def test_get(self):
"""Tests the HashMap get method"""
test_values = [("test_5", 5), ("test_-5", -5), ("test_5_", 5),
("diff_word", 15), ("another_word", 20), ("set", 10),
("anotha_one", -7), ("completely_different", 5),
("getting_there", -1)]
collision_values = [("completely_different", 5), ("anotha_one", -7),
("set", 10), ("another_word", 20)]
head_node = collision_values[0]
tail_node = collision_values[3]
student_map = HashMap(10, hash_function_1)
# add all key value pairs to the table
for key, val in test_values:
student_map.put(key, val)
# test get at linked_list head
self.assertEqual(student_map.get(head_node[0]), head_node[1])
# test get at linked_list tail
self.assertEqual(student_map.get(tail_node[0]), tail_node[1])
# test get at > 2 collision bucket
for node in collision_values:
self.assertEqual(student_map.get(node[0]), node[1])
# test get with no collision
self.assertEqual(student_map.get("getting_there"), -1)
# test that all values are in the list
for node in test_values:
self.assertEqual(student_map.get(node[0]), node[1])
def top_words(source, number):
"""
Takes a plain text file and counts the number of occurrences of case insensitive words.
Returns the top `number` of words in a list of tuples of the form (word, count).
Args:
source: the file name containing the text
number: the number of top results to return (e.g. 5 would return the 5 most common words)
Returns:
A list of tuples of the form (word, count), sorted by most common word. (e.g. [("a", 23), ("the", 20), ("it", 10)])
"""
keys = set()
ht = HashMap(2500, hash_function_2)
# Reads a file one word as a time and
with open(source) as f:
for line in f:
words = rgx.findall(line)
for w in words:
w = w.lower(
) # covert word to lowercase for case-insensitive comparisons
if ht.contains_key(
w
): # if word already exists as key in ht, add 1 to value to track count
value = ht.get(w)
ht.put(w, value + 1)
else:
ht.put(
w, 1
) # if word does not exist in ht as key, add word as key and initialize value as 1
keys.add(w) # add word to set of keys
count_dict = {} # initialize empty dictionary
count_array = [] # initialize empty array
for key in keys: # for each key, get it's value from ht and then add key/value pair to count_dict
value = ht.get(key)
count_dict[key] = value
for key in keys: # for each key, add value/key pair to array for sorting
count_array.append((count_dict[key], key))
count_array = sorted(
count_array, reverse=True
) # reverse sort count_array from largest to smallest value
for i in range(
len(count_array)
): # reswap key/value pairs to get (word, count) for each tuple in count_array
count_array[i] = (count_array[i][1], count_array[i][0])
return count_array[:
number] # return only the requested number of top words
def test_change_val(self):
h = HashMap(3)
h.set('1', SampleObject('A'))
b_obj = SampleObject('B')
h.set('2', b_obj)
self.assertEqual(h.get('2'), b_obj)
h.set('3', SampleObject('C'))
b_obj_2 = SampleObject('B2')
h.set('2', b_obj_2)
self.assertEqual(h.get('2'), b_obj_2)
def test_resize_table_1(self):
"""
Test resize_table() with Example #1 from the guidelines.
:passed: yes
"""
print("--- EXAMPLE 1 ---")
m = HashMap(20, hash_function_1)
m.put('key1', 10)
print(m.size, m.capacity, m.get('key1'), m.contains_key('key1'))
m.resize_table(30)
print(m.size, m.capacity, m.get('key1'), m.contains_key('key1'))
def test_remove_1(self):
"""
Test remove() with Example #1 from the guidelines.
:passed: yes
"""
print("--- EXAMPLE 1 ---")
m = HashMap(50, hash_function_1)
print(m.get('key1'))
m.put('key1', 10)
print(m.get('key1'))
m.remove('key1')
print(m.get('key1'))
m.remove('key4')
def top_words(source, number):
"""
Takes a plain text file and counts the number of occurrences of case insensitive words.
Returns the top `number` of words in a list of tuples of the form (word, count).
