Python 英文分词

'''
Created on 2015-11-18
'''
#encoding=utf-8

# List Of English Stop Words
# http://armandbrahaj.blog.al/2009/04/14/list-of-english-stop-words/
_WORD_MIN_LENGTH = 3
_STOP_WORDS = frozenset([
'a', 'about', 'above', 'above', 'across', 'after', 'afterwards', 'again', 
'against', 'all', 'almost', 'alone', 'along', 'already', 'also','although',
'always','am','among', 'amongst', 'amoungst', 'amount',  'an', 'and', 'another',
'any','anyhow','anyone','anything','anyway', 'anywhere', 'are', 'around', 'as',
'at', 'back','be','became', 'because','become','becomes', 'becoming', 'been', 
'before', 'beforehand', 'behind', 'being', 'below', 'beside', 'besides', 
'between', 'beyond', 'bill', 'both', 'bottom','but', 'by', 'call', 'can', 
'cannot', 'cant', 'co', 'con', 'could', 'couldnt', 'cry', 'de', 'describe', 
'detail', 'do', 'done', 'down', 'due', 'during', 'each', 'eg', 'eight', 
'either', 'eleven','else', 'elsewhere', 'empty', 'enough', 'etc', 'even', 
'ever', 'every', 'everyone', 'everything', 'everywhere', 'except', 'few', 
'fifteen', 'fify', 'fill', 'find', 'fire', 'first', 'five', 'for', 'former', 
'formerly', 'forty', 'found', 'four', 'from', 'front', 'full', 'further', 'get',
'give', 'go', 'had', 'has', 'hasnt', 'have', 'he', 'hence', 'her', 'here', 
'hereafter', 'hereby', 'herein', 'hereupon', 'hers', 'herself', 'him', 
'himself', 'his', 'how', 'however', 'hundred', 'ie', 'if', 'in', 'inc', 
'indeed', 'interest', 'into', 'is', 'it', 'its', 'itself', 'keep', 'last', 
'latter', 'latterly', 'least', 'less', 'ltd', 'made', 'many', 'may', 'me', 
'meanwhile', 'might', 'mill', 'mine', 'more', 'moreover', 'most', 'mostly', 
'move', 'much', 'must', 'my', 'myself', 'name', 'namely', 'neither', 'never', 
'nevertheless', 'next', 'nine', 'no', 'nobody', 'none', 'noone', 'nor', 'not', 
'nothing', 'now', 'nowhere', 'of', 'off', 'often', 'on', 'once', 'one', 'only',
'onto', 'or', 'other', 'others', 'otherwise', 'our', 'ours', 'ourselves', 'out',
'over', 'own','part', 'per', 'perhaps', 'please', 'put', 'rather', 're', 'same',
'see', 'seem', 'seemed', 'seeming', 'seems', 'serious', 'several', 'she', 
'should', 'show', 'side', 'since', 'sincere', 'six', 'sixty', 'so', 'some', 
'somehow', 'someone', 'something', 'sometime', 'sometimes', 'somewhere', 
'still', 'such', 'system', 'take', 'ten', 'than', 'that', 'the', 'their', 
'them', 'themselves', 'then', 'thence', 'there', 'thereafter', 'thereby', 
'therefore', 'therein', 'thereupon', 'these', 'they', 'thickv', 'thin', 'third',
'this', 'those', 'though', 'three', 'through', 'throughout', 'thru', 'thus', 
'to', 'together', 'too', 'top', 'toward', 'towards', 'twelve', 'twenty', 'two', 
'un', 'under', 'until', 'up', 'upon', 'us', 'very', 'via', 'was', 'we', 'well', 
'were', 'what', 'whatever', 'when', 'whence', 'whenever', 'where', 'whereafter',
'whereas', 'whereby', 'wherein', 'whereupon', 'wherever', 'whether', 'which', 
'while', 'whither', 'who', 'whoever', 'whole', 'whom', 'whose', 'why', 'will', 
'with', 'within', 'without', 'would', 'yet', 'you', 'your', 'yours', 'yourself',
'yourselves', 'the'])

def word_split_out(text):
    word_list = []
    wcurrent = []

    for i, c in enumerate(text):
        if c.isalnum():
            wcurrent.append(c)
        elif wcurrent:
            word = u''.join(wcurrent)
            word_list.append(word)
            wcurrent = []

    if wcurrent:
        word = u''.join(wcurrent)
        word_list.append(word)

