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@ -1,6 +1,7 @@
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FROM python:3.9
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FROM python:3.9
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RUN mkdir /app
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RUN mkdir /app
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COPY requirements.txt /app
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COPY requirements.txt /app
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RUN pip install -r requirements.txt
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RUN pip install -r /app/requirements.txt
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COPY *.py /app
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COPY *.py /app
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WORKDIR /app
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WORKDIR /app
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ENTRYPOINT ["python", "./mongocrawler.py"]
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@ -278,8 +278,7 @@ def get_link_features(link):
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for i,feature in enumerate(features):
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for i,feature in enumerate(features):
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if len(feature) < 1:
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if len(feature) < 1:
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continue
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continue
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if feature.isdigit():
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feature = re.sub("[0-9]","*",feature)
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feature = "<NUM>"
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res.append(str(i)+ "-" + feature)
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res.append(str(i)+ "-" + feature)
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if len(res) < 2:
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if len(res) < 2:
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return None
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return None
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@ -322,6 +321,9 @@ class LinkClassifier:
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def test(self,testset):
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def test(self,testset):
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# eval
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# eval
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gg = 0
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gg = 0
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true_positive = 0
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positive = 0
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false_negative = 0
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for item in testset:
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for item in testset:
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l = item["url"]
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l = item["url"]
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cl = 0
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cl = 0
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@ -331,12 +333,19 @@ class LinkClassifier:
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r = 0
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r = 0
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if pcp > 0:
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if pcp > 0:
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r = 1
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r = 1
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if cl == 1:
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if r == 1:
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true_positive += 1
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positive += 1
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if r == 1 and cl == 0:
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false_negative += 1
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if r == cl:
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if r == cl:
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gg += 1
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gg += 1
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else:
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else:
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print("MISS",l,cl,pcp)
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print("MISS",l,cl,pcp)
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print("Accuracy:")
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print(len(testset))
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print(len(testset))
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print("Precision: {}, Recall: {}".format(true_positive/positive,true_positive/(true_positive+false_negative)))
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print("Accuracy:")
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acc = gg / len(testset)
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acc = gg / len(testset)
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print(acc)
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print(acc)
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return acc
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return acc
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@ -407,6 +416,7 @@ def link_summary(db,hostname):
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goodcount = 0
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goodcount = 0
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info = {}
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info = {}
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crawled_count = 0
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crawled_count = 0
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bad_crawl_count = 0
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for item in res:
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for item in res:
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count = item["count"]
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count = item["count"]
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st = item["_id"]
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st = item["_id"]
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@ -415,7 +425,11 @@ def link_summary(db,hostname):
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goodcount += count
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goodcount += count
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if st != "frontlink" and st != "backlink":
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if st != "frontlink" and st != "backlink":
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crawled_count += count
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crawled_count += count
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if st != "good":
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bad_crawl_count += count
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info[st] = count
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info[st] = count
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info["crawled_count"] = crawled_count
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info["bad_crawl_count"] = bad_crawl_count
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baclink_cout = 0
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baclink_cout = 0
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if "backlink" in info:
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if "backlink" in info:
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backlink_count = info["backlink"]
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backlink_count = info["backlink"]
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@ -469,7 +483,7 @@ def sample_links(db,hostname,status,batch_size):
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for item in res:
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for item in res:
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for item in res:
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for item in res:
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cll = cl.classify(item["url"])
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cll = cl.classify(item["url"])
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cll += random.uniform(-0.1,0.1)
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#cll += random.uniform(-0.1,0.1)
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sample_links.append((item["url"],cll))
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sample_links.append((item["url"],cll))
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if cll > 0:
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if cll > 0:
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predicted_good += 1
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predicted_good += 1
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@ -521,6 +535,7 @@ def createdb():
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htmlcol.create_index("html_md5",unique=True)
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htmlcol.create_index("html_md5",unique=True)
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domaincol = db["domains"]
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domaincol = db["domains"]
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domaincol.create_index("host",unique=True)
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domaincol.create_index("host",unique=True)
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domaincol.create_index("average_fetch_characters",unique=True)
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@cli.command()
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@cli.command()
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@click.argument("link")
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@click.argument("link")
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