Args:
source: the file name containing the text
number: the number of top results to return (e.g. 5 would return the 5 most common words)
Returns:
A list of tuples of the form (word, count), sorted by most common word. (e.g. [("a", 23), ("the", 20), ("it", 10)])
"""
keys = set()
ht = HashMap(2500, hash_function_2)
# This block of code will read a file one word as a time and |
# put the word in `w`. It should be left as starter code. |
with open(source) as f: # |
for line in f: # |
words = rgx.findall(line) # |
for w in words: # |
# lower case all incoming words to make case insensitive
w = w.lower()
# Check if hashtable already contains word
if ht.contains_key(w):
# If so retrieve the count for the given word
count = ht.get(w)
# Update existing key with incremented count value
ht.put(w, count + 1)
else:
# Add new word to keys set collection
keys.add(w)
# put new word in hash table with a count of 1
ht.put(w, 1)
# Check if table load is over load limit before next word
if ht.table_load() > 8:
# if so, resize hash table to twice the capacity
ht.resize_table(2 * ht.capacity)
# initialize tuple word/count list
topWords = []
# for each key in the set of keys
for key in keys:
# append the key and value as a tuple in the topWords list
topWords.append((key, ht.get(key)))
# once all tuples are added to list, sort list by the count of each key in descending order
topWords.sort(key=lambda keyCountTup: keyCountTup[1], reverse=True)
# After sort, set top word list to only contain the given number of tuples requested
topWords = topWords[:number]
# return topWords list of tuples of length equal to number
return topWords
def top_words(source, number):
"""
Takes a plain text file and counts the number of occurrences of case insensitive words.
Returns the top `number` of words in a list of tuples of the form (word, count).
Args:
source: the file name containing the text
number: the number of top results to return (e.g. 5 would return the 5 most common words)
Returns:
A list of tuples of the form (word, count), sorted by most common word. (e.g. [("a", 23), ("the", 20), ("it", 10)])
"""
keys = set()
ht = HashMap(2500, hash_function_2)
# This block of code will read a file one word as a time and
# put the word in `w`. It should be left as starter code.
with open(source) as f:
for line in f:
words = rgx.findall(line)
for w in words: # Iterate through all the words in the line.
# Place lowercased version of words.
if ht.contains_key(
w.lower()): # If the word is in the hashmap.
ht.put(w.lower(),
ht.get(w.lower()) +
1) # Update the word count by 1.
else: # If the word does not exist in the hashmap.
ht.put(w.lower(),
1) # Place the key in the map with the value of 1.
keys.add(w.lower()) # Add the new keys into the keys set.
list_of_occurences = [
] # Create an empty list to hold the tuples of keys and values.
for key in keys: # Iterate through all the keys.
list_of_occurences.append(
(key, ht.get(key))) # Add the key and value tuple into the list.
# Source to help me find a way to implement this:
# stackoverflow.com/questions/10695139/sort-a-list-of-tuples-by-2nd-item-integer-value
# We use lambda here to sort the list of tuples by its second value.
# The sorting is also reversed to make it in descending order.
sorted_list = sorted(list_of_occurences, key=lambda x: x[1], reverse=True)
return sorted_list[:
number] # Using list slice, return the top numbers of the list depending on what the user inputs
# print(top_words("alice.txt",10)) # COMMENT THIS OUT WHEN SUBMITTING TO GRADESCOPE
def top_words(source, number):
"""
Takes a plain text file and counts the number of occurrences of case insensitive words.
Returns the top `number` of words in a list of tuples of the form (word, count).
Args:
source: the file name containing the text
number: the number of top results to return (e.g. 5 would return the 5 most common words)
Returns:
A list of tuples of the form (word, count), sorted by most common word. (e.g. [("a", 23), ("the", 20), ("it", 10)])
"""
keys = set()
ht = HashMap(2500,hash_function_2)
# This block of code will read a file one word as a time and
# put the word in `w`. It should be left as starter code.
with open(source) as f:
for line in f:
words = rgx.findall(line)
for w in words:
w = w.lower() # make everything lower case
# if the word is already in keys, get and increase the count.
if w in keys:
count = ht.get(w)
count += 1
ht.put(w, count) # update the count
# otherwise add the new word to the hashmap with count of 1
else:
ht.put(w, 1)
keys.add(w)
count_list = [] # list of tuples of keys and counts
# for each key, get the value, and add these pairs as tuples to count_list
for k in keys:
val = ht.get(k)
pair = (k, val)
count_list.append(pair)
# sort count_list with a lambda function using sorted(). Reverse the list for descending order
count_list = sorted(count_list, key=lambda x: x[1], reverse=True) # where x is a tuple and x[1] is the word count
# return the appropriate number of top words
return count_list[:number]
def top_words(source, number):
"""
Takes a plain text file and counts the number of occurrences of case insensitive words.
Returns the top `number` of words in a list of tuples of the form (word, count).
