def setup_bot(self, settings, spec, items, extractors):
"""
Perform any initialization needed for crawling using this plugin
"""
_item_template_pages = sorted(([
t['scrapes'],
dict_to_page(t, 'annotated_body'),
t.get('extractors', [])
] for t in spec['templates'] if t.get('page_type', 'item') == 'item'),
key=lambda pair: pair[0])
self.itemcls_info = {}
if settings.get('AUTO_PAGINATION'):
self.html_link_extractor = PaginationExtractor()
else:
self.html_link_extractor = HtmlLinkExtractor()
for itemclass_name, triplets in groupby(_item_template_pages,
itemgetter(0)):
page_extractors_pairs = map(itemgetter(1, 2), triplets)
schema = items[itemclass_name]
item_cls = SlybotItem.create_iblitem_class(schema)
page_descriptor_pairs = []
for page, template_extractors in page_extractors_pairs:
item_descriptor = create_slybot_item_descriptor(schema)
apply_extractors(item_descriptor, template_extractors,
extractors)
page_descriptor_pairs.append((page, item_descriptor))
extractor = InstanceBasedLearningExtractor(page_descriptor_pairs)
self.itemcls_info[itemclass_name] = {
'class': item_cls,
'descriptor': item_descriptor,
'extractor': extractor,
}
# generate ibl extractor for links pages
_links_pages = [
dict_to_page(t, 'annotated_body') for t in spec['templates']
if t.get('page_type') == 'links'
]
_links_item_descriptor = create_slybot_item_descriptor({'fields': {}})
self._links_ibl_extractor = InstanceBasedLearningExtractor(
[(t, _links_item_descriptor) for t in _links_pages]) \
if _links_pages else None
self.build_url_filter(spec)
def setup_bot(self, settings, spec, items, extractors):
"""
Perform any initialization needed for crawling using this plugin
"""
_item_template_pages = sorted((
[t.get('scrapes'), dict_to_page(t, 'annotated_body'),
t.get('extractors', []), t.get('version', '0.12.0')]
for t in spec['templates'] if t.get('page_type', 'item') == 'item'
), key=lambda x: x[0])
self.item_classes = {}
self.template_scrapes = {template.get('page_id'): template['scrapes']
for template in spec.get('templates')}
self.html_link_extractor = HtmlLinkExtractor()
for schema_name, schema in items.items():
if schema_name not in self.item_classes:
if not schema.get('name'):
schema['name'] = schema_name
item_cls = SlybotItem.create_iblitem_class(schema)
self.item_classes[schema_name] = item_cls
# Create descriptors and apply additional extractors to fields
page_descriptor_pairs = []
self.schema_descriptors = {}
for default, template, template_extractors, v in _item_template_pages:
descriptors = OrderedDict()
for schema_name, schema in items.items():
item_descriptor = create_slybot_item_descriptor(schema,
schema_name)
apply_extractors(item_descriptor, template_extractors,
extractors)
descriptors[schema_name] = item_descriptor
descriptor = descriptors.values() or [{}]
descriptors['#default'] = descriptors.get(default, descriptor[0])
self.schema_descriptors[template.page_id] = descriptors['#default']
page_descriptor_pairs.append((template, descriptors, v))
add_extractors_to_descriptors(descriptors, extractors)
grouped = itertools.groupby(sorted(page_descriptor_pairs,
key=operator.itemgetter(2)),
lambda x: x[2] < '0.13.0')
self.extractors = []
for version, group in grouped:
if version:
self.extractors.append(
InstanceBasedLearningExtractor(
[(page, scrapes['#default'])
for page, scrapes, version in group]))
else:
self.extractors.append(SlybotIBLExtractor(list(group)))
# generate ibl extractor for links pages
_links_pages = [dict_to_page(t, 'annotated_body')
for t in spec['templates']
if t.get('page_type') == 'links']
_links_item_descriptor = create_slybot_item_descriptor({'fields': {}})
self._links_ibl_extractor = InstanceBasedLearningExtractor(
[(t, _links_item_descriptor) for t in _links_pages]) \
if _links_pages else None
self.build_url_filter(spec)
def setup_bot(self, settings, spec, items, extractors):
"""
Perform any initialization needed for crawling using this plugin
"""
_item_template_pages = sorted((
[t['scrapes'], dict_to_page(t, 'annotated_body'),
t.get('extractors', [])]
for t in spec['templates'] if t.get('page_type', 'item') == 'item'
), key=lambda pair: pair[0])
self.itemcls_info = {}
if settings.get('AUTO_PAGINATION'):
self.html_link_extractor = PaginationExtractor()
else:
self.html_link_extractor = HtmlLinkExtractor()
for itemclass_name, triplets in groupby(_item_template_pages,
itemgetter(0)):
page_extractors_pairs = map(itemgetter(1, 2), triplets)
schema = items[itemclass_name]
item_cls = SlybotItem.create_iblitem_class(schema)
page_descriptor_pairs = []
for page, template_extractors in page_extractors_pairs:
item_descriptor = create_slybot_item_descriptor(schema)
apply_extractors(item_descriptor, template_extractors,
extractors)
page_descriptor_pairs.append((page, item_descriptor))
extractor = InstanceBasedLearningExtractor(page_descriptor_pairs)
self.itemcls_info[itemclass_name] = {
'class': item_cls,
'descriptor': item_descriptor,
'extractor': extractor,
}
# generate ibl extractor for links pages
_links_pages = [dict_to_page(t, 'annotated_body')
for t in spec['templates']
if t.get('page_type') == 'links']
_links_item_descriptor = create_slybot_item_descriptor({'fields': {}})
self._links_ibl_extractor = InstanceBasedLearningExtractor(
[(t, _links_item_descriptor) for t in _links_pages]) \
if _links_pages else None
self.build_url_filter(spec)
def __init__(self, name, spec, item_schemas, all_extractors, **kw):
super(IblSpider, self).__init__(name, **kw)
spec = deepcopy(spec)
for key, val in kw.items():
if isinstance(val, basestring) and key in ['start_urls', 'exclude_patterns', 'follow_patterns', 'allowed_domains']:
val = val.splitlines()
spec[key] = val
self._item_template_pages = sorted((
[t['scrapes'], dict_to_page(t, 'annotated_body'),
t.get('extractors', [])] \
for t in spec['templates'] if t.get('page_type', 'item') == 'item'
), key=lambda pair: pair[0])
# generate ibl extractor for links pages
_links_pages = [dict_to_page(t, 'annotated_body')
for t in spec['templates'] if t.get('page_type') == 'links']
_links_item_descriptor = create_slybot_item_descriptor({'fields': {}})
self._links_ibl_extractor = InstanceBasedLearningExtractor([(t, _links_item_descriptor) for t in _links_pages]) \
if _links_pages else None
self._ipages = [page for _, page, _ in self._item_template_pages]
self.html_link_extractor = HtmlLinkExtractor()
self.rss_link_extractor = RssLinkExtractor()
self.build_url_filter(spec)
self.itemcls_info = {}
for itemclass_name, triplets in itertools.groupby(self._item_template_pages, operator.itemgetter(0)):
page_extractors_pairs = map(operator.itemgetter(1, 2), triplets)
schema = item_schemas[itemclass_name]
item_cls = SlybotItem.create_iblitem_class(schema)
page_descriptor_pairs = []
for page, template_extractors in page_extractors_pairs:
