class CardPipeline(object):
def __init__(self):
self.files = {}
def process_item(self, item, spider):
if not item['wb_nick']\
or not item['wb_location']\
or not item['wb_images']:
raise DropItem
print item['wb_nick'][0]
item['wb_content'] = ''.join(item['wb_content'])
item['wb_date'] = item['wb_date'][0]
item['wb_location'] = item['wb_location'][0]
images_urls = item.pop('wb_images')
item['wb_images'] = []
for image_url in images_urls:
image_url = image_url.replace('thumbnail', 'large')
image_url = image_url.replace('square', 'large')
item['wb_images'].append(image_url)
self.exporter.export_item(item)
return item
def open_spider(self, spider):
file = open('json/{}_products.json'.format(spider.name), 'w+b')
self.files[spider] = file
self.exporter = JsonLinesItemExporter(file)
self.exporter.start_exporting()
def close_spider(self, spider):
self.exporter.finish_exporting()
file = self.files.pop(spider)
file.close()
class JsonExportPipeline(object):
def __init__(self):
self.files = {}
@classmethod
def from_crawler(cls, crawler):
pipeline = cls()
crawler.signals.connect(pipeline.spider_opened, signals.spider_opened)
crawler.signals.connect(pipeline.spider_closed, signals.spider_closed)
return pipeline
def spider_opened(self, spider):
file = open('%s_all.json' % spider.name, 'w+b')
self.files[spider] = file
self.exporter = JsonLinesItemExporter(file, encoding='utf-8', ensure_ascii=False)
self.exporter.start_exporting()
def spider_closed(self, spider):
self.exporter.finish_exporting()
file = self.files.pop(spider)
file.close()
def process_item(self, item, spider):
self.exporter.export_item(item)
return item
class KinoPipeline(object):
def __init__(self):
self.files = {}
@classmethod
def from_crawler(cls, crawler):
pipeline = cls()
crawler.signals.connect(pipeline.spider_opened, signals.spider_opened)
crawler.signals.connect(pipeline.spider_closed, signals.spider_closed)
return pipeline
def spider_opened(self, spider):
# It might be possible to add indent=4 and ensure_ascii=False somewhere.
file = open('output/' + spider.name + '.jsonl', 'w+b', encoding='utf-8')
self.files[spider] = file
self.exporter = JsonLinesItemExporter(file)
self.exporter.start_exporting()
def spider_closed(self, spider):
self.exporter.finish_exporting()
file = self.files.pop(spider)
file.close()
def process_item(self, item, spider):
self.exporter.export_item(item)
return item
class MedPipeline(object):
def __init__(self):
self.ids_seen = set()
@classmethod
def from_crawler(cls, crawler):
pipeline = cls()
crawler.signals.connect(pipeline.spider_opened, signals.spider_opened)
crawler.signals.connect(pipeline.spider_closed, signals.spider_closed)
return pipeline
def spider_opened(self, spider):
self.file = open('medData.json', 'wb')
self.expoter = JsonLinesItemExporter(self.file)
self.expoter.start_exporting()
def spider_closed(self, spider):
self.expoter.finish_exporting()
self.file.close()
def process_item(self, item, spider):
if int(item['reply_num'][0]) == 0:
raise DropItem("no reply in %s" % item)
elif item['post_id'] in self.ids_seen:
raise DropItem("Duplicate item found: %s" % item)
else:
self.ids_seen.add(item['post_id'])
self.expoter.export_item(item)
return item
class QiushiPipeline(object):
def __init__(self):
self.files = {}
@classmethod
def from_crawler(cls, crawler):
pipeline = cls()
crawler.signals.connect(pipeline.spider_opened, signals.spider_opened)
