/usr/lib/python3/dist-packages/pyzolib/ssdf/ssdf_base.py is in python3-pyzolib 0.3.4-1.
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# Copyright (C) 2012, Almar Klein
#
# SSDF is distributed under the terms of the (new) BSD License.
# See http://www.opensource.org/licenses/bsd-license.php
""" ssdf.ssdf_base.py
Implements the base functionality for ssdf:
* The Struct class
* Some constants and small functions
* The VirtualArray class
* The base classes for SSDFReader, SSDFWriter anf Block
"""
import sys
from . import ClassManager
# Proxy class for numpy module. We try to delay importing numpy if possible.
class _NumpyProxy(object):
def __init__(self):
self._np = None
self._tried_hard = False
self._try_soft_import()
def __bool__(self):
if self._np is None:
self._try_soft_import()
return bool(self._np)
def need(self):
if not self._tried_hard:
self._try_hard_import()
def _try_soft_import(self):
self._np = sys.modules.get('numpy', None)
if self._np:
self._inject()
self._set_types()
def _try_hard_import(self):
self._tried_hard = True
try:
import numpy as np
except ImportError:
np = None
self._np = np
if self._np:
self._inject()
self._set_types()
def _inject(self):
for name in dir(self._np):
if not name.startswith('_'):
setattr(self, name, getattr(self._np, name))
def _set_types(self):
global _FLOAT_TYPES
global _INT_TYPES
np = self._np
_FLOAT_TYPES, _INT_TYPES = set(_FLOAT_TYPES), set(_INT_TYPES)
_FLOAT_TYPES.update([np.float32, np.float64])
_INT_TYPES.update([ np.int8, np.int16, np.int32, np.int64,
np.uint8, np.uint16, np.uint32, np.uint64 ])
_FLOAT_TYPES, _INT_TYPES = tuple(_FLOAT_TYPES), tuple(_INT_TYPES)
# From six.py
PY3 = sys.version_info[0] == 3
if PY3:
string_types = str,
integer_types = int,
text_type = str
binary_type = bytes
ascii_type = str # Simple string
from functools import reduce
else:
string_types = basestring,
integer_types = (int, long)
text_type = unicode
binary_type = str
ascii_type = str # Simple string
reduce = reduce
# To store other classes
_CLASS_NAME = '_CLASS_NAME_'
# Same as in ssdf_bin (we only need the dict type id.
_TYPE_DICT = ord('D')
# Determine float and int types
_FLOAT_TYPES = tuple(set([float]))
_INT_TYPES = tuple(set(integer_types))
# The numpy proxy
np = _NumpyProxy()
def isstruct(ob):
""" isstruct(ob)
Returns whether the given object is an SSDF struct.
"""
if hasattr(ob, '__is_ssdf_struct__'):
return bool(ob.__is_ssdf_struct__)
else:
return False
def _not_equal(ob1, ob2):
""" _not_equal(ob1, ob2)
Returns None if the objects are equal. Otherwise returns a string
indicating how the objects are inequal.
"""
if isstruct(ob1) or isinstance(ob1, dict):
if not ( isstruct(ob2) or isinstance(ob2, dict) ):
return '<type does not match>'
# Test number of elements
keys1 = [key for key in ob1]
keys2 = [key for key in ob2]
if len(keys1) != len(keys2):
return '<lengths do not match>'
# Test all elements
for key in keys1:
if key not in keys2:
return '<key not present in other struct/dict>'
not_equal = _not_equal(ob1[key], ob2[key])
if not_equal:
return '.' + key + not_equal
elif isinstance(ob1, (tuple, list)):
if not isinstance(ob2, (tuple, list)):
return '<type does not match>'
if len(ob1) != len(ob2):
return '<lengths do not match>'
# Test all elements
for i in range(len(ob1)):
not_equal = _not_equal(ob1[i], ob2[i])
if not_equal:
return ('[%i]' % i) + not_equal
elif isinstance(ob1, VirtualArray):
if not isinstance(ob2, VirtualArray):
return '<type does not match>'
# Test properties
if not ( ob1.shape==ob2.shape and
ob1.dtype==ob2.dtype and
ob1.data==ob2.data ):
return '<array does not match>'
elif np and isinstance(ob1, np.ndarray):
if not isinstance(ob2, np.ndarray):
return '<type does not match>'
# Test properties
if not ( ob1.shape==ob2.shape and
ob1.dtype==ob2.dtype and
(ob1==ob2).sum()==ob1.size ):
return '<array does not match>'
else:
# Use default equality operator
if not (ob1 == ob2):
return '<objects not equal>'
def _isvalidname(name):
""" _isvalidname(name)
Returns attribute name, or None, if not valid
"""