item_descriptor = create_slybot_item_descriptor(schema)
apply_extractors(item_descriptor, template_extractors, all_extractors)
page_descriptor_pairs.append((page, item_descriptor))
extractor = InstanceBasedLearningExtractor(page_descriptor_pairs)
self.itemcls_info[itemclass_name] = {
'class': item_cls,
'descriptor': item_descriptor,
'extractor': extractor,
}
self.login_requests = []
self.form_requests = []
self._start_requests = []
self.generic_form = GenericForm(**kw)
self._create_init_requests(spec.get("init_requests", []))
self._process_start_urls(spec)
self.allowed_domains = spec.get('allowed_domains',
self._get_allowed_domains(self._ipages))
if not self.allowed_domains:
self.allowed_domains = None
def setup_bot(self, settings, spec, items, extractors):
"""
Perform any initialization needed for crawling using this plugin
"""
_item_template_pages = sorted(
(
[t["scrapes"], dict_to_page(t, "annotated_body"), t.get("extractors", [])]
for t in spec["templates"]
if t.get("page_type", "item") == "item"
),
key=lambda pair: pair[0],
)
self.itemcls_info = {}
self.html_link_extractor = HtmlLinkExtractor()
self.rss_link_extractor = RssLinkExtractor()
for itemclass_name, triplets in groupby(_item_template_pages, itemgetter(0)):
page_extractors_pairs = map(itemgetter(1, 2), triplets)
schema = items[itemclass_name]
item_cls = SlybotItem.create_iblitem_class(schema)
page_descriptor_pairs = []
for page, template_extractors in page_extractors_pairs:
item_descriptor = create_slybot_item_descriptor(schema)
apply_extractors(item_descriptor, template_extractors, extractors)
page_descriptor_pairs.append((page, item_descriptor))
extractor = InstanceBasedLearningExtractor(page_descriptor_pairs)
self.itemcls_info[itemclass_name] = {
"class": item_cls,
"descriptor": item_descriptor,
"extractor": extractor,
}
# generate ibl extractor for links pages
_links_pages = [dict_to_page(t, "annotated_body") for t in spec["templates"] if t.get("page_type") == "links"]
_links_item_descriptor = create_slybot_item_descriptor({"fields": {}})
self._links_ibl_extractor = (
InstanceBasedLearningExtractor([(t, _links_item_descriptor) for t in _links_pages])
if _links_pages
else None
)
self.build_url_filter(spec)
def setup_bot(self, settings, spec, items, extractors):
"""
Perform any initialization needed for crawling using this plugin
"""
_item_template_pages = sorted((
[t.get('scrapes'), dict_to_page(t, 'annotated_body'),
t.get('extractors', [])]
for t in spec['templates'] if t.get('page_type', 'item') == 'item'
))
self.item_classes = {}
self.html_link_extractor = HtmlLinkExtractor()
for schema_name, schema in items.items():
if schema_name not in self.item_classes:
if not schema.get('name'):
schema['name'] = schema_name
item_cls = SlybotItem.create_iblitem_class(schema)
self.item_classes[schema_name] = item_cls
# Create descriptors and apply additional extractors to fields
page_descriptor_pairs = []
for default, template, template_extractors in _item_template_pages:
descriptors = OrderedDict()
for schema_name, schema in items.items():
item_descriptor = create_slybot_item_descriptor(schema,
schema_name)
apply_extractors(item_descriptor, template_extractors,
extractors)
descriptors[schema_name] = item_descriptor
descriptor = descriptors.values() or [{}]
descriptors['#default'] = descriptors.get(default, descriptor[0])
page_descriptor_pairs.append((template, descriptors))
self.extractors = SlybotIBLExtractor(page_descriptor_pairs)
# generate ibl extractor for links pages
_links_pages = [dict_to_page(t, 'annotated_body')
for t in spec['templates']
if t.get('page_type') == 'links']
_links_item_descriptor = create_slybot_item_descriptor({'fields': {}})
self._links_ibl_extractor = InstanceBasedLearningExtractor(
[(t, _links_item_descriptor) for t in _links_pages]) \
if _links_pages else None
self.build_url_filter(spec)
def setup_bot(self, settings, spec, items, extractors, logger):
"""
Perform any initialization needed for crawling using this plugin
"""
self.logger = logger
templates = map(self._get_annotated_template, spec['templates'])
_item_template_pages = sorted(([
t.get('scrapes'),
dict_to_page(t, 'annotated_body'),
t.get('extractors', []),
t.get('version', '0.12.0')
] for t in templates if t.get('page_type', 'item') == 'item'),
key=lambda x: x[0])
self.item_classes = {}
self.template_scrapes = {
template.get('page_id'): template['scrapes']
for template in templates
}
if (settings.get('AUTO_PAGINATION')
or spec.get('links_to_follow') == 'auto'):
self.html_link_extractor = PaginationExtractor()
else:
self.html_link_extractor = HtmlLinkExtractor()
for schema_name, schema in items.items():
if schema_name not in self.item_classes:
if not schema.get('name'):
schema['name'] = schema_name
item_cls = SlybotItem.create_iblitem_class(schema)
self.item_classes[schema_name] = item_cls
# Create descriptors and apply additional extractors to fields
page_descriptor_pairs = []
self.schema_descriptors = {}
for default, template, template_extractors, v in _item_template_pages:
descriptors = OrderedDict()
for schema_name, schema in items.items():
item_descriptor = create_slybot_item_descriptor(
schema, schema_name)
apply_extractors(item_descriptor, template_extractors,
extractors)
descriptors[schema_name] = item_descriptor
descriptor = descriptors.values() or [{}]
descriptors['#default'] = descriptors.get(default, descriptor[0])
self.schema_descriptors[template.page_id] = descriptors['#default']
page_descriptor_pairs.append((template, descriptors, v))
add_extractors_to_descriptors(descriptors, extractors)
grouped = itertools.groupby(
sorted(page_descriptor_pairs, key=operator.itemgetter(2)),
lambda x: x[2] < '0.13.0')
self.extractors = []
for version, group in grouped:
if version:
self.extractors.append(
InstanceBasedLearningExtractor([
(page, scrapes['#default'])
for page, scrapes, version in group
]))
else:
self.extractors.append(SlybotIBLExtractor(list(group)))
# generate ibl extractor for links pages
_links_pages = [
dict_to_page(t, 'annotated_body') for t in templates
if t.get('page_type') == 'links'
]
_links_item_descriptor = create_slybot_item_descriptor({'fields': {}})
self._links_ibl_extractor = InstanceBasedLearningExtractor(
[(t, _links_item_descriptor) for t in _links_pages]) \
if _links_pages else None
self.build_url_filter(spec)
# Clustering
self.template_names = [t.get('page_id') for t in spec['templates']]
if settings.get('PAGE_CLUSTERING'):
try:
import page_clustering
self.clustering = page_clustering.kmeans_from_samples(
spec['templates'])
self.logger.info("Clustering activated")
except ImportError:
self.clustering = None
self.logger.warning(
"Clustering could not be used because it is not installed")
else:
self.clustering = None
class Annotations(object):
"""
Base Class for adding plugins to Portia Web and Slybot.