Args:
source: the file name containing the text
number: the number of top results to return (e.g. 5 would return the 5 most common words)
Returns:
A list of tuples of the form (word, count), sorted by most common word. (e.g. [("a", 23), ("the", 20), ("it", 10)])
"""
keys = set()
ht = HashMap(2500, hash_function_2)
# This block of code will read a file one word as a time and
# put the word in `w`. It should be left as starter code.
with open(source) as f:
for line in f:
words = rgx.findall(line)
for w in words:
if (ht.get(w) is None):
ht.put(w, 1)
else:
#Buffer into hash map
ht.put(w, ht.get(w) + 1)
#Handle sorting
tuples = []
for i in range(ht.capacity):
cur = ht._buckets[i]
if cur.head is not None:
cur = cur.head
while (cur != None):
#Buffer key pair into tuples
tuples.append((cur.key, cur.value))
#Go to next
cur = cur.next
tuples = sorted(tuples, key=lambda x: x[1], reverse=True)
newTuples = []
for j in range(number):
newTuples.append(tuples[j])
return newTuples
def test_all():
hash_map = HashMap()
el_count = EL_COUNT
for x in range(el_count):
hash_map.put(str(x), str(x))
for x in range(el_count):
assert hash_map.get(str(x)) == str(x)
def top_words(source, number):
"""
Takes a plain text file and counts the number of occurrences of case insensitive words.
Returns the top `number` of words in a list of tuples of the form (word, count).
Args:
source: the file name containing the text
number: the number of top results to return (e.g. 5 would return the 5 most common words)
Returns:
A list of tuples of the form (word, count), sorted by most common word. (e.g. [("a", 23), ("the", 20), ("it", 10)])
"""
keys = set()
ht = HashMap(2500,hash_function_2)
# This block of code will read a file one word as a time and
# put the word in `w`. It should be left as starter code.
with open(source) as f:
for line in f:
words = rgx.findall(line)
for w in words:
if ht.contains_key(w.lower()):
ht.put(w.lower(), ht.get(w.lower()) + 1)
else:
ht.put(w.lower(), 1)
tup = ht.sorted_tup()
return tup[:number]
def top_words(source, number):
"""
Takes a plain text file and counts the number of occurrences of case insensitive words.
Returns the top `number` of words in a list of tuples of the form (word, count).
Args:
source: the file name containing the text
number: the number of top results to return (e.g. 5 would return the 5 most common words)
Returns:
A list of tuples of the form (word, count), sorted by most common word. (e.g. [("a", 23), ("the", 20), ("it", 10)])
"""
keys = set() # Variable representing empty set.
ht = HashMap(
2500, hash_function_2
) # Variable to represent hash map construct utilizing above function.
# This block of code will read a file one word as a time and
# put the word in `w`. It should be left as starter code.
with open(source
) as f: # Opens file to be used declaring it as variable 'f'.
for line in f: # Loops through each line within file (f).
words = rgx.findall(
line) # Variable utilized to represent words within each line.
for w in words: # Loops through each word within each line.
lw = w.lower(
) # Turns words lowercase to remove case sensitivity.
keys.add(
lw
) # Adds lowercase word to set represented by variable 'key'.
if ht.contains_key(
lw): # Checks if word is already present in hash map.
new_value = (
ht.get(lw) + 1
) # Variable represents word count increased by one.
ht.put(
lw, new_value
) # Inserts word into hash map to have word count be updated.
else:
ht.put(
lw, 1
) # Inserts word into hash map with initial count of one.
keys_list = [] # Variable represents an empty list.
for values in keys: # Loops through words present in set represented by variable 'keys'.
ind = ht._hash_function(values) % ht.capacity
# Variable to represent number established by chosen function and available capacity.
temp = ht._buckets[
ind] # Variable to represent position within hash map containing linked list.
node = temp.contains(
values
) # Variable to represent node containing key if already present.
keys_list.append(
(node.key,
node.value)) # Adds tuple to list containing word, word count.
keys_list.sort(
key=lambda tup: tup[1],
reverse=True) # Sorts list in descending order based on word count.
return keys_list[
0:
number] # Returns list of top words within given range provided by user.
def top_words(source, number):
"""
Takes a plain text file and counts the number of occurrences of case insensitive words.
Returns the top `number` of words in a list of tuples of the form (word, count).
Args:
source: the file name containing the text
number: the number of top results to return (e.g. 5 would return the 5 most common words)
Returns:
A list of tuples of the form (word, count), sorted by most common word. (e.g. [("a", 23), ("the", 20), ("it", 10)])
"""
keys = set()
ht = HashMap(2500, hash_function_2)
# This block of code will read a file one word as a time and
# put the word in `w`. It should be left as starter code.
# build hash table
with open(source) as f:
for line in f:
words = rgx.findall(line)
for w in words:
# convert to lowercase so words are counted properly
lowercase_w = w.lower()
keys.add(lowercase_w)
word_count = ht.get(lowercase_w)
# have value of node track number of times word has appeared
if word_count is None:
ht.put(lowercase_w, 1)
else:
ht.put(lowercase_w, word_count + 1)
# for the amount of top words requested, find the word with maximum count
max_list = []
for count in range(number):
max_w = ""
max_value = 0
# iterate over all words to find max key, value
for w in keys:
value = ht.get(w)
if value > max_value:
max_key = w
max_value = value
max_list.append((max_key, max_value))
# remove max word from set for next iteration to get next top word
keys.remove(max_key)
return max_list
def top_words(source, number):
"""
Takes a plain text file and counts the number of occurrences of case insensitive words.