crawler.signals.connect(pipeline.spider_closed, signals.spider_closed)
return pipeline
def spider_opened(self, spider):
# The file created on Dec20 2015 will be named as "12-20-2015.json"
datestr = date.today().strftime("%m-%d-%Y")
file = open('scraped_data/%s.json' % datestr, 'w+b')
self.files[spider] = file
self.exporter = JsonLinesItemExporter(file, ensure_ascii=False)
self.exporter.start_exporting()
def spider_closed(self, spider):
self.exporter.finish_exporting()
file = self.files.pop(spider)
file.close()
def process_item(self, item, spider):
self.exporter.export_item(item)
# print item['author']
# print item['title']
# print item['content']
# print item['href']
return item
class JsonLinesExportPipeline(object):
"""
app.pipelines.exporter_json_lines.JsonLinesExportPipeline
"""
def __init__(self):
self.files = {}
self.exporter = None
@classmethod
def from_crawler(cls, crawler):
pipeline = cls()
crawler.signals.connect(pipeline.spider_opened, signals.spider_opened)
crawler.signals.connect(pipeline.spider_closed, signals.spider_closed)
return pipeline
def spider_opened(self, spider):
file_json_lines = open('%s_item_lines.json' % spider.name, 'w+b')
self.files[spider] = file_json_lines
self.exporter = JsonLinesItemExporter(file_json_lines)
self.exporter.start_exporting()
def spider_closed(self, spider):
self.exporter.finish_exporting()
file_json_lines = self.files.pop(spider)
file_json_lines.close()
def process_item(self, item, spider):
self.exporter.export_item(item)
return item
def load_table(table, source = "default/test-0.jsonlines",\
modifier = "" , dblogin = "******" , \
as_name = None ):
filename = source if as_name is None else as_name
dbname, collectioname = parse_path(filename , modifier)
connection = pymongo.MongoClient( dblogin )
db = getattr(connection, dbname)
collection = getattr( db , collectioname )
try:
result = collection.insert_many((set_id(obj) for obj in odicts(table)),ordered=False)
except BulkWriteError as e:
result = e.details
errs = set()
with open( "%s.%s" % (filename,"errors") , "a") as f:
exporter = JsonLinesItemExporter(f)
exporter.start_exporting()
for err in result.get("writeErrors"):
if not err.get("op").get("_id") in errs:
obj = dict( item = err.get("op") , \
error = err.get("errmsg") )
errs.add( err.get("op").get("_id") )
exporter.export_item(obj)
exporter.finish_exporting()
f.close()
return result
def export_item(self, item):
storage_file = open(self.item_storage_path(item["id"]), "w")
item_exporter = JsonLinesItemExporter(storage_file)
item_exporter.start_exporting()
item_exporter.export_item(item)
item_exporter.finish_exporting()
storage_file.close()
class EduSpider(scrapy.Spider):
""" Used to scrape .edu websites for web technology statistics """
name = 'edu'
def __init__(self):
scrapy.Spider.__init__(self)
baseurl = 'https://domaintyper.com/top-websites/most-popular-websites-with-edu-domain/page/'
logpath = '/home/www/flasksite/static/scenes/unipagestats/schools.jl'
self.start_urls = [baseurl + str(i) for i in xrange(1, 30)]
self.domain = 'domaintyper.com'
self.exporter = JsonLinesItemExporter(open(logpath, 'wb+'))
def parse(self, response):
self.exporter.start_exporting()
urls = [url.encode('utf-8') for url in response.css('.wsTR > td:nth-child(2)').xpath('text()').extract()]
for url in urls:
fullurl = 'http://www.' + url + '/'
yield scrapy.Request(fullurl, callback=self.parse_edu_site)
def parse_edu_site(self, response):