"""
def setup_bot(self, settings, spec, items, extractors, logger):
"""
Perform any initialization needed for crawling using this plugin
"""
self.logger = logger
templates = map(self._get_annotated_template, spec['templates'])
_item_template_pages = sorted(([
t.get('scrapes'),
dict_to_page(t, 'annotated_body'),
t.get('extractors', []),
t.get('version', '0.12.0')
] for t in templates if t.get('page_type', 'item') == 'item'),
key=lambda x: x[0])
self.item_classes = {}
self.template_scrapes = {
template.get('page_id'): template['scrapes']
for template in templates
}
if (settings.get('AUTO_PAGINATION')
or spec.get('links_to_follow') == 'auto'):
self.html_link_extractor = PaginationExtractor()
else:
self.html_link_extractor = HtmlLinkExtractor()
for schema_name, schema in items.items():
if schema_name not in self.item_classes:
if not schema.get('name'):
schema['name'] = schema_name
item_cls = SlybotItem.create_iblitem_class(schema)
self.item_classes[schema_name] = item_cls
# Create descriptors and apply additional extractors to fields
page_descriptor_pairs = []
self.schema_descriptors = {}
for default, template, template_extractors, v in _item_template_pages:
descriptors = OrderedDict()
for schema_name, schema in items.items():
item_descriptor = create_slybot_item_descriptor(
schema, schema_name)
apply_extractors(item_descriptor, template_extractors,
extractors)
descriptors[schema_name] = item_descriptor
descriptor = descriptors.values() or [{}]
descriptors['#default'] = descriptors.get(default, descriptor[0])
self.schema_descriptors[template.page_id] = descriptors['#default']
page_descriptor_pairs.append((template, descriptors, v))
add_extractors_to_descriptors(descriptors, extractors)
grouped = itertools.groupby(
sorted(page_descriptor_pairs, key=operator.itemgetter(2)),
lambda x: x[2] < '0.13.0')
self.extractors = []
for version, group in grouped:
if version:
self.extractors.append(
InstanceBasedLearningExtractor([
(page, scrapes['#default'])
for page, scrapes, version in group
]))
else:
self.extractors.append(SlybotIBLExtractor(list(group)))
# generate ibl extractor for links pages
_links_pages = [
dict_to_page(t, 'annotated_body') for t in templates
if t.get('page_type') == 'links'
]
_links_item_descriptor = create_slybot_item_descriptor({'fields': {}})
self._links_ibl_extractor = InstanceBasedLearningExtractor(
[(t, _links_item_descriptor) for t in _links_pages]) \
if _links_pages else None
self.build_url_filter(spec)
# Clustering
self.template_names = [t.get('page_id') for t in spec['templates']]
if settings.get('PAGE_CLUSTERING'):
try:
import page_clustering
self.clustering = page_clustering.kmeans_from_samples(
spec['templates'])
self.logger.info("Clustering activated")
except ImportError:
self.clustering = None
self.logger.warning(
"Clustering could not be used because it is not installed")
else:
self.clustering = None
def _get_annotated_template(self, template):
if template.get('version', '0.12.0') >= '0.13.0':
_build_sample(template)
return template
def handle_html(self, response, seen=None):
htmlpage = htmlpage_from_response(response)
items, link_regions = self.extract_items(htmlpage)
htmlpage.headers['n_items'] = len(items)
try:
response.meta['n_items'] = len(items)
except AttributeError:
pass # response not tied to any request
for item in items:
yield item
for request in self._process_link_regions(htmlpage, link_regions):
yield request
def extract_items(self, htmlpage):
"""This method is also called from UI webservice to extract items"""
for extractor in self.extractors:
items, links = self._do_extract_items_from(htmlpage, extractor)
if items:
return items, links
return [], []
def _do_extract_items_from(self, htmlpage, extractor):
# Try to predict template to use
pref_template_id = None
template_cluster = _CLUSTER_NA
if self.clustering:
self.clustering.add_page(htmlpage)
if self.clustering.is_fit:
clt = self.clustering.classify(htmlpage)
if clt != -1:
template_cluster = self.template_names[clt]
pref_template_id = template_cluster
else:
template_cluster = _CLUSTER_OUTLIER
extracted_data, template = extractor.extract(htmlpage,
pref_template_id)
link_regions = []
for ddict in extracted_data or []:
link_regions.extend(ddict.pop("_links", []))
descriptor = None
unprocessed = False
if template is not None and hasattr(template, 'descriptor'):
descriptor = template.descriptor()
if hasattr(descriptor, 'name'):
item_cls_name = descriptor.name
elif hasattr(descriptor, 'get'):
item_cls_name = descriptor.get('name',
descriptor.get('display_name'))
else:
item_cls_name = ''
else:
unprocessed = True
try:
descriptor = self.schema_descriptors[template.id]
item_cls_name = self.template_scrapes[template.id]
except AttributeError:
descriptor = sorted(self.schema_descriptors.items())[0][1]
item_cls_name = sorted(self.template_scrapes.items())[0][1]
item_cls = self.item_classes.get(item_cls_name)
items = []
for processed_attributes in extracted_data or []:
if processed_attributes.get('_type') in self.item_classes:
_type = processed_attributes['_type']
item = self.item_classes[_type](processed_attributes)
item['_type'] = item.display_name()
elif unprocessed:
item = self._process_attributes(processed_attributes,
descriptor, htmlpage)
if item_cls:
item = item_cls(item)
elif item_cls:
item = item_cls(processed_attributes)
else:
item = dict(processed_attributes)
item['url'] = htmlpage.url
item['_template'] = str(template.id)
item.setdefault('_type', item_cls_name)
if not isinstance(item, SlybotItem):
default_meta = {
'type': 'text',
'required': False,
'vary': False
}
item_cls = SlybotItem.create_iblitem_class(
{'fields': {k: default_meta
for k in item}})
item = item_cls(**item)
if self.clustering:
item['_template_cluster'] = template_cluster
items.append(item)
return items, link_regions
def _process_attributes(self, item, descriptor, htmlpage):
new_item = {}
try:
attr_map = descriptor.attribute_map
except AttributeError:
attr_map = {}
page = getattr(htmlpage, 'htmlpage', htmlpage)
for field, value in item.items():
if field.startswith('_sticky'):
continue
if field == 'variants':
value = [
self._process_attributes(v, descriptor, page)
for v in value
]
elif field in attr_map:
value = [attr_map[field].adapt(v, page) for v in value]
new_item[field] = value
return new_item
def build_url_filter(self, spec):
"""make a filter for links"""
respect_nofollow = spec.get('respect_nofollow', True)
if spec.get("links_to_follow") == "none":
url_filterf = lambda x: False
elif spec.get("links_to_follow") == "all":
if respect_nofollow:
url_filterf = lambda x: x.nofollow
else:
url_filterf = lambda x: True
else: # patterns
patterns = spec.get('follow_patterns')
excludes = spec.get('exclude_patterns')
pattern_fn = include_exclude_filter(patterns, excludes)
if respect_nofollow:
url_filterf = lambda x: not x.nofollow and pattern_fn(x.url)
else:
url_filterf = lambda x: pattern_fn(x.url)
self.url_filterf = url_filterf
def _filter_link(self, link, seen):
url = link.url
if self.url_filterf(link):
# filter out duplicate urls, later we should handle link text
if url not in seen:
seen.add(url)
request = Request(url)
if link.text:
request.meta['link_text'] = link.text
return request
def _process_link_regions(self, htmlpage, link_regions):
"""Process link regions if any, and generate requests"""
if link_regions:
for link_region in link_regions:
htmlregion = HtmlPage(htmlpage.url,