Returns the top `number` of words in a list of tuples of the form (word, count).
Args:
source: the file name containing the text
number: the number of top results to return (e.g. 5 would return the 5 most common words)
Returns:
A list of tuples of the form (word, count), sorted by most common word. (e.g. [("a", 23), ("the", 20), ("it", 10)])
"""
keys = set()
ht = HashMap(2500, hash_function_2)
# This block of code will read a file one word as a time and
# put the word in `w`. It should be left as starter code.
with open(source) as f:
for line in f:
words = rgx.findall(line)
for w in words:
# Place word in hash map or update value by one
w = w.lower()
if not ht.contains_key(w):
keys.add(w)
ht.put(w, 1)
else:
ht.put(w, ht.get(w) + 1)
# Sort the words by mentions
sorted_words = []
for word in keys:
next_word = (word, ht.get(word))
if sorted_words == []:
sorted_words.append(next_word)
else:
for index, value in enumerate(sorted_words):
if next_word[1] >= value[1]:
sorted_words.insert(index, next_word)
break
return sorted_words[:number]
# print(top_words("alice.txt",10)) # COMMENT THIS OUT WHEN SUBMITTING TO GRADESCOPE
def test_get(self):
h = HashMap(100)
h.set('1', SampleObject('A'))
b_obj = SampleObject('B')
h.set('2', b_obj)
h.set('3', SampleObject('C'))
self.assertEqual(h.get('2'), b_obj)
self.assertEqual(h.get('4'), None)
def top_words(source, number):
"""
Takes a plain text file and counts the number of occurrences of case insensitive words.
Returns the top `number` of words in a list of tuples of the form (word, count).
Args:
source: the file name containing the text
number: the number of top results to return (e.g. 5 would return the 5 most common words)
Returns:
A list of tuples of the form (word, count), sorted by most common word. (e.g. [("a", 23), ("the", 20), ("it", 10)])
"""
keys = set()
ht = HashMap(2500, hash_function_2)
# This block of code will read a file one word as a time and
# put the word in `w`. It should be left as starter code.
with open(source) as f:
for line in f:
words = rgx.findall(line)
for w in words:
word = w.lower()
# check if the word is in the hash table
if word in keys:
# if the word is in the hash table, add one to the value of it's node
ht.put(word, ht.get(word) + 1)
# if the word is not in the hash table, add the word to the table with a value of one
else:
keys.add(word)
ht.put(word, 1)
# place all words and counts in an array as tuples
words_count = [(key, ht.get(key)) for key in keys]
# sort the words in the hash table by count
words_count.sort(reverse=True, key=sort_by_value)
return words_count[:number]
def top_words(source, number):
"""
Takes a plain text file and counts the number of occurrences of case insensitive words.
Returns the top `number` of words in a list of tuples of the form (word, count).
Args:
source: the file name containing the text
number: the number of top results to return (e.g. 5 would return the 5 most common words)
Returns:
A list of tuples of the form (word, count), sorted by most common word. (e.g. [("a", 23), ("the", 20), ("it", 10)])
"""
keys = set()
ht = HashMap(2500,hash_function_2)
# This block of code will read a file one word as a time and
# put the word in `w`. It should be left as starter code.
with open(source) as f:
for line in f:
words = rgx.findall(line)
for w in words:
w = w.lower()
if ht.contains_key(w):
node_value = ht.get(w)
node_value += 1
ht.put(w, node_value)
else:
node_value = 1
ht.put(w, node_value)
keys.add(w)
key_value_arr = []
for i in keys:
key_value = (i, ht.get(i))
key_value_arr.append(key_value)
key_value_arr.sort(key=lambda x: x[1], reverse=True)
top = []
for i in range(number):
top.append(key_value_arr[i])
return top
def top_words(source, number):
"""
Takes a plain text file and counts the number of occurrences of case insensitive words.
Returns the top `number` of words in a list of tuples of the form (word, count).
