zz
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@ -1,6 +1,8 @@
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import click
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import mongocrawler
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import rq
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import redis
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import sys
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import os
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REDIS_URL= os.getenv("REDIS_URL","redis://localhost:6379/")
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@ -154,21 +154,16 @@ def fetch_robot(base_url:str)->urllib.robotparser.RobotFileParser:
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# exceptions happening here
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return rules
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def extract_page(final_link,html):
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doc = None
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if html is not None:
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doc = trafilatura.bare_extraction(html,url=final_link,with_metadata=True,include_formatting=False,target_language=LANGUAGE,favor_precision=True)
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if doc is not None:
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if not "text" in doc or len(doc["text"]) < MINTEXTSIZE:
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# text too small
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doc = None
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return doc
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def extract_pages(link_batch:list,responses:list)->list:
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out = []
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for original_link,(final_link,html) in zip(link_batch,responses):
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doc = None
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assert original_link is not None
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if html is not None:
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doc = trafilatura.bare_extraction(html,url=final_link,with_metadata=True,include_formatting=False,target_language=LANGUAGE,favor_precision=True)
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if doc is not None:
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if not "text" in doc or len(doc["text"]) < MINTEXTSIZE:
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# text too small
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doc = None
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out.append((original_link,final_link,html,doc))
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return out
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def set_content_checksums(doc):
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text = doc["text"]
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@ -186,85 +181,82 @@ def set_content_checksums(doc):
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sentences += 1
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doc["sentences_count"] = sentences
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def index_pages(db,hostname,extracted_pages):
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def index_page(db,original_link,final_link,html,doc):
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linkcol = db["links"]
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htmlcol = db["html"]
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contentcol = db["content"]
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checkcol = db["check"]
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links = []
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# stats of the batch
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good_document_count = 0
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document_count = 0
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text_size = 0
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good_text_size = 0
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original_text_size = 0
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for original_link,final_link,html,doc in extracted_pages:
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document_count += 1
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state = "good"
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link = original_link
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if original_link != final_link:
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print(original_link,final_link)
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linkcol.update_one({"url":original_link},{"$set":{"status":"redirect"}})
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link = final_link
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if html is None:
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state = "html_error"
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elif doc is None:
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state = "content_error"
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if doc is not None:
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set_content_checksums(doc)
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tsz = doc["text_size"]
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text_size += tsz
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psz = doc["paragraph_sizes_sum"]
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if tsz < TEXT_TRASH_SIZE or psz/tsz < TEXT_TRASH_RATIO:
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state = "small"
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# check copy
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if state == "good":
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origsz = 0
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for chs,paragraph_size in zip(doc["paragraph_checksums"],doc["paragraph_sizes"]):
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# index paragraph checksums
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nd = checkcol.find_one({"_id":chs})
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if nd is None:
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origsz += paragraph_size
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state = "good"
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link = original_link
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if original_link != final_link:
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print(original_link,final_link)
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linkcol.update_one({"url":original_link},{"$set":{"status":"redirect"}})
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link = final_link
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if html is None:
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state = "html_error"
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elif doc is None:
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state = "content_error"
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if doc is not None:
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set_content_checksums(doc)
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tsz = doc["text_size"]
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psz = doc["paragraph_sizes_sum"]
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if tsz < TEXT_TRASH_SIZE or psz/tsz < TEXT_TRASH_RATIO:
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state = "small"
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# check copy
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if state == "good":
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origsz = 0
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for chs,paragraph_size in zip(doc["paragraph_checksums"],doc["paragraph_sizes"]):
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# index paragraph checksums
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nd = checkcol.find_one({"_id":chs})
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if nd is None:
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origsz += paragraph_size
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doc["original_text_size"] = origsz
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if (1 - (origsz / tsz)) > TEXT_TRASH_RATIO:
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state = "copy"
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original_text_size += origsz
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print(origsz)
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if (1 - (origsz / tsz)) > TEXT_TRASH_RATIO:
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state = "copy"
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print(origsz)
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if state == "good":
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htdoc = get_link_doc(link,state)
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htdoc["html"] = html
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htdoc["html_size"] = len(html)
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htdoc["html_md5"]= hashlib.md5(html.encode("utf8")).hexdigest()
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# can be revisited - upsert
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del htdoc["url"]
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htmlcol.update_one({"url":link},{"$set":htdoc},upsert=True)
