def crawlSingleURL(link, idx, total_links):
try:
opener = buildOpener()
start = time.time()
data = opener.open(link).read()
soup = BeautifulSoup(data)
meta_data_keywords = soup.findAll('meta', {'name':'keywords'})
meta_data_descr = soup.findAll('meta', {'name':'description'})
keywords = get_meta_content(meta_data_keywords)
descr = get_meta_content(meta_data_descr)
# Extract the title tag
titleTag = None
try:
titleTag = soup.html.head.title
titleTag = str(titleTag.string)
except:
titleTag = ""
end = time.time()
# Return the basic URL data structure
field = URLField(link, titleTag, descr, keywords)
field.populate()
if ((idx % LINK_SET_INDICATOR) == 0):
sys.stdout.write("[%s/%s] " % (idx, total_links))
# Exit crawl single URL with url field.
# @return URLField
return field
except socket.timeout:
print "ERR: timeout [%s/%s] " % (idx, total_links)
except urllib2.URLError:
print "ERR: timeout [%s/%s] " % (idx, total_links)
except Exception, e:
pass
def crawlSingleURL(link, idx, total_links):
try:
opener = buildOpener()
start = time.time()
data = opener.open(link).read()
soup = BeautifulSoup(data)
meta_data_keywords = soup.findAll('meta', {'name': 'keywords'})
meta_data_descr = soup.findAll('meta', {'name': 'description'})
keywords = get_meta_content(meta_data_keywords)
descr = get_meta_content(meta_data_descr)
# Extract the title tag
titleTag = None
try:
titleTag = soup.html.head.title
titleTag = str(titleTag.string)
except:
titleTag = ""
end = time.time()
# Return the basic URL data structure
field = URLField(link, titleTag, descr, keywords)
field.populate()
if ((idx % LINK_SET_INDICATOR) == 0):
sys.stdout.write("[%s/%s] " % (idx, total_links))
# Exit crawl single URL with url field.
# @return URLField
return field
except socket.timeout:
print "ERR: timeout [%s/%s] " % (idx, total_links)
except urllib2.URLError:
print "ERR: timeout [%s/%s] " % (idx, total_links)
except Exception, e:
pass
def extractPageData(opener, url_str):
"""Request a page through urllib2 libraries, through beautiful soup,
extract the page content data including number links, imgs, etc"""
req = None
cur_time = datetime.datetime.now()
status_code_res = 0
model = WebAnalysisModel()
try:
start = time.clock()
req = urllib2.Request(url_str)
req.add_header('user-agent', FF_USER_AGENT)
data = opener.open(req).read()
soup = BeautifulSoup(data)
links = soup.findAll('a')
imgs = soup.findAll('img')
para = soup.findAll('p')
meta_data_keywords = soup.findAll('meta', {'name': 'keywords'})
meta_data_descr = soup.findAll('meta', {'name': 'description'})
keywords = get_meta_content(meta_data_keywords)
descr = get_meta_content(meta_data_descr)
keywords_arr = [0, 0]
descr_arr = [0, 0]
if keywords:
keywords_arr[0] = len(keywords)
keywords_arr[1] = len(keywords.split(","))
if descr:
descr_arr[0] = len(descr)
descr_arr[1] = len(descr.split(","))
end = time.clock()
response_time = int((end - start) * 1000.0)
# Build a web content model
model.links_ct = len(links)
model.inbound_link_ct = 0
model.outbound_links_ct = 0
model.image_ct = len(imgs)
model.meta_keywords_len = keywords_arr[0]
model.meta_descr_len = descr_arr[0]
model.meta_keywords_wct = keywords_arr[1]
model.meta_descr_wct = descr_arr[1]
model.para_tag_ct = len(para)
model.geo_locations_ct = 0
model.document_size = 0
model.request_time = response_time
status_code_res = 200
except urllib2.HTTPError, e:
print 'Error status code: ', e.code
print "ERR [%s]:scan_url HTTPError: url=%s" % (cur_time, url_str)
status_code_res = e.code
print e
def extractPageData(opener, url_str):
"""Request a page through urllib2 libraries, through beautiful soup,
extract the page content data including number links, imgs, etc"""
req = None
cur_time = datetime.datetime.now()
status_code_res = 0
model = WebAnalysisModel()
try:
start = time.clock()
req = urllib2.Request(url_str)
req.add_header('user-agent', FF_USER_AGENT)
data = opener.open(req).read()
soup = BeautifulSoup(data)
links = soup.findAll('a')
imgs = soup.findAll('img')
para = soup.findAll('p')
meta_data_keywords = soup.findAll('meta', {'name':'keywords'})
