2014-05-17 18:11:40 +00:00
|
|
|
# sqlalchemy/processors.py
|
2014-09-30 16:15:32 +00:00
|
|
|
# Copyright (C) 2010-2014 the SQLAlchemy authors and contributors
|
|
|
|
# <see AUTHORS file>
|
2014-05-17 18:11:40 +00:00
|
|
|
# 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' "
|
2014-09-30 16:15:32 +00:00
|
|
|
"- value is not a string." %
|
|
|
|
(type_.__name__, value))
|
2014-05-17 18:11:40 +00:00
|
|
|
if m is None:
|
|
|
|
raise ValueError("Couldn't parse %s string: "
|
2014-09-30 16:15:32 +00:00
|
|
|
"'%s'" % (type_.__name__, value))
|
2014-05-17 18:11:40 +00:00
|
|
|
if has_named_groups:
|
|
|
|
groups = m.groupdict(0)
|
2014-09-30 16:15:32 +00:00
|
|
|
return type_(**dict(list(zip(
|
|
|
|
iter(groups.keys()),
|
|
|
|
list(map(int, iter(groups.values())))
|
|
|
|
))))
|
2014-05-17 18:11:40 +00:00
|
|
|
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(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 value and True or False
|
|
|
|
|
|
|
|
DATETIME_RE = re.compile(
|
2014-09-30 16:15:32 +00:00
|
|
|
"(\d+)-(\d+)-(\d+) (\d+):(\d+):(\d+)(?:\.(\d+))?")
|
2014-05-17 18:11:40 +00:00
|
|
|
TIME_RE = re.compile("(\d+):(\d+):(\d+)(?:\.(\d+))?")
|
|
|
|
DATE_RE = re.compile("(\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, \
|
2014-09-30 16:15:32 +00:00
|
|
|
DecimalResultProcessor, \
|
|
|
|
to_float, to_str, int_to_boolean, \
|
|
|
|
str_to_datetime, str_to_time, \
|
|
|
|
str_to_date
|
2014-05-17 18:11:40 +00:00
|
|
|
|
|
|
|
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())
|