    return word_list

def word_split(text):
    """
    Split a text in words. Returns a list of tuple that contains
    (word, location) location is the starting byte position of the word.
    """
    word_list = []
    wcurrent = []
    windex = 0

    for i, c in enumerate(text):
        if c.isalnum():
            wcurrent.append(c)
        elif wcurrent:
            word = u''.join(wcurrent)
            word_list.append((windex, word))
            windex += 1
            wcurrent = []

    if wcurrent:
        word = u''.join(wcurrent)
        word_list.append((windex, word))
        windex += 1

    return word_list

def words_cleanup(words):
    """
    Remove words with length less then a minimum and stopwords.
    """
    cleaned_words = []
    for index, word in words:
        if len(word) < _WORD_MIN_LENGTH or word in _STOP_WORDS:
            continue
        cleaned_words.append((index, word))
    return cleaned_words

def words_normalize(words):
    """
    Do a normalization precess on words. In this case is just a tolower(),
    but you can add accents stripping, convert to singular and so on...
    """
    normalized_words = []
    for index, word in words:
        wnormalized = word.lower()
        normalized_words.append((index, wnormalized))
    return normalized_words

def word_index(text):
    """
    Just a helper method to process a text.
    It calls word split, normalize and cleanup.
    """
    words = word_split(text)
    words = words_normalize(words)
    words = words_cleanup(words)
    return words

def inverted_index(text):
    """
    Create an Inverted-Index of the specified text document.
        {word:[locations]}
    """
    inverted = {}

    for index, word in word_index(text):
        locations = inverted.setdefault(word, [])
        locations.append(index)

    return inverted

def inverted_index_add(inverted, doc_id, doc_index):
    """
    Add Invertd-Index doc_index of the document doc_id to the 
    Multi-Document Inverted-Index (inverted), 
    using doc_id as document identifier.
        {word:{doc_id:[locations]}}
    """
    for word, locations in doc_index.iteritems():
        indices = inverted.setdefault(word, {})
        indices[doc_id] = locations
    return inverted

def search(inverted, query):
    """
    Returns a set of documents id that contains all the words in your query.
    """
    words = [word for _, word in word_index(query) if word in inverted]
    results = [set(inverted[word].keys()) for word in words]
    return reduce(lambda x, y: x & y, results) if results else []

if __name__ == '__main__':
    doc1 = """
Niners head coach Mike Singletary will let Alex Smith remain his starting 
quarterback, but his vote of confidence is anything but a long-term mandate.
Smith now will work on a week-to-week basis, because Singletary has voided 
his year-long lease on the job.
"I think from this point on, you have to do what's best for the football team,"
Singletary said Monday, one day after threatening to bench Smith during a 
27-24 loss to the visiting Eagles.
"""

    doc2 = """
The fifth edition of West Coast Green, a conference focusing on "green" home 
innovations and products, rolled into San Francisco's Fort Mason last week 
intent, per usual, on making our living spaces more environmentally friendly 
- one used-tire house at a time.
To that end, there were presentations on topics such as water efficiency and 
the burgeoning future of Net Zero-rated buildings that consume no energy and 
produce no carbon emissions.
"""

    # Build Inverted-Index for documents
    inverted = {}
    documents = {'doc1':doc1, 'doc2':doc2}
    for doc_id, text in documents.iteritems():
        doc_index = inverted_index(text)
        inverted_index_add(inverted, doc_id, doc_index)

    # Print Inverted-Index
    for word, doc_locations in inverted.iteritems():
        print word, doc_locations

    # Search something and print results
    queries = ['Week', 'Niners week', 'West-coast Week']
    for query in queries:
        result_docs = search(inverted, query)
        print "Search for '%s': %r" % (query, result_docs)
        for _, word in word_index(query):
            def extract_text(doc, index): 
                word_list = word_split_out(documents[doc])
                word_string = ""
                for i in range(index, index +4):
                    word_string += word_list[i] + " "
                word_string = word_string.replace("\n", "")
                return word_string

            for doc in result_docs:
                for index in inverted[word][doc]:
                    print '   - %s...' % extract_text(doc, index)
        print