htmlpage.headers,
link_region,
encoding=htmlpage.encoding)
for request in self._requests_to_follow(htmlregion):
yield request
else:
for request in self._requests_to_follow(htmlpage):
yield request
def _requests_to_follow(self, htmlpage):
if self._links_ibl_extractor is not None:
extracted = self._links_ibl_extractor.extract(htmlpage)[0]
if extracted:
extracted_regions = extracted[0].get('_links', [])
seen = set()
for region in extracted_regions:
htmlregion = HtmlPage(htmlpage.url,
htmlpage.headers,
region,
encoding=htmlpage.encoding)
for request in self._request_to_follow_from_region(
htmlregion):
if request.url in seen:
continue
seen.add(request.url)
yield request
else:
for request in self._request_to_follow_from_region(htmlpage):
yield request
def _request_to_follow_from_region(self, htmlregion):
seen = set()
for link in self.html_link_extractor.links_to_follow(htmlregion):
request = self._filter_link(link, seen)
if request is not None:
yield request
def handle_xml(self, response, seen):
_type = XML_APPLICATION_TYPE(response.headers.get('Content-Type', ''))
_type = _type.groupdict()['type'] if _type else 'xml'
try:
link_extractor = create_linkextractor_from_specs({
'type': _type,
'value': ''
})
except ValueError:
link_extractor = SitemapLinkExtractor()
for link in link_extractor.links_to_follow(response):
request = self._filter_link(link, seen)
if request:
yield request
class Annotations(object):
"""
Base Class for adding plugins to Portia Web and Slybot.
"""
def setup_bot(self, settings, spec, items, extractors):
"""
Perform any initialization needed for crawling using this plugin
"""
_item_template_pages = sorted((
[t['scrapes'], dict_to_page(t, 'annotated_body'),
t.get('extractors', [])]
for t in spec['templates'] if t.get('page_type', 'item') == 'item'
), key=lambda pair: pair[0])
self.itemcls_info = {}
if settings.get('AUTO_PAGINATION'):
self.html_link_extractor = PaginationExtractor()
else:
self.html_link_extractor = HtmlLinkExtractor()
for itemclass_name, triplets in groupby(_item_template_pages,
itemgetter(0)):
page_extractors_pairs = map(itemgetter(1, 2), triplets)
schema = items[itemclass_name]
item_cls = SlybotItem.create_iblitem_class(schema)
page_descriptor_pairs = []
for page, template_extractors in page_extractors_pairs:
item_descriptor = create_slybot_item_descriptor(schema)
apply_extractors(item_descriptor, template_extractors,
extractors)
page_descriptor_pairs.append((page, item_descriptor))
extractor = InstanceBasedLearningExtractor(page_descriptor_pairs)
self.itemcls_info[itemclass_name] = {
'class': item_cls,
'descriptor': item_descriptor,
'extractor': extractor,
}
# generate ibl extractor for links pages
_links_pages = [dict_to_page(t, 'annotated_body')
for t in spec['templates']
if t.get('page_type') == 'links']
_links_item_descriptor = create_slybot_item_descriptor({'fields': {}})
self._links_ibl_extractor = InstanceBasedLearningExtractor(
[(t, _links_item_descriptor) for t in _links_pages]) \
if _links_pages else None
self.build_url_filter(spec)
def handle_html(self, response, seen=None):
htmlpage = htmlpage_from_response(response)
items, link_regions = self.extract_items(htmlpage)
htmlpage.headers['n_items'] = len(items)
try:
response.meta['n_items'] = len(items)
except AttributeError:
pass # response not tied to any request
for item in items:
yield item
for request in self._process_link_regions(htmlpage, link_regions):
yield request
def extract_items(self, htmlpage):
"""This method is also called from UI webservice to extract items"""
items = []
link_regions = []
for item_cls_name, info in self.itemcls_info.items():
item_descriptor = info['descriptor']
extractor = info['extractor']
extracted, _link_regions = self._do_extract_items_from(
htmlpage,
item_descriptor,
extractor,
item_cls_name,
)
items.extend(extracted)
link_regions.extend(_link_regions)
return items, link_regions
def _do_extract_items_from(self, htmlpage, item_descriptor, extractor,
item_cls_name):
extracted_data, template = extractor.extract(htmlpage)
link_regions = []
for ddict in extracted_data or []:
link_regions.extend(ddict.pop("_links", []))
processed_data = _process_extracted_data(extracted_data,
item_descriptor,
htmlpage)
items = []
item_cls = self.itemcls_info[item_cls_name]['class']
for processed_attributes in processed_data:
item = item_cls(processed_attributes)
item['url'] = htmlpage.url
item['_type'] = item_cls_name
item['_template'] = str(template.id)
items.append(item)
return items, link_regions
def build_url_filter(self, spec):
"""make a filter for links"""
respect_nofollow = spec.get('respect_nofollow', True)
patterns = spec.get('follow_patterns')
if spec.get("links_to_follow") == "none":
url_filterf = lambda x: False
elif patterns:
pattern = patterns[0] if len(patterns) == 1 \
else "(?:%s)" % '|'.join(patterns)
follow_pattern = re.compile(pattern)
if respect_nofollow:
url_filterf = lambda x: follow_pattern.search(x.url) \
and not x.nofollow
else:
url_filterf = lambda x: follow_pattern.search(x.url)
elif respect_nofollow:
url_filterf = lambda x: not x.nofollow
else:
url_filterf = bool
# apply exclude patterns
excludes = spec.get('exclude_patterns')
if excludes:
pattern = excludes[0] if len(excludes) == 1 \
else "(?:%s)" % '|'.join(excludes)
exclude_pattern = re.compile(pattern)
self.url_filterf = lambda x: not exclude_pattern.search(x.url) \
and url_filterf(x)
else:
self.url_filterf = url_filterf
def _filter_link(self, link, seen):
url = link.url
if self.url_filterf(link):
# filter out duplicate urls, later we should handle link text
if url not in seen:
seen.add(url)
request = Request(url)
if link.text:
request.meta['link_text'] = link.text
return request
def _process_link_regions(self, htmlpage, link_regions):
"""Process link regions if any, and generate requests"""
if link_regions:
for link_region in link_regions:
htmlregion = HtmlPage(htmlpage.url, htmlpage.headers,
link_region, encoding=htmlpage.encoding)
for request in self._requests_to_follow(htmlregion):
yield request
else:
for request in self._requests_to_follow(htmlpage):
yield request
def _requests_to_follow(self, htmlpage):
if self._links_ibl_extractor is not None:
extracted = self._links_ibl_extractor.extract(htmlpage)[0]
if extracted:
extracted_regions = extracted[0].get('_links', [])
seen = set()
for region in extracted_regions:
htmlregion = HtmlPage(htmlpage.url, htmlpage.headers,
region, encoding=htmlpage.encoding)
for request in self._request_to_follow_from_region(
htmlregion):
if request.url in seen:
continue
seen.add(request.url)
yield request
else:
for request in self._request_to_follow_from_region(htmlpage):
yield request
def _request_to_follow_from_region(self, htmlregion):
seen = set()
for link in self.html_link_extractor.links_to_follow(htmlregion):
request = self._filter_link(link, seen)
if request is not None:
yield request
def handle_xml(self, response, seen):
_type = XML_APPLICATION_TYPE(response.headers.get('Content-Type', ''))
_type = _type.groupdict()['type'] if _type else 'xml'
try:
link_extractor = create_linkextractor_from_specs({
'type': _type, 'value': ''
})
except ValueError:
link_extractor = SitemapLinkExtractor()
for link in link_extractor.links_to_follow(response):
request = self._filter_link(link, seen)
if request:
yield request
class Annotations(object):
"""
Base Class for adding plugins to Portia Web and Slybot.
