if __name__ == '__main__':
from os import getcwd
from os import sys
sys.path.append(getcwd())
from MOAL.helpers.display import Section
from MOAL.helpers.display import prnt
from MOAL.helpers.display import print_h2
from MOAL.helpers.datamaker import make_sparselist
from MOAL.helpers.datamaker import make_sparsematrix
from MOAL.helpers.text import gibberish2
from pprint import pprint as ppr
from random import randrange as rr
DEBUG = True if __name__ == '__main__' else False
if DEBUG:
with Section('Sparse linear data structures'):
max = 100
density = 0.1
items = {rr(0, max): gibberish2() for _ in range(int(max * density))}
splist = make_sparselist(items, max)
prnt('Sparse list', splist)
sparse_data = {(x, x): gibberish2() for x in range(0, 10)}
sparsematrix = make_sparsematrix(sparse_data, max, rows=10, cols=10)
print_h2('Sparse matrix')
ppr(sparsematrix)
pnode['foo'] = {'foo': 'bar'}
except MutableAccessException:
print('Successfully blocked write of existing version.')
print_h2('Persistent full node')
pfatnode = FullyPersistentNode()
# Updating and overriding existing data
print(pfatnode)
pfatnode['foo'] = {'bar': 'baz'}
print(pfatnode)
pfatnode['bar'] = {'baz': 'bar'}
print(pfatnode)
print_simple('Current fat node data', pfatnode.get_current())
for _ in range(2):
pfatnode[gibberish2()] = {gibberish2(): gibberish2()}
print_simple('Fat node data', pfatnode.versions)
print_h2('Persistent confluent')
confluent = ConfluentlyPersistentNode()
confluent['foo'] = {gibberish2(): gibberish2()}
confluent['bar'] = {gibberish2(): gibberish2()}
confluent['bim'] = {gibberish2(): gibberish2()}
confluent['baz'] = {gibberish2(): gibberish2()}
print_simple('Confluent node data', confluent.versions)
confluent.meld('melded_example', versions=['foo', 'bar', 'baz', 'bim'])
print_simple('Confluent node data', confluent.versions)
print_h2('Persistent partial Fat Node')
confluentfat = ConfluentlyPersistentFatNode()
__author__ = """Chris Tabor ([email protected])""" if __name__ == '__main__': from os import getcwd from os import sys sys.path.append(getcwd()) from MOAL.helpers.display import Section from MOAL.helpers.display import prnt from MOAL.helpers.display import print_h2 from MOAL.helpers.datamaker import make_sparselist from MOAL.helpers.datamaker import make_sparsematrix from MOAL.helpers.text import gibberish2 from pprint import pprint as ppr from random import randrange as rr DEBUG = True if __name__ == '__main__' else False if DEBUG: with Section('Sparse linear data structures'): max = 100 density = 0.1 items = {rr(0, max): gibberish2() for _ in range(int(max * density))} splist = make_sparselist(items, max) prnt('Sparse list', splist) sparse_data = {(x, x): gibberish2() for x in range(0, 10)} sparsematrix = make_sparsematrix(sparse_data, max, rows=10, cols=10) print_h2('Sparse matrix') ppr(sparsematrix)
def _hash(self, data):
return tiger.new(data).hexdigest()
if DEBUG:
with Section('Hashed array tree'):
data = {
0: {'edges': [1, 2, 3], 'is_root': True},
1: {'edges': [], 'parent': 0},
2: {'edges': [4], 'parent': 0},
3: {'edges': [5], 'parent': 0},
4: {'edges': [], 'parent': 0},
5: {'edges': [], 'parent': 0},
}
for k, node in data.iteritems():
node['val'] = gibberish2()
print_h2('Merkle Tree')
merkle = MerkleTree(data)
for k, node in merkle.vertices.iteritems():
print('Node edges: {}, Child hash: {}'.format(
node['edges'], node['val']))
print_h2('Tiger Tree Hash')
data[0]['edges'].remove(3)
tth = TigerTreeHash(data)
for k, node in tth.vertices.iteritems():
print('Node edges: {}, Child hash: {}'.format(
node['edges'], node['val']))
for _ in range(4)}
}
})
prnt('List comprehension', [x**2 for x in range(10) if x % 2 == 0])
prnt('List comprehension - nested',
[[x**y for x in range(1, 4) if x % 2 == 0] for y in range(1, 8)])
wtf = [[_nested(min=x), _nested(max=y)]
for x, y in enumerate(range(1, 10))]
print_h2('List comprehensions - triple nested')
ppr(wtf)
print_h2('Dictionary and list comprehensions, combined')
dl_combined = {
txt.gibberish2(): _nested(min=x, max=x * 2)
for x in range(8)
}
ppr(dl_combined)
print_h2('Set comprehension')
set_comp = set([choice(range(100)) for _ in range(10)])
ppr(set_comp)
print_h2('Frozenset comprehension')
frozen_set_comp = frozenset([choice(range(100)) for _ in range(10)])
ppr(frozen_set_comp)
print_h2('Tuple comprehension')
tup = tuple((x, x * 2) for x in range(5))
ppr(tup)
pnode['foo'] = {'foo': 'bar'}
except MutableAccessException:
print('Successfully blocked write of existing version.')
print_h2('Persistent full node')
pfatnode = FullyPersistentNode()
# Updating and overriding existing data
print(pfatnode)
pfatnode['foo'] = {'bar': 'baz'}
print(pfatnode)
pfatnode['bar'] = {'baz': 'bar'}
print(pfatnode)
print_simple('Current fat node data', pfatnode.get_current())
for _ in range(2):
pfatnode[gibberish2()] = {gibberish2(): gibberish2()}
print_simple('Fat node data', pfatnode.versions)
print_h2('Persistent confluent')
confluent = ConfluentlyPersistentNode()
confluent['foo'] = {gibberish2(): gibberish2()}
confluent['bar'] = {gibberish2(): gibberish2()}
confluent['bim'] = {gibberish2(): gibberish2()}
confluent['baz'] = {gibberish2(): gibberish2()}
print_simple('Confluent node data', confluent.versions)
confluent.meld('melded_example', versions=['foo', 'bar', 'baz', 'bim'])
print_simple('Confluent node data', confluent.versions)
print_h2('Persistent partial Fat Node')
confluentfat = ConfluentlyPersistentFatNode()