data = SiteData()
tc = TagCounter()
# Fill summary fields
data['url'] = response.url
data['domain'] = '.'.join(response.url.split('/')[2].split('.')[-2:])
data['name'] = data['domain'].split('.')[0]
data['title'] = response.xpath('//title/text()').extract()[0].encode('utf-8')
# Fill CSS fields
data['css_paths'] = [stylesheet.encode('utf-8') for stylesheet in response.xpath('//link[@rel="stylesheet"]/@href').extract()]
data['css_files'] = [stylesheet.split('/')[-1] for stylesheet in data['css_paths']]
# Fill JS fields
data['js_paths'] = [script.encode('utf-8') for script in response.xpath('//script/@src').extract()]
data['js_files'] = [script.split('/')[-1] for script in data['js_paths']]
# Fill tag fields
tc.feed(response.body)
data['tagcount'] = tc.tagcount
data['nonvoidcount'] = tc.nonvoid_tagcount
data['topnest'] = tc.topnest
self.exporter.export_item(data)
yield data
def __del__(self):
scrapy.Spider.__del__(self)
self.exporter.finish_exporting()
class OKCupidJsonPipeline(object):
def __init__(self):
dispatcher.connect(self.spider_opened, signals.spider_opened)
dispatcher.connect(self.spider_closed, signals.spider_closed)
self.files = {}
def spider_opened(self, spider):
file = open('%s_items.json' % spider.name, 'w+b')
self.files[spider] = file
self.exporter = JsonLinesItemExporter(file, ensure_ascii=True)
self.exporter.start_exporting()
def spider_closed(self, spider):
self.exporter.finish_exporting()
file = self.files.pop(spider)
file.close()
def process_item(self, item, spider):
#print item
#uItem = urllib.urlencode(item)
#jItem = dumps(uItem, cls=PythonObjectEncoder)
self.exporter.export_item(item)
return item
class JsonExportPipeline(object):
def __init__(self):
self.file_name = 'svet_androida_links_to_articles.json'
self.file_handle = None
def open_spider(self, spider):
print('JsonExportPipeline Exporter opened')
file = open(self.file_name, 'wb')
self.file_handle = file
self.exporter = JsonLinesItemExporter(file,
encoding='utf-8',
ensure_ascii=False)
self.exporter.start_exporting()
def close_spider(self, spider):
print('JsonExportPipeline Exporter closed')
self.exporter.finish_exporting()
self.file_handle.close()
def process_item(self, item, spider):
self.exporter.export_item(item)
return item
class HuabanPipeline(object):
def __init__(self):
'''Open file to save the exported Items'''
# save info of BoardItem
self.board_info = open(
'D:/litreily/Pictures/python/huaban/boards.json', 'w+b')
self.board_exporter = JsonItemExporter(self.board_info,
encoding='utf-8',
indent=4)
# save info of PinItem
self.pin_info = open('D:/litreily/Pictures/python/huaban/pins.json',
'w+b')
self.pin_exporter = JsonLinesItemExporter(self.pin_info,
encoding='utf-8',
indent=4)
def open_spider(self, spider):
'''Start exporting BoardItem'''
self.board_exporter.start_exporting()
self.pin_exporter.start_exporting()
def process_item(self, item, spider):
if isinstance(item, BoardItem):
self.board_exporter.export_item(item)
elif isinstance(item, PinItem):
self.pin_exporter.export_item(item)
return item
def close_spider(self, spider):
'''finish exporting and close files'''
self.board_exporter.finish_exporting()
self.pin_exporter.finish_exporting()
self.board_info.close()
self.pin_info.close()
class EquationscraperPipeline(object):
def __init__(self):
self.jsl_exporter = None
self.pprnt_exporter = None
self.files = {}
authenticate('localhost:7474', 'neo4j', 'big-theta-team')
