# Constructor. Opens the dictionary of token meta-data

def __init__(self):

self.stemmer = PorterStemmer()

"""

self.tokens is a dictionary containing all the meta-data for all of the tokens and documents.

It has the structure:

{(Token):

{(Document Number):

[(list of all the positions of the token in that document.)]

}

}

"""

try:

f = open(os.getcwd() + "/data/tokensDict.p", "r")

self.tokens = pickle.load(f)

except:

print "Pickle file not found"

print "Creating the dictionary of meta-data."

self.tokens = scanCleanDir()

f = open(os.getcwd() + "/data/tokensDict.p", "w")

pickle.dump(self.tokens, f)

# Connects to the sqlite database, performs a given search query and

# returns a list conaining each row of the resulting table.

def dbQuery(self, query, args = ()):

conn = sqlite3.connect(os.getcwd() + '/data/cache.db')

db = conn.cursor()

# args should be a tuple of the arguments in the query

db.execute(query, args)

# get all the rows of the results from the sql query.

rows = db.fetchall()

conn.close()

return rows

"""

Searches for a single token in all the databases and displays all the

resulting documents, how many times the token occured in each document,

and which document had the most instances of that token.

"""

def singleToken(self):

# Get the token from the user, format it correctly and stem it.

print

word = raw_input("Enter your one word query: ")

token = word.lower()

token = self.stemmer.stem(token, 0, len(token) - 1)

# If the token is not found in any of the documents, end the search.

try:

wordDict = self.tokens[token]

except:

print word, "does not seem to exist in our files. Please try a different word"

print

return

# The number of times the token occurs across all documents.

occurenceTotal = 0

# Contains the documents with the highest frequency of document occurences.

highestFreq = {'freq': 0, 'docs':[]}

i = 1

for doc in wordDict.keys():

freq = len(wordDict[doc])

occurenceTotal += freq

linksQuery = """

SELECT webPage.linkText, item.itemName FROM (

SElECT itemToWebPage.webPageId, itemToWebPage.itemId

FROM itemToWebPage

WHERE webPageId = ?) AS linkItem

JOIN item

ON item.itemId = linkItem.itemId

JOIN webPage

ON webPage.webPageId = linkItem.webPageId;

"""

# Get the URL for each valid web-page document found.

linksRow = self.dbQuery(linksQuery, (doc,))

# Display the current document and it's frequency

print

print i,"\t",linksRow[0][0]

print "\t item: ",linksRow[0][1]

print "\t occured ",freq,"times"

i += 1

# Update the document[s] with the highest frequency

if freq > highestFreq['freq']:

highestFreq['freq'] = freq

highestFreq['docs'] = [linksRow[0][0]]

elif freq == highestFreq['freq']:

highestFreq['docs'].append(doc)

# Display the most relevant document[s]

print

print "Total occurence of", word, "is", occurenceTotal, "times"

print "Highest frequency: ", highestFreq['freq'], " times in: ",

for i in range(len(highestFreq['docs'])):

if i > 0:

print "and"

print highestFreq['docs'][i]

print

"""

Takes two tokens, gets all the documents that either or both tokens

appear in and displays the results.

"""

def orQuery(self):

print

# Get the two tokens, format and stem them.

word1 = raw_input("Enter the first word of your query: ")

word2 = raw_input("Enter the second word of your query: ")

token1 = word1.lower()

token1 = self.stemmer.stem(token1, 0, len(token1) - 1)

token2 = word2.lower()

token2 = self.stemmer.stem(token2, 0, len(token2) - 1)

try:

docs = self.tokens[token1].keys()

except:

print word1, "does not seem to exist in our files. Please try a different word"

print

return

try:

docs2 = self.tokens[token2].keys()

except:

print word2, "does not seem to exist in our files. Please try a different word"

print

return

# Collect all documents where either or both tokens appear in.

# Store them in keys

for doc in docs2:

if doc not in docs:

docs.append(doc)