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doc.update(get_link_doc(link,"good"))
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# todo extract links
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print(link,doc)
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del doc["url"]
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contentcol.update_one({"url":link},{"$set":doc},upsert=True)
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for chs in doc["paragraph_checksums"]:
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try:
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checkcol.insert_one({"_id":chs})
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except pymongo.errors.DuplicateKeyError as err:
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pass
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linkdoc = get_link_doc(link,state)
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del linkdoc["url"]
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linkcol.update_one({"url":link},{"$set":linkdoc})
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return state
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def save_batch_info(db,host,states,docs):
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good_document_count = 0
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original_text_size = 0
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batch_size = 0
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_,domain = courlan.get_hostinfo(host)
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for state,doc in zip(states,docs):
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batch_size += 1
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if state == "good":
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good_document_count += 1
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good_text_size += doc["text_size"]
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htdoc = get_link_doc(link,state)
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htdoc["html"] = html
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htdoc["html_size"] = len(html)
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htdoc["html_md5"]= hashlib.md5(html.encode("utf8")).hexdigest()
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# can be revisited - upsert
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del htdoc["url"]
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htmlcol.update_one({"url":link},{"$set":htdoc},upsert=True)
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doc.update(get_link_doc(link,"good"))
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# todo extract links
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print(link,doc)
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del doc["url"]
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contentcol.update_one({"url":link},{"$set":doc},upsert=True)
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for chs in doc["paragraph_checksums"]:
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try:
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checkcol.insert_one({"_id":chs})
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except pymongo.errors.DuplicateKeyError as err:
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pass
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linkdoc = get_link_doc(link,state)
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del linkdoc["url"]
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linkcol.update_one({"url":link},{"$set":linkdoc})
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original_text_size += doc["original_text_size"]
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batchdoc = {
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"host": linkdoc["host"],
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"domain": linkdoc["domain"],
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"host": host,
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"domain": domain,
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"created_at": dat.utcnow(),
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"good_document_count":good_document_count,
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"document_count":document_count,
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"text_size":text_size,
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"good_text_size":good_text_size,
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"original_text_size":original_text_size,
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"batch_size": BATCHSIZE,
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"average_fetch_characters": text_size / BATCHSIZE,
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"good_prob": good_document_count / batch_size,
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"batch_size": batch_size,
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}
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db["batches"].insert_one(batchdoc)
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print(batchdoc)
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@ -699,10 +691,23 @@ def visit(hostname):
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responses = []
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for link in links:
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responses.append(fetch_page(link))
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extracted_pages = extract_pages(links,responses)
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extracted_pages = []
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for original_link,(final_link,html) in zip(links,responses):
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doc = None
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assert original_link is not None
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doc = extract_page(final_link,html)
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extracted_pages.append((original_link,final_link,html,doc))
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extracted_links = extract_links(links,responses,hostname,rules,"frontlink")
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index_links(db,extracted_links)
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index_pages(db,hostname,extracted_pages)
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final_states = []
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docs = []
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for original_link,final_link,html,doc in extracted_pages:
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status = index_page(db,original_link,final_link,html,doc)
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final_states.append(status)
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docs.append(doc)
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save_batch_info(db,hostname,final_states,docs)
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link_summary(db,hostname)
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def crawl_summary():
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@ -719,17 +724,28 @@ def crawl_summary():
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"batch_count":{"$sum":"$batch_size"},
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"text_size":{"$sum":"$text_size"},
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"original_text_size":{"$sum":"$original_text_size"},
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"count":{"$sum":1},
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}
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},
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{"$sort":{"original_text_size":-1}},
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])
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print(">>>> Batches")
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headers = ["_id","document_count","good_document_count","count","batch_count","text_size","original_text_size"]
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headers = ["_id","document_count","good_document_count","batch_count","text_size","original_text_size"]
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print("\t".join(headers))
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for item in res:
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values = [str(item[x]) for x in headers]
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print("\t".join(values))
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import binascii
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def import_html():
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myclient = pymongo.MongoClient(CONNECTION)
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for l in sys.stdin:
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hdoc = json.loads(l)
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url = hdoc["url"]
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html = bs4.BeautifulSoup(binascii.b2a_qp(hdoc["quoted_html"])).prettify()
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doc = extract_pages(url,html)
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index_page(db,url,url,html,doc)
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def sample_domains():
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myclient = pymongo.MongoClient(CONNECTION)
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db=myclient[DBNAME]
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