/usr/share/pyshared/gluon/contrib/pg8000/types.py is in python-gluon 1.99.7-1.
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#
# Copyright (c) 2007-2009, Mathieu Fenniak
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are
# met:
#
# * Redistributions of source code must retain the above copyright notice,
# this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice,
# this list of conditions and the following disclaimer in the documentation
# and/or other materials provided with the distribution.
# * The name of the author may not be used to endorse or promote products
# derived from this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
# ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
# LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
# CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
# SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
# INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
# CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
# ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
# POSSIBILITY OF SUCH DAMAGE.
__author__ = "Mathieu Fenniak"
import datetime
import decimal
import struct
import math
from errors import (NotSupportedError, ArrayDataParseError, InternalError,
ArrayContentEmptyError, ArrayContentNotHomogenousError,
ArrayContentNotSupportedError, ArrayDimensionsNotConsistentError)
try:
from pytz import utc
except ImportError:
ZERO = datetime.timedelta(0)
class UTC(datetime.tzinfo):
def utcoffset(self, dt):
return ZERO
def tzname(self, dt):
return "UTC"
def dst(self, dt):
return ZERO
utc = UTC()
class Bytea(str):
pass
class Interval(object):
def __init__(self, microseconds=0, days=0, months=0):
self.microseconds = microseconds
self.days = days
self.months = months
def _setMicroseconds(self, value):
if not isinstance(value, int) and not isinstance(value, long):
raise TypeError("microseconds must be an int or long")
elif not (min_int8 < value < max_int8):
raise OverflowError("microseconds must be representable as a 64-bit integer")
else:
self._microseconds = value
def _setDays(self, value):
if not isinstance(value, int) and not isinstance(value, long):
raise TypeError("days must be an int or long")
elif not (min_int4 < value < max_int4):
raise OverflowError("days must be representable as a 32-bit integer")
else:
self._days = value
def _setMonths(self, value):
if not isinstance(value, int) and not isinstance(value, long):
raise TypeError("months must be an int or long")
elif not (min_int4 < value < max_int4):
raise OverflowError("months must be representable as a 32-bit integer")
else:
self._months = value
microseconds = property(lambda self: self._microseconds, _setMicroseconds)
days = property(lambda self: self._days, _setDays)
months = property(lambda self: self._months, _setMonths)
def __repr__(self):
return "<Interval %s months %s days %s microseconds>" % (self.months, self.days, self.microseconds)
def __cmp__(self, other):
if other == None: return -1
c = cmp(self.months, other.months)
if c != 0: return c
c = cmp(self.days, other.days)
if c != 0: return c
return cmp(self.microseconds, other.microseconds)
def pg_type_info(typ):
value = None
if isinstance(typ, dict):
value = typ["value"]
typ = typ["type"]
data = py_types.get(typ)
if data == None:
raise NotSupportedError("type %r not mapped to pg type" % typ)
# permit the type data to be determined by the value, if provided
inspect_func = data.get("inspect")
if value != None and inspect_func != None:
data = inspect_func(value)
type_oid = data.get("typeoid")
if type_oid == None:
raise InternalError("type %r has no type_oid" % typ)
elif type_oid == -1:
# special case: NULL values
return type_oid, 0
# prefer bin, but go with whatever exists
if data.get("bin_out"):
format = 1
elif data.get("txt_out"):
format = 0
else:
raise InternalError("no conversion fuction for type %r" % typ)
return type_oid, format
def pg_value(value, fc, **kwargs):
typ = type(value)
data = py_types.get(typ)
if data == None:
raise NotSupportedError("type %r not mapped to pg type" % typ)