'''
Created on 2015-11-18
'''
#encoding=utf-8

# List Of English Stop Words
# http://armandbrahaj.blog.al/2009/04/14/list-of-english-stop-words/
_WORD_MIN_LENGTH = 3
_STOP_WORDS = frozenset([
'a', 'about', 'above', 'above', 'across', 'after', 'afterwards', 'again', 
'against', 'all', 'almost', 'alone', 'along', 'already', 'also','although',
'always','am','among', 'amongst', 'amoungst', 'amount',  'an', 'and', 'another',
'any','anyhow','anyone','anything','anyway', 'anywhere', 'are', 'around', 'as',
'at', 'back','be','became', 'because','become','becomes', 'becoming', 'been', 
'before', 'beforehand', 'behind', 'being', 'below', 'beside', 'besides', 
'between', 'beyond', 'bill', 'both', 'bottom','but', 'by', 'call', 'can', 
'cannot', 'cant', 'co', 'con', 'could', 'couldnt', 'cry', 'de', 'describe', 
'detail', 'do', 'done', 'down', 'due', 'during', 'each', 'eg', 'eight', 
'either', 'eleven','else', 'elsewhere', 'empty', 'enough', 'etc', 'even', 
'ever', 'every', 'everyone', 'everything', 'everywhere', 'except', 'few', 
'fifteen', 'fify', 'fill', 'find', 'fire', 'first', 'five', 'for', 'former', 
'formerly', 'forty', 'found', 'four', 'from', 'front', 'full', 'further', 'get',
'give', 'go', 'had', 'has', 'hasnt', 'have', 'he', 'hence', 'her', 'here', 
'hereafter', 'hereby', 'herein', 'hereupon', 'hers', 'herself', 'him', 
'himself', 'his', 'how', 'however', 'hundred', 'ie', 'if', 'in', 'inc', 
'indeed', 'interest', 'into', 'is', 'it', 'its', 'itself', 'keep', 'last', 
'latter', 'latterly', 'least', 'less', 'ltd', 'made', 'many', 'may', 'me', 
'meanwhile', 'might', 'mill', 'mine', 'more', 'moreover', 'most', 'mostly', 
'move', 'much', 'must', 'my', 'myself', 'name', 'namely', 'neither', 'never', 
'nevertheless', 'next', 'nine', 'no', 'nobody', 'none', 'noone', 'nor', 'not', 
'nothing', 'now', 'nowhere', 'of', 'off', 'often', 'on', 'once', 'one', 'only',
'onto', 'or', 'other', 'others', 'otherwise', 'our', 'ours', 'ourselves', 'out',
'over', 'own','part', 'per', 'perhaps', 'please', 'put', 'rather', 're', 'same',
'see', 'seem', 'seemed', 'seeming', 'seems', 'serious', 'several', 'she', 
'should', 'show', 'side', 'since', 'sincere', 'six', 'sixty', 'so', 'some', 
'somehow', 'someone', 'something', 'sometime', 'sometimes', 'somewhere', 
'still', 'such', 'system', 'take', 'ten', 'than', 'that', 'the', 'their', 
'them', 'themselves', 'then', 'thence', 'there', 'thereafter', 'thereby', 
'therefore', 'therein', 'thereupon', 'these', 'they', 'thickv', 'thin', 'third',
'this', 'those', 'though', 'three', 'through', 'throughout', 'thru', 'thus', 
'to', 'together', 'too', 'top', 'toward', 'towards', 'twelve', 'twenty', 'two', 
'un', 'under', 'until', 'up', 'upon', 'us', 'very', 'via', 'was', 'we', 'well', 
'were', 'what', 'whatever', 'when', 'whence', 'whenever', 'where', 'whereafter',
'whereas', 'whereby', 'wherein', 'whereupon', 'wherever', 'whether', 'which', 
'while', 'whither', 'who', 'whoever', 'whole', 'whom', 'whose', 'why', 'will', 
'with', 'within', 'without', 'would', 'yet', 'you', 'your', 'yours', 'yourself',
'yourselves', 'the'])

def word_split_out(text):
    word_list = []
    wcurrent = []

    for i, c in enumerate(text):
        if c.isalnum():
            wcurrent.append(c)
        elif wcurrent:
            word = u''.join(wcurrent)
            word_list.append(word)
            wcurrent = []

    if wcurrent:
        word = u''.join(wcurrent)
        word_list.append(word)

    return word_list

def word_split(text):
    """
    Split a text in words. Returns a list of tuple that contains
    (word, location) location is the starting byte position of the word.
    """
    word_list = []
    wcurrent = []
    windex = 0

    for i, c in enumerate(text):
        if c.isalnum():
            wcurrent.append(c)
        elif wcurrent:
            word = u''.join(wcurrent)
            word_list.append((windex, word))
            windex += 1
            wcurrent = []

    if wcurrent:
        word = u''.join(wcurrent)
        word_list.append((windex, word))
        windex += 1