self.graph = Graph('localhost:7474/db/data')
@classmethod
def from_crawler(cls, crawler):
pipeline = cls()
crawler.signals.connect(pipeline.spider_opened, signals.spider_opened)
crawler.signals.connect(pipeline.spider_closed, signals.spider_closed)
return pipeline
def spider_opened(self, spider):
file_pprnt = open(
'%s_pprint-items0' % spider.name,
'w+b',
)
file_jsl = open(
'%s_json-items0' % spider.name,
'w+b',
)
self.jsl_exporter = JsonLinesItemExporter(file_jsl)
self.pprnt_exporter = PprintItemExporter(file_pprnt)
self.files[spider] = [file_pprnt, file_jsl]
self.pprnt_exporter.indent = 2
self.pprnt_exporter.start_exporting()
self.jsl_exporter.start_exporting()
def spider_closed(self, spider):
self.pprnt_exporter.finish_exporting()
self.jsl_exporter.finish_exporting()
for f in self.files[spider]:
f.close()
def process_item(self, item, spider):
if spider.settings.getbool("EXPORT_JSON"):
self.pprnt_exporter.export_item(item)
self.jsl_exporter.export_item(item)
node_equation_label = 'EQUATION'
node_subject_label = 'SUBJECT'
link_relation = 'LINKS_TO'
page_relation = 'SAME_PAGE_AS'
item_array = [item['last_item'].copy(), item.copy()]
subject_nodes_array = []
for idx, elem in enumerate(item_array):
subject_nodes_array.append(
Node(node_subject_label,
title=item_array[idx]['title'],
url=item_array[idx]['url'],
categories=item_array[idx]['categories']))
for expression in elem['maths']:
expression = latexutils.strip_styles(expression)
if latexutils.contains_equality_command(expression):
latex_equation_node = Node(node_equation_label,
name='Equation<' +
item_array[idx]['title'] + '>',
equation=expression)
self.graph.merge(
Relationship(subject_nodes_array[idx],
page_relation,
latex_equation_node,
distance=0))
self.graph.merge(
Relationship(subject_nodes_array[0],
link_relation,
subject_nodes_array[1],
distance=item_array[1]['link_dist']))
del item
raise exceptions.DropItem
class ResolutionPipeline(object):
"""Pipeline used for ResolutionSpider."""
def __init__(self):
self.file = None
self.exporter = None
# compile regular expressions:
# input looks like 'dec14R.aspx'
# we need the resolution number (14R)
self.resolution_number_pattern = re.compile(r"^\D+(?P<number>.+?)\..*$")
# input looks like 'ממשלה/הממשלה ה - 34 בנימין נתניהו;'
# we need the government number (34) and prime minister name (בנימין נתניהו)
self.gov_pattern = re.compile(r'^.+\s??\-\s?(?P<gov_number>.+?)\s+?(?P<pm_name>.+?);?$')
def open_spider(self, spider):
"""Initialize export JSON lines file."""
self.file = open("gov.json", "wb")
self.exporter = JsonLinesItemExporter(self.file, ensure_ascii=False)
self.exporter.start_exporting()
def close_spider(self, spider):
"""Close export file."""
self.file.close()
self.exporter.finish_exporting()
def process_item(self, item, spider):
"""Sanitize text for each field, and export to file."""
try:
data = {
'url': item["url"],
'date': self.get_date(item).timestamp,
'resolution_number': self.get_resolution_number(item),
'gov_number': self.get_gov_number(item),
'pm_name': self.get_pm_name(item),
'title': self.get_title(item),
'subject': self.get_subject(item),
'body': self.get_body(item),
}
except ResolutionError as ex:
# if one of the fields fails sanitation,
# raise and exception
# and export the url leading to the specific resolution
# for later (human) review
self.exporter.export_item({'error': repr(ex),
'url': item["url"],
})
else:
self.exporter.export_item(data)
