implement datatypes
+tests as agreed in last meeting Change-Id: Ibc382f808927797e7e7ea268b97a5632713bfb56
This commit is contained in:
Enrico Faulhaber
parent
f984129986
commit
a87e568b55
382
secop/datatypes.py
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382
secop/datatypes.py
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# -*- coding: utf-8 -*-
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# *****************************************************************************
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#
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# This program is free software; you can redistribute it and/or modify it under
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# the terms of the GNU General Public License as published by the Free Software
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# Foundation; either version 2 of the License, or (at your option) any later
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# version.
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#
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# This program is distributed in the hope that it will be useful, but WITHOUT
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# ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
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# FOR A PARTICULAR PURPOSE. See the GNU General Public License for more
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# details.
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#
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# You should have received a copy of the GNU General Public License along with
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# this program; if not, write to the Free Software Foundation, Inc.,
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# 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
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#
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# Module authors:
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# Enrico Faulhaber <enrico.faulhaber@frm2.tum.de>
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#
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# *****************************************************************************
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"""Define validated data types."""
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# a Validator returns a validated object or raises an ValueError
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# also validators should have a __repr__ returning a 'python' string
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# which recreates them
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# if a validator does a mapping, it normally maps to the
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# internal representation with method :meth:`validate`
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# to get the external representation (aöso for logging),
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# call method :meth:`export`
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from .errors import ProgrammingError
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from collections import OrderedDict
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# base class for all DataTypes
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class DataType(object):
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as_json = ['undefined']
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def validate(self, value):
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"""validate a external representation and return an internal one"""
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raise NotImplemented
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def export(self, value):
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"""returns a python object fit for external serialisation or logging"""
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raise NotImplemented
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# goodie: if called, validate
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def __call__(self, value):
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return self.validate(value)
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class FloatRange(DataType):
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"""Restricted float type"""
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def __init__(self, min=None, max=None):
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self.min = float('-Inf') if min is None else float(min)
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self.max = float('+Inf') if max is None else float(max)
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# note: as we may compare to Inf all comparisons would be false
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if self.min <= self.max:
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self.as_json = ['double', min, max]
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else:
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raise ValueError('Max must be larger then min!')
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def validate(self, value):
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try:
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value = float(value)
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if self.min <= value <= self.max:
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return value
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raise ValueError('%r should be an float between %.3f and %.3f' %
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(value, self.min, self.max))
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except:
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raise ValueError('Can not validate %r to float' % value)
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def __repr__(self):
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return "FloatRange(%f, %f)" % (self.min, self.max)
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def export(self, value):
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"""returns a python object fit for serialisation"""
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return float(value)
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class IntRange(DataType):
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"""Restricted int type"""
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def __init__(self, min=None, max=None):
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self.min = int(min) if min is not None else min
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self.max = int(max) if max is not None else max
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if self.min is not None and self.max is not None and self.min > self.max:
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raise ValueError('Max must be larger then min!')
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self.as_json = ['int', self.min, self.max]
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def validate(self, value):
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try:
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value = int(value)
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if self.min is not None and value < self.min:
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raise ValueError('%r should be an int between %d and %d' %
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(value, self.min, self.max or 0))
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if self.max is not None and value > self.max:
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raise ValueError('%r should be an int between %d and %d' %
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(value, self.min or 0, self.max))
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return value
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except:
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raise ValueError('Can not validate %r to int' % value)
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def __repr__(self):
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return "IntRange(%d, %d)" % (self.min, self.max)
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def export(self, value):
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"""returns a python object fit for serialisation"""
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return int(value)
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class EnumType(DataType):
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as_json = ['enum']
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def __init__(self, *args, **kwds):
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# enum keys are ints! check
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self.entries = {}
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num = 0
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for arg in args:
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if type(args) != str:
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raise ValueError('EnumType entries MUST be strings!')
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self.entries[num] = arg
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num += 1
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for k, v in kwds.items():
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v = int(v)
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if v in self.entries:
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raise ValueError('keyword argument %r=%d is already assigned %r', k, v, self.entries[v])
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self.entries[v] = k
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if len(self.entries) == 0:
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raise ValueError('Empty enums ae not allowed!')