# permit the type conversion to be determined by the value, if provided
inspect_func = data.get("inspect")
if value != None and inspect_func != None:
data = inspect_func(value)
# special case: NULL values
if data.get("typeoid") == -1:
return None
if fc == 0:
func = data.get("txt_out")
elif fc == 1:
func = data.get("bin_out")
else:
raise InternalError("unrecognized format code %r" % fc)
if func == None:
raise NotSupportedError("type %r, format code %r not supported" % (typ, fc))
return func(value, **kwargs)
def py_type_info(description):
type_oid = description['type_oid']
data = pg_types.get(type_oid)
if data == None:
raise NotSupportedError("type oid %r not mapped to py type" % type_oid)
# prefer bin, but go with whatever exists
if data.get("bin_in"):
format = 1
elif data.get("txt_in"):
format = 0
else:
raise InternalError("no conversion fuction for type oid %r" % type_oid)
return format
def py_value(v, description, **kwargs):
if v == None:
# special case - NULL value
return None
type_oid = description['type_oid']
format = description['format']
data = pg_types.get(type_oid)
if data == None:
raise NotSupportedError("type oid %r not supported" % type_oid)
if format == 0:
func = data.get("txt_in")
elif format == 1:
func = data.get("bin_in")
else:
raise NotSupportedError("format code %r not supported" % format)
if func == None:
raise NotSupportedError("data response format %r, type %r not supported" % (format, type_oid))
return func(v, **kwargs)
def boolrecv(data, **kwargs):
return data == "\x01"
def boolsend(v, **kwargs):
if v:
return "\x01"
else:
return "\x00"
min_int2, max_int2 = -2 ** 15, 2 ** 15
min_int4, max_int4 = -2 ** 31, 2 ** 31
min_int8, max_int8 = -2 ** 63, 2 ** 63
def int_inspect(value):
if min_int2 < value < max_int2:
return {"typeoid": 21, "bin_out": int2send}
elif min_int4 < value < max_int4:
return {"typeoid": 23, "bin_out": int4send}
elif min_int8 < value < max_int8:
return {"typeoid": 20, "bin_out": int8send}
else:
return {"typeoid": 1700, "bin_out": numeric_send}
def int2recv(data, **kwargs):
return struct.unpack("!h", data)[0]
def int2send(v, **kwargs):
return struct.pack("!h", v)
def int4recv(data, **kwargs):
return struct.unpack("!i", data)[0]
def int4send(v, **kwargs):
return struct.pack("!i", v)
def int8recv(data, **kwargs):
return struct.unpack("!q", data)[0]
def int8send(v, **kwargs):
return struct.pack("!q", v)
def float4recv(data, **kwargs):
return struct.unpack("!f", data)[0]
def float8recv(data, **kwargs):
return struct.unpack("!d", data)[0]
def float8send(v, **kwargs):
return struct.pack("!d", v)
def datetime_inspect(value):
if value.tzinfo != None:
# send as timestamptz if timezone is provided
return {"typeoid": 1184, "bin_out": timestamptz_send}
else:
# otherwise send as timestamp
return {"typeoid": 1114, "bin_out": timestamp_send}
def timestamp_recv(data, integer_datetimes, **kwargs):
if integer_datetimes:
# data is 64-bit integer representing milliseconds since 2000-01-01
val = struct.unpack("!q", data)[0]
return datetime.datetime(2000, 1, 1) + datetime.timedelta(microseconds = val)
else:
# data is double-precision float representing seconds since 2000-01-01
val = struct.unpack("!d", data)[0]
return datetime.datetime(2000, 1, 1) + datetime.timedelta(seconds = val)
# return a timezone-aware datetime instance if we're reading from a
# "timestamp with timezone" type. The timezone returned will always be UTC,
# but providing that additional information can permit conversion to local.
def timestamptz_recv(data, **kwargs):
return timestamp_recv(data, **kwargs).replace(tzinfo=utc)
def timestamp_send(v, integer_datetimes, **kwargs):
delta = v - datetime.datetime(2000, 1, 1)
val = delta.microseconds + (delta.seconds * 1000000) + (delta.days * 86400000000)
if integer_datetimes:
# data is 64-bit integer representing milliseconds since 2000-01-01
return struct.pack("!q", val)
else:
# data is double-precision float representing seconds since 2000-01-01
return struct.pack("!d", val / 1000.0 / 1000.0)
def timestamptz_send(v, **kwargs):