return item
# the following are specific field handling functions
# e.g. cleaning, stripping, etc.
# these should be called before dumping the data
def get_date(self, item):
if len(item["date"]) != 1:
raise ResolutionError("Date field length is not 1 for item %s", item)
return arrow.get(item["date"][0], "YYYYMMDD")
def get_resolution_number(self, item):
if len(item["resolution_number"]) != 1:
raise ResolutionError("Resolution number field length is not 1 for item %s", item)
return self.resolution_number_pattern.search(item["resolution_number"][0]).group('number')
def get_gov_number(self, item):
if len(item["gov"]) != 1:
raise ResolutionError("Government field length is not 1 for item %s", item)
gov_match = self.gov_pattern.search(item["gov"][0])
return gov_match.group("gov_number")
def get_pm_name(self, item):
if len(item["gov"]) != 1:
raise ResolutionError("Government field length is not 1 for item %s", item)
gov_match = self.gov_pattern.search(item["gov"][0])
return gov_match.group("pm_name")
def get_title(self, item):
if len(item["title"]) == 0:
raise ResolutionError("Title fields is empty for item %s", item)
return '\n'.join(item["title"]).strip()
def get_subject(self, item):
if len(item["subject"]) == 0:
raise ResolutionError("Subject field is empty for item %s", item)
return '\n'.join(item["subject"]).strip()
def get_body(self, item):
if len(item["body"]) == 0:
raise ResolutionError("Body field is empty for item %s", item)
# return '\n'.join(item["body"]).strip()
# body is originally a list of lines
# it is intentionally not stripped
# some resolutions have custom css, tables,
# and other crap which i'd rather not process here,
# but in a later stage, unrelated to the scraper
return item["body"]
class JsonExportPipeline(object):
def __init__(self):
self.files = {}
self.room_count = 0
self.user_count = 0
self.room_file_count = 0
self.user_file_count = 0
self.exporter_room = None
self.exporter_user = None
@classmethod
def from_crawler(cls, crawler):
pipeline = cls()
crawler.signals.connect(pipeline.spider_opened, signals.spider_opened)
crawler.signals.connect(pipeline.spider_closed, signals.spider_closed)
return pipeline
def spider_opened(self, spider, mode=0):
if mode == 1 or mode == 0:
room_file = open(
'Airbnb_room_{}.json'.format(self.room_file_count), 'w+b')
self.files['room'] = room_file
self.exporter_room = JsonLinesItemExporter(room_file)
self.exporter_room.start_exporting()
if mode == 2 or mode == 0:
user_file = open(
'Airbnb_user_{}.json'.format(self.user_file_count), 'w+b')
self.files['user'] = user_file
self.exporter_user = JsonLinesItemExporter(user_file)
self.exporter_user.start_exporting()
def spider_closed(self, spider, mode=0):
if mode == 1 or mode == 0:
self.exporter_room.finish_exporting()
file = self.files['room']
file.close()
if mode == 2 or mode == 0:
self.exporter_user.finish_exporting()
file = self.files['user']
file.close()
def process_item(self, item, spider):
if isinstance(item, AirbnbItem):
self.room_count += 1
if self.room_count > 100000:
self.room_count = 0
self.room_file_count += 1
self.spider_closed(spider, mode=1)
self.spider_opened(spider, mode=1)
self.exporter_room.export_item(item)
elif isinstance(item, UserItem):
self.user_count += 1
if self.user_count > 100000:
self.user_count = 0
self.user_file_count += 1
self.spider_closed(spider, mode=2)
self.spider_opened(spider, mode=2)
self.exporter_user.export_item(item)
else:
logger.info('Some error happened!')
class KjvPipeline(FileExporter):
def __init__(self):
self.files = {}
@classmethod
def from_crawler(cls, crawler):
pipeline = cls()
crawler.signals.connect(pipeline.spider_opened, signals.spider_opened)
crawler.signals.connect(pipeline.spider_closed, signals.spider_closed)
return pipeline
def spider_opened(self, spider):
pass
def spider_closed(self, spider):
pass
def process_item(self, item, spider):
DATA_STORE = spider.settings.get('DATA_STORE')
if item and \
'book' in item.keys() and \
'text' in item.keys() and \
'mp3' in item.keys() and \
'url' in item.keys():
book_name = get_book_name(item)
ensure_dir(os.path.join(DATA_STORE, book_name))
filename = os.path.join(DATA_STORE, book_name,
get_filename(item, 'txt'))
if not os.path.exists(filename):
chapter_file = open(filename, 'w')
self.files[spider] = chapter_file
self.exporter = FileExporter(chapter_file)
self.exporter.start_exporting()
self.exporter.export_item("\n".join(item['text']))
self.exporter.finish_exporting()