    return word_list

def words_cleanup(words):
    """
    Remove words with length less then a minimum and stopwords.
    """
    cleaned_words = []
    for index, word in words:
        if len(word) < _WORD_MIN_LENGTH or word in _STOP_WORDS:
            continue
        cleaned_words.append((index, word))
    return cleaned_words

def words_normalize(words):
    """
    Do a normalization precess on words. In this case is just a tolower(),
    but you can add accents stripping, convert to singular and so on...
    """
    normalized_words = []
    for index, word in words:
        wnormalized = word.lower()
        normalized_words.append((index, wnormalized))
    return normalized_words

def word_index(text):
    """
    Just a helper method to process a text.
    It calls word split, normalize and cleanup.
    """
    words = word_split(text)
    words = words_normalize(words)
    words = words_cleanup(words)
    return words

def inverted_index(text):
    """
    Create an Inverted-Index of the specified text document.
        {word:[locations]}
    """
    inverted = {}

    for index, word in word_index(text):
        locations = inverted.setdefault(word, [])
        locations.append(index)

    return inverted

def inverted_index_add(inverted, doc_id, doc_index):
    """
    Add Invertd-Index doc_index of the document doc_id to the 
    Multi-Document Inverted-Index (inverted), 
    using doc_id as document identifier.
        {word:{doc_id:[locations]}}
    """
    for word, locations in doc_index.iteritems():
        indices = inverted.setdefault(word, {})
        indices[doc_id] = locations
    return inverted

def search(inverted, query):
    """
    Returns a set of documents id that contains all the words in your query.
    """
    words = [word for _, word in word_index(query) if word in inverted]
    results = [set(inverted[word].keys()) for word in words]
    return reduce(lambda x, y: x & y, results) if results else []

def distance_between_word(word_index_1, word_index_2, distance):
    """
    To judge whether the distance between the two words is equal distance
    """ 
    distance_list = []
    for index_1 in word_index_1:
        for index_2 in word_index_2:
            if (index_1 < index_2):
                if(index_2 - index_1 == distance):
                    distance_list.append(index_1)
            else:
                continue        
    return distance_list

def extract_text(doc, index): 
    """
    Output search results
    """
    word_list = word_split_out(documents[doc])
    word_string = ""
    for i in range(index, index +4):
        word_string += word_list[i] + " "
    word_string = word_string.replace("\n", "")
    return word_string

if __name__ == '__main__':
    doc1 = """
Niners head coach Mike Singletary will let Alex Smith remain his starting 
quarterback, but his vote of confidence is anything but a long-term mandate.
Smith now will work on a week-to-week basis, because Singletary has voided 
his year-long lease on the job.
"I think from this point on, you have to do what's best for the football team,"
Singletary said Monday, one day after threatening to bench Smith during a 
27-24 loss to the visiting Eagles.
"""

    doc2 = """
The fifth edition of West Coast Green, a conference focusing on "green" home 
innovations and products, rolled into San Francisco's Fort Mason last week 
intent, per usual, on making our living spaces more environmentally friendly 
- one used-tire house at a time.
To that end, there were presentations on topics such as water efficiency and 
the burgeoning future of Net Zero-rated buildings that consume no energy and 
produce no carbon emissions.
"""

    # Build Inverted-Index for documents
    inverted = {}
    documents = {'doc1':doc1, 'doc2':doc2}
    for doc_id, text in documents.iteritems():
        doc_index = inverted_index(text)
        inverted_index_add(inverted, doc_id, doc_index)

    # Print Inverted-Index
    for word, doc_locations in inverted.iteritems():
        print word, doc_locations

    # Search something and print results
    queries = ['Week', 'water efficiency', 'Singletary said Monday']
    for query in queries:
        result_docs = search(inverted, query)
        print "Search for '%s': %r" % (query, result_docs)
        query_word_list = word_index(query)
        for doc in result_docs:
            index_first = []
            distance = 1
            for _, word in query_word_list:
                index_second = inverted[word][doc]
                index_new = []
                if(index_first != []):
                    index_first = distance_between_word(index_first, index_second, distance)
                    distance += 1
                else:
                    index_first = index_second
            for index in index_first:
                print '   - %s...' % extract_text(doc, index)
            
