Viewing file:  processors.py (5.09 KB) -rw-r--r--
Select action/file-type:
 (+) |  (+) |  (+) | Code (+) | Session (+) |  (+) | SDB (+) |  (+) |  (+) |  (+) |  (+) |  (+) |
# sqlalchemy/processors.py
# Copyright (C) 2010-2017 the SQLAlchemy authors and contributors
# <see AUTHORS file>
# Copyright (C) 2010 Gaetan de Menten gdementen@gmail.com
#
# This module is part of SQLAlchemy and is released under
# the MIT License: http://www.opensource.org/licenses/mit-license.php
"""defines generic type conversion functions, as used in bind and result
processors.
They all share one common characteristic: None is passed through unchanged.
"""
import codecs
import re
import datetime
from . import util
def str_to_datetime_processor_factory(regexp, type_):
rmatch = regexp.match
# Even on python2.6 datetime.strptime is both slower than this code
# and it does not support microseconds.
has_named_groups = bool(regexp.groupindex)
def process(value):
if value is None:
return None
else:
try:
m = rmatch(value)
except TypeError:
raise ValueError("Couldn't parse %s string '%r' "
"- value is not a string." %
(type_.__name__, value))
if m is None:
raise ValueError("Couldn't parse %s string: "
"'%s'" % (type_.__name__, value))
if has_named_groups:
groups = m.groupdict(0)
return type_(**dict(list(zip(
iter(groups.keys()),
list(map(int, iter(groups.values())))
))))
else:
return type_(*list(map(int, m.groups(0))))
return process
def boolean_to_int(value):
if value is None:
return None
else:
return int(bool(value))
def py_fallback():
def to_unicode_processor_factory(encoding, errors=None):
decoder = codecs.getdecoder(encoding)
def process(value):
if value is None:
return None
else:
# decoder returns a tuple: (value, len). Simply dropping the
# len part is safe: it is done that way in the normal
# 'xx'.decode(encoding) code path.
return decoder(value, errors)[0]
return process
def to_conditional_unicode_processor_factory(encoding, errors=None):
decoder = codecs.getdecoder(encoding)
def process(value):
if value is None:
return None
elif isinstance(value, util.text_type):
return value
else:
# decoder returns a tuple: (value, len). Simply dropping the
# len part is safe: it is done that way in the normal
# 'xx'.decode(encoding) code path.
return decoder(value, errors)[0]
return process
def to_decimal_processor_factory(target_class, scale):
fstring = "%%.%df" % scale
def process(value):
if value is None:
return None
else:
return target_class(fstring % value)
return process
def to_float(value):
if value is None:
return None
else:
return float(value)
def to_str(value):
if value is None:
return None
else:
return str(value)
def int_to_boolean(value):
if value is None:
return None
else:
return bool(value)
DATETIME_RE = re.compile(
r"(\d+)-(\d+)-(\d+) (\d+):(\d+):(\d+)(?:\.(\d+))?")
TIME_RE = re.compile(r"(\d+):(\d+):(\d+)(?:\.(\d+))?")
DATE_RE = re.compile(r"(\d+)-(\d+)-(\d+)")
str_to_datetime = str_to_datetime_processor_factory(DATETIME_RE,
datetime.datetime)
str_to_time = str_to_datetime_processor_factory(TIME_RE, datetime.time)
str_to_date = str_to_datetime_processor_factory(DATE_RE, datetime.date)
return locals()
try:
from sqlalchemy.cprocessors import UnicodeResultProcessor, \
DecimalResultProcessor, \
to_float, to_str, int_to_boolean, \
str_to_datetime, str_to_time, \
str_to_date
def to_unicode_processor_factory(encoding, errors=None):
if errors is not None:
return UnicodeResultProcessor(encoding, errors).process
else:
return UnicodeResultProcessor(encoding).process
def to_conditional_unicode_processor_factory(encoding, errors=None):
if errors is not None:
return UnicodeResultProcessor(encoding, errors).conditional_process
else:
return UnicodeResultProcessor(encoding).conditional_process
def to_decimal_processor_factory(target_class, scale):
# Note that the scale argument is not taken into account for integer
# values in the C implementation while it is in the Python one.
# For example, the Python implementation might return
# Decimal('5.00000') whereas the C implementation will
# return Decimal('5'). These are equivalent of course.
return DecimalResultProcessor(target_class, "%%.%df" % scale).process
except ImportError:
globals().update(py_fallback())
|