# timestamps should be sent as UTC. If they have zone info,
# convert them.
return timestamp_send(v.astimezone(utc).replace(tzinfo=None), **kwargs)
def date_in(data, **kwargs):
year = int(data[0:4])
month = int(data[5:7])
day = int(data[8:10])
return datetime.date(year, month, day)
def date_out(v, **kwargs):
return v.isoformat()
def time_in(data, **kwargs):
hour = int(data[0:2])
minute = int(data[3:5])
sec = decimal.Decimal(data[6:])
return datetime.time(hour, minute, int(sec), int((sec - int(sec)) * 1000000))
def time_out(v, **kwargs):
return v.isoformat()
def numeric_in(data, **kwargs):
if data.find(".") == -1:
return int(data)
else:
return decimal.Decimal(data)
def numeric_recv(data, **kwargs):
num_digits, weight, sign, scale = struct.unpack("!hhhh", data[:8])
data = data[8:]
digits = struct.unpack("!" + ("h" * num_digits), data)
weight = decimal.Decimal(weight)
retval = 0
for d in digits:
d = decimal.Decimal(d)
retval += d * (10000 ** weight)
weight -= 1
if sign:
retval *= -1
return retval
DEC_DIGITS = 4
def numeric_send(d, **kwargs):
# This is a very straight port of src/backend/utils/adt/numeric.c set_var_from_str()
s = str(d)
pos = 0
sign = 0
if s[0] == '-':
sign = 0x4000 # NEG
pos=1
elif s[0] == '+':
sign = 0 # POS
pos=1
have_dp = False
decdigits = [0, 0, 0, 0]
dweight = -1
dscale = 0
for char in s[pos:]:
if char.isdigit():
decdigits.append(int(char))
if not have_dp:
dweight += 1
else:
dscale += 1
pos+=1
elif char == '.':
have_dp = True
pos+=1
else:
break
if len(s) > pos:
char = s[pos]
if char == 'e' or char == 'E':
pos+=1
exponent = int(s[pos:])
dweight += exponent
dscale -= exponent
if dscale < 0: dscale = 0
if dweight >= 0:
weight = (dweight + 1 + DEC_DIGITS - 1) / DEC_DIGITS - 1
else:
weight = -((-dweight - 1) / DEC_DIGITS + 1)
offset = (weight + 1) * DEC_DIGITS - (dweight + 1)
ndigits = (len(decdigits)-DEC_DIGITS + offset + DEC_DIGITS - 1) / DEC_DIGITS
i = DEC_DIGITS - offset
decdigits.extend([0, 0, 0])
ndigits_ = ndigits
digits = ''
while ndigits_ > 0:
# ifdef DEC_DIGITS == 4
digits += struct.pack("!h", ((decdigits[i] * 10 + decdigits[i + 1]) * 10 + decdigits[i + 2]) * 10 + decdigits[i + 3])
ndigits_ -= 1
i += DEC_DIGITS
# strip_var()
if ndigits == 0:
sign = 0x4000 # pos
weight = 0
# ----------
retval = struct.pack("!hhhh", ndigits, weight, sign, dscale) + digits
return retval
def numeric_out(v, **kwargs):
return str(v)
# PostgreSQL encodings:
# http://www.postgresql.org/docs/8.3/interactive/multibyte.html
# Python encodings:
# http://www.python.org/doc/2.4/lib/standard-encodings.html
#
# Commented out encodings don't require a name change between PostgreSQL and
# Python. If the py side is None, then the encoding isn't supported.
pg_to_py_encodings = {
# Not supported:
"mule_internal": None,
"euc_tw": None,
# Name fine as-is:
#"euc_jp",
#"euc_jis_2004",
#"euc_kr",
#"gb18030",
#"gbk",
#"johab",
#"sjis",
#"shift_jis_2004",
#"uhc",
#"utf8",
# Different name:
"euc_cn": "gb2312",
"iso_8859_5": "is8859_5",
"iso_8859_6": "is8859_6",
"iso_8859_7": "is8859_7",
"iso_8859_8": "is8859_8",
"koi8": "koi8_r",
"latin1": "iso8859-1",
"latin2": "iso8859_2",
"latin3": "iso8859_3",
"latin4": "iso8859_4",
"latin5": "iso8859_9",
"latin6": "iso8859_10",
"latin7": "iso8859_13",
"latin8": "iso8859_14",
"latin9": "iso8859_15",
"sql_ascii": "ascii",
"win866": "cp886",
"win874": "cp874",
"win1250": "cp1250",
"win1251": "cp1251",
"win1252": "cp1252",
"win1253": "cp1253",
"win1254": "cp1254",
"win1255": "cp1255",
"win1256": "cp1256",
"win1257": "cp1257",
"win1258": "cp1258",
}
def encoding_convert(encoding):
return pg_to_py_encodings.get(encoding.lower(), encoding)
def varcharin(data, client_encoding, **kwargs):
return unicode(data, encoding_convert(client_encoding))
def textout(v, client_encoding, **kwargs):
if isinstance(v, unicode):