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self.reversed = {}
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for k,v in self.entries.items():
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if v in self.reversed:
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raise ValueError('Mapping for %r=%r is not Unique!', v, k)
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self.reversed[v] = k
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self.as_json = ['enum', self.reversed.copy()]
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def __repr__(self):
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return "EnumType(%s)" % ', '.join(['%r=%d' % (v,k) for k,v in self.entries.items()])
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def export(self, value):
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"""returns a python object fit for serialisation"""
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if value in self.reversed:
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return self.reversed[value]
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if int(value) in self.entries:
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return int(value)
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raise ValueError('%r is not one of %s', str(value), ', '.join(self.reversed.keys()))
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def validate(self, value):
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"""return the validated (internal) value or raise"""
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if value in self.reversed:
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return value
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if int(value) in self.entries:
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return self.entries[int(value)]
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raise ValueError('%r is not one of %s', str(value), ', '.join(map(str,self.entries.keys())))
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class BLOBType(DataType):
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def __init__(self, minsize=0, maxsize=None):
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self.minsize = minsize
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self.maxsize = maxsize
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if minsize or maxsize:
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self.as_json = ['blob', minsize, maxsize]
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else:
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self.as_json = ['blob']
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if minsize is not None and maxsize is not None and minsize > maxsize:
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raise ValueError('maxsize must be bigger than minsize!')
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def __repr__(self):
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if self.minsize or self.maxsize:
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return 'BLOB(%d, %s)' % (self.minsize, self.maxsize)
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return 'BLOB()'
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def validate(self, value):
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"""return the validated (internal) value or raise"""
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if type(value) not in [str, unicode]:
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raise ValueError('%r has the wrong type!', value)
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size = len(value)
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if size < self.minsize:
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raise ValueError('%r must be at least %d bytes long!', value, self.minsize)
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if self.maxsize is not None:
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if size > self.maxsize:
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raise ValueError('%r must be at most %d bytes long!', value, self.maxsize)
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return value
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def export(self, value):
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"""returns a python object fit for serialisation"""
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return b'%s' % value
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class StringType(DataType):
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as_json = ['string']
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def __init__(self, minsize=0, maxsize=None):
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self.minsize = minsize
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self.maxsize = maxsize
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if (minsize, maxsize) == (0, None):
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self.as_json = ['string']
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else:
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self.as_json = ['string', minsize, maxsize]
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if minsize is not None and maxsize is not None and minsize > maxsize:
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raise ValueError('maxsize must be bigger than minsize!')
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def __repr__(self):
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return 'StringType(%d, %s)' % (self.minsize, self.maxsize)
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def validate(self, value):
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"""return the validated (internal) value or raise"""
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if type(value) not in [str, unicode]:
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raise ValueError('%r has the wrong type!', value)
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size = len(value)
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if size < self.minsize:
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raise ValueError('%r must be at least %d bytes long!', value, self.minsize)
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if self.maxsize is not None:
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if size > self.maxsize:
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raise ValueError('%r must be at most %d bytes long!', value, self.maxsize)
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if '\0' in value:
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raise ValueError('Strings are not allowed to embed a \\0! Use a Blob instead!')
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return value
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def export(self, value):
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"""returns a python object fit for serialisation"""
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return '%s' % value
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# Bool is a special enum
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class BoolType(DataType):
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as_json = ['bool']
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def __repr__(self):
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return 'BoolType()'
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def validate(self, value):
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"""return the validated (internal) value or raise"""
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if value in [0, '0', 'False', 'false', 'no', 'off', False]:
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return False
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if value in [1, '1', 'True', 'true', 'yes', 'on', True]:
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return True
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raise ValueError('%r is not a boolean value!', value)
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def export(self, value):
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"""returns a python object fit for serialisation"""
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return True if self.validate(value) else False
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#
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# nested types
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#
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class ArrayOf(DataType):
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def __init__(self, subtype, minsize_or_size=None, maxsize=None):
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if maxsize is None:
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maxsize = minsize_or_size
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self.minsize = minsize_or_size
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self.maxsize = maxsize
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if self.minsize is not None and self.maxsize is not None and \
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self.minsize > self.maxsize:
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raise ValueError('minsize must be less than or equal to maxsize!')