Args:
source: the file name containing the text
number: the number of top results to return (e.g. 5 would return the 5 most common words)
Returns:
A list of tuples of the form (word, count), sorted by most common word. (e.g. [("a", 23), ("the", 20), ("it", 10)])
"""
keys = set()
ht = HashMap(2500, hash_function_2)
# This block of code will read a file one word as a time
with open(source) as f:
for line in f:
words = rgx.findall(line)
for w in words:
# check if word is already in hash map (ht). if none, create an entry with value as 1
if ht.contains_key(w) is False:
ht.put(w, 1)
# if True, value += 1
else:
val = ht.get(w)
ht.put(w, val + 1)
# put the word in the set keys
keys.add(w.lower())
# create empty array, push pair values of keys in
pairs = [(word, ht.get(word)) for word in keys]
# sort the array, slice the array by number given
pairs = sorted(pairs, key=lambda x: x[1], reverse=True)
return pairs[:number]
class Account(object):
# Initialize Account object with cash and hash map of stocks, where
# stock name points to number of shares
def __init__(self):
self.cash = 0
self.stocks = HashMap()
# Compare account's cash and stocks with that of another account
# Used in TransactionParser's reconcile() method
def compare(self, other_acct):
diffs = []
other_stocks = other_acct.stocks
all_keys = list(set(self.stocks.keys() + other_stocks.keys()))
for key in all_keys:
diff = self.stock_diff(key, other_stocks)
if diff and diff != 0:
diffs.append(key + " " + str(int(diff)))
diffs.insert(0, "Cash " + str(self.cash_diff(other_acct.cash)))
return "\n".join(diffs)
def cash_diff(self, other_cash):
return int(other_cash) - self.cash
# Calculates differences in shares of stocks between two accounts
def stock_diff(self, key, declared_results):
if self.stocks[key] and declared_results[key]:
return float(declared_results[key]) - self.stocks[key]
elif self.stocks[key]:
return -1 * self.stocks[key]
elif declared_results[key] and key != "Cash":
return float(declared_results[key])
else:
return None
# Wrapper for setting a stock into self.stocks
def set_stock(self, name, value):
self.stocks[name] = value
# Wrapper for getting a stock
def get_stock(self, stock):
return self.stocks.get(stock, 0)
def top_words(source, number):
"""
Takes a plain text file and counts the number of occurrences of case insensitive words.
Returns the top `number` of words in a list of tuples of the form (word, count).
Args:
source: the file name containing the text
number: the number of top results to return (e.g. 5 would return the 5 most common words)
Returns:
A list of tuples of the form (word, count), sorted by most common word. (e.g. [("a", 23), ("the", 20), ("it", 10)])
"""
keys = set()
ht = HashMap(2500, hash_function_2)
# This block of code will read a file one word as a time and
# put the word in `w`. It should be left as starter code.
with open(source) as f:
for line in f:
words = rgx.findall(line)
for w in words:
#append the individual words to the list and convert letters
#to lowercase for case sensitivity
lower_case = w.lower()
keys.add(lower_case)
#check if word is alread in hashmap
if ht.contains_key(lower_case):
#increase word count and insert into hasmap and update count
val = (ht.get(lower_case) + 1)
ht.put(lower_case, val)
else:
#insert into hasmap with initial count being one 1 if not in hashmap already
ht.put(lower_case, 1)
#create a new list if words
word_list = []
#loop thru the list
for k in keys:
index = ht._hash_function(k) % ht.capacity
temp = ht._buckets[index]
#add tuples to list containing word and count
linked_node = temp.contains(k)
word_list.append((linked_node.key, linked_node.value))
#sort list in descending order
word_list.sort(key=lambda tup: tup[1], reverse=True)
#return list of top words
return word_list[0:number]
# print(top_words("alice.txt",10)) # COMMENT THIS OUT WHEN SUBMITTING TO GRADESCOPE
def top_words(source, number):
"""
Takes a plain text file and counts the number of occurrences of case insensitive words.
Returns the top `number` of words in a list of tuples of the form (word, count).
Args:
source: the file name containing the text
number: the number of top results to return (e.g. 5 would return the 5 most common words)
Returns:
A list of tuples of the form (word, count), sorted by most common word. (e.g. [("a", 23), ("the", 20), ("it", 10)])
"""
keys = set()
ht = HashMap(2500, hash_function_2)
# This block of code will read a file one word at a time and
# put the word in `w`. It should be left as starter code.
with open(source) as f:
for line in f:
words = rgx.findall(line)
for w in words:
# Convert all words to lowercase prior to insertion
w = w.lower()
# If the word is already in the hash map, pass the value with a new updated count
if ht.contains_key(w):
count = ht.get(w) + 1
ht.put(w, count)
else:
# Otherwise, create a new entry in the hashmap
ht.put(w, 1)
# Add all of the words to the keys set
for bucket in ht.get_buckets():
# Iterate through each bucket/linked list
curr = bucket.head
while curr is not None:
# Add the keys as a tuple
keys.add((curr.key, curr.value))
curr = curr.next
# Cast the set as a list
all_words = list(keys)
# Sort the words according to their value in the tuple
all_words.sort(key=lambda word: word[1])
slice_val = (number * -1 - 1)
top_wds = all_words[:slice_val:-1]
return top_wds
def top_words(source, number):
"""
Takes a plain text file and counts the number of occurrences of case insensitive words.