        print

'''
Created on 2015-11-18
'''
#encoding=utf-8

# List Of English Stop Words
# http://armandbrahaj.blog.al/2009/04/14/list-of-english-stop-words/
_WORD_MIN_LENGTH = 3
_STOP_WORDS = frozenset([
'a', 'about', 'above', 'above', 'across', 'after', 'afterwards', 'again', 
'against', 'all', 'almost', 'alone', 'along', 'already', 'also','although',
'always','am','among', 'amongst', 'amoungst', 'amount',  'an', 'and', 'another',
'any','anyhow','anyone','anything','anyway', 'anywhere', 'are', 'around', 'as',
'at', 'back','be','became', 'because','become','becomes', 'becoming', 'been', 
'before', 'beforehand', 'behind', 'being', 'below', 'beside', 'besides', 
'between', 'beyond', 'bill', 'both', 'bottom','but', 'by', 'call', 'can', 
'cannot', 'cant', 'co', 'con', 'could', 'couldnt', 'cry', 'de', 'describe', 
'detail', 'do', 'done', 'down', 'due', 'during', 'each', 'eg', 'eight', 
'either', 'eleven','else', 'elsewhere', 'empty', 'enough', 'etc', 'even', 
'ever', 'every', 'everyone', 'everything', 'everywhere', 'except', 'few', 
'fifteen', 'fify', 'fill', 'find', 'fire', 'first', 'five', 'for', 'former', 
'formerly', 'forty', 'found', 'four', 'from', 'front', 'full', 'further', 'get',
'give', 'go', 'had', 'has', 'hasnt', 'have', 'he', 'hence', 'her', 'here', 
'hereafter', 'hereby', 'herein', 'hereupon', 'hers', 'herself', 'him', 
'himself', 'his', 'how', 'however', 'hundred', 'ie', 'if', 'in', 'inc', 
'indeed', 'interest', 'into', 'is', 'it', 'its', 'itself', 'keep', 'last', 
'latter', 'latterly', 'least', 'less', 'ltd', 'made', 'many', 'may', 'me', 
'meanwhile', 'might', 'mill', 'mine', 'more', 'moreover', 'most', 'mostly', 
'move', 'much', 'must', 'my', 'myself', 'name', 'namely', 'neither', 'never', 
'nevertheless', 'next', 'nine', 'no', 'nobody', 'none', 'noone', 'nor', 'not', 
'nothing', 'now', 'nowhere', 'of', 'off', 'often', 'on', 'once', 'one', 'only',
'onto', 'or', 'other', 'others', 'otherwise', 'our', 'ours', 'ourselves', 'out',
'over', 'own','part', 'per', 'perhaps', 'please', 'put', 'rather', 're', 'same',
'see', 'seem', 'seemed', 'seeming', 'seems', 'serious', 'several', 'she', 
'should', 'show', 'side', 'since', 'sincere', 'six', 'sixty', 'so', 'some', 
'somehow', 'someone', 'something', 'sometime', 'sometimes', 'somewhere', 
'still', 'such', 'system', 'take', 'ten', 'than', 'that', 'the', 'their', 
'them', 'themselves', 'then', 'thence', 'there', 'thereafter', 'thereby', 
'therefore', 'therein', 'thereupon', 'these', 'they', 'thickv', 'thin', 'third',
'this', 'those', 'though', 'three', 'through', 'throughout', 'thru', 'thus', 
'to', 'together', 'too', 'top', 'toward', 'towards', 'twelve', 'twenty', 'two', 
'un', 'under', 'until', 'up', 'upon', 'us', 'very', 'via', 'was', 'we', 'well', 
'were', 'what', 'whatever', 'when', 'whence', 'whenever', 'where', 'whereafter',
'whereas', 'whereby', 'wherein', 'whereupon', 'wherever', 'whether', 'which', 
'while', 'whither', 'who', 'whoever', 'whole', 'whom', 'whose', 'why', 'will', 
'with', 'within', 'without', 'would', 'yet', 'you', 'your', 'yours', 'yourself',
'yourselves', 'the'])

def word_split_out(text):
    word_list = []
    wcurrent = []

    for i, c in enumerate(text):
        if c.isalnum():
            wcurrent.append(c)
        elif wcurrent:
            word = u''.join(wcurrent)
            word_list.append(word)
            wcurrent = []

    if wcurrent:
        word = u''.join(wcurrent)
        word_list.append(word)

    return word_list

def word_split(text):
    """
    Split a text in words. Returns a list of tuple that contains
    (word, location) location is the starting byte position of the word.
    """
    word_list = []
    wcurrent = []
    windex = 0

