mongo/Dockerfile

@@ -2,7 +2,7 @@ FROM python:3.9
 RUN mkdir /app
 COPY requirements.txt /app
 RUN pip install -r /app/requirements.txt
-COPY *.py /app/
+COPY *.py /app
 WORKDIR /app
 # redis config
 ENV REDIS_URL="redis://localhost:6379/"

mongo/cli.py

@@ -25,13 +25,9 @@ def classify(start_link):
     mongocrawler.classify(start_link)
 
 @cli.command()
-@click.argument("hostname")
-def visit(hostname):
-    mongocrawler.visit(hostname)
-
-@cli.command()
-def summary():
-    mongocrawler.crawl_summary()
+@click.argument("start_link")
+def visit(start_link):
+    mongocrawler.visit(start_link)
 
 if __name__ == "__main__":
     cli()

mongo/mongocrawler.py

@@ -9,8 +9,7 @@ import trafilatura.external
 import sys
 import courlan
 import urllib
-from datetime import datetime as dat
-import datetime
+from datetime import datetime
 import click
 import logging as LOGGER
 import os
@@ -108,7 +107,7 @@ def get_link_doc(link:str,status="frontlink")->dict:
     assert r is not None
     link,host = r
     domain = courlan.extract_domain(link)
-    return {"url":link,"host":host,"domain":domain,"status":status,"created_at":dat.utcnow()}
+    return {"url":link,"host":host,"domain":domain,"status":status,"created_at":datetime.utcnow()}
 
 
 def fetch_page(link:str)->(str,str):
@@ -257,7 +256,7 @@ def index_pages(db,hostname,extracted_pages):
     batchdoc = {
       "host": linkdoc["host"],
       "domain": linkdoc["domain"],
-      "created_at":  dat.utcnow(),
+      "created_at":  datetime.utcnow(),
       "good_document_count":good_document_count,
       "document_count":document_count,
       "text_size":text_size,
@@ -281,7 +280,8 @@ def get_bs_links(link,html):
         base = bs.base["href"]
     base = urllib.parse.urlparse(courlan.normalize_url(base))
 
-    links = set()
+    external_links = set()
+    internal_links = set()
     # Normalizacia linkov
     for l in bs.find_all("a", href=True):
         if "rel" in l.attrs and l.attrs["rel"] == "nofollow" or "nofollow" in l.attrs:
@@ -305,13 +305,19 @@ def get_bs_links(link,html):
             if path.endswith(")"):
                 # javascript
                 continue
+            external = True
+            if parsed.netloc == base.netloc:
+                external = False
             href = urllib.parse.urlunparse((scheme,netloc,path,"","",""))
             href = courlan.normalize_url(href)
-            links.add(href)
+            if external:
+                external_links.add(href)
+            else:
+                internal_links.add(href)
         except ValueError as err:
             print(err)
             pass
-    return links
+    return internal_links,external_links
 
 def extract_links(link_batch:list,responses:list,hostname:str,rules,default_status="frontlink")->list:
     links = {}
@@ -320,12 +326,12 @@ def extract_links(link_batch:list,responses:list,hostname:str,rules,default_stat
         status = default_status
         if html is None or len(html) < 256:
             continue
-        page_links = get_bs_links(final_link,html)
+        internal_links, external_links = get_bs_links(final_link,html)
         #external_links = courlan.extract_links(html,final_link,external_bool=True,language=LANGUAGE)
         #internal_links = courlan.extract_links(html,final_link,external_bool=False,language=LANGUAGE)
         #print(extracted_links)
-        for link in page_links:
-            if not courlan.is_external(link,final_link) and not is_robot_good(link,rules):
+        for link in internal_links:
+            if not is_robot_good(link,rules):
                 badrobot += 1
                 continue
             status = str(default_status)
@@ -356,7 +362,7 @@ def index_links(db,extracted_links):
                 pass
         else:
             print("updating " + link,status)
-            linkcol.update_one({"url":link},{"$set":{"status":status,"updated_at":dat.utcnow()}})
+            linkcol.update_one({"url":link},{"$set":{"status":status,"updated_at":datetime.utcnow()}})
 
 def get_link_features(link):
     a, urlpath = courlan.get_host_and_path(link)
@@ -495,7 +501,7 @@ def link_summary(db,hostname):
     res = linkcol.aggregate([
         {"$match":{"host":hostname}},
         {"$group":{"_id":"$status",
-                   "count":{"$sum":1},
+                   "count":{"$count":{}},
                    }
          },
     ])
@@ -545,7 +551,7 @@ def link_summary(db,hostname):
     info["total_good_characters"] = text_size
     info["average_good_characters"] = good_document_characters
     info["average_fetch_characters"] = fetch_average_characters
-    domaincol = db["domains"]
+    domaincol = db["domain"]
     domaincol.update_one({"host":hostname},{"$set":info},upsert=True)
     res = domaincol.find_one({"host":hostname})
     print(res)
@@ -628,7 +634,7 @@ def createdb():
     htmlcol.create_index("html_md5",unique=True)
     domaincol = db["domains"]
     domaincol.create_index("host",unique=True)
-    domaincol.create_index("average_fetch_characters")
+    domaincol.create_index("average_fetch_characters",unique=True)
     batchcol = db["batches"]
     batchcol.create_index("host")
     batchcol.create_index("created_at")
@@ -678,12 +684,12 @@ def classify(start_link):
     cl.train(trainset)
     cl.test(testset)
 
-def visit(hostname):
+def visit(start_link):
     myclient = pymongo.MongoClient(CONNECTION)
     db=myclient[DBNAME]
+    start_link,hostname = courlan.check_url(start_link)
     batch_size = BATCHSIZE
     rules = fetch_robot(hostname)
-    start_link = "https://" + hostname
     # renew front links
     front_links = fetch_front_links(start_link,rules)
     index_links(db,front_links)
@@ -705,29 +711,3 @@ def visit(hostname):
     index_pages(db,hostname,extracted_pages)
     link_summary(db,hostname)
 
-def crawl_summary():
-    myclient = pymongo.MongoClient(CONNECTION)
-    db=myclient[DBNAME]
-    batchcol = db["batches"]
-    yesterday =  datetime.datetime.today() - datetime.timedelta(days=1)
-    print(yesterday)
-    res = batchcol.find({"created_at":{"$lt": yesterday.utcnow()}},limit=20).sort("average_fetch_characters")
-    res = batchcol.aggregate([
-        {"$match":{"created_at":{"$lt": yesterday.utcnow()}}},
-        {"$group":{"_id":"$host",
-                   "document_count":{"$sum":{"document_count":1}},
-                   "good_document_count":{"$sum":{"good_document_count":1}},
-                   "batch_size":{"$sum":{"batch_size":1}},
-                   "count":{"$sum":1},
-                   }
-         },
-    ])
-    print(">>>> Batches")
-    for item in res:
-        print(item)
-        #print(item["host"],item["document_count"],item["good_document_count"],item["created_at"])
-    domaincol = db["domains"]
-    print(">>>> Best domains")
-    res = domaincol.find({},limit=100).sort("average_fetch_characters")
-    for item in res:
-        print(item)