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Clean up site map scanning. Return all results instead of 10

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rmgr 2024-06-09 21:53:57 +09:30
parent 2a99a61dbe
commit bbba459480
6 changed files with 140 additions and 57 deletions
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33
client/src/css/styles.css Normal file
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@ -0,0 +1,33 @@
html, body {
height: 100%;
}
body {
margin: 0;
}
input {
padding: 7px;
font-size: 1.1rem;
}
.search-container {
display: flex;
justify-content: center;
align-items: center;
text-align: center;
min-height: 25vh;
}
.flex-container {
padding: 0;
margin: 0;
display: flex;
align-items: center;
justify-content: center;
flex-direction: column;
}
.flex-item {
}
.result {
display:block;
max-width: 60vw;
overflow-x: hidden;
}

16
client/src/index.html Normal file
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@ -0,0 +1,16 @@
<html>
<head>
<link rel="stylesheet" href="css/styles.css">
</head>
<body>
<div class="search-container">
<input type="text" class="searchbox" id="searchbox">
</div>
<div class="flex-container">
<div class="flex-item" id="results">
</div>
</div>
<script src="js/index.js"></script>
</body>
</html>

28
client/src/js/index.js Normal file
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@ -0,0 +1,28 @@
function debounce(func, timeout = 300){
let timer;
return (...args) => {
clearTimeout(timer);
timer = setTimeout(() => { func.apply(this, args); }, timeout);
};
}
async function search(searchBox){
const response = await fetch(`http://localhost:5000/search/${searchBox.value}`);
const results = await response.json();
const resultView = document.getElementById("results");
resultView.replaceChildren();
for (let i = 0; i < results.length; i++){
let result = results[i];
let resultElement = document.createElement("a");
resultElement.innerText = result[0];
resultElement.href = result[0];
resultElement.className = "flex-item result";
resultView.appendChild(resultElement);
}
}
const searchBoxKeyUp = debounce(() => search())
const searchBox = document.getElementById("searchbox");
searchBox.addEventListener("keyup", debounce(() => search(searchBox)))

42
src/crawl.py
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@ -2,7 +2,6 @@
import argparse
import requests
import hashlib
from urllib.parse import urlparse, urljoin
import urllib.robotparser
import os
@ -10,7 +9,7 @@ from time import sleep
from bs4 import BeautifulSoup
from sqlalchemy import create_engine
from config import DATABASE_URI
from models import Base, Documents, Document_Tokens
from models import Base, Documents
from sqlalchemy.orm import sessionmaker
import datetime
import yt_dlp as youtube_dl
@ -23,7 +22,7 @@ Session = sessionmaker(bind=engine)
excluded_domains = ['amazon.', 'news.ycombinator.',
'facebook.com', 'amzn', 'fb.com']
excluded_filetypes = [".jpg", ".xml", ".mp4",
excluded_filetypes = [".jpg", ".xml", ".mp4", ".jpeg", ".db",
".mp3", ".png", ".tiff", ".gif", ".webp", ".pdf"]
@ -33,6 +32,7 @@ def get_html(url: str) -> str:
def parse_youtube(video_url: str) -> bool:
return
# Language preference for subtitles (set to None for auto-generated)
# Change this to 'en' for English subtitles, or None for auto-generated
subtitle_language = 'en'
@ -91,6 +91,8 @@ def parse_html(url: str, html: str, recursion: int = 0, traversed_links=[], robo
for domain in excluded_domains:
if domain in url:
return
if any(ext in url for ext in excluded_filetypes):
return
if "youtube.com" in url:
parse_youtube(url)
return
@ -110,8 +112,6 @@ def parse_html(url: str, html: str, recursion: int = 0, traversed_links=[], robo
return
soup = BeautifulSoup(html, 'html.parser')
hash = hashlib.sha256()
hash.update(url.encode('ascii'))
s = Session()
existing_website = s.query(Documents).filter_by(url=url).first()
@ -151,13 +151,25 @@ def parse_html(url: str, html: str, recursion: int = 0, traversed_links=[], robo
parse_html(link, link_html, r, traversed_links)
except:
pass
elif link not in traversed_links:
with open('data/links.txt', 'r+') as linksfile:
while line := linksfile.readline():
if line.strip() == link.strip():
found = True
if not found:
linksfile.write(f'{link}\n')
# elif link not in traversed_links:
# with open('data/links.txt', 'r+') as linksfile:
# while line := linksfile.readline():
# if line.strip() == link.strip():
# found = True
# if not found:
# linksfile.write(f'{link}\n')
def parse_site_map(base_url):
map = BeautifulSoup(requests.get(base_url).content, 'xml')
print(map.find_all('loc'))
for loc in map.find_all('loc'):
if "xml" in loc.contents[0]:
parse_site_map(loc.contents[0])
else:
url = loc.contents[0]
html = get_html(url)
parse_html(url, html, max_recursion)
if __name__ == "__main__":
@ -189,11 +201,7 @@ if __name__ == "__main__":
print("Robots prevents crawling url: " + args.url)
exit(0)
if len(rp.site_maps()) > 0:
map = BeautifulSoup(requests.get(rp.site_maps()[0]).content, 'xml')
for loc in map.find_all('loc'):
url = loc.contents[0]
html = get_html(url)
parse_html(url, html, max_recursion)
parse_site_map(rp.site_maps()[0])
else:
html = get_html(args.url)
parse_html(args.url, html, max_recursion)