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if not isinstance(subtype, DataType):
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raise ValueError('ArrayOf only works with DataType objs as first argument!')
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self.subtype = subtype
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self.as_json = ['array', self.subtype.as_json, self.minsize, self.maxsize]
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if self.minsize is not None and self.minsize < 0:
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raise ValueError('Minimum size must be >= 0!')
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if self.maxsize is not None and self.maxsize < 1:
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raise ValueError('Maximum size must be >= 1!')
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if self.minsize is not None and self.maxsize is not None and self.minsize > self.maxsize:
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raise ValueError('Maximum size must be >= Minimum size')
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def validate(self, value):
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"""validate a external representation to an internal one"""
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if isinstance(value, (tuple, list)):
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# check number of elements
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if self.minsize is not None and len(value) < self.minsize:
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raise ValueError('Array too small, needs at least %d elements!', self.minsize)
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if self.maxsize is not None and len(value) > self.maxsize:
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raise ValueError('Array too big, holds at most %d elements!', self.minsize)
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# apply subtype valiation to all elements and return as list
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return [self.subtype.validate(elem) for elem in value]
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raise ValueError('Can not convert %s to ArrayOf DataType!', repr(value))
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def export(self, value):
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"""returns a python object fit for serialisation"""
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return [self.subtype.export(elem) for elem in value]
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class TupleOf(DataType):
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def __init__(self, *subtypes):
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if not subtypes:
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raise ValueError('Empty tuples are not allowed!')
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for subtype in subtypes:
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if not isinstance(subtype, DataType):
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raise ValueError('TupleOf only works with DataType objs as arguments!')
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self.subtypes = subtypes
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self.as_json = ['tuple', [subtype.as_json for subtype in subtypes]]
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def validate(self, value):
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"""return the validated value or raise"""
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# keep the ordering!
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try:
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if len(value) != len(self.subtypes):
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raise ValueError('Illegal number of Arguments! Need %d arguments.', len(self.subtypes))
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# validate elements and return as list
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return [sub.validate(elem) for sub,elem in zip(self.subtypes, value)]
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except Exception as exc:
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raise ValueError('Can not validate:', str(exc))
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def export(self, value):
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"""returns a python object fit for serialisation"""
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return [sub.export(elem) for sub,elem in zip(self.subtypes, value)]
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class StructOf(DataType):
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def __init__(self, **named_subtypes):
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if not named_subtypes:
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raise ValueError('Empty structs are not allowed!')
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for name, subtype in named_subtypes.items():
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if not isinstance(subtype, DataType):
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raise ProgrammingError('StructOf only works with named DataType objs as keyworded arguments!')
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if not isinstance(name, (str, unicode)):
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raise ProgrammingError('StructOf only works with named DataType objs as keyworded arguments!')
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self.named_subtypes = named_subtypes
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self.as_json = ['struct', dict((n,s.as_json) for n,s in named_subtypes.items())]
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def validate(self, value):
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"""return the validated value or raise"""
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try:
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if len(value.keys()) != len(self.named_subtypes.keys()):
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raise ValueError('Illegal number of Arguments! Need %d arguments.', len(self.namd_subtypes.keys()))
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# validate elements and return as dict
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return dict((str(k), self.named_subtypes[k].validate(v))
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for k,v in value.items())
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except Exception as exc:
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raise ValueError('Can not validate %s: %s', repr(value),str(exc))
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def export(self, value):
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"""returns a python object fit for serialisation"""
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if len(value.keys()) != len(self.named_subtypes.keys()):
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raise ValueError('Illegal number of Arguments! Need %d arguments.', len(self.namd_subtypes.keys()))
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return dict((str(k),self.named_subtypes[k].export(v))
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for k,v in value.items())
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# XXX: derive from above classes automagically!
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DATATYPES = dict(
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bool = lambda : BoolType(),
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int = lambda _min=None, _max=None: IntRange(_min, _max),
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double = lambda _min=None, _max=None: FloatRange(_min, _max),
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blob = lambda _min=None, _max=None: BLOBType(_min, _max),
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string = lambda _min=None, _max=None: StringType(_min, _max),
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array = lambda subtype, _min=None, _max=None: ArrayOf(get_datatype(subtype), _min, _max),
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tuple = lambda subtypes: TupleOf(*map(get_datatype,subtypes)),
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enum = lambda kwds: EnumType(**kwds),
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struct = lambda named_subtypes: StructOf(**dict((n,get_datatype(t)) for n,t in named_subtypes.items())),
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)
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# probably not needed...