    for i, c in enumerate(text):
        if c.isalnum():
            wcurrent.append(c)
        elif wcurrent:
            word = u''.join(wcurrent)
            word_list.append((windex, word))
            windex += 1
            wcurrent = []

    if wcurrent:
        word = u''.join(wcurrent)
        word_list.append((windex, word))
        windex += 1

    return word_list

def words_cleanup(words):
    """
    Remove words with length less then a minimum and stopwords.
    """
    cleaned_words = []
    for index, word in words:
        if len(word) < _WORD_MIN_LENGTH or word in _STOP_WORDS:
            continue
        cleaned_words.append((index, word))
    return cleaned_words

def words_normalize(words):
    """
    Do a normalization precess on words. In this case is just a tolower(),
    but you can add accents stripping, convert to singular and so on...
    """
    normalized_words = []
    for index, word in words:
        wnormalized = word.lower()
        normalized_words.append((index, wnormalized))
    return normalized_words

def word_index(text):
    """
    Just a helper method to process a text.
    It calls word split, normalize and cleanup.
    """
    words = word_split(text)
    words = words_normalize(words)
    words = words_cleanup(words)
    return words

def inverted_index(text):
    """
    Create an Inverted-Index of the specified text document.
        {word:[locations]}
    """
    inverted = {}

    for index, word in word_index(text):
        locations = inverted.setdefault(word, [])
        locations.append(index)

    return inverted

def inverted_index_add(inverted, doc_id, doc_index):
    """
    Add Invertd-Index doc_index of the document doc_id to the 
    Multi-Document Inverted-Index (inverted), 
    using doc_id as document identifier.
        {word:{doc_id:[locations]}}
    """
    for word, locations in doc_index.iteritems():
        indices = inverted.setdefault(word, {})
        indices[doc_id] = locations
    return inverted

def search(inverted, query):
    """
    Returns a set of documents id that contains all the words in your query.
    """
    words = [word for _, word in word_index(query) if word in inverted]
    results = [set(inverted[word].keys()) for word in words]
    return reduce(lambda x, y: x & y, results) if results else []

def distance_between_word(word_index_1, word_index_2, distance):
    """
    To judge whether the distance between the two words is smaller than distance
    """ 
    distance_list = []
    for index_1 in word_index_1:
        for index_2 in word_index_2:
            if (index_1 < index_2):
                if(index_2 - index_1 <= distance):
                    distance_list.append(index_1)
            else:
                continue       
    return distance_list

def extract_text(doc, index): 
    """
    Output search results
    """
    word_list = word_split_out(documents[doc])
    word_string = ""
    for i in range(index, index + 7):
        word_string += word_list[i] + " "
    word_string = word_string.replace("\n", "")
    return word_string

if __name__ == '__main__':
    doc1 = """
Niners head coach Mike Singletary will let Alex Smith remain his starting 
quarterback, but his vote of confidence is anything but a long-term mandate.
Smith now will work on a week-to-week basis, because Singletary has voided 
his year-long lease on the job.
"I think from this point on, you have to do what's best for the football team,"
Singletary said Monday, one day after threatening to bench Smith during a 
27-24 loss to the visiting Eagles.
"""

    doc2 = """
The fifth edition of West Coast Green, a conference focusing on "green" home 
innovations and products, rolled into San Francisco's Fort Mason last week 
intent, per usual, on making our living spaces more environmentally friendly 
- one used-tire house at a time.
To that end, there were presentations on topics such as water efficiency and 
the burgeoning future of Net Zero-rated buildings that consume no energy and 
produce no carbon emissions.
"""

    # Build Inverted-Index for documents
    inverted = {}
    documents = {'doc1':doc1, 'doc2':doc2}
    for doc_id, text in documents.iteritems():
        doc_index = inverted_index(text)
        inverted_index_add(inverted, doc_id, doc_index)

    # Print Inverted-Index
    for word, doc_locations in inverted.iteritems():
        print word, doc_locations

    # Search something and print results
    queries = ['Week', 'buildings consume', 'Alex remain quarterback']
    for query in queries:
        result_docs = search(inverted, query)
        print "Search for '%s': %r" % (query, result_docs)
        query_word_list = word_index(query)
        for doc in result_docs:
            index_first = []
            step = 3
            distance = 3
            for _, word in query_word_list:
                index_second = inverted[word][doc]
                index_new = []
                if(index_first != []):
                    index_first = distance_between_word(index_first, index_second, distance)
                    distance += step 
                else:
                    index_first = index_second
            for index in index_first:
                print '   - %s...' % extract_text(doc, index)
            
        print