
raise _UnsupportedTypeError("parameters must be sequence, not '%s'" % type(procname).__name__)
query = "{CALL %s(%s)}" % (procname, ",".join("?" * len(parameters)))
try:
self._statement = self._jcx.prepareCall(query)
except _SQLException as ex:
raise ProgrammingError(ex.message()) from ex
# This is a special one as we need to deal with in and out arguments
out = list(parameters)
cx = self._connection
meta = self._statement.getParameterMetaData()
count = meta.getParameterCount()
if types is None:
types = [None] * count
else:
if len(types) != count:
raise ProgrammingError("expected '%d' types, got '%d'" % (count, len(types)))
for i in range(count):
# Lookup the JDBC Type
p = parameters[i]
a = cx._adapters.get(type(p), None)
if a is not None:
p = a(p)
if types[i] is None:
types[i] = cx._setters(cx, meta, i, type(p))
jdbcType = types[i]
if jdbcType is None:
raise _UnsupportedTypeError("no setter found for '%s'" % type(p).__name__)
mode = meta.getParameterMode(i + 1)
if mode == 1:
jdbcType.set(self._statement, i + 1, p)
types[i] = None
if mode == 2:
jdbcType.set(self._statement, i + 1, p)
self.registerOutParameter(i + 1, jdbcType._code)
if mode == 4:
self.registerOutParameter(i + 1, jdbcType._code)
if self._statement.execute():
self._onResultSet(self._statement.getResultSet())
self._rowcount = self._statement.getUpdateCount()
for i, t in enumerate(types):
if t is None:
continue
# Find the converter to apply to the column
value = t.get(self._statement, i + 1, True)
# FIXME how do we get a converv
converter = cx._converters[type(value)]
out[i] = converter(value)
return out
# Restore the defaults
except Exception as ex:
self._converters = self._connection._converters
self._getters = self._connection._getters
raise ex
finally:
self._adapters = self._connection._adapters
self._setters = self._connection._setters
def execute(self, operation, parameters=None, *, types=None, keys=False):
"""
Prepare and execute a database operation (query or command).
Parameters may be provided as sequence and will be bound to variables
in the operation. Variables are specified in a qmark notation. JDBC
does not support mapping style parameters.
After executing a statement, the rowcount will be updated. If the
statement has no result set then the rowcount will be -1. A statement
can produce multiple result sets. Use ``.nextset()`` to traverse the
sets.
Parameters:
operation (str): A statement to be executed.
parameters (list, optional): A list of parameters for the statement.
The number of parameters much match the number required by the
statement or an Error will be raised.
keys (bool, optional): Specify if the keys should be available to
retrieve. (Default False)
Returns:
This cursor.
"""
self._last = None
self._parameterTypes = types
self._validate()
self._finish()
if parameters is None:
parameters = ()
if not isinstance(parameters, (typing.Sequence, typing.Iterable, typing.Iterator)):
raise _UnsupportedTypeError("parameters are of unsupported type '%s'" % type(parameters).__name__)
# complete the previous operation
try:
if keys:
self._statement = self._jcx.prepareStatement(operation, 1)
else:
self._statement = self._jcx.prepareStatement(operation)
except TypeError as ex:
raise _UnsupportedTypeError(str(ex))
except _SQLException as ex:
raise ProgrammingError(ex.message()) from ex
self._executeone(parameters)
return self
def _executeone(self, params):
self._setParams(params)
if self._statement.execute():
self._onResultSet(self._statement.getResultSet())
self._rowcount = self._statement.getUpdateCount()
return self._rowcount
def executemany(self, operation, seq_of_parameters, *, types=None, keys=False):
"""
Prepare a database operation (query or command) and then execute it
against all parameter sequences or mappings found in the sequence
seq_of_parameters.
Modules are free to implement this method using multiple calls to the
.execute() method or by using array operations to have the database
process the sequence as a whole in one call.
Use of this method for an operation which produces one or more result
sets constitutes undefined behavior, and the implementation is
permitted (but not required) to raise an exception when it detects that
a result set has been created by an invocation of the operation.
The same comments as for .execute() also apply accordingly to this
method.
Args:
operation (str): A statement to be executed.
seq_of_parameters (list, optional): A list of lists of parameters
for the statement. The number of parameters much match the number
required by the statement or an Error will be raised.
keys (bool, optional): Specify if the keys should be available to
retrieve. (Default False) For drivers that do not support
batch updates only that last key will be returned.
Returns:
This cursor.