return v.encode(encoding_convert(client_encoding))
else:
return v
def byteasend(v, **kwargs):
return str(v)
def bytearecv(data, **kwargs):
return Bytea(data)
# interval support does not provide a Python-usable interval object yet
def interval_recv(data, integer_datetimes, **kwargs):
if integer_datetimes:
microseconds, days, months = struct.unpack("!qii", data)
else:
seconds, days, months = struct.unpack("!dii", data)
microseconds = int(seconds * 1000 * 1000)
return Interval(microseconds, days, months)
def interval_send(data, integer_datetimes, **kwargs):
if integer_datetimes:
return struct.pack("!qii", data.microseconds, data.days, data.months)
else:
return struct.pack("!dii", data.microseconds / 1000.0 / 1000.0, data.days, data.months)
def array_recv(data, **kwargs):
dim, hasnull, typeoid = struct.unpack("!iii", data[:12])
data = data[12:]
# get type conversion method for typeoid
conversion = pg_types[typeoid]["bin_in"]
# Read dimension info
dim_lengths = []
element_count = 1
for idim in range(dim):
dim_len, dim_lbound = struct.unpack("!ii", data[:8])
data = data[8:]
dim_lengths.append(dim_len)
element_count *= dim_len
# Read all array values
array_values = []
for i in range(element_count):
if len(data):
element_len, = struct.unpack("!i", data[:4])
data = data[4:]
if element_len == -1:
array_values.append(None)
else:
array_values.append(conversion(data[:element_len], **kwargs))
data = data[element_len:]
if data != "":
raise ArrayDataParseError("unexpected data left over after array read")
# at this point, {{1,2,3},{4,5,6}}::int[][] looks like [1,2,3,4,5,6].
# go through the dimensions and fix up the array contents to match
# expected dimensions
for dim_length in reversed(dim_lengths[1:]):
val = []
while array_values:
val.append(array_values[:dim_length])
array_values = array_values[dim_length:]
array_values = val
return array_values
def array_inspect(value):
# Check if array has any values. If not, we can't determine the proper
# array typeoid.
first_element = array_find_first_element(value)
if first_element == None:
raise ArrayContentEmptyError("array has no values")
# supported array output
typ = type(first_element)
if issubclass(typ, int) or issubclass(typ, long):
# special int array support -- send as smallest possible array type
special_int_support = True
int2_ok, int4_ok, int8_ok = True, True, True
for v in array_flatten(value):
if v == None:
continue
if min_int2 < v < max_int2:
continue
int2_ok = False
if min_int4 < v < max_int4:
continue
int4_ok = False
if min_int8 < v < max_int8:
continue
int8_ok = False
if int2_ok:
array_typeoid = 1005 # INT2[]
elif int4_ok:
array_typeoid = 1007 # INT4[]
elif int8_ok:
array_typeoid = 1016 # INT8[]
else:
raise ArrayContentNotSupportedError("numeric not supported as array contents")
else:
special_int_support = False
array_typeoid = py_array_types.get(typ)
if array_typeoid == None:
raise ArrayContentNotSupportedError("type %r not supported as array contents" % typ)
# check for homogenous array
for v in array_flatten(value):
if v != None and not (isinstance(v, typ) or (typ == long and isinstance(v, int)) or (typ == int and isinstance(v, long))):
raise ArrayContentNotHomogenousError("not all array elements are of type %r" % typ)
# check that all array dimensions are consistent
array_check_dimensions(value)
type_data = py_types[typ]
if special_int_support:
if array_typeoid == 1005:
type_data = {"typeoid": 21, "bin_out": int2send}
elif array_typeoid == 1007:
type_data = {"typeoid": 23, "bin_out": int4send}
elif array_typeoid == 1016:
type_data = {"typeoid": 20, "bin_out": int8send}
else:
type_data = py_types[typ]
return {
"typeoid": array_typeoid,
"bin_out": array_send(type_data["typeoid"], type_data["bin_out"])
}
def array_find_first_element(arr):
for v in array_flatten(arr):
if v != None:
return v