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def export_datatype(datatype):
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return datatype.as_json
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# important for getting the right datatype from formerly jsonified descr.
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def get_datatype(json):
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if not isinstance(json, list):
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raise ValueError('Argument must be a properly formatted list!')
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if len(json)<1:
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raise ValueError('can not validate %r', json)
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base = json[0]
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if base in DATATYPES:
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if base in ('enum', 'struct'):
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if len(json) > 1:
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args = json[1:]
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else:
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args = []
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else:
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args = json[1:]
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try:
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return DATATYPES[base](*args)
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except (TypeError, AttributeError) as exc:
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raise ValueError('Invalid datatype descriptor')
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raise ValueError('can not validate %r', json)
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19
test/conftest.py
Normal file
19
test/conftest.py
Normal file
@ -0,0 +1,19 @@
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# content of conftest.py
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import pytest
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@pytest.fixture(scope="module")
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def constants():
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# setup
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class Constants(object):
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ONE = 1
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TWO = 2
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c = Constants()
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yield c
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# teardown
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del c
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@pytest.fixture(scope="session")
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def globals():
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return dict()
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8
test/test_blubb.py
Normal file
8
test/test_blubb.py
Normal file
@ -0,0 +1,8 @@
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def test_assert():
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assert 1
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def test_constants(constants):
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assert constants.ONE == 1
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assert constants.TWO == 2
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344
test/test_datatypes.py
Normal file
344
test/test_datatypes.py
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@ -0,0 +1,344 @@
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# -*- coding: utf-8 -*-
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# *****************************************************************************
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#
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# This program is free software; you can redistribute it and/or modify it under
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# the terms of the GNU General Public License as published by the Free Software