Returns the top `number` of words in a list of tuples of the form (word, count).
Args:
source: the file name containing the text
number: the number of top results to return (e.g. 5 would return the 5 most common words)
Returns:
A list of tuples of the form (word, count), sorted by most common word. (e.g. [("a", 23), ("the", 20), ("it", 10)])
"""
keys = set()
ht = HashMap(2500, hash_function_2)
# This block of code will read a file one word as a time and
# put the word in `w`. It should be left as starter code.
with open(source) as f:
for line in f:
words = rgx.findall(line)
for w in words:
w = w.lower()
count = ht.get(w)
if count is None:
ht.put(w, 1) # Word is not in the hash map; add it
else:
ht.put(w, count +
1) # Word is in the hash map; increment the count
heap = Heap() # Create a heap to do the sorting
for i in range(ht.capacity):
node = ht._buckets[i].head
while node is not None:
t = (node.key, node.value)
heap.insert(t) # Add each tuple to the heap
node = node.next
heap.sort() # Sort by word count, descending
if number <= len(heap.heap):
return heap.heap[0:number]
else:
return heap.heap # Handles the case where the user requests too many words
def top_words(source, number):
"""
Take a plain text file and count the number of occurrences of case insensitive words.
Return the top `number` of words in a list of tuples of the form (word, count).
:param source: the file name containing the text
:param number: the number of top results to return (e.g. 5 would return the 5 most common words)
:return: a list of tuples of the form (word, count), sorted by most common word (e.g. [("a", 23), ("the", 20), ("it", 10)])
"""
keys = set()
ht = HashMap(2500, hash_function_2)
# Read the file one word at a time and put the word in `w`
with open(source) as f:
for line in f:
words = rgx.findall(line)
for w in words:
# Convert the word to lowercase to enforce case insensitivity
word_lower = w.lower()
# If the word already exists in the table, get and update its
# current count
if ht.contains_key(word_lower):
cur_count = ht.get(word_lower) # Get current count
ht.put(word_lower, cur_count + 1) # Update current count
# If the word does not exist in the table, add it and set its
# count to 1
else:
ht.put(word_lower, 1)
# Get a list of tuples consisting of all the key-value pairs in the table
tuple_list = ht.get_tuples()
# Sort the list of tuples in descending order by word count
tuple_list.sort(key=get_count, reverse=True)
# print("sorted tuple_list:", tuple_list)
# Slice the list of tuples to contain `number` amount of tuples
sliced_list = tuple_list[0:number]
# Return the sliced list of tuples
return sliced_list
def top_words(source, number):
"""
Takes a plain text file and counts the number of occurrences of case insensitive words.
Returns the top `number` of words in a list of tuples of the form (word, count).
Args:
source: the file name containing the text
number: the number of top results to return (e.g. 5 would return the 5 most common words)
Returns:
A list of tuples of the form (word, count), sorted by most common word. (e.g. [("a", 23), ("the", 20), ("it", 10)])
"""
keys = set()
ht = HashMap(2500, hash_function_2)
# This block of code will read a file one word as a time and
# put the word in `w`. It should be left as starter code.
with open(source) as f:
for line in f:
words = rgx.findall(line)
for w in words:
w = w.lower()
value = 1
if ht.contains_key(w):
value = ht.get(w) + 1
ht.put(w, value)
else:
ht.put(w, value)
temp_list = ht.word_count_list()
lst = len(temp_list)
for i in range(0, lst):
for j in range(0, lst - i - 1):
if temp_list[j][1] < temp_list[j + 1][1]:
temp_list[j], temp_list[j + 1] = temp_list[j + 1], temp_list[j]
final_tuples = []
for k in range(0, number):
final_tuples.append(temp_list[k])
return final_tuples
def top_words(source, number):
"""
Takes a plain text file and counts the number of occurrences of case insensitive words.
Returns the top `number` of words in a list of tuples of the form (word, count).
Args:
source: the file name containing the text
number: the number of top results to return (e.g. 5 would return the 5 most common words)
Returns:
A list of tuples of the form (word, count), sorted by most common word. (e.g. [("a", 23), ("the", 20), ("it", 10)])
"""
result = []
ht = HashMap(2500, hash_function_2)
# This block of code will read a file one word at a time
# and add it to the hash map
with open(source) as f:
for line in f:
words = rgx.findall(line)
for w in words:
lw = w.lower()
# If the word is not in the hash map, add it with a value of 1
if not ht.contains_key(lw):
ht.put(lw, 1)
else:
# Otherwise, update the value by increasing it by 1
ht.put(lw, ht.get(lw) + 1)
for bucket in ht._buckets:
cur = bucket.head
while cur is not None:
result.append((cur.key, cur.value))
cur = cur.next
print(ht.table_load())
print(ht.empty_buckets())
sort_words(result)
return result[:number]
def top_words(source, number):
"""
Takes a plain text file and counts the number of occurrences of case insensitive words.