"""
self._last = None
self._parameterTypes = types
self._validate()
if seq_of_parameters is None:
seq_of_parameters = ()
# complete the previous operation
self._finish()
try:
if keys:
self._statement = self._jcx.prepareStatement(operation, 1)
else:
self._statement = self._jcx.prepareStatement(operation)
except TypeError as ex:
raise _UnsupportedTypeError(str(ex))
except _SQLException as ex:
raise ProgrammingError("Failed to prepare '%s'" % operation) from ex
if self._connection._batch:
return self._executeBatch(seq_of_parameters)
else: # pragma: no cover
return self._executeRepeat(seq_of_parameters)
def _executeBatch(self, seq_of_parameters):
if isinstance(seq_of_parameters, typing.Iterable):
for params in seq_of_parameters:
self._setParams(params)
self._statement.addBatch()
else:
raise _UnsupportedTypeError("'%s' is not supported" % type(seq_of_parameters).__name__)
try:
counts = self._statement.executeBatch()
except _SQLException as ex: # pragma: no cover
raise ProgrammingError(ex.message()) from ex
self._rowcount = sum(counts)
if self._rowcount < 0: # pragma: no cover
self._rowcount = -1
return self
def _executeRepeat(self, seq_of_parameters): # pragma: no cover
counts = []
if isinstance(seq_of_parameters, typing.Iterable):
for params in seq_of_parameters:
counts.append(self._executeone(params))
elif isinstance(seq_of_parameters, typing.Iterator):
while True:
try:
params = next(seq_of_parameters)
counts.append(self._executeone(params))
except StopIteration:
break
else:
raise _UnsupportedTypeError("'%s' is not supported" % str(type(seq_of_parameters)))
self._rowcount = sum(counts)
if self._rowcount < 0:
self._rowcount = -1
return self
def fetchone(self, *, types=None, converters=_default):
"""
Fetch the next row of a query result set, returning a single
sequence, or None when no more data is available.
An Error (or subclass) exception is raised if the previous call to
.execute*() did not produce any result set or no call was issued yet.
"""
self._check_executed()
if not self._resultSet.next():
return None
if types is not None:
self._columnTypes = types
return self._fetchRow(converters)
def fetchmany(self, size=None, *, types=None, converters=_default):
""" Fetch multiple results.
Fetch the next set of rows of a query result, returning a sequence of
sequences (e.g. a list of tuples). An empty sequence is returned when
no more rows are available.
The number of rows to fetch per call is specified by the parameter. If it
is not given, the cursor's arraysize determines the number of rows to be
fetched. The method should try to fetch as many rows as indicated by the
size parameter. If this is not possible due to the specified number of rows
not being available, fewer rows may be returned.
An Error (or subclass) exception is raised if the previous call to
``.execute*()`` did not produce any result set or no call was issued yet.
Note there are performance considerations involved with the size parameter.
For optimal performance, it is usually best to use the .arraysize
attribute. If the size parameter is used, then it is best for it to retain
the same value from one ``.fetchmany()`` call to the next.
"""
self._check_executed()
if size is None:
size = self._arraysize
# Set a fetch size
self._resultSet.setFetchSize(size)
rows = []
if types is not None:
self._columnTypes = types
for i in range(size):
if not self._resultSet.next():
break
row = self._fetchRow(converters)
rows.append(row)
# Restore the default fetch size
self._resultSet.setFetchSize(0)
return rows
def fetchall(self, *, types=None, converters=_default):
""" Fetch all (remaining) rows of a query result, returning them as
a sequence of sequences (e.g. a list of tuples). Note that the cursor's
arraysize attribute can affect the performance of this operation.
An Error (or subclass) exception is raised if the previous call to
``.execute*()`` did not produce any result set or no call was issued yet.
"""
self._check_executed()
# Set a fetch size
rows = []
if types is not None:
self._columnTypes = types
while self._resultSet.next():
row = self._fetchRow(converters)
rows.append(row)
return rows
def __iter__(self):
""" (extension) Iterate through a cursor one record at a time.
"""
self._check_executed()
# Set a fetch size
while self._resultSet.next():
yield self._fetchRow(_default)
def nextset(self):
""" Get the next result set in this cursor.
Not all databases support multiple result sets.
This method will make the cursor skip to the next available set, discarding
any remaining rows from the current set.
If there are no more sets, the method returns None. Otherwise, it returns a
true value and subsequent calls to the ``.fetch*()`` methods will return rows
from the next result set.
An Error (or subclass) exception is raised if the previous call to
``.execute*()`` did not produce any result set or no call was issued yet.
"""
self._resultSet.close()
if self._statement.getMoreResults(): # pragma: no cover
self._onResultSet(_statement.getResultSet())
return True
else:
self._rowcount = self._statement.getUpdateCount()
return None
@property
def arraysize(self):
"""
Specify the number of rows to fetch with ``.fetchmany()``.
This read/write attribute specifies the number of rows to fetch
at a time with ``.fetchmany()``. It defaults to 1 meaning to fetch a single row
at a time.
"""
return self._arraysize
@arraysize.setter
def arraysize(self, sz):
self._arraysize = sz
@property
def lastrowid(self):
""" Get the id of the last row inserted.
This is not supported on all JDBC drivers. The ``.execute*()`` must have
been executed with keys set to True.
Returns:
None if there is no rowid, the rowid if only one row was inserted,
or a list of row ids if multiple rows were inserted.