# Is it a string?
if not ( name and isinstance(name, string_types) ):
return None
# Check name
namechars = str('abcdefghijklmnopqrstuvwxyz_0123456789')
name2 = name.lower()
if name2[0] not in namechars[0:-10]:
return None
tmp = list(map(lambda x: x not in namechars, name2[2:]))
# Return
if sum(tmp)==0:
return name
def _shapeString(ob):
""" _shapeString(ob)
Returns a string that represents the shape of the given array.
"""
ss = str()
for n in ob.shape:
ss += '%ix' % n
return ss[:-1]
class Struct(object):
""" Struct(dictionary=None)
Object to holds named data (syntactic sugar for a dictionary).
Attributes can be any of the seven SSDF supported types:
struct/dict, tuple/list, numpy array, (Unicode) string, int, float, None.
Elements can be added in two ways:
* s.foo = 'bar' # the object way
* s['foo'] = 'bar' # the dictionary way
Supported features
------------------
* Iteration - yields the keys/names in the struct
* len() - returns the number of elements in the struct
* del statement can be used to remove elements
* two structs can be added, yielding a new struct with combined elements
* testing for equality with other structs
Notes
-----
* The keys in the given dict should be valid names (invalid
keys are ignoired).
* On saving, names starting with two underscores are ignored.
* This class does not inherit from dict to keep its namespace clean,
avoid nameclashes, and to enable autocompletion of its items in
most IDE's.
* To get the underlying dict, simply use s.__dict__.
"""
# Indentifier
__is_ssdf_struct__ = True
def __init__(self, a_dict=None):
# Plain struct?
if a_dict is None:
return
if not isinstance(a_dict, dict) and not isstruct(a_dict):
tmp = "Struct can only be initialized with a Struct or a dict."
raise ValueError(tmp)
else:
# Try loading from object
def _getValue(val):
""" Get the value, as suitable for Struct. """
if isinstance(val, (string_types,) + _FLOAT_TYPES + _INT_TYPES ):
return val
if np and isinstance(val, np.ndarray):
return val
elif isinstance(val,(tuple,list)):
L = list()
for element in val:
L.append( _getValue(element) )
return L
elif isinstance(val, dict):
return Struct(val)
else:
pass # leave it
# Copy all keys in the dict that are not methods
for key in a_dict:
if not _isvalidname(key):
print("Ignoring invalid key-name '%s'." % key)
continue
val = a_dict[key]
self[key] = _getValue(val)
def __getitem__(self, key):
# Name ok?
key2 = _isvalidname(key)
if not key2:
raise KeyError("Trying to get invalid name '%s'." % key)
# Name exists?
if not key in self.__dict__:
raise KeyError(str(key))
# Return
return self.__dict__[key]
def __setitem__(self, key, value):
# Name ok?
key2 = _isvalidname(key)
if not key2:
raise KeyError("Trying to set invalid name '%s'." % key)
# Set
self.__dict__[key] = value
def __iter__(self):
""" Returns iterator over keys. """
return self.__dict__.__iter__()
def __delitem__(self, key):
return self.__dict__.__delitem__(key)
def __len__(self):
""" Return amount of fields in the Struct object. """
return len(self.__dict__)
def __add__(self, other):
""" Enable adding two structs by combining their elemens. """
s = Struct()
s.__dict__.update(self.__dict__)
s.__dict__.update(other.__dict__)
return s
def __eq__(self, other):
return not _not_equal(self, other)
def __ne__(self, other):
return _not_equal(self, other)
def __repr__(self):
""" Short string representation. """
return "<SSDF struct instance with %i elements>" % len(self)
def __str__(self):
""" Long string representation. """
# Get alignment value
c = 0
for key in self:
c = max(c, len(key))
# How many chars left (to display on less than 80 lines)
charsLeft = 79 - (c+4) # 2 spaces and ': '
s = 'Elements in SSDF struct:\n'
for key in self:
if key.startswith("__"):
continue
tmp = "%s" % (key)
value = self[key]
valuestr = repr(value)
if len(valuestr)>charsLeft or '\n' in valuestr:
typestr = str(type(value))[7:-2]
if np and isinstance(value,np.ndarray):
shapestr = _shapeString(value)
valuestr = "<array %s %s>" %(shapestr,str(value.dtype))
elif isinstance(value, string_types):
valuestr = valuestr[:charsLeft-3] + '...'