# Total number of times either token occurs accross all documents.

occurenceTotal = 0

i = 1

# Keep track of which documents have the highest token frequency

highestFreq = {'freq': 0, 'docs':[]}

for doc in docs:

freq1 = 0

freq2 = 0

try:

freq1 = len(self.tokens[token1][doc])

except:

None

try:

freq2 = len(self.tokens[token2][doc])

except:

None

# Combine the frequency of each token for the current document.

freq = freq1 + freq2

occurenceTotal += freq

linksQuery = """

SELECT webPage.linkText, item.itemName FROM (

SElECT itemToWebPage.webPageId, itemToWebPage.itemId

FROM itemToWebPage

WHERE webPageId = ?) AS linkItem

JOIN item

ON item.itemId = linkItem.itemId

JOIN webPage

ON webPage.webPageId = linkItem.webPageId;

"""

# Get the URL for each valid web-page document found.

linksRow = self.dbQuery(linksQuery, (doc,))

# Display the current document and it's frequency

print

print i,"\t",linksRow[0][0]

print "\t item: ",linksRow[0][1]

print "\t occured ",freq,"times"

i += 1

# Update which document[s] have the highest frequency for both tokens

if freq > highestFreq['freq']:

highestFreq['freq'] = freq

highestFreq['docs'] = [linksRow[0][0]]

elif freq == highestFreq['freq']:

highestFreq['docs'].append(doc)

# Display which Document[s] have the highest frequency for both tokens

print

print "Total occurence of", word1, "or", word2, "is", occurenceTotal, "times"

print "Highest frequency: ", highestFreq['freq'], " times in: ",

for i in range(len(highestFreq['docs'])):

if i > 0:

print "and"

print highestFreq['docs'][i]

print

"""

Takes two tokens, gets all the documents that ONLY BOTH tokens

appear in and displays the results.

"""

def andQuery(self):

print

# Get each token, format and stem both of them.

word1 = raw_input("Enter the first word of your query: ")

word2 = raw_input("Enter the second word of your query: ")

token1 = word1.lower()

token1 = self.stemmer.stem(token1, 0, len(token1) - 1)

token2 = word2.lower()

token2 = self.stemmer.stem(token2, 0, len(token2) - 1)

# Will contain all documents where both tokens appear in

docs = []

# If either of the tokens is not found in any document, stop the search

try:

docs1 = self.tokens[token1].keys()

except:

print word1, "does not seem to exist in our files. Please try a different word"

print

return

try:

docs2 = self.tokens[token2].keys()

except:

print word2, "does not seem to exist in our files. Please try a different word"

print

return

# Collect all documents where both tokens appear in.

# Store them in keys

for doc in docs1:

if doc in docs2:

docs.append(doc)

# Total number of times either token occurs accross all documents

# that contain both tokens.

occurenceTotal = 0

i = 1

# Keep track of which documents have the highest token frequency

highestFreq = {'freq': 0, 'docs':[]}

for doc in docs:

freq1 = 0

freq2 = 0

try:

freq1 = len(self.tokens[token1][doc])

except:

None

try:

freq2 = len(self.tokens[token2][doc])

except:

None

# Combine the frequency of each token for the current document.

freq = freq1 + freq2

occurenceTotal += freq

linksQuery = """

SELECT webPage.linkText, item.itemName FROM (

SElECT itemToWebPage.webPageId, itemToWebPage.itemId

FROM itemToWebPage

WHERE webPageId = ?) AS linkItem

JOIN item

ON item.itemId = linkItem.itemId

JOIN webPage

ON webPage.webPageId = linkItem.webPageId;

"""

# Get the URL for each valid web-page document found.

linksRow = self.dbQuery(linksQuery, (doc,))

# Display the current document and it's frequency

print

print i,"\t",linksRow[0][0]

print "\t item: ",linksRow[0][1]

print "\t occured ",freq,"times"

i += 1

# Update which document[s] have the highest frequency for both tokens

if freq > highestFreq['freq']:

highestFreq['freq'] = freq

highestFreq['docs'] = [linksRow[0][0]]

elif freq == highestFreq['freq']:

highestFreq['docs'].append(doc)