"""
if self._last is not None:
return self._last
with self._statement.getGeneratedKeys() as rs:
if rs.isClosed():
return self._last
last = []
while rs.next():
last.append(rs.getLong(1))
if len(last) == 0:
return None
if len(last) == 1:
self._last = last[0]
return last[0]
self._last = last
return last
def setinputsizes(self, sizes):
""" This can be used before a call to .execute*() to
predefine memory areas for the operation's parameters.
sizes is specified as a sequence — one item for each input parameter. The
item should be a Type Object that corresponds to the input that will be
used, or it should be an integer specifying the maximum length of a string
parameter. If the item is None, then no predefined memory area will be
reserved for that column (this is useful to avoid predefined areas for
large inputs).
This method would be used before the .execute*() method is invoked.
(not implemented)
"""
pass
def setoutputsize(self, size, column=None):
"""
Set a column buffer size for fetches of large columns (e.g. LONGs, BLOBs, etc.).
The column is specified as an index into the result sequence. Not
specifying the column will set the default size for all large columns
in the cursor.
(not implemented)
"""
pass
def __del__(self):
try:
self._close()
except Exception: # pragma: no cover
pass
def __enter__(self):
return self
def __exit__(self, exception_type, exception_value, traceback):
self._close()
###############################################################################
# Factories
def Date(year, month, day):
""" This function constructs an object holding a date value. """
return _jpype.JClass('java.sql.Date')(year - 1900, month - 1, day)
def Time(hour, minute, second):
""" This function constructs an object holding a time value. """
return _jpype.JClass('java.sql.Time')(hour, minute, second)
def Timestamp(year, month, day, hour, minute, second, nano=0):
""" This function constructs an object holding a time stamp value. """
return _jpype.JClass('java.sql.Timestamp')(year - 1900, month - 1, day, hour, minute, second, nano)
def DateFromTicks(ticks):
"""
This function constructs an object holding a date value from the given
ticks value (number of seconds since the epoch; see the documentation of
the standard Python time module for details).
"""
return Date(*time.localtime(ticks)[:3])
def TimeFromTicks(ticks):
"""
This function constructs an object holding a time value from the given
ticks value (number of seconds since the epoch; see the documentation of
the standard Python time module for details).
"""
return Time(*time.localtime(ticks)[3:6])
def TimestampFromTicks(ticks):
"""
This function constructs an object holding a time stamp value from the
given ticks value (number of seconds since the epoch; see the documentation
of the standard Python time module for details).
"""
return Timestamp(*time.localtime(ticks)[:6])
def Binary(data):
"""
This function constructs an object capable of holding a binary (long)
string value.
"""
return _jtypes.JArray(_jtypes.JByte)(data)
# SQL NULL values are represented by the Python None singleton on input and output.
_accepted = set(["exact", "implicit"])
def _populateTypes():
global _SQLException, _SQLTimeoutException
_SQLException = _jpype.JClass("java.sql.SQLException")
_SQLTimeoutException = _jpype.JClass("java.sql.SQLTimeoutException")
cs = _jpype.JClass("java.sql.CallableStatement")
ps = _jpype.JClass("java.sql.PreparedStatement")
rs = _jpype.JClass("java.sql.ResultSet")
for v in _types:
v._initialize(cs, ps, rs)
java = _jpype._JPackage("java")
byteArray = _jpype.JArray(_jtypes.JByte)
_default_setters[java.lang.String] = STRING
_default_setters[java.sql.Date] = DATE
_default_setters[java.sql.Time] = TIME
_default_setters[java.sql.Timestamp] = TIMESTAMP
_default_setters[byteArray] = BINARY
_default_setters[java.math.BigDecimal] = DECIMAL
_default_setters[_jtypes.JFloat] = REAL
_default_setters[_jtypes.JDouble] = DOUBLE
_default_setters[_jtypes.JBoolean] = BOOLEAN
_default_setters[_jtypes.JShort] = INTEGER
_default_setters[_jtypes.JInt] = INTEGER
_default_setters[_jtypes.JLong] = BIGINT
_default_setters[bool] = BOOLEAN
_default_setters[int] = BIGINT
_default_setters[float] = DOUBLE
_default_setters[str] = STRING
_default_setters[memoryview] = BINARY
_default_setters[bytes] = BINARY
_default_setters[bytearray] = BINARY
_default_setters[type(None)] = OBJECT
_default_setters[java.sql.Clob] = CLOB
_default_setters[java.sql.Blob] = BLOB
_default_setters[datetime.datetime] = TIMESTAMP
_default_setters[datetime.date] = DATE
_default_setters[datetime.time] = TIME
_default_converters[java.lang.String] = str
_default_converters[java.sql.Date] = _asPython
_default_converters[java.sql.Time] = _asPython
_default_converters[java.sql.Timestamp] = _asPython
_default_converters[java.math.BigDecimal] = _asPython
_default_converters[byteArray] = bytes
_default_converters[type(None)] = _nop
# Adaptors can be installed after the JVM is started
# JByteArray = _jpype.JArray(_jtypes.JByte)
# VARCHAR.adapters[memoryview] = JByteArray
_jcustomizer.getClassHints("java.sql.SQLException").registerClassBase(Error)
_jinit.registerJVMInitializer(_populateTypes)
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