meta_data_descr = soup.findAll('meta', {'name':'description'})
keywords = get_meta_content(meta_data_keywords)
descr = get_meta_content(meta_data_descr)
keywords_arr = [0, 0]
descr_arr = [0, 0]
if keywords:
keywords_arr[0] = len(keywords)
keywords_arr[1] = len(keywords.split(","))
if descr:
descr_arr[0] = len(descr)
descr_arr[1] = len(descr.split(","))
end = time.clock()
response_time = int((end - start) * 1000.0)
# Build a web content model
model.links_ct = len(links)
model.inbound_link_ct = 0
model.outbound_links_ct = 0
model.image_ct = len(imgs)
model.meta_keywords_len = keywords_arr[0]
model.meta_descr_len = descr_arr[0]
model.meta_keywords_wct = keywords_arr[1]
model.meta_descr_wct = descr_arr[1]
model.para_tag_ct = len(para)
model.geo_locations_ct = 0
model.document_size = 0
model.request_time = response_time
status_code_res = 200
except urllib2.HTTPError, e:
print 'Error status code: ', e.code
print "ERR [%s]:scan_url HTTPError: url=%s" % (cur_time, url_str)
status_code_res = e.code
print e
def crawlSingleURLForContent(link, idx, total_links):
""" Crawl this URL but only extract the content for content
analysis. A more extensive model than crawlSingleURL"""
try:
opener = buildOpener()
start = time.time()
data = opener.open(link).read()
istats = build_page_info(link, data)
data = clean_content(data)
soup = BeautifulSoup(data)
meta_data_keywords = soup.findAll('meta', {'name': 'keywords'})
meta_data_descr = soup.findAll('meta', {'name': 'description'})
keywords = get_meta_content(meta_data_keywords)
descr = get_meta_content(meta_data_descr)
# Extract the title tag
titleTag = None
try:
titleTag = soup.html.head.title
titleTag = str(titleTag.string)
except:
titleTag = ""
# Ignore content we aren't concerned with
partial_content = doc_ignore_content(soup)
end = time.time()
# Return the basic URL data structure
field = URLField(link, titleTag, descr, keywords)
field.descr = field.tokenizeTags(field.descr)
field.keywords = field.tokenizeTags(field.keywords)
field.full_content = data
field.extract_content = partial_content
field.info_stats = istats
field.populate()
if ((idx % LINK_SET_INDICATOR) == 0):
sys.stdout.write("[%s/%s] " % (idx, total_links))
# Exit crawl single URL with url field.
# @return URLField
return field
except urllib2.URLError:
print "ERR: timeout [%s/%s] " % (idx, total_links)
except Exception, e:
# NOTE: if pass allowed, compile errors will be ignored.
print "ERR<crawlSingleURLForContent>: %s" % e
pass
def crawlSingleURLForContent(link, idx, total_links):
""" Crawl this URL but only extract the content for content
analysis. A more extensive model than crawlSingleURL"""
try:
opener = buildOpener()
start = time.time()
data = opener.open(link).read()
istats = build_page_info(link, data)
data = clean_content(data)
soup = BeautifulSoup(data)
meta_data_keywords = soup.findAll('meta', {'name':'keywords'})
meta_data_descr = soup.findAll('meta', {'name':'description'})
keywords = get_meta_content(meta_data_keywords)
descr = get_meta_content(meta_data_descr)
# Extract the title tag
titleTag = None
try:
titleTag = soup.html.head.title
titleTag = str(titleTag.string)
except:
titleTag = ""
# Ignore content we aren't concerned with
partial_content = doc_ignore_content(soup)
end = time.time()
# Return the basic URL data structure
field = URLField(link, titleTag, descr, keywords)
field.descr = field.tokenizeTags(field.descr)
field.keywords = field.tokenizeTags(field.keywords)
field.full_content = data
field.extract_content = partial_content
field.info_stats = istats
field.populate()
if ((idx % LINK_SET_INDICATOR) == 0):
sys.stdout.write("[%s/%s] " % (idx, total_links))
# Exit crawl single URL with url field.
# @return URLField
return field
except urllib2.URLError:
print "ERR: timeout [%s/%s] " % (idx, total_links)
except Exception, e:
# NOTE: if pass allowed, compile errors will be ignored.
print "ERR<crawlSingleURLForContent>: %s" % e
pass
def build_page_info(page_url, data):
""" Build page statistics based on beautiful soup invoke,
note: this may reload the data content again in order have a fresh start.