chapter_file = self.files.pop(spider)
chapter_file.close()
if item and \
'name' in item.keys() and \
'urls' in item.keys():
found_in_bible_file = False
CONTENT_FILE = os.path.join(DATA_STORE,
spider.settings.get('CONTENT_FILE'))
if os.path.exists(CONTENT_FILE):
with open(CONTENT_FILE, 'r') as bible:
for books in bible:
if item['name'] in books:
found_in_bible_file = True
break
else:
ensure_dir('%s' % DATA_STORE)
if not found_in_bible_file:
bible_file = open(CONTENT_FILE, 'a+')
self.files[spider] = bible_file
self.exporter = JsonLinesItemExporter(bible_file)
self.exporter.start_exporting()
self.exporter.export_item(item)
self.exporter.finish_exporting()
chapter_file = self.files.pop(spider)
chapter_file.close()
return item
class EduSpider(scrapy.Spider):
""" Used to scrape .edu websites for web technology statistics """
name = 'edu'
def __init__(self):
scrapy.Spider.__init__(self)
baseurl = 'https://domaintyper.com/top-websites/most-popular-websites-with-edu-domain/page/'
logpath = '/home/www/flasksite/static/scenes/unipagestats/schools.jl'
self.start_urls = [baseurl + str(i) for i in xrange(1, 30)]
self.domain = 'domaintyper.com'
self.exporter = JsonLinesItemExporter(open(logpath, 'wb+'))
def parse(self, response):
self.exporter.start_exporting()
urls = [
url.encode('utf-8') for url in response.css(
'.wsTR > td:nth-child(2)').xpath('text()').extract()
]
for url in urls:
fullurl = 'http://www.' + url + '/'
yield scrapy.Request(fullurl, callback=self.parse_edu_site)
def parse_edu_site(self, response):
data = SiteData()
tc = TagCounter()
# Fill summary fields
data['url'] = response.url
data['domain'] = '.'.join(response.url.split('/')[2].split('.')[-2:])
data['name'] = data['domain'].split('.')[0]
data['title'] = response.xpath('//title/text()').extract()[0].encode(
'utf-8')
# Fill CSS fields
data['css_paths'] = [
stylesheet.encode('utf-8') for stylesheet in response.xpath(
'//link[@rel="stylesheet"]/@href').extract()
]
data['css_files'] = [
stylesheet.split('/')[-1] for stylesheet in data['css_paths']
]
# Fill JS fields
data['js_paths'] = [
script.encode('utf-8')
for script in response.xpath('//script/@src').extract()
]
data['js_files'] = [
script.split('/')[-1] for script in data['js_paths']
]
# Fill tag fields
tc.feed(response.body)
data['tagcount'] = tc.tagcount
data['nonvoidcount'] = tc.nonvoid_tagcount
data['topnest'] = tc.topnest
self.exporter.export_item(data)
yield data
def __del__(self):
scrapy.Spider.__del__(self)
self.exporter.finish_exporting()
def process_item(self, item, spider):
if not isinstance(item, GraphImage):
return item
try:
ret = self.coll.update({"_id": item["_id"]}, {
"$setOnInsert": {
"_id": item["_id"],
"instagram_id": item["instagram_id"],
"owner_id": item["owner_id"],
"thumbnail_src": item["thumbnail_src"],
"thumbnail_resources": item["thumbnail_resources"],
"typename": item.get("typename"),
"is_video": item["is_video"],
"date": item["date"],
"display_src": item["display_src"],
"caption": item["caption"],
"download_urls": item["download_urls"],
"downloaded_img_info": item.get("downloaded_img_info"),
"status": 1,
"scraped_ts": int(time.time()),
},
"$set": {
"update_ts": int(time.time())
},
"$addToSet": {
"hashtags": {
"$each": item.get('hashtags', [])
}
}
},
upsert=True)
if item["date"] > self.latest_downloaded_ts:
self.latest_downloaded_ts = item["date"]
if item["date"] < self.earliest_downloaded_ts:
self.earliest_downloaded_ts = item["date"]
if ret['updatedExisting']:
logger.info('Updated graph images: %s', item["_id"])
self.existed += 1
else:
filename = '{}.jl'.format(item["_id"])
filename = os.path.join(self.export_filepath, filename)
export_file = open(filename, 'wb')
exportor = JsonLinesItemExporter(export_file)
exportor.start_exporting()
exportor.export_item(item)
exportor.finish_exporting()
logger.info('dumped item to file: %s', ret['upserted'])
logger.info('Inserted graph images: %s', ret['upserted'])
self.task.send_task('fetch_image', (item['_id'], ))
logger.info('Send task fetch_image: %s', item['_id'])
self.inserted += 1
except RedisError:
logger.error('Send task Failed. Network unreachable')
raise DropItem('Send fetch_image task FAILED. DROP ITEM %s' %
item["_id"])
except:
logger.error('DB FAILED: %s', traceback.format_exc())
raise DropItem('Save graph image to db FAILED. DROP ITEM %s' %
item["_id"])
else:
return item
class ResolutionPipeline(object):
"""Pipeline used for ResolutionSpider."""
