From 37a115fb94d30959408266025a0299ad04217f8c Mon Sep 17 00:00:00 2001
From: Daniel Hladek <daniel.hladek@tuke.sk>
Date: Thu, 13 Apr 2023 09:10:03 +0200
Subject: [PATCH] zz

---
 mongo/cli.py          | 14 ++++++++++++++
 mongo/mongocrawler.py | 20 ++++++++++++++------
 2 files changed, 28 insertions(+), 6 deletions(-)

diff --git a/mongo/cli.py b/mongo/cli.py
index 1e7dcfe..093dcc9 100644
--- a/mongo/cli.py
+++ b/mongo/cli.py
@@ -1,5 +1,10 @@
 import click
 import mongocrawler
+import rq
+import os
+
+REDIS_URL= os.getenv("REDIS_URL","redis://localhost:6379/")
+QUEUES=os.getenv("QUEUES","high,default,low")
 
 @click.group()
 def cli():
@@ -37,5 +42,14 @@ def summary():
 def sampledomains():
     mongocrawler.sample_domains()
 
+
+@cli.command(help="Enqueue a list of links into redis queue for crawling")
+def enqueue():
+    q = rq.Queue(connection=redis.from_url(REDIS_URL))
+    for l in sys.stdin:
+        print(l.strip())
+        r = q.enqueue(mongocrawler.visit, l.strip())
+        print(r)
+
 if __name__ == "__main__":
     cli()
diff --git a/mongo/mongocrawler.py b/mongo/mongocrawler.py
index a2fc796..7179f82 100644
--- a/mongo/mongocrawler.py
+++ b/mongo/mongocrawler.py
@@ -628,7 +628,7 @@ 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",pymongo.DESCENDING))
     batchcol = db["batches"]
     batchcol.create_index("host")
     batchcol.create_index("created_at")
@@ -711,7 +711,6 @@ def crawl_summary():
     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":"$host",
@@ -737,11 +736,20 @@ def sample_domains():
     linkscol = db["links"]
     # discover domains
     domains = linkscol.distinct("host",filter={"status":"frontlink"})
+    all_domains = []
     for domain in domains:
-        print(domain)
+        all_domains.append(domain)
+    sample_size = min(int(DISCOVER_LINK_RATIO* BATCHSIZE), len(all_domains))
+    print(">>> Discover domains {}".format(sample_size))
+    sample_domains = random.sample(all_domains,sample_size)
     domaincol = db["domains"]
     # exploit domains
-    print(">>>> Best domains")
-    res = domaincol.find({},limit=100).sort("average_fetch_characters",-1)
+    res = domaincol.find({"average_fetch_characters":{"$gt":1000}}).sort("average_fetch_characters",-1)
+    all_domains = []
     for item in res:
-        print(item)
+        all_domains.append(item["host"])
+    sample_size = min(int((1 - DISCOVER_LINK_RATIO) * BATCHSIZE),len(all_domains))
+    print(">>>> Best domains {}".format(sample_size))
+    sample_domains += random.sample(all_domains,sample_size)
+    for domain in sample_domains:
+        print(domain)