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# Foundation; either version 2 of the License, or (at your option) any later
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# version.
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#
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# This program is distributed in the hope that it will be useful, but WITHOUT
|
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# ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
|
||||
# FOR A PARTICULAR PURPOSE. See the GNU General Public License for more
|
||||
# details.
|
||||
#
|
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# You should have received a copy of the GNU General Public License along with
|
||||
# this program; if not, write to the Free Software Foundation, Inc.,
|
||||
# 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
|
||||
#
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# Module authors:
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# Enrico Faulhaber <enrico.faulhaber@frm2.tum.de>
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#
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# *****************************************************************************
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"""test data types."""
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# no fixtures needed
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import pytest
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import sys
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sys.path.insert(0, sys.path[0]+'/..')
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from secop.datatypes import DataType, FloatRange, IntRange, \
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EnumType, BLOBType, StringType, BoolType, ArrayOf, TupleOf, StructOf, \
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get_datatype, ProgrammingError
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def test_DataType():
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dt = DataType()
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assert dt.as_json == ['undefined']
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with pytest.raises(TypeError):
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||||
dt = DataType()
|
||||
dt.validate('')
|
||||
dt.export()
|
||||
|
||||
def test_FloatRange():
|
||||
dt = FloatRange(-3.14, 3.14)
|
||||
assert dt.as_json == ['double', -3.14, 3.14]
|
||||
|
||||
with pytest.raises(ValueError):
|
||||
dt.validate(9)
|
||||
with pytest.raises(ValueError):
|
||||
dt.validate(-9)
|
||||
with pytest.raises(ValueError):
|
||||
dt.validate('XX')
|
||||
with pytest.raises(ValueError):
|
||||
dt.validate([19,'X'])
|
||||
dt.validate(1)
|
||||
dt.validate(0)
|
||||
assert dt.export(-2.718) == -2.718
|
||||
with pytest.raises(ValueError):
|
||||
FloatRange('x','Y')
|
||||
|
||||
def test_IntRange():
|
||||
dt = IntRange(-3, 3)
|
||||
assert dt.as_json == ['int', -3, 3]
|
||||
|
||||
with pytest.raises(ValueError):
|
||||
dt.validate(9)
|
||||
with pytest.raises(ValueError):
|
||||
dt.validate(-9)
|
||||
with pytest.raises(ValueError):
|
||||
dt.validate('XX')
|
||||
with pytest.raises(ValueError):
|
||||
dt.validate([19,'X'])
|
||||
dt.validate(1)
|
||||
dt.validate(0)
|
||||
with pytest.raises(ValueError):
|
||||
IntRange('xc','Yx')
|
||||
|
||||
|
||||
def test_EnumType():
|
||||
# test constructor catching illegal arguments
|
||||
with pytest.raises(ValueError):
|
||||
EnumType(1)
|
||||
with pytest.raises(ValueError):
|
||||
EnumType('a',b=0)
|
||||
|
||||
dt = EnumType(a=3, c=7, stuff=1)
|
||||
assert dt.as_json == ['enum', dict(a=3, c=7, stuff=1)]
|
||||
|
||||
with pytest.raises(ValueError):
|
||||
dt.validate(9)
|
||||
with pytest.raises(ValueError):
|
||||
dt.validate(-9)
|
||||
with pytest.raises(ValueError):
|
||||
dt.validate('XX')
|
||||
with pytest.raises(TypeError):
|
||||
dt.validate([19,'X'])
|
||||
|
||||
assert dt.validate('a') == 'a'
|
||||
assert dt.validate('stuff') == 'stuff'
|
||||
assert dt.validate(1) == 'stuff'
|
||||
with pytest.raises(ValueError):
|
||||
dt.validate(2)
|
||||
|
||||
assert dt.export('c') == 7