"""
def setup_bot(self, settings, spec, items, extractors):
"""
Perform any initialization needed for crawling using this plugin
"""
_item_template_pages = sorted((
[t.get('scrapes'), dict_to_page(t, 'annotated_body'),
t.get('extractors', []), t.get('version', '0.12.0')]
for t in spec['templates'] if t.get('page_type', 'item') == 'item'
), key=lambda x: x[0])
self.item_classes = {}
self.template_scrapes = {template.get('page_id'): template['scrapes']
for template in spec.get('templates')}
self.html_link_extractor = HtmlLinkExtractor()
for schema_name, schema in items.items():
if schema_name not in self.item_classes:
if not schema.get('name'):
schema['name'] = schema_name
item_cls = SlybotItem.create_iblitem_class(schema)
self.item_classes[schema_name] = item_cls
# Create descriptors and apply additional extractors to fields
page_descriptor_pairs = []
self.schema_descriptors = {}
for default, template, template_extractors, v in _item_template_pages:
descriptors = OrderedDict()
for schema_name, schema in items.items():
item_descriptor = create_slybot_item_descriptor(schema,
schema_name)
apply_extractors(item_descriptor, template_extractors,
extractors)
descriptors[schema_name] = item_descriptor
descriptor = descriptors.values() or [{}]
descriptors['#default'] = descriptors.get(default, descriptor[0])
self.schema_descriptors[template.page_id] = descriptors['#default']
page_descriptor_pairs.append((template, descriptors, v))
grouped = itertools.groupby(sorted(page_descriptor_pairs,
key=operator.itemgetter(2)),
lambda x: x[2] < '0.13.0')
self.extractors = []
for version, group in grouped:
if version:
self.extractors.append(
InstanceBasedLearningExtractor(
[(page, scrapes['#default'])
for page, scrapes, version in group]))
else:
self.extractors.append(SlybotIBLExtractor(list(group)))
# generate ibl extractor for links pages
_links_pages = [dict_to_page(t, 'annotated_body')
for t in spec['templates']
if t.get('page_type') == 'links']
_links_item_descriptor = create_slybot_item_descriptor({'fields': {}})
self._links_ibl_extractor = InstanceBasedLearningExtractor(
[(t, _links_item_descriptor) for t in _links_pages]) \
if _links_pages else None
self.build_url_filter(spec)
def handle_html(self, response, seen=None):
htmlpage = htmlpage_from_response(response)
items, link_regions = self.extract_items(htmlpage)
htmlpage.headers['n_items'] = len(items)
try:
response.meta['n_items'] = len(items)
except AttributeError:
pass # response not tied to any request
for item in items:
yield item
for request in self._process_link_regions(htmlpage, link_regions):
yield request
def extract_items(self, htmlpage):
"""This method is also called from UI webservice to extract items"""
for extractor in self.extractors:
items, links = self._do_extract_items_from(htmlpage, extractor)
if items:
return items, links
return [], []
def _do_extract_items_from(self, htmlpage, extractor):
extracted_data, template = extractor.extract(htmlpage)
link_regions = []
for ddict in extracted_data or []:
link_regions.extend(ddict.pop("_links", []))
descriptor = None
unprocessed = False
if template is not None and hasattr(template, 'descriptor'):
descriptor = template.descriptor()
item_cls_name = descriptor.name if descriptor is not None else ''
else:
unprocessed = True
try:
descriptor = self.schema_descriptors[template.id]
item_cls_name = self.template_scrapes[template.id]
except AttributeError:
descriptor = sorted(self.schema_descriptors.items())[0][1]
item_cls_name = sorted(self.template_scrapes.items())[0][1]
item_cls = self.item_classes.get(item_cls_name)
items = []
for processed_attributes in extracted_data or []:
if processed_attributes.get('_type') in self.item_classes:
_type = processed_attributes['_type']
item = self.item_classes[_type](processed_attributes)
item['_type'] = item.display_name()
elif unprocessed:
item = self._process_attributes(processed_attributes,
descriptor, htmlpage)
if item_cls:
item = item_cls(item)
elif item_cls:
item = item_cls(processed_attributes)
else:
item = dict(processed_attributes)
item['url'] = htmlpage.url
item['_template'] = str(template.id)
item.setdefault('_type', item_cls_name)
if not isinstance(item, SlybotItem):
default_meta = {'type': 'text', 'required': False,
'vary': False}
item_cls = SlybotItem.create_iblitem_class(
{'fields': {k: default_meta for k in item}}
)
item = item_cls(**item)
items.append(item)
return items, link_regions
def _process_attributes(self, item, descriptor, htmlpage):
new_item = {}
attr_map = descriptor.attribute_map
for field, value in item.items():
if field.startswith('_sticky'):
continue
if field == 'variants':
value = [self._process_attributes(v, descriptor, htmlpage)
for v in value]
elif field in attr_map:
value = [attr_map[field].adapt(v, htmlpage) for v in value]
new_item[field] = value
return new_item
def build_url_filter(self, spec):
"""make a filter for links"""
respect_nofollow = spec.get('respect_nofollow', True)
if spec.get("links_to_follow") == "none":
url_filterf = lambda x: False
elif spec.get("links_to_follow") == "all":
if respect_nofollow:
url_filterf = lambda x: x.nofollow
else:
url_filterf = lambda x: True
else: # patterns
patterns = spec.get('follow_patterns')
excludes = spec.get('exclude_patterns')
pattern_fn = include_exclude_filter(patterns, excludes)
if respect_nofollow:
url_filterf = lambda x: not x.nofollow and pattern_fn(x.url)
else:
url_filterf = lambda x: pattern_fn(x.url)
self.url_filterf = url_filterf
def _filter_link(self, link, seen):
url = link.url
if self.url_filterf(link):
# filter out duplicate urls, later we should handle link text
if url not in seen:
seen.add(url)
request = Request(url)
if link.text:
request.meta['link_text'] = link.text
return request
def _process_link_regions(self, htmlpage, link_regions):
"""Process link regions if any, and generate requests"""
if link_regions:
for link_region in link_regions:
htmlregion = HtmlPage(htmlpage.url, htmlpage.headers,
link_region, encoding=htmlpage.encoding)
for request in self._requests_to_follow(htmlregion):
yield request
else:
for request in self._requests_to_follow(htmlpage):
yield request
def _requests_to_follow(self, htmlpage):
if self._links_ibl_extractor is not None:
extracted = self._links_ibl_extractor.extract(htmlpage)[0]
if extracted:
extracted_regions = extracted[0].get('_links', [])
seen = set()
for region in extracted_regions:
htmlregion = HtmlPage(htmlpage.url, htmlpage.headers,
region, encoding=htmlpage.encoding)
for request in self._request_to_follow_from_region(
htmlregion):
if request.url in seen:
continue
seen.add(request.url)
yield request
else:
for request in self._request_to_follow_from_region(htmlpage):
yield request
def _request_to_follow_from_region(self, htmlregion):
seen = set()