#Display which Document[s] have the highest frequency for both tokens

print

print "Total occurence of", word1, "and", word2, "is", occurenceTotal, "times"

print "Highest frequency: ", highestFreq['freq'], " times in: ",

for i in range(len(highestFreq['docs'])):

if i > 0:

print "and"

print highestFreq['docs'][i]

print

"""

Takes a two token phrase and finds all the documents where that phrase occurs

exactly as it is in the query (token1 followed by token2).

Works exactly like the andQuery, except that it checks to make sure the

position of token2 occurs immediately after token1.

"""

def phraseQuery(self):

print

# Get the two-word phrase and get each token from it.

phrase = raw_input("Enter a two word phrase: ")

while len(phrase.split(' ')) != 2:

phrase = raw_input("Make sure your phrase is two words (e.g. 'hello goodbye'): ")

# Format and stem each token.

words = phrase.split(' ')

word1 = words[0]

word2 = words[1]

token1 = word1.lower()

token1 = self.stemmer.stem(token1, 0, len(token1) - 1)

token2 = word2.lower()

token2 = self.stemmer.stem(token2, 0, len(token2) - 1)

# Will contain all documents where both tokens appear in

docs = []

# If either of the tokens is not found in any document, stop the search

try:

docs1 = self.tokens[token1].keys()

except:

print word1, "does not seem to exist in our files. Please try a different word"

print

return

try:

docs2 = self.tokens[token2].keys()

except:

print word2, "does not seem to exist in our files. Please try a different word"

print

return

# Collect all documents where both tokens appear.

# Store them in keys

phraseDict = {}

# Check which documents have both words

for doc in docs1:

if doc in docs2:

doc1Pos = self.tokens[token1][doc]

doc2Pos = self.tokens[token2][doc]

# Check which documents have the phrase in the correct order

freq = 0

for pos1 in doc1Pos:

for pos2 in doc2Pos:

if pos2 == pos1 + 1:

freq += 1

# Keep track of only the docuements where the phrase occurs.

if freq > 0:

phraseDict[doc] = freq

#Total number of times the phrase occurs

occurenceTotal = 0

i = 1

# Keep track of the documents with the highest frequency

highestFreq = {'freq': 0, 'docs':[]}

for doc in phraseDict.keys():

freq = phraseDict[doc]

occurenceTotal += freq

linksQuery = """

SELECT webPage.linkText, item.itemName FROM (

SElECT itemToWebPage.webPageId, itemToWebPage.itemId

FROM itemToWebPage

WHERE webPageId = ?) AS linkItem

JOIN item

ON item.itemId = linkItem.itemId

JOIN webPage

ON webPage.webPageId = linkItem.webPageId;

"""

# Get the URL for each valid web-page document found.

linksRow = self.dbQuery(linksQuery, (doc,))

# Display the current document and it's frequency

print

print i,"\t",linksRow[0][0]

print "\t item: ",linksRow[0][1]

print "\t occured ",freq,"times"

i += 1

# Update which document[s] have the highest frequency for both tokens

if freq > highestFreq['freq']:

highestFreq['freq'] = freq

highestFreq['docs'] = [linksRow[0][0]]

elif freq == highestFreq['freq']:

highestFreq['docs'].append(doc)

# Displat the document[s] with the highest frequency for the two-token phrase.

print

print "Total occurence of",phrase, "is", occurenceTotal, "times"

print "Highest frequency: ", highestFreq['freq'], " times in: ",

for i in range(len(highestFreq['docs'])):

if i > 0:

print "and"

print highestFreq['docs'][i]

print

"""

Performs a query using two tokens and an integer. The integer represents

a distance between two words.