See http://www.w3schools.com/tags/default.asp
for HTML tag references."""
soup = BeautifulSoup(data)
stats = PageInfoStats(page_url)
for info_tag in KEY_HTML_TAGS:
tag_arr = soup.findAll(info_tag)
n = len(tag_arr)
# Simple switch statement, change handler depending on tag type
page_info_switch = {
KEY_HTML_TAGS[TAG_a]: lambda x: set_stats_prop(stats, 'anchor_ct', x),
KEY_HTML_TAGS[TAG_b]: lambda x: set_stats_prop(stats, 'bold_ct', x),
KEY_HTML_TAGS[TAG_bq]: lambda x: set_stats_prop(stats, 'block_ct', x),
KEY_HTML_TAGS[TAG_div]: lambda x: set_stats_prop(stats, 'div_ct', x),
KEY_HTML_TAGS[TAG_h1]: lambda x: set_stats_prop(stats, 'h1_ct', x),
KEY_HTML_TAGS[TAG_h2]: lambda x: set_stats_prop(stats, 'h2_ct', x),
KEY_HTML_TAGS[TAG_i]: lambda x: set_stats_prop(stats, 'italic_ct', x),
KEY_HTML_TAGS[TAG_img]: lambda x: set_stats_prop(stats, 'img_ct', x),
KEY_HTML_TAGS[TAG_p]: lambda x: set_stats_prop(stats, 'para_ct', x),
KEY_HTML_TAGS[TAG_span]: lambda x: set_stats_prop(stats, 'span_ct', x),
KEY_HTML_TAGS[TAG_strong]: lambda x: set_stats_prop(stats, 'strong_ct', x),
KEY_HTML_TAGS[TAG_table]: lambda x: set_stats_prop(stats, 'table_ct', x)
} [info_tag](n)
return stats
def crawlBuildLinks(link_list):
opener = buildOpener()
""" Iterate through the list of links and collect links found
on each page through the use of the beautiful soup lib."""
total_links = 0
total_links_tag = 0
sub_links = None
for link in link_list:
try:
data = opener.open(link).read()
soup = BeautifulSoup(data)
sub_links_tag = soup.findAll('a')
total_links_tag = total_links_tag + len(sub_links_tag)
sub_links = [processSubLink(el) for el in sub_links_tag if validateSubLink(el)]
# Filter out duplicates with set
sub_links = set(sub_links)
total_links = total_links + len(sub_links)
except Exception, e:
print "ERR <crawlBuildLinks>: %s" % e
print " <crawlBuildLinks>: url=[%s]" % link
def build_page_info(page_url, data):
""" Build page statistics based on beautiful soup invoke,
note: this may reload the data content again in order have a fresh start.
See http://www.w3schools.com/tags/default.asp
for HTML tag references."""
soup = BeautifulSoup(data)
stats = PageInfoStats(page_url)
for info_tag in KEY_HTML_TAGS:
tag_arr = soup.findAll(info_tag)
n = len(tag_arr)
# Simple switch statement, change handler depending on tag type
page_info_switch = {
KEY_HTML_TAGS[TAG_a]:
lambda x: set_stats_prop(stats, 'anchor_ct', x),
KEY_HTML_TAGS[TAG_b]:
lambda x: set_stats_prop(stats, 'bold_ct', x),
KEY_HTML_TAGS[TAG_bq]:
lambda x: set_stats_prop(stats, 'block_ct', x),
KEY_HTML_TAGS[TAG_div]:
lambda x: set_stats_prop(stats, 'div_ct', x),
KEY_HTML_TAGS[TAG_h1]:
lambda x: set_stats_prop(stats, 'h1_ct', x),
KEY_HTML_TAGS[TAG_h2]:
lambda x: set_stats_prop(stats, 'h2_ct', x),
KEY_HTML_TAGS[TAG_i]:
lambda x: set_stats_prop(stats, 'italic_ct', x),
KEY_HTML_TAGS[TAG_img]:
lambda x: set_stats_prop(stats, 'img_ct', x),
KEY_HTML_TAGS[TAG_p]:
lambda x: set_stats_prop(stats, 'para_ct', x),
KEY_HTML_TAGS[TAG_span]:
lambda x: set_stats_prop(stats, 'span_ct', x),
KEY_HTML_TAGS[TAG_strong]:
lambda x: set_stats_prop(stats, 'strong_ct', x),
KEY_HTML_TAGS[TAG_table]:
lambda x: set_stats_prop(stats, 'table_ct', x)
}[info_tag](n)
return stats
def crawlBuildLinks(link_list):
opener = buildOpener()
""" Iterate through the list of links and collect links found
on each page through the use of the beautiful soup lib."""
total_links = 0
total_links_tag = 0
sub_links = None
for link in link_list:
try:
data = opener.open(link).read()
soup = BeautifulSoup(data)
sub_links_tag = soup.findAll('a')
total_links_tag = total_links_tag + len(sub_links_tag)
sub_links = [
processSubLink(el) for el in sub_links_tag
if validateSubLink(el)
]
# Filter out duplicates with set
sub_links = set(sub_links)
total_links = total_links + len(sub_links)
except Exception, e:
print "ERR <crawlBuildLinks>: %s" % e
print " <crawlBuildLinks>: url=[%s]" % link