for link in self.html_link_extractor.links_to_follow(htmlregion):
request = self._filter_link(link, seen)
if request is not None:
yield request
def handle_xml(self, response, seen):
_type = XML_APPLICATION_TYPE(response.headers.get('Content-Type', ''))
_type = _type.groupdict()['type'] if _type else 'xml'
try:
link_extractor = create_linkextractor_from_specs({
'type': _type, 'value': ''
})
except ValueError:
link_extractor = SitemapLinkExtractor()
for link in link_extractor.links_to_follow(response):
request = self._filter_link(link, seen)
if request:
yield request
def __init__(self, name, spec, item_schemas, all_extractors, **kw):
super(IblSpider, self).__init__(name, **kw)
self._item_template_pages = sorted((
[t['scrapes'], dict_to_page(t, 'annotated_body'),
t.get('extractors', [])] \
for t in spec['templates'] if t.get('page_type', 'item') == 'item'
), key=lambda pair: pair[0])
# generate ibl extractor for links pages
_links_pages = [dict_to_page(t, 'annotated_body')
for t in spec['templates'] if t.get('page_type') == 'links']
_links_item_descriptor = create_slybot_item_descriptor({'fields': {}})
self._links_ibl_extractor = InstanceBasedLearningExtractor([(t, _links_item_descriptor) for t in _links_pages]) \
if _links_pages else None
self._ipages = [page for _, page, _ in self._item_template_pages]
self.start_urls = self.start_urls or spec.get('start_urls')
if isinstance(self.start_urls, basestring):
self.start_urls = self.start_urls.splitlines()
self.html_link_extractor = HtmlLinkExtractor()
self.rss_link_extractor = RssLinkExtractor()
self.allowed_domains = spec.get('allowed_domains',
self._get_allowed_domains(self._ipages))
if not self.allowed_domains:
self.allowed_domains = None
self.build_url_filter(spec)
self.itemcls_info = {}
for itemclass_name, triplets in itertools.groupby(self._item_template_pages, operator.itemgetter(0)):
page_extractors_pairs = map(operator.itemgetter(1, 2), triplets)
schema = item_schemas[itemclass_name]
item_cls = get_iblitem_class(schema)
page_descriptor_pairs = []
for page, template_extractors in page_extractors_pairs:
item_descriptor = create_slybot_item_descriptor(schema)
apply_extractors(item_descriptor, template_extractors, all_extractors)
page_descriptor_pairs.append((page, item_descriptor))
extractor = InstanceBasedLearningExtractor(page_descriptor_pairs)
self.itemcls_info[itemclass_name] = {
'class': item_cls,
'descriptor': item_descriptor,
'extractor': extractor,
}
self.login_requests = []
self.form_requests = []
for rdata in spec.get("init_requests", []):
if rdata["type"] == "login":
request = Request(url=rdata.pop("loginurl"), meta=rdata,
callback=self.parse_login_page, dont_filter=True)
self.login_requests.append(request)
elif rdata["type"] == "form":
self.generic_form = GenericForm(**kw)
self.form_requests.append(self.get_generic_form_start_request(rdata))
class Annotations(object):
"""
Base Class for adding plugins to Portia Web and Slybot.
"""
def setup_bot(self, settings, spec, items, extractors):
"""
Perform any initialization needed for crawling using this plugin
"""
_item_template_pages = sorted(([
t['scrapes'],
dict_to_page(t, 'annotated_body'),
t.get('extractors', [])
] for t in spec['templates'] if t.get('page_type', 'item') == 'item'),
key=lambda pair: pair[0])
self.itemcls_info = {}
self.html_link_extractor = HtmlLinkExtractor()
self.rss_link_extractor = RssLinkExtractor()
for itemclass_name, triplets in groupby(_item_template_pages,
itemgetter(0)):
page_extractors_pairs = map(itemgetter(1, 2), triplets)
schema = items[itemclass_name]
item_cls = SlybotItem.create_iblitem_class(schema)
page_descriptor_pairs = []
for page, template_extractors in page_extractors_pairs:
item_descriptor = create_slybot_item_descriptor(schema)
apply_extractors(item_descriptor, template_extractors,
extractors)
page_descriptor_pairs.append((page, item_descriptor))
extractor = InstanceBasedLearningExtractor(page_descriptor_pairs)
self.itemcls_info[itemclass_name] = {
'class': item_cls,
'descriptor': item_descriptor,
'extractor': extractor,
}
# generate ibl extractor for links pages
_links_pages = [
dict_to_page(t, 'annotated_body') for t in spec['templates']
if t.get('page_type') == 'links'
]
_links_item_descriptor = create_slybot_item_descriptor({'fields': {}})
self._links_ibl_extractor = InstanceBasedLearningExtractor(
[(t, _links_item_descriptor) for t in _links_pages]) \
if _links_pages else None
self.build_url_filter(spec)
def handle_html(self, response):
htmlpage = htmlpage_from_response(response)
items, link_regions = self.extract_items(htmlpage)
for item in items:
yield item
for request in self._process_link_regions(htmlpage, link_regions):
yield request
def extract_items(self, htmlpage):
"""This method is also called from UI webservice to extract items"""
items = []
link_regions = []
for item_cls_name, info in self.itemcls_info.iteritems():
item_descriptor = info['descriptor']
extractor = info['extractor']
extracted, _link_regions = self._do_extract_items_from(
htmlpage,
item_descriptor,
extractor,
item_cls_name,
)
items.extend(extracted)
link_regions.extend(_link_regions)
return items, link_regions
def _do_extract_items_from(self, htmlpage, item_descriptor, extractor,
item_cls_name):
extracted_data, template = extractor.extract(htmlpage)
link_regions = []
for ddict in extracted_data or []:
link_regions.extend(ddict.pop("_links", []))
processed_data = _process_extracted_data(extracted_data,
item_descriptor, htmlpage)
items = []
item_cls = self.itemcls_info[item_cls_name]['class']
for processed_attributes in processed_data:
item = item_cls(processed_attributes)
item['url'] = htmlpage.url
item['_type'] = item_cls_name
item['_template'] = str(template.id)
items.append(item)
return items, link_regions
def build_url_filter(self, spec):
"""make a filter for links"""
respect_nofollow = spec.get('respect_nofollow', True)
patterns = spec.get('follow_patterns')
if spec.get("links_to_follow") == "none":
url_filterf = lambda x: False
elif patterns:
pattern = patterns[0] if len(patterns) == 1 \
else "(?:%s)" % '|'.join(patterns)
follow_pattern = re.compile(pattern)
if respect_nofollow:
url_filterf = lambda x: follow_pattern.search(x.url) \
and not x.nofollow
else:
url_filterf = lambda x: follow_pattern.search(x.url)
elif respect_nofollow:
url_filterf = lambda x: not x.nofollow
else:
url_filterf = bool
# apply exclude patterns
excludes = spec.get('exclude_patterns')
if excludes:
pattern = excludes[0] if len(excludes) == 1 \
else "(?:%s)" % '|'.join(excludes)
exclude_pattern = re.compile(pattern)
self.url_filterf = lambda x: not exclude_pattern.search(x.url) \
and url_filterf(x)
else:
self.url_filterf = url_filterf
def _filter_link(self, link, seen):
url = link.url
if self.url_filterf(link):