def __init__(self):
self.file = None
self.exporter = None
# compile regular expressions:
# input looks like 'dec14R.aspx'
# we need the resolution number (14R)
self.resolution_number_pattern = re.compile(
r"^\D+(?P<number>.+?)\..*$")
# input looks like 'ממשלה/הממשלה ה - 34 בנימין נתניהו;'
# we need the government number (34) and prime minister name (בנימין נתניהו)
self.gov_pattern = re.compile(
r'^.+\s??\-\s?(?P<gov_number>.+?)\s+?(?P<pm_name>.+?);?$')
def open_spider(self, spider):
"""Initialize export JSON lines file."""
self.file = open("gov.json", "wb")
self.exporter = JsonLinesItemExporter(self.file, ensure_ascii=False)
self.exporter.start_exporting()
def close_spider(self, spider):
"""Close export file."""
self.file.close()
self.exporter.finish_exporting()
def process_item(self, item, spider):
"""Sanitize text for each field, and export to file."""
try:
data = {
'url': item["url"],
'date': self.get_date(item).timestamp,
'resolution_number': self.get_resolution_number(item),
'gov_number': self.get_gov_number(item),
'pm_name': self.get_pm_name(item),
'title': self.get_title(item),
'subject': self.get_subject(item),
'body': self.get_body(item),
}
except ResolutionError as ex:
# if one of the fields fails sanitation,
# raise and exception
# and export the url leading to the specific resolution
# for later (human) review
self.exporter.export_item({
'error': repr(ex),
'url': item["url"],
})
else:
self.exporter.export_item(data)
return item
# the following are specific field handling functions
# e.g. cleaning, stripping, etc.
# these should be called before dumping the data
def get_date(self, item):
if len(item["date"]) != 1:
raise ResolutionError("Date field length is not 1 for item %s",
item)
return arrow.get(item["date"][0], "YYYYMMDD")
def get_resolution_number(self, item):
if len(item["resolution_number"]) != 1:
raise ResolutionError(
"Resolution number field length is not 1 for item %s", item)
return self.resolution_number_pattern.search(
item["resolution_number"][0]).group('number')
def get_gov_number(self, item):
if len(item["gov"]) != 1:
raise ResolutionError(
"Government field length is not 1 for item %s", item)
gov_match = self.gov_pattern.search(item["gov"][0])
return gov_match.group("gov_number")
def get_pm_name(self, item):
if len(item["gov"]) != 1:
raise ResolutionError(
"Government field length is not 1 for item %s", item)
gov_match = self.gov_pattern.search(item["gov"][0])
return gov_match.group("pm_name")
def get_title(self, item):
if len(item["title"]) == 0:
raise ResolutionError("Title fields is empty for item %s", item)
return '\n'.join(item["title"]).strip()
def get_subject(self, item):
if len(item["subject"]) == 0:
raise ResolutionError("Subject field is empty for item %s", item)
return '\n'.join(item["subject"]).strip()
def get_body(self, item):
if len(item["body"]) == 0:
raise ResolutionError("Body field is empty for item %s", item)
# return '\n'.join(item["body"]).strip()
# body is originally a list of lines
# it is intentionally not stripped
# some resolutions have custom css, tables,
# and other crap which i'd rather not process here,
# but in a later stage, unrelated to the scraper
return item["body"]
class S3RawStorage(object):
"""Store items as JSON lines on S3.