|
||||
assert dt.export('stuff') == 1
|
||||
assert dt.export(1) == 1
|
||||
with pytest.raises(ValueError):
|
||||
dt.export(2)
|
||||
|
||||
def test_BLOBType():
|
||||
# test constructor catching illegal arguments
|
||||
dt = BLOBType(3, 10)
|
||||
assert dt.as_json == ['blob', 3, 10]
|
||||
|
||||
with pytest.raises(ValueError):
|
||||
dt.validate(9)
|
||||
with pytest.raises(ValueError):
|
||||
dt.validate('av')
|
||||
with pytest.raises(ValueError):
|
||||
dt.validate('abcdefghijklmno')
|
||||
assert dt.validate('abcd') == b'abcd'
|
||||
assert dt.validate(b'abcd') == b'abcd'
|
||||
assert dt.validate(u'abcd') == b'abcd'
|
||||
|
||||
assert dt.export('abcd') == b'abcd'
|
||||
assert dt.export(b'abcd') == b'abcd'
|
||||
assert dt.export(u'abcd') == b'abcd'
|
||||
|
||||
|
||||
def test_StringType():
|
||||
# test constructor catching illegal arguments
|
||||
dt = StringType(4, 11)
|
||||
assert dt.as_json == ['string', 4, 11]
|
||||
|
||||
with pytest.raises(ValueError):
|
||||
dt.validate(9)
|
||||
with pytest.raises(ValueError):
|
||||
dt.validate('av')
|
||||
with pytest.raises(ValueError):
|
||||
dt.validate('abcdefghijklmno')
|
||||
with pytest.raises(ValueError):
|
||||
dt.validate('abcdefg\0')
|
||||
assert dt.validate('abcd') == b'abcd'
|
||||
assert dt.validate(b'abcd') == b'abcd'
|
||||
assert dt.validate(u'abcd') == b'abcd'
|
||||
|
||||
assert dt.export('abcd') == b'abcd'
|
||||
assert dt.export(b'abcd') == b'abcd'
|
||||
assert dt.export(u'abcd') == b'abcd'
|
||||
|
||||
|
||||
def test_BoolType():
|
||||
# test constructor catching illegal arguments
|
||||
dt = BoolType()
|
||||
assert dt.as_json == ['bool']
|
||||
|
||||
with pytest.raises(ValueError):
|
||||
dt.validate(9)
|
||||
with pytest.raises(ValueError):
|
||||
dt.validate('av')
|
||||
|
||||
assert dt.validate('true') == True
|
||||
assert dt.validate('off') == False
|
||||
assert dt.validate(1) == True
|
||||
|
||||
assert dt.export('false') == False
|
||||
assert dt.export(0) == False
|
||||
assert dt.export('on') == True
|
||||
|
||||
|
||||
def test_ArrayOf():
|
||||
# test constructor catching illegal arguments
|
||||
with pytest.raises(ValueError):
|
||||
ArrayOf(int)
|
||||
dt = ArrayOf(IntRange(-10,10),1,3)
|
||||
assert dt.as_json == ['array', ['int', -10, 10], 1, 3]
|
||||
with pytest.raises(ValueError):
|
||||
dt.validate(9)
|
||||
with pytest.raises(ValueError):
|
||||
dt.validate('av')
|
||||
|
||||
assert dt.validate([1,2,3]) == [1,2,3]
|
||||
|
||||
assert dt.export([1,2,3]) == [1,2,3]
|
||||
|
||||
|
||||
def test_TupleOf():
|
||||
# test constructor catching illegal arguments
|
||||
with pytest.raises(ValueError):
|
||||
TupleOf(2)
|
||||
|
||||
dt = TupleOf(IntRange(-10,10), BoolType())
|
||||
assert dt.as_json == ['tuple', [['int', -10, 10], ['bool']]]
|
||||
|
||||
with pytest.raises(ValueError):
|
||||
dt.validate(9)
|
||||
with pytest.raises(ValueError):
|
||||
dt.validate([99,'X'])
|
||||
|
||||
assert dt.validate([1,True]) == [1,True]
|
||||
|
||||
assert dt.export([1,True]) == [1,True]
|
||||
|
||||
|
||||
def test_StructOf():
|
||||
# test constructor catching illegal arguments
|
||||
with pytest.raises(TypeError):
|
||||
StructOf(IntRange)
|
||||
with pytest.raises(ProgrammingError):
|
||||
StructOf(IntRange=1)
|
||||
|
||||
dt = StructOf(a_string=StringType(), an_int=IntRange(0, 999))
|
||||
assert dt.as_json == ['struct', {'a_string': ['string'],
|
||||
'an_int': ['int', 0, 999],
|
||||
}]
|
||||
|
||||
with pytest.raises(ValueError):
|
||||
dt.validate(9)
|
||||
with pytest.raises(ValueError):
|
||||
dt.validate([99,'X'])
|
||||
with pytest.raises(ValueError):
|
||||
dt.validate(dict(a_string='XXX', an_int=1811))
|
||||
|
||||
assert dt.validate(dict(a_string='XXX', an_int=8)) == {'a_string': 'XXX',
|
||||
'an_int': 8}
|
||||
assert dt.export({'an_int':13, 'a_string':'WFEC'}) == {'a_string': 'WFEC',
|
||||
'an_int': 13}
|
||||
|
||||
def test_get_datatype():
|
||||
with pytest.raises(ValueError):
|
||||
get_datatype(1)
|
||||
with pytest.raises(ValueError):
|
||||
get_datatype(True)
|
||||
with pytest.raises(ValueError):
|
||||
get_datatype(str)
|
||||
with pytest.raises(ValueError):
|
||||