Returns the top `number` of words in a list of tuples of the form (word, count).
Args:
source: the file name containing the text
number: the number of top results to return (e.g. 5 would return the 5 most common words)
Returns:
A list of tuples of the form (word, count), sorted by most common word. (e.g. [("a", 23), ("the", 20), ("it", 10)])
"""
keys = set()
lst = []
ht = HashMap(2500, hash_function_2)
# This block of code will read a file one word as a time and
# put the word in `w`. It should be left as starter code.
with open(source) as f:
for line in f:
words = rgx.findall(line)
for w in words:
key = w.lower()
value = ht.get(key)
if value is not None:
ht.put(key, value + 1)
else:
ht.put(key, 1)
for i in range(ht.capacity):
ll = ht._buckets[i]
cur = ll.head
while cur is not None:
lst.append((cur.key, cur.value))
cur = cur.next
lst.sort(key=lambda x: x[1], reverse=True)
if number <= len(lst):
return lst[:number]
else:
return lst
def top_words(source, number):
"""
Takes a plain text file and counts the number of occurrences of case insensitive words.
Returns the top `number` of words in a list of tuples of the form (word, count).
Args:
source: the file name containing the text
number: the number of top results to return (e.g. 5 would return the 5 most common words)
Returns:
A list of tuples of the form (word, count), sorted by most common word. (e.g. [("a", 23), ("the", 20), ("it", 10)])
"""
keys = set()
word_list = []
ht = HashMap(2500,hash_function_2)
# This block of code will read a file one word as a time and
# put the word in `w`. It should be left as starter code.
with open(source) as f:
for line in f:
words = rgx.findall(line)
count = 1
for w in words:
w = w.lower()
ht.put_count(w,1) # using helper put method to just add the key and keep track of value
word_list.append(w) # creating a new list of just words
word_list = list(dict.fromkeys(word_list)) # removing duplicates
word_tuple = []
for i in word_list:
word_tuple.append((i,ht.get(i))) #appends a tuple with the word key and its corresponding value
word_tuple = sorted(word_tuple, key=lambda x: x[1],reverse=True) # sorting the tuple from Greatest to Least based on Value
top_list = []
for i in range(number):
top_list.append(word_tuple[i]) # appending tuple index key/value up to arg number, keys with highest value at index 0
return top_list
def top_words(source, number):
"""
Takes a plain text file and counts the number of occurrences of case insensitive words.
Returns the top `number` of words in a list of tuples of the form (word, count).
Args:
source: the file name containing the text
number: the number of top results to return (e.g. 5 would return the 5 most common words)
Returns:
A list of tuples of the form (word, count), sorted by most common word. (e.g. [("a", 23), ("the", 20), ("it", 10)])
"""
ht = HashMap(2500, hash_function_2)
# This block of code will read a file one word as a time and
# put the word in `w`. It should be left as starter code.
with open(source) as f:
for line in f:
words = rgx.findall(line)
for w in words:
w = w.lower()
count = ht.get(w)
if ht.contains_key(w):
ht.put(w, count + 1)
else:
ht.put(w, 1)
# Add all items in hash table to list
sorted_list = []
for list in ht.get_buckets():
current = list.head
for tuple in range(list.size):
sorted_list.append((current.key, current.value))
current = current.next
# Sort list by value in descending order. Return given number of 'top-words'.
sorted_list = sorted(sorted_list, key=get_second, reverse=True)
return_list = []
for i in range(number):
return_list.append(sorted_list[i])
return return_list
def top_words(source, number):
"""
Takes a plain text file and counts the number of occurrences of case insensitive words.
Returns the top `number` of words in a list of tuples of the form (word, count).
Args:
source: the file name containing the text
number: the number of top results to return (e.g. 5 would return the 5 most common words)
Returns:
A list of tuples of the form (word, count), sorted by most common word. (e.g. [("a", 23), ("the", 20), ("it", 10)])
"""
# keys = set()
ht = HashMap(25,hash_function_2)
tuple_list = []
# This block of code will read a file one word as a time and
# put the word in `w`.
with open(source) as f:
for line in f:
words = rgx.findall(line)
for w in words:
w = w.lower()
if ht.contains_key(w):
# inc count
ht.put(w, ht.get(w) +1)
else:
# start count
ht.put(w, 1)
for bucket in ht._buckets:
current = bucket.head
while current is not None:
tuple_list.append((current.key, current.value))
current = current.next
sort_tuples(tuple_list)
return tuple_list[:number]
def top_words(source, number):
"""
Takes a plain text file and counts the number of occurrences of case insensitive words.
