PYTHON ORDERED HASHTABLE Ordered Hashtable Overview For this assignment you will
ID: 3730831 • Letter: P
Question
PYTHON ORDERED HASHTABLE
Ordered Hashtable
Overview
For this assignment you will update and complete the implementation of the hashtable data structure presented in class, which exposes an API mirroring that of the built-in Python dict. When iterating over its contents (supported by the __iter__, keys, values, and items methods), your updated implementation will also reflect the order in which key/value pairs were originally inserted into the hashtable. This will require that you implement the two-tiered list system described during lecture.
The operations you will implement are listed alongside their descriptions below (h refers to a hashtable):
Your hashtable will be provided with the initial number of buckets on creation (i.e., in __init__); your implementation must heed this value, as there may be performance ramifications if it does not.
In [ ]:
In [ ]:
In [ ]:
In [ ]:
In [ ]:
In [ ]:
In [ ]:
Operation Description h[k] = v If h does not contain key k, a new kv mapping is added, else the value for key k is updated to v. h[k] If h contains key k, the corresponding value is returned, else a KeyError is raised. del h[k] If h contains key k, it is removed along with its value, else a KeyError is raised. Note that if k is re-inserted at some later point it is considered a new key (for ordering purposes). k in h Returns True if key k is in h. len(h) Returns the number of keys in h. iter(h) Returns an iterator over all the keys in h, in the order they were added. h.keys() (Same as above) h.values() Returns an iterator over all the values in h, in the order they were added. h.items() Returns an iterator over all the key/value pairs (as tuples) in h, in the order they were added.Explanation / Answer
class OrderedHashtable:
class Node:
"""This class is used to create nodes in the singly linked "chains" in
each hashtable bucket."""
def __init__(self, index, next=None):
# don't rename the following attributes!
self.index = index
self.next = next
def __init__(self, n_buckets=1000):
# the following two variables should be used to implement the "two-tiered"
# ordered hashtable described in class -- don't rename them!
self.indices = [None] * n_buckets
self.entries = []
self.count = 0
def __getitem__(self, key):
# YOUR CODE HERE
if key in self.entries:
return self.entries[key]
if hasattr(self.__class__, "__missing__"):
return self.__class__.__getitem__(self, key)
raise NotImplementedError()
def __setitem__(self, key, val):
# YOUR CODE HERE
self.entries[int(key)] =val
raise NotImplementedError()
def __delitem__(self, key):
# YOUR CODE HERE
del self.entries[key]
raise NotImplementedError()
def __contains__(self, key):
try:
_ = self[key]
return True
except:
return False
def __len__(self):
return self.count
def __iter__(self):
# YOUR CODE HERE
return self.entries.__iter__(self)
raise NotImplementedError()
def keys(self):
return iter(self)
def values(self):
# YOUR CODE HERE
return self.entries.values()
raise NotImplementedError()
def items(self):
# YOUR CODE HERE
return self.entries.items()
raise NotImplementedError()
def __str__(self):
return '{ ' + ', '.join(str(k) + ': ' + str(v) for k, v in self.items()) + ' }'
def __repr__(self):
return str(self)
# (3 tests) Short tests
from unittest import TestCase
import random
tc = TestCase()
ht = OrderedHashtable(2)
for k, v in (('batman', 'bruce wayne'), ('superman', 'clark kent'), ('spiderman', 'peter parker')):
ht[k] = v
tc.assertEqual(len(ht), 3)
tc.assertEqual(ht['superman'], 'clark kent')
tc.assertTrue('spiderman' in ht)
tc.assertFalse('iron man' in ht)
with tc.assertRaises(KeyError):
ht['iron man']
# (3 points) Basic tests (insertion, fetch, count, chain-lengths)
from unittest import TestCase
import random
tc = TestCase()
class MyInt(int):
def __hash__(self):
"""MyInts hash to themselves — already current Python default,
but just to ensure consistency."""
return self
def ll_len(l):
"""Returns the length of a linked list with head `l` (assuming no sentinel)"""
c = 0
while l:
c += 1
l = l.next
return c
ht = OrderedHashtable(10)
for i in range(25):
ht[MyInt(i)] = i*2
tc.assertEqual(len(ht), 25)
for i in range(5):
tc.assertEqual(ll_len(ht.indices[i]), 3)
for i in range(5, 10):
tc.assertEqual(ll_len(ht.indices[i]), 2)
for i in range(25):
tc.assertTrue(MyInt(i) in ht)
tc.assertEqual(ht[MyInt(i)], i*2)
# (3 points) Update testing
from unittest import TestCase
import random
tc = TestCase()
ht = OrderedHashtable(100)
d = {}
for i in range(100):
k, v = str(i), str(i*2)
d[k] = v
ht[k] = v
for j in range(0, 100, 2):
k, v = str(i), str(i*3)
d[k] = v
ht[k] = v
for j in range(0, 100, 4):
k, v = str(i), str(i*4)
d[k] = v
ht[k] = v
for i in range(100):
tc.assertTrue(k in ht)
tc.assertEqual(d[k], ht[k])
# (3 points) Deletion testing
from unittest import TestCase
import random
tc = TestCase()
ht = OrderedHashtable(100)
d = {}
for i in range(100):
k, v = str(i), str(random.randrange(10000000, 99999999))
d[k] = v
ht[k] = v
for _ in range(50):
k = str(random.randrange(100))
if k in d:
del d[k]
del ht[k]
tc.assertEqual(len(ht), len(d))
for k,v in ht.items():
tc.assertEqual(d[k], v)
# (4 points) Iteration order testing
from unittest import TestCase
import random
tc = TestCase()
ht = OrderedHashtable(1000)
l = [str(i) for i in range(0, 1000)]
random.shuffle(l)
for x in l:
ht[x] = x
for _ in range(50):
idx_to_del = random.randrange(len(l))
val_to_del = l[idx_to_del]
del ht[val_to_del]
del l[idx_to_del]
if random.randrange(2) == 0:
l.append(val_to_del)
ht[val_to_del] = val_to_del
for x, y in zip(l, ht):
tc.assertEqual(x, y)
# (4 points) Stress testing
from unittest import TestCase
from time import time
import random
tc = TestCase()
ht = OrderedHashtable(100000)
d = {}
start = time()
for _ in range(100000):
k, v = str(random.randrange(100000)), str(random.randrange(10000000, 99999999))
d[k] = v
ht[k] = v
for k,v in d.items():
tc.assertTrue(k in ht)
tc.assertEqual(d[k], ht[k])
end = time()
print(end-start)
tc.assertLess(end-start, 1.5, 'Your implementation ran too slow!')
Related Questions
Navigate
Integrity-first tutoring: explanations and feedback only — we do not complete graded work. Learn more.