# filter out duplicate urls, later we should handle link text
if url not in seen:
seen.add(url)
request = Request(url)
if link.text:
request.meta['link_text'] = link.text
return request
def _process_link_regions(self, htmlpage, link_regions):
"""Process link regions if any, and generate requests"""
if link_regions:
for link_region in link_regions:
htmlregion = HtmlPage(htmlpage.url,
htmlpage.headers,
link_region,
encoding=htmlpage.encoding)
for request in self._requests_to_follow(htmlregion):
yield request
else:
for request in self._requests_to_follow(htmlpage):
yield request
def _requests_to_follow(self, htmlpage):
if self._links_ibl_extractor is not None:
extracted = self._links_ibl_extractor.extract(htmlpage)[0]
if extracted:
extracted_regions = extracted[0].get('_links', [])
seen = set()
for region in extracted_regions:
htmlregion = HtmlPage(htmlpage.url,
htmlpage.headers,
region,
encoding=htmlpage.encoding)
for request in self._request_to_follow_from_region(
htmlregion):
if request.url in seen:
continue
seen.add(request.url)
yield request
else:
for request in self._request_to_follow_from_region(htmlpage):
yield request
def _request_to_follow_from_region(self, htmlregion):
seen = set()
for link in self.html_link_extractor.links_to_follow(htmlregion):
request = self._filter_link(link, seen)
if request is not None:
yield request
def handle_rss(self, response, seen):
for link in self.rss_link_extractor.links_to_follow(response):
request = self._filter_link(link, seen)
if request:
yield request
def setup_bot(self, settings, spec, items, extractors, logger):
"""
Perform any initialization needed for crawling using this plugin
"""
self.logger = logger
templates = map(self._get_annotated_template, spec['templates'])
_item_template_pages = sorted((
[t.get('scrapes'), dict_to_page(t, 'annotated_body'),
t.get('extractors', []), t.get('version', '0.12.0')]
for t in templates if t.get('page_type', 'item') == 'item'
), key=lambda x: x[0])
self.item_classes = {}
self.template_scrapes = {template.get('page_id'): template['scrapes']
for template in templates}
if (settings.get('AUTO_PAGINATION') or
spec.get('links_to_follow') == 'auto'):
self.html_link_extractor = PaginationExtractor()
else:
self.html_link_extractor = HtmlLinkExtractor()
for schema_name, schema in items.items():
if schema_name not in self.item_classes:
if not schema.get('name'):
schema['name'] = schema_name
item_cls = SlybotItem.create_iblitem_class(schema)
self.item_classes[schema_name] = item_cls
# Create descriptors and apply additional extractors to fields
page_descriptor_pairs = []
self.schema_descriptors = {}
for default, template, template_extractors, v in _item_template_pages:
descriptors = OrderedDict()
for schema_name, schema in items.items():
item_descriptor = create_slybot_item_descriptor(schema,
schema_name)
apply_extractors(item_descriptor, template_extractors,
extractors)
descriptors[schema_name] = item_descriptor
descriptor = descriptors.values() or [{}]
descriptors['#default'] = descriptors.get(default, descriptor[0])
self.schema_descriptors[template.page_id] = descriptors['#default']
page_descriptor_pairs.append((template, descriptors, v))
add_extractors_to_descriptors(descriptors, extractors)
grouped = itertools.groupby(sorted(page_descriptor_pairs,
key=operator.itemgetter(2)),
lambda x: x[2] < '0.13.0')
self.extractors = []
for version, group in grouped:
if version:
self.extractors.append(
InstanceBasedLearningExtractor(
[(page, scrapes['#default'])
for page, scrapes, version in group]))
else:
self.extractors.append(SlybotIBLExtractor(list(group)))
# generate ibl extractor for links pages
_links_pages = [dict_to_page(t, 'annotated_body')
for t in templates if t.get('page_type') == 'links']
_links_item_descriptor = create_slybot_item_descriptor({'fields': {}})
self._links_ibl_extractor = InstanceBasedLearningExtractor(
[(t, _links_item_descriptor) for t in _links_pages]) \
if _links_pages else None
self.build_url_filter(spec)
# Clustering
self.template_names = [t.get('page_id') for t in spec['templates']]
if settings.get('PAGE_CLUSTERING'):
try:
import page_clustering
self.clustering = page_clustering.kmeans_from_samples(spec['templates'])
self.logger.info("Clustering activated")
except ImportError:
self.clustering = None
self.logger.warning(
"Clustering could not be used because it is not installed")
else:
self.clustering = None
def setup_bot(self, settings, spec, items, extractors):
"""
Perform any initialization needed for crawling using this plugin
"""
_item_template_pages = sorted(([
t.get('scrapes'),
dict_to_page(t, 'annotated_body'),
t.get('extractors', []),
t.get('version', '0.12.0')
] for t in spec['templates'] if t.get('page_type', 'item') == 'item'),
key=lambda x: x[0])
self.item_classes = {}
self.template_scrapes = {
template.get('page_id'): template['scrapes']
for template in spec.get('templates')
}
self.html_link_extractor = HtmlLinkExtractor()
for schema_name, schema in items.items():
if schema_name not in self.item_classes:
if not schema.get('name'):
schema['name'] = schema_name
item_cls = SlybotItem.create_iblitem_class(schema)
self.item_classes[schema_name] = item_cls
# Create descriptors and apply additional extractors to fields
page_descriptor_pairs = []
self.schema_descriptors = {}
for default, template, template_extractors, v in _item_template_pages:
descriptors = OrderedDict()
for schema_name, schema in items.items():
item_descriptor = create_slybot_item_descriptor(
schema, schema_name)
apply_extractors(item_descriptor, template_extractors,
extractors)
descriptors[schema_name] = item_descriptor
descriptor = descriptors.values() or [{}]
descriptors['#default'] = descriptors.get(default, descriptor[0])
self.schema_descriptors[template.page_id] = descriptors['#default']
page_descriptor_pairs.append((template, descriptors, v))
add_extractors_to_descriptors(descriptors, extractors)
grouped = itertools.groupby(
sorted(page_descriptor_pairs, key=operator.itemgetter(2)),
lambda x: x[2] < '0.13.0')
self.extractors = []
for version, group in grouped:
if version:
self.extractors.append(
InstanceBasedLearningExtractor([
(page, scrapes['#default'])
for page, scrapes, version in group
]))
else:
self.extractors.append(SlybotIBLExtractor(list(group)))
# generate ibl extractor for links pages
_links_pages = [
dict_to_page(t, 'annotated_body') for t in spec['templates']
if t.get('page_type') == 'links'
]
_links_item_descriptor = create_slybot_item_descriptor({'fields': {}})
self._links_ibl_extractor = InstanceBasedLearningExtractor(
[(t, _links_item_descriptor) for t in _links_pages]) \
if _links_pages else None
self.build_url_filter(spec)
class Annotations(object):
"""
Base Class for adding plugins to Portia Web and Slybot.
