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L23Q5_FeelingLucky.py
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L23Q5_FeelingLucky.py
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#Feeling Lucky
#In Unit 6, we implemented a page ranking algorithm, but didn't finish the final
#step of using it to improve our search results. For this question, you will use
#the page rankings to produce the best output for a given query.
#Define a procedure, lucky_search, that takes as input an index, a ranks
#dictionary (the result of compute_ranks), and a keyword, and returns the one
#URL most likely to be the best site for that keyword. If the keyword does not
#appear in the index, lucky_search should return None.
cache = {
'http://udacity.com/cs101x/urank/index.html': """<html>
<body>
<h1>Dave's Cooking Algorithms</h1>
<p>
Here are my favorite recipies:
<ul>
<li> <a href="http://udacity.com/cs101x/urank/hummus.html">Hummus Recipe</a>
<li> <a href="http://udacity.com/cs101x/urank/arsenic.html">World's Best Hummus</a>
<li> <a href="http://udacity.com/cs101x/urank/kathleen.html">Kathleen's Hummus Recipe</a>
</ul>
For more expert opinions, check out the
<a href="http://udacity.com/cs101x/urank/nickel.html">Nickel Chef</a>
and <a href="http://udacity.com/cs101x/urank/zinc.html">Zinc Chef</a>.
</body>
</html>
""",
'http://udacity.com/cs101x/urank/zinc.html': """<html>
<body>
<h1>The Zinc Chef</h1>
<p>
I learned everything I know from
<a href="http://udacity.com/cs101x/urank/nickel.html">the Nickel Chef</a>.
</p>
<p>
For great hummus, try
<a href="http://udacity.com/cs101x/urank/arsenic.html">this recipe</a>.
</body>
</html>
""",
'http://udacity.com/cs101x/urank/nickel.html': """<html>
<body>
<h1>The Nickel Chef</h1>
<p>
This is the
<a href="http://udacity.com/cs101x/urank/kathleen.html">
best Hummus recipe!
</a>
</body>
</html>
""",
'http://udacity.com/cs101x/urank/kathleen.html': """<html>
<body>
<h1>
Kathleen's Hummus Recipe
</h1>
<p>
<ol>
<li> Open a can of garbonzo beans.
<li> Crush them in a blender.
<li> Add 3 tablesppons of tahini sauce.
<li> Squeeze in one lemon.
<li> Add salt, pepper, and buttercream frosting to taste.
</ol>
</body>
</html>
""",
'http://udacity.com/cs101x/urank/arsenic.html': """<html>
<body>
<h1>
The Arsenic Chef's World Famous Hummus Recipe
</h1>
<p>
<ol>
<li> Kidnap the <a href="http://udacity.com/cs101x/urank/nickel.html">Nickel Chef</a>.
<li> Force her to make hummus for you.
</ol>
</body>
</html>
""",
'http://udacity.com/cs101x/urank/hummus.html': """<html>
<body>
<h1>
Hummus Recipe
</h1>
<p>
<ol>
<li> Go to the store and buy a container of hummus.
<li> Open it.
</ol>
</body>
</html>
""",
}
def get_page(url):
if url in cache:
return cache[url]
return ""
def get_next_target(page):
start_link = page.find('<a href=')
if start_link == -1:
return None, 0
start_quote = page.find('"', start_link)
end_quote = page.find('"', start_quote + 1)
url = page[start_quote + 1:end_quote]
return url, end_quote
def get_all_links(page):
links = []
while True:
url, endpos = get_next_target(page)
if url:
links.append(url)
page = page[endpos:]
else:
break
return links
def union(a, b):
for e in b:
if e not in a:
a.append(e)
def add_page_to_index(index, url, content):
words = content.split()
for word in words:
add_to_index(index, word, url)
def add_to_index(index, keyword, url):
if keyword in index:
index[keyword].append(url)
else:
index[keyword] = [url]
def lookup(index, keyword):
if keyword in index:
return index[keyword]
else:
return None
def crawl_web(seed): # returns index, graph of inlinks
tocrawl = [seed]
crawled = []
graph = {} # <url>, [list of pages it links to]
index = {}
while tocrawl:
page = tocrawl.pop()
if page not in crawled:
content = get_page(page)
add_page_to_index(index, page, content)
outlinks = get_all_links(content)
graph[page] = outlinks
union(tocrawl, outlinks)
crawled.append(page)
return index, graph
def compute_ranks(graph):
d = 0.8 # damping factor
numloops = 10
ranks = {}
npages = len(graph)
for page in graph:
ranks[page] = 1.0 / npages
for i in range(0, numloops):
newranks = {}
for page in graph:
newrank = (1 - d) / npages
for node in graph:
if page in graph[node]:
newrank = newrank + d * (ranks[node] / len(graph[node]))
newranks[page] = newrank
ranks = newranks
return ranks
def lucky_search(index, ranks, keyword):
if keyword not in index:
return None
else:
for i in ranked_ranks: #searches the ordered list, most popular downwards
if i in index[keyword]:
return i
def lucky_search_udacity(index, ranks, keyword):
pages = lookup(index,keyword)
if not pages:
return None
best_page = pages[0]
for i in pages:
if ranks[i] > ranks[best_page]:
best_page = i
return best_page
#Here's an example of how your procedure should work on the test site:
index, graph = crawl_web('http://udacity.com/cs101x/urank/index.html')
ranks = compute_ranks(graph)
#sorting the rankings, starting from highest
ranked_ranks = sorted(ranks, key=ranks.get, reverse=True)
print lucky_search(index, ranks, 'Hummus')
#>>> http://udacity.com/cs101x/urank/kathleen.html
print lucky_search(index, ranks, 'the')
#>>> http://udacity.com/cs101x/urank/nickel.html
print lucky_search(index, ranks, 'babaganoush')
#>>> None