Currently almost equivalent to the default scrapy built-in S3 exporter.
It just brings full control over the process and start leveraging it with
custom Scrapy metrics. It helps us distinguish items scraped and data
actually stored.
"""
STATS_TPL = 'pipeline/storage/{metric}'
def __init__(self, stats):
self.stats = stats
@staticmethod
def _validate_settings(settings):
"""Disable pipeline if criteria are not met."""
feed_uri_tpl = settings.get('KP_RAW_FEED_URI')
if not feed_uri_tpl:
raise NotConfigured('no feed uri defined')
builtin_feed_uri_tpl = settings.get('FEED_URI')
if builtin_feed_uri_tpl:
raise NotConfigured('conflict: built-in Scrapy feed exporter is already configured')
@classmethod
def _namespace(cls, metric):
"""Namespace metrics to distinguish them in Scrapy stats.
Examples:
>>> S3RawStorage._namespace('foo')
'pipeline/storage/foo'
"""
return cls.STATS_TPL.format(metric=metric)
@classmethod
def from_crawler(cls, crawler):
cls._validate_settings(crawler.settings)
pipeline = cls(crawler.stats)
crawler.signals.connect(pipeline.spider_opened, signals.spider_opened)
crawler.signals.connect(pipeline.spider_closed, signals.spider_closed)
return pipeline
@staticmethod
def feed_uri(spider):
"""Generate item storage URI.
Args:
spider (scrapy.Spider):
Returns:
str: S3 object key to which data should be uploaded to
"""
# use spider finish_time as default, else UTC time
_spider_finish = spider.crawler.stats._stats.get('finish_time')
if _spider_finish:
_time = _spider_finish - dt.timedelta(hours=system_tz_offset())
else:
_time = dt.datetime.utcnow()
uri_opts = {
'name': spider.name,
'time': _time.isoformat(),
'job_id': spider.job_id,
'bucket': ITEMS_BUCKET,
# use the same semantic as on the ETL
# default env is a safe playground where we can dump whatever items
# we want without taking the risk of polluting production
# environments
# con: actual production env MUST specify this setting
# pro: new environment will have by default somewhere to upload
# items, withput displaying an error because an env-dependant
# bucket was not created.
#
# we allow fallback on the env since alternative runtimes like EC2 dont
# benefit from scrapinghub settings interface.
'env': spider.settings.get('KP_ENV', os.getenv('KP_ENV', 'pre-production')),
}
return spider.settings.get('KP_RAW_FEED_URI') % uri_opts
def spider_opened(self, spider):
self.stats.set_value(self._namespace('backend'), 'rawS3')
# spider finish time only available when `spider_closed`
# uri used here only as a filler to fulfil feed storage contract
self.storage = S3FeedStorage(
uri=f's3://{ITEMS_BUCKET}',
access_key=spider.settings['AWS_ACCESS_KEY_ID'],
secret_key=spider.settings['AWS_SECRET_ACCESS_KEY'],
)
self.raw_content = self.storage.open(spider)
self.exporter = JsonLinesItemExporter(self.raw_content)
self.exporter.start_exporting()
def spider_closed(self, spider):
# push items to json lines feed
self.exporter.finish_exporting()
# update object key to use job finish time
uri = urlparse(self.feed_uri(spider))
self.storage.keyname = uri.path[1:] # remove first "/"
logger.debug(f"Data will be uploaded to `{self.storage.keyname}`")
# push items to S3
self.raw_content.file.seek(0)
if len(self.raw_content.file.read()) != 0:
self.storage.store(self.raw_content)
else:
logger.info("No items are scrapped, not pushing to s3")
def process_item(self, item, spider):
self.stats.inc_value(self._namespace('items_stored'))
self.exporter.export_item(item)
# running jobs on scrapinghub will still store them
# in their database. The point of this pipeline is
# obviously to stop relying on it but that way it
# remains a cheap fallback/backup
return item