return None
def array_flatten(arr):
for v in arr:
if isinstance(v, list):
for v2 in array_flatten(v):
yield v2
else:
yield v
def array_check_dimensions(arr):
v0 = arr[0]
if isinstance(v0, list):
req_len = len(v0)
req_inner_lengths = array_check_dimensions(v0)
for v in arr:
inner_lengths = array_check_dimensions(v)
if len(v) != req_len or inner_lengths != req_inner_lengths:
raise ArrayDimensionsNotConsistentError("array dimensions not consistent")
retval = [req_len]
retval.extend(req_inner_lengths)
return retval
else:
# make sure nothing else at this level is a list
for v in arr:
if isinstance(v, list):
raise ArrayDimensionsNotConsistentError("array dimensions not consistent")
return []
def array_has_null(arr):
for v in array_flatten(arr):
if v == None:
return True
return False
def array_dim_lengths(arr):
v0 = arr[0]
if isinstance(v0, list):
retval = [len(v0)]
retval.extend(array_dim_lengths(v0))
else:
return [len(arr)]
return retval
class array_send(object):
def __init__(self, typeoid, bin_out_func):
self.typeoid = typeoid
self.bin_out_func = bin_out_func
def __call__(self, arr, **kwargs):
has_null = array_has_null(arr)
dim_lengths = array_dim_lengths(arr)
data = struct.pack("!iii", len(dim_lengths), has_null, self.typeoid)
for i in dim_lengths:
data += struct.pack("!ii", i, 1)
for v in array_flatten(arr):
if v == None:
data += struct.pack("!i", -1)
else:
inner_data = self.bin_out_func(v, **kwargs)
data += struct.pack("!i", len(inner_data))
data += inner_data
return data
py_types = {
bool: {"typeoid": 16, "bin_out": boolsend},
int: {"inspect": int_inspect},
long: {"inspect": int_inspect},
str: {"typeoid": 25, "bin_out": textout},
unicode: {"typeoid": 25, "bin_out": textout},
float: {"typeoid": 701, "bin_out": float8send},
decimal.Decimal: {"typeoid": 1700, "bin_out": numeric_send},
Bytea: {"typeoid": 17, "bin_out": byteasend},
datetime.datetime: {"typeoid": 1114, "bin_out": timestamp_send, "inspect": datetime_inspect},
datetime.date: {"typeoid": 1082, "txt_out": date_out},
datetime.time: {"typeoid": 1083, "txt_out": time_out},
Interval: {"typeoid": 1186, "bin_out": interval_send},
type(None): {"typeoid": -1},
list: {"inspect": array_inspect},
}
# py type -> pg array typeoid
py_array_types = {
float: 1022,
bool: 1000,
str: 1009, # TEXT[]
unicode: 1009, # TEXT[]
decimal.Decimal: 1231, # NUMERIC[]
}
pg_types = {
16: {"bin_in": boolrecv},
17: {"bin_in": bytearecv},
19: {"bin_in": varcharin}, # name type
20: {"bin_in": int8recv},
21: {"bin_in": int2recv},
23: {"bin_in": int4recv, "txt_in": numeric_in},
25: {"bin_in": varcharin, "txt_in": varcharin}, # TEXT type
26: {"txt_in": numeric_in}, # oid type
142: {"bin_in": varcharin, "txt_in": varcharin}, # XML
194: {"bin_in": varcharin}, # "string representing an internal node tree"
700: {"bin_in": float4recv},
701: {"bin_in": float8recv},
705: {"txt_in": varcharin}, # UNKNOWN
829: {"txt_in": varcharin}, # MACADDR type
1000: {"bin_in": array_recv}, # BOOL[]
1003: {"bin_in": array_recv}, # NAME[]
1005: {"bin_in": array_recv}, # INT2[]
1007: {"bin_in": array_recv, "txt_in": varcharin}, # INT4[]
1009: {"bin_in": array_recv}, # TEXT[]
1014: {"bin_in": array_recv}, # CHAR[]
1015: {"bin_in": array_recv}, # VARCHAR[]
1016: {"bin_in": array_recv}, # INT8[]
1021: {"bin_in": array_recv}, # FLOAT4[]
1022: {"bin_in": array_recv}, # FLOAT8[]
1042: {"bin_in": varcharin}, # CHAR type
1043: {"bin_in": varcharin}, # VARCHAR type
1082: {"txt_in": date_in},
1083: {"txt_in": time_in},
1114: {"bin_in": timestamp_recv},
1184: {"bin_in": timestamptz_recv}, # timestamp w/ tz
1186: {"bin_in": interval_recv},
1231: {"bin_in": array_recv}, # NUMERIC[]
1263: {"bin_in": array_recv}, # cstring[]
1700: {"bin_in": numeric_recv},
2275: {"bin_in": varcharin}, # cstring
}
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