get_datatype(['undefined'])
|
||||
|
||||
assert isinstance(get_datatype(['bool']), BoolType)
|
||||
with pytest.raises(ValueError):
|
||||
get_datatype(['bool', 3])
|
||||
|
||||
assert isinstance(get_datatype(['int']), IntRange)
|
||||
assert isinstance(get_datatype(['int', -10]), IntRange)
|
||||
assert isinstance(get_datatype(['int', None, 10]), IntRange)
|
||||
assert isinstance(get_datatype(['int', -10, 10]), IntRange)
|
||||
|
||||
with pytest.raises(ValueError):
|
||||
get_datatype(['int',10, -10])
|
||||
with pytest.raises(ValueError):
|
||||
get_datatype(['int', 1, 2, 3])
|
||||
|
||||
|
||||
assert isinstance(get_datatype(['double']), FloatRange)
|
||||
assert isinstance(get_datatype(['double', -2.718]), FloatRange)
|
||||
assert isinstance(get_datatype(['double', None, 3.14]), FloatRange)
|
||||
assert isinstance(get_datatype(['double', -9.9, 11.1]), FloatRange)
|
||||
|
||||
with pytest.raises(ValueError):
|
||||
get_datatype(['double',10, -10])
|
||||
with pytest.raises(ValueError):
|
||||
get_datatype(['double', 1, 2, 3])
|
||||
|
||||
|
||||
with pytest.raises(ValueError):
|
||||
get_datatype(['enum'])
|
||||
assert isinstance(get_datatype(['enum', dict(a=-2.718)]), EnumType)
|
||||
|
||||
with pytest.raises(ValueError):
|
||||
get_datatype(['enum',10, -10])
|
||||
with pytest.raises(ValueError):
|
||||
get_datatype(['enum', [1, 2, 3]])
|
||||
|
||||
|
||||
assert isinstance(get_datatype(['blob']), BLOBType)
|
||||
assert isinstance(get_datatype(['blob', 1]), BLOBType)
|
||||
assert isinstance(get_datatype(['blob', 1, 10]), BLOBType)
|
||||
|
||||
with pytest.raises(ValueError):
|
||||
get_datatype(['blob',10, -10])
|
||||
with pytest.raises(ValueError):
|
||||
get_datatype(['blob',10, -10, 1])
|
||||
|
||||
|
||||
assert isinstance(get_datatype(['string']), StringType)
|
||||
assert isinstance(get_datatype(['string', 1]), StringType)
|
||||
assert isinstance(get_datatype(['string', 1, 10]), StringType)
|
||||
|
||||
with pytest.raises(ValueError):
|
||||
get_datatype(['string',10, -10])
|
||||
with pytest.raises(ValueError):
|
||||
get_datatype(['string',10, -10, 1])
|
||||
|
||||
|
||||
with pytest.raises(ValueError):
|
||||
get_datatype(['array'])
|
||||
with pytest.raises(ValueError):
|
||||
get_datatype(['array', 1])
|
||||
with pytest.raises(ValueError):
|
||||
get_datatype(['array', [1], 2, 3])
|
||||
assert isinstance(get_datatype(['array', ['blob']]), ArrayOf)
|
||||
assert isinstance(get_datatype(['array', ['blob']]).subtype, BLOBType)
|
||||
|
||||
with pytest.raises(ValueError):
|
||||
get_datatype(['array', ['blob'], -10])
|
||||
with pytest.raises(ValueError):
|
||||
get_datatype(['array', ['blob'], -10, 10])
|
||||
|
||||
assert isinstance(get_datatype(['array', ['blob'], 1, 10]), ArrayOf)
|
||||
|
||||
|
||||
with pytest.raises(ValueError):
|
||||
get_datatype(['tuple'])
|
||||
with pytest.raises(ValueError):
|
||||
get_datatype(['tuple', 1])
|
||||
with pytest.raises(ValueError):
|
||||
get_datatype(['tuple', [1], 2, 3])
|
||||
assert isinstance(get_datatype(['tuple', [['blob']]]), TupleOf)
|
||||
assert isinstance(get_datatype(['tuple', [['blob']]]).subtypes[0], BLOBType)
|
||||
|
||||
with pytest.raises(ValueError):
|
||||
get_datatype(['tuple', [['blob']], -10])
|
||||
with pytest.raises(ValueError):
|
||||
get_datatype(['tuple', [['blob']], -10, 10])
|
||||
|
||||
assert isinstance(get_datatype(['tuple', [['blob'],['int']]]), TupleOf)
|
||||
|
||||
|
||||
with pytest.raises(ValueError):
|
||||
get_datatype(['struct'])
|
||||
with pytest.raises(ValueError):
|
||||
get_datatype(['struct', 1])
|
||||
with pytest.raises(ValueError):
|
||||
get_datatype(['struct', [1], 2, 3])
|
||||
assert isinstance(get_datatype(['struct', {'blob':['blob']}]), StructOf)
|
||||
assert isinstance(get_datatype(['struct', {'blob':['blob']}]).named_subtypes['blob'], BLOBType)
|
||||
|
||||
with pytest.raises(ValueError):
|
||||
get_datatype(['struct', [['blob']], -10])
|
||||
with pytest.raises(ValueError):
|
||||
get_datatype(['struct', [['blob']], -10, 10])
|
||||
|
||||
assert isinstance(get_datatype(['struct', {'blob':['blob'], 'int':['int']}]), StructOf)
|
||||
Loading…
x
Reference in New Issue
Block a user