"""
def setup_bot(self, settings, spec, items, extractors):
"""
Perform any initialization needed for crawling using this plugin
"""
_item_template_pages = sorted(
(
[t["scrapes"], dict_to_page(t, "annotated_body"), t.get("extractors", [])]
for t in spec["templates"]
if t.get("page_type", "item") == "item"
),
key=lambda pair: pair[0],
)
self.itemcls_info = {}
self.html_link_extractor = HtmlLinkExtractor()
self.rss_link_extractor = RssLinkExtractor()
for itemclass_name, triplets in groupby(_item_template_pages, itemgetter(0)):
page_extractors_pairs = map(itemgetter(1, 2), triplets)
schema = items[itemclass_name]
item_cls = SlybotItem.create_iblitem_class(schema)
page_descriptor_pairs = []
for page, template_extractors in page_extractors_pairs:
item_descriptor = create_slybot_item_descriptor(schema)
apply_extractors(item_descriptor, template_extractors, extractors)
page_descriptor_pairs.append((page, item_descriptor))
extractor = InstanceBasedLearningExtractor(page_descriptor_pairs)
self.itemcls_info[itemclass_name] = {
"class": item_cls,
"descriptor": item_descriptor,
"extractor": extractor,
}
# generate ibl extractor for links pages
_links_pages = [dict_to_page(t, "annotated_body") for t in spec["templates"] if t.get("page_type") == "links"]
_links_item_descriptor = create_slybot_item_descriptor({"fields": {}})
self._links_ibl_extractor = (
InstanceBasedLearningExtractor([(t, _links_item_descriptor) for t in _links_pages])
if _links_pages
else None
)
self.build_url_filter(spec)
def handle_html(self, response):
htmlpage = htmlpage_from_response(response)
items, link_regions = self.extract_items(htmlpage)
for item in items:
yield item
for request in self._process_link_regions(htmlpage, link_regions):
yield request
def extract_items(self, htmlpage):
"""This method is also called from UI webservice to extract items"""
items = []
link_regions = []
for item_cls_name, info in self.itemcls_info.iteritems():
item_descriptor = info["descriptor"]
extractor = info["extractor"]
extracted, _link_regions = self._do_extract_items_from(htmlpage, item_descriptor, extractor, item_cls_name)
items.extend(extracted)
link_regions.extend(_link_regions)
return items, link_regions
def _do_extract_items_from(self, htmlpage, item_descriptor, extractor, item_cls_name):
extracted_data, template = extractor.extract(htmlpage)
link_regions = []
for ddict in extracted_data or []:
link_regions.extend(ddict.pop("_links", []))
processed_data = _process_extracted_data(extracted_data, item_descriptor, htmlpage)
items = []
item_cls = self.itemcls_info[item_cls_name]["class"]
for processed_attributes in processed_data:
item = item_cls(processed_attributes)
item["url"] = htmlpage.url
item["_type"] = item_cls_name
item["_template"] = str(template.id)
items.append(item)
return items, link_regions
def build_url_filter(self, spec):
"""make a filter for links"""
respect_nofollow = spec.get("respect_nofollow", True)
patterns = spec.get("follow_patterns")
if spec.get("links_to_follow") == "none":
url_filterf = lambda x: False
elif patterns:
pattern = patterns[0] if len(patterns) == 1 else "(?:%s)" % "|".join(patterns)
follow_pattern = re.compile(pattern)
if respect_nofollow:
url_filterf = lambda x: follow_pattern.search(x.url) and not x.nofollow
else:
url_filterf = lambda x: follow_pattern.search(x.url)
elif respect_nofollow:
url_filterf = lambda x: not x.nofollow
else:
url_filterf = bool
# apply exclude patterns
excludes = spec.get("exclude_patterns")
if excludes:
pattern = excludes[0] if len(excludes) == 1 else "(?:%s)" % "|".join(excludes)
exclude_pattern = re.compile(pattern)
self.url_filterf = lambda x: not exclude_pattern.search(x.url) and url_filterf(x)
else:
self.url_filterf = url_filterf
def _filter_link(self, link, seen):
url = link.url
if self.url_filterf(link):
# filter out duplicate urls, later we should handle link text
if url not in seen:
seen.add(url)
request = Request(url)
if link.text:
request.meta["link_text"] = link.text
return request
def _process_link_regions(self, htmlpage, link_regions):
"""Process link regions if any, and generate requests"""
if link_regions:
for link_region in link_regions:
htmlregion = HtmlPage(htmlpage.url, htmlpage.headers, link_region, encoding=htmlpage.encoding)
for request in self._requests_to_follow(htmlregion):
yield request
else:
for request in self._requests_to_follow(htmlpage):
yield request
def _requests_to_follow(self, htmlpage):
if self._links_ibl_extractor is not None:
extracted = self._links_ibl_extractor.extract(htmlpage)[0]
if extracted:
extracted_regions = extracted[0].get("_links", [])
seen = set()
for region in extracted_regions:
htmlregion = HtmlPage(htmlpage.url, htmlpage.headers, region, encoding=htmlpage.encoding)
for request in self._request_to_follow_from_region(htmlregion):
if request.url in seen:
continue
seen.add(request.url)
yield request
else:
for request in self._request_to_follow_from_region(htmlpage):
yield request
def _request_to_follow_from_region(self, htmlregion):
seen = set()
for link in self.html_link_extractor.links_to_follow(htmlregion):
request = self._filter_link(link, seen)
if request is not None:
yield request
def handle_rss(self, response, seen):
for link in self.rss_link_extractor.links_to_follow(response):
request = self._filter_link(link, seen)
if request:
yield request