Returns the top `number` of words in a list of tuples of the form (word, count).
Args:
source: the file name containing the text
number: the number of top results to return (e.g. 5 would return the 5 most common words)
Returns:
A list of tuples of the form (word, count), sorted by most common word. (e.g. [("a", 23), ("the", 20), ("it", 10)])
"""
keys = set()
ht = HashMap(2500, hash_function_2)
# This block of code will read a file one word as a time and
with open(source) as f:
for line in f:
words = rgx.findall(line)
for w in words:
# FIXME: Complete this function
word = w.lower()
if ht.contains_key(word) == False:
ht.put(word, 1)
else:
curVal = ht.get(word)
newVal = curVal + 1
ht.put(word, newVal)
curVal = 0
newList = []
printTuple = ()
listWords = ht.bucket_keys(
) #fills a list with all nodes in bucketlist and then sorts them
listWords.sort(key=get_value, reverse=True)
for i in range(number): #takes the top 5 words and puts them in a list
newList.append(listWords[i].returnNode())
printTuple = tuple(newList) #convert list into tuple
return printTuple
class HashMapTests(unittest.TestCase, DictTestCases):
def setUp(self):
self.uut = HashMap()
def mock_hashes_to(self, index=0):
class Mock(object):
def __hash__(self):
return index
def __str__(self):
return "mock(%s)" % index
__repr__ = __str__
return Mock()
def test_initial_current_capacity_is_16(self):
self.assertEqual(16, self.uut.capacity())
def test_initial_doubling_size_is_12(self):
self.assertEqual(12, self.uut.doubling_size())
def test_when_inialized_with_one_half_then_doubling_size_is_8(self):
uut = HashMap(0.5)
self.assertEqual(8, uut.doubling_size())
def test_initial_len_is_0(self):
self.assertEqual(0, len(self.uut))
def test_insertion_increses_size_to_1(self):
self.uut.insert(self.mock_hashes_to(), 42)
def test_collisions_are_handled(self):
first = self.mock_hashes_to(1)
second = self.mock_hashes_to(1)
self.uut.insert(first, "spam")
self.uut.insert(second, "eggs")
self.assertEqual("spam", self.uut.get(first))
self.assertEqual("eggs", self.uut.get(second))
def test_inserting_items_with_a_higher_value_works(self):
item = self.mock_hashes_to(99)
self.uut.insert(item, 42)
self.assertEqual(42, self.uut.get(item))
def test_when_at_doubling_size_then_the_capacity_doubles(self):
for i in xrange(11):
self.uut.insert(i, "_")
self.assertEqual(16, self.uut.capacity())
self.uut.insert(12, "_")
self.assertEqual(32, self.uut.capacity())
self.assertEqual(12, len(self.uut))
def test_len_is_0_after_delete_of_empty(self):
self.uut.delete("foo")
self.assertEqual(0, len(self.uut))
def test_len_is_0_after_delete_of_only_item(self):
self.uut.insert("foo", "_")
self.uut.delete("foo")
self.assertEqual(0, len(self.uut))
def test_len_is_0_after_delete_of_only_item_twice(self):
self.uut.insert("foo", "_")
self.uut.delete("foo")
self.uut.delete("foo")
self.assertEqual(0, len(self.uut))
def test_hash_map(self):
test_map = HashMap()
for i in range(0,1000):
if i%2 is 0:
test_map.put((i,), i)
else: # i%2 is 1
test_map.put(str(i), [i])
# initialize the map with 1001 kv pairs
self.assertEquals(test_map.size(), 1000)
for i in range(0,1000):
if i%2 is 0:
self.assertEquals(test_map.get((i,)), i)
else: # i%2 is 1
self.assertEquals(test_map.get(str(i)), [i])
with self.assertRaises(KeyNotFound):
test_map.get("8")
with self.assertRaises(KeyNotFound):
test_map.get((991,))
with self.assertRaises(KeyNotFound):
test_map.get("test_key")
with self.assertRaises(KeyNotFound):
test_map.get((1002,))
# remove 700 elements
for i in range(100,800):
if i%2 is 0:
test_map.remove((i,))
else: # i%2 is 1
test_map.remove(str(i))
self.assertEquals(test_map.size(), 300)
self.assertTrue(test_map.contains((80,)))
self.assertFalse(test_map.contains((120,)))
# insert 9000 more values
for i in range(1000,10000):
if i%2 is 1:
test_map.put((i,), i)
else: # i%2 is 0
test_map.put(str(i), [i])
self.assertEquals(test_map.size(), 9300)
for i in range(1000,10000):
if i%2 is 1:
self.assertEquals(test_map.get((i,)), i)
else: # i%2 is 0
self.assertEquals(test_map.get(str(i)), [i])
