zz

mongo/cli.py

@@ -1,6 +1,8 @@
 import click
 import mongocrawler
 import rq
+import redis
+import sys
 import os
 
 REDIS_URL= os.getenv("REDIS_URL","redis://localhost:6379/")

mongo/mongocrawler.py

@@ -154,21 +154,16 @@ def fetch_robot(base_url:str)->urllib.robotparser.RobotFileParser:
     # exceptions happening here
     return rules
 
-
-def extract_pages(link_batch:list,responses:list)->list:
-    out = []
-    for original_link,(final_link,html) in zip(link_batch,responses):
+def extract_page(final_link,html):
     doc = None
-        assert original_link is not None
     if html is not None:
         doc = trafilatura.bare_extraction(html,url=final_link,with_metadata=True,include_formatting=False,target_language=LANGUAGE,favor_precision=True)
         if doc is not None:
             if not "text" in doc or len(doc["text"]) < MINTEXTSIZE:
                 # text too small
                 doc = None
+    return doc
 
-        out.append((original_link,final_link,html,doc))
-    return out
 
 def set_content_checksums(doc):
     text = doc["text"]
@@ -186,20 +181,11 @@ def set_content_checksums(doc):
             sentences += 1
     doc["sentences_count"] = sentences
 
-def index_pages(db,hostname,extracted_pages):
+def index_page(db,original_link,final_link,html,doc):
     linkcol = db["links"]
     htmlcol = db["html"]
     contentcol = db["content"]
     checkcol = db["check"]
-    links = []
-    # stats of the batch
-    good_document_count = 0
-    document_count = 0
-    text_size = 0
-    good_text_size = 0
-    original_text_size = 0
-    for original_link,final_link,html,doc in extracted_pages:
-        document_count += 1
     state = "good"
     link = original_link
     if original_link != final_link:
@@ -213,7 +199,6 @@ def index_pages(db,hostname,extracted_pages):
     if doc is not None:
         set_content_checksums(doc)
         tsz = doc["text_size"]
-            text_size += tsz
         psz = doc["paragraph_sizes_sum"]
         if tsz < TEXT_TRASH_SIZE or psz/tsz < TEXT_TRASH_RATIO:
             state = "small"
@@ -225,14 +210,12 @@ def index_pages(db,hostname,extracted_pages):
             nd = checkcol.find_one({"_id":chs})
             if nd is None:
                 origsz += paragraph_size
+        doc["original_text_size"] = origsz
 
         if (1 - (origsz / tsz)) > TEXT_TRASH_RATIO:
             state = "copy"
-            original_text_size += origsz
         print(origsz)
     if state == "good":
-            good_document_count += 1
-            good_text_size += doc["text_size"]
         htdoc = get_link_doc(link,state)
         htdoc["html"] = html
         htdoc["html_size"] = len(html)
@@ -254,17 +237,26 @@ def index_pages(db,hostname,extracted_pages):
     linkdoc = get_link_doc(link,state)
     del linkdoc["url"]
     linkcol.update_one({"url":link},{"$set":linkdoc})
+    return state
+
+def save_batch_info(db,host,states,docs):
+    good_document_count = 0
+    original_text_size = 0
+    batch_size = 0
+    _,domain = courlan.get_hostinfo(host)
+    for state,doc in zip(states,docs):
+        batch_size += 1
+        if state == "good":
+            good_document_count += 1
+            original_text_size += doc["original_text_size"]
     batchdoc = {
-      "host": linkdoc["host"],
-      "domain": linkdoc["domain"],
+      "host": host,
+      "domain": domain,
       "created_at":  dat.utcnow(),
       "good_document_count":good_document_count,
-      "document_count":document_count,
-      "text_size":text_size,
-      "good_text_size":good_text_size,
       "original_text_size":original_text_size,
-      "batch_size": BATCHSIZE,
-      "average_fetch_characters": text_size / BATCHSIZE,
+      "good_prob": good_document_count / batch_size,
+      "batch_size": batch_size,
     }
     db["batches"].insert_one(batchdoc)
     print(batchdoc)
@@ -699,10 +691,23 @@ def visit(hostname):
     responses = []
     for link in links:
         responses.append(fetch_page(link))
-    extracted_pages = extract_pages(links,responses)
+
+    extracted_pages = []
+    for original_link,(final_link,html) in zip(links,responses):
+        doc = None
+        assert original_link is not None
+        doc = extract_page(final_link,html)
+        extracted_pages.append((original_link,final_link,html,doc))
+
     extracted_links = extract_links(links,responses,hostname,rules,"frontlink")
     index_links(db,extracted_links)
-    index_pages(db,hostname,extracted_pages)
+    final_states = []
+    docs = []
+    for original_link,final_link,html,doc in extracted_pages:
+        status = index_page(db,original_link,final_link,html,doc)
+        final_states.append(status)
+        docs.append(doc)
+    save_batch_info(db,hostname,final_states,docs)
     link_summary(db,hostname)
 
 def crawl_summary():
@@ -719,17 +724,28 @@ def crawl_summary():
                    "batch_count":{"$sum":"$batch_size"},
                    "text_size":{"$sum":"$text_size"},
                    "original_text_size":{"$sum":"$original_text_size"},
-                   "count":{"$sum":1},
                    }
          },
+        {"$sort":{"original_text_size":-1}},
     ])
     print(">>>> Batches")
-    headers = ["_id","document_count","good_document_count","count","batch_count","text_size","original_text_size"]
+    headers = ["_id","document_count","good_document_count","batch_count","text_size","original_text_size"]
     print("\t".join(headers))
     for item in res:
         values = [str(item[x]) for x in headers]
         print("\t".join(values))
 
+import binascii
+
+def import_html():
+    myclient = pymongo.MongoClient(CONNECTION)
+    for l in sys.stdin:
+        hdoc = json.loads(l)
+        url = hdoc["url"]
+        html = bs4.BeautifulSoup(binascii.b2a_qp(hdoc["quoted_html"])).prettify()
+        doc = extract_pages(url,html)
+        index_page(db,url,url,html,doc)
+
 def sample_domains():
     myclient = pymongo.MongoClient(CONNECTION)
     db=myclient[DBNAME]