#valuestr = "<string with length %i>" % (typestr, len(value))
else:
valuestr = "<%s with length %i>" % (typestr, len(value))
s += tmp.rjust(c+2) + ": %s\n" % (valuestr)
return s
class VirtualArray(object):
""" VirtualArray
A VirtualArray represents an array when numpy is not available.
This enables preserving the array when saving back a loaded dataset.
"""
def __init__(self, shape, dtype, data):
self.shape = tuple(shape)
self.dtype = dtype
self.data = data
def tostring(self):
return self.data
@property
def size(self):
if self.shape:
return reduce( lambda a,b:a*b, self.shape)
else:
return 1
class SSDFReader:
def build_tree(self, root, blocks):
""" build_tree(root, blocks)
Build up the tree using the indentation information in the blocks.
The tree is build up from the given root.
"""
tree = [root]
for block in blocks:
# Select leaf in tree
while block._indent <= tree[-1]._indent:
tree.pop()
# Append (to object and to simple tree structure)
tree[-1]._children.append(block)
tree.append(block)
def serialize_struct(self, object, f=None):
raise NotImplementedError()
def read(self, file_or_string):
raise NotImplementedError()
class SSDFWriter:
def flatten_tree(self, block, sort=False):
""" flatten_tree(block, sort=False)
Returns a flat list containing the given block and
all its children.
If sort is True, packs blocks such that the data
structures consisting of less blocks appear first.
"""
# Get list of strings for each child
listOfLists = []
for child in block._children:
childList = self.flatten_tree(child, sort)
listOfLists.append( childList )
# Sort by length
if sort and listOfLists and block._type == _TYPE_DICT:
listOfLists.sort(key=len)
# Produce flat list
flatList = [block]
for childList in listOfLists:
flatList.extend(childList)
# Done
return flatList
def write(self, object, f=None):
raise NotImplementedError()
class Block:
""" Block
A block represents a data element. This is where the conversion from
Python objects to text/bytes and vice versa occurs.
A block is a line in a text file or a piece of data in a binary file.
A block contains all information about indentation, name, and value
of the data element that it represents. The raw representation of its
value is refered to as 'data'.
"""
def __init__(self, indent, blocknr, name=None, type=None, data=None):
self._indent = indent
self._blocknr = blocknr # for producing usefull read error messages
self._name = name
self._type = type # used by binary only (and text-dict)
self._data = data # the raw data, bytes or string
self._children = [] # used only by dicts and lists
@classmethod
def from_object(cls, indent, name, value):
# Instantiate a block
self = cls(indent, -1, name)
# Set object's data
if value is None:
self._from_none()
elif ClassManager.is_registered_class(value.__class__):
s = value.__to_ssdf__()
s[_CLASS_NAME] = value.__class__.__name__
self._from_dict(s)
elif isinstance(value, _INT_TYPES):
self._from_int(value)
elif isinstance(value, _FLOAT_TYPES):
self._from_float(value)
elif isinstance(value, bool):
self._from_int(int(value))
elif isinstance(value, string_types):
self._from_unicode(value)
elif np and isinstance(value, np.ndarray):
self._from_array(value)
elif isinstance(value, VirtualArray):
self._from_array(value)
elif isinstance(value, dict) or isstruct(value):
self._from_dict(value)
elif isinstance(value, (list, tuple)):
self._from_list(value)
else:
# We do not know
self._from_none()
tmp = repr(value)
if len(tmp) > 64:
tmp = tmp[:64] + '...'
if name is not None:
print("SSDF: %s is unknown object: %s %s" %
(name, tmp, repr(type(value)) ))
else:
print("SSDF: unknown object: %s %s" %
(tmp, repr(type(value)) ))
# Done
return self
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