Collects all the documents where both tokens occur within the given

distance from each other and displays the results. For example in the

document, "and i think to myself what a wonderful world" The two tokens "think"

and "myself" occur within a distance of two words from each other.

"""

def nearQuery(self):

print

# Get both tokens and the distance

word1 = raw_input("Enter the first word: ")

word2 = raw_input("Enter the second word: ")

distance = input ("Enter the number of positions away you want to look: ")

# Format and stem each token

token1 = word1.lower()

token1 = self.stemmer.stem(token1, 0, len(token1) - 1)

token2 = word2.lower()

token2 = self.stemmer.stem(token2, 0, len(token2) - 1)

# Will contain all documents where both tokens appear in, within the given

# distance of each other.

docs = []

# If either token does not appear in any document, stop the search.

try:

docs1 = self.tokens[token1].keys()

except:

print word1, "does not seem to exist in our files. Please try a different word"

print

return

try:

docs2 = self.tokens[token2].keys()

except:

print word2, "does not seem to exist in our files. Please try a different word"

print

return

# Collect all documents where both tokens appear.

# Store them in keys

phraseDict = {}

# Check which documents have both words

for doc in docs1:

if doc in docs2:

doc1Pos = self.tokens[token1][doc]

doc2Pos = self.tokens[token2][doc]

# Check which documents have the words within the allotted distance of each other

freq = 0

for pos1 in doc1Pos:

for pos2 in doc2Pos:

if (pos2 - pos1 >= 0 - distance) and (pos2 - pos1 <= distance):

freq += 1

if freq > 0:

phraseDict[doc] = freq

#Total number of times the two tokens occur within each other across all docs

occurenceTotal = 0

i = 1

# Keep track of the documents with the highest frequency

highestFreq = {'freq': 0, 'docs':[]}

for doc in phraseDict.keys():

freq = phraseDict[doc]

occurenceTotal += freq

linksQuery = """

SELECT webPage.linkText, item.itemName FROM (

SElECT itemToWebPage.webPageId, itemToWebPage.itemId

FROM itemToWebPage

WHERE webPageId = ?) AS linkItem

JOIN item

ON item.itemId = linkItem.itemId

JOIN webPage

ON webPage.webPageId = linkItem.webPageId;

"""

# Get the URL for each valid web-page document found.

linksRow = self.dbQuery(linksQuery, (doc,))

# Display the current document and it's frequency

print

print i,"\t",linksRow[0][0]

print "\t item: ",linksRow[0][1]

print "\t occured ",freq,"times"

i += 1

# Update the document with the highest frequency.

if freq > highestFreq['freq']:

highestFreq['freq'] = freq

highestFreq['docs'] = [linksRow[0][0]]

elif freq == highestFreq['freq']:

highestFreq['docs'].append(doc)

# Display the document with the highest frequency.

print

print "Total occurence of",word1, "within ", distance, "positions of", word2, "was",occurenceTotal, "times"

print "Highest frequency: ", highestFreq['freq'], " times in: ",

for i in range(len(highestFreq['docs'])):

if i > 0:

print "and"

print highestFreq['docs'][i]

print

def searchMenu(self):

print

print "-----------------------------------------------------------"

print "\t Welcome to Stensland-ipedia!"

print "\tWhere you can search to your hearts content!"

print "-----------------------------------------------------------"

print

menu = True

while menu:

print "Choose the number corresponding to the query you would like to perform"

print "---------------------------------------------------------------------"

print "1.\tSingle token query."

print "2.\tAND query."

print "3.\tOR query."

print "4.\t2-Token query."

print "5.\tNear query."

print "6.\tQuit"

choice = raw_input("Enter your choice: ")

if choice == '1':

self.singleToken()

elif choice == '2':

self.andQuery()

elif choice == '3':

self.orQuery()

elif choice == '4':

self.phraseQuery()

elif choice == '5':

self.nearQuery()

elif choice == '6':

menu = False

print "\n"

else:

print "That is not a thing I understand."

print

print

print "Thank you for being my friend!"