Python 英文分词，词倒排索引
【一.一般多次查询】
'''
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【二. 短语查询】
'''
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