72
src/search.py
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@ -1,14 +1,17 @@
#!/usr/bin/python3
from sqlalchemy import create_engine, func, and_, or_
from sqlalchemy import create_engine, func, and_, or_, not_
from config import DATABASE_URI
from models import Base, Tokens, Documents, Document_Tokens, NGrams, Document_NGrams
from models import Base, NGrams, Documents, Document_NGrams, NGrams, Document_NGrams
from sqlalchemy.orm import sessionmaker
from sqlalchemy.sql.expression import distinct
import time
from flask import Flask
from flask_cors import CORS
from flask import send_from_directory
from urllib.parse import unquote
app = Flask(__name__)
app = Flask(__name__, static_url_path='/static/')
CORS(app)
engine = create_engine(DATABASE_URI)
Base.metadata.create_all(engine)
Session = sessionmaker(bind=engine)
@ -16,7 +19,9 @@ Session = sessionmaker(bind=engine)
def split_query(query):
result = {'ands': [], 'ors': [], 'words': [], 'ngrams': []}
query = query.lower()
result = {'ands': [], 'ors': [], 'words': [],
'ngrams': [], 'exclusions': []}
query_words = query.split()
i = 0
while i < len(query_words):
@ -39,6 +44,11 @@ def split_query(query):
quoted_query[1:len(quoted_query)-2].rstrip())
i += n + 1
continue
elif query_words[i][0] == "-":
excluded_query = query_words[i][1: len(query_words[i])]
result['exclusions'].append(excluded_query)
i += 1
continue
result['ngrams'].append(query_words[i])
i += 1
return result
@ -52,19 +62,26 @@ def search(query):
query_words = split_query(unquote(query))
print(query_words)
if len(query_words['ands']) > 0:
print('entering ands: ' +
str((time.time_ns() - start_time) // 1_000_000) + "ms")
for a in query_words['ands']:
query = session.query(Documents.url, func.count(1)). \
join(Document_Tokens, Documents.id == Document_Tokens.document_id).\
join(Tokens, Document_Tokens.token_id == Tokens.id).\
filter(Tokens.token.in_([a.split(',')[0], a.split(',')[1]])).\
join(Document_NGrams, Documents.id == Document_NGrams.document_id). \
join(NGrams, Document_NGrams.ngram_id == NGrams.id). \
filter(NGrams.gram.in_([a.split(',')[0], a.split(',')[1]])).\
group_by(Documents.url). \
having(func.count(distinct(Document_Tokens.token_id)) == 2).\
having(func.count(distinct(Document_NGrams.ngram_id)) == 2). \
order_by(func.count(1).desc())
# limit(100)
print(query)
for result in query.all():
if result[0] in results.keys():
results[result[0]] += result[1]
else:
results[result[0]] = result[1]
print('exiting ands: ' +
str((time.time_ns() - start_time) // 1_000_000) + "ms")
if len(query_words['ngrams']) > 0:
print('entering ngrams: ' +
str((time.time_ns() - start_time) // 1_000_000) + "ms")
@ -83,7 +100,7 @@ def search(query):
q = q.filter(or_(*and_conditions))
print('query built: ' + str((time.time_ns() - start_time) // 1_000_000) + "ms")
print(q)
x = q.all()
x = q.limit(100).all()
print('query executed: ' +
str((time.time_ns() - start_time) // 1_000_000) + "ms")
print(x)
@ -101,30 +118,11 @@ def search(query):
# results[document_ngram.document.url] = 1
print('exiting ngrams: ' +
str((time.time_ns() - start_time) // 1_000_000) + "ms")
if len(query_words['words']) > 0:
print('entering words: ' +
str((time.time_ns() - start_time) // 1_000_000) + "ms")
q = session.query(Documents.url, func.count(1)) \
.join(Document_Tokens, Documents.id == Document_Tokens.document_id) \
.join(Tokens, Document_Tokens.token_id == Tokens.id) \
.group_by(Documents.url).filter(Tokens.token.in_(query_words['words']))
print('query built: ' + str((time.time_ns() - start_time) // 1_000_000) + "ms")
print(q)
x = q.all()
print('query executed: ' +
str((time.time_ns() - start_time) // 1_000_000) + "ms")
for result in x:
if result[0] in results.keys():
results[result[0]] += result[1]
else:
results[result[0]] = result[1]
print('exiting words: ' +
str((time.time_ns() - start_time) // 1_000_000) + "ms")
print(str((time.time_ns() - start_time) // 1_000_000) + "ms")
session.close()
return sorted(results.items(), key=lambda x: x[1], reverse=True)[:10]
return sorted(results.items(), key=lambda x: x[1], reverse=True)[:len(results.items())]
# @app.route("/search/<query>")
# def search(query):
@ -132,17 +130,17 @@ def search(query):
# session = Session()
# result = {}
# query_words = unquote(query).split()
# x= session.query(Tokens).filter(Tokens.token.in_(query_words)).take(1000)
# x= session.query(NGrams).filter(NGrams.ngram.in_(query_words)).take(1000)
# for word in query_words:
# word = word.lower()
# matching_token = session.query(Tokens).filter_by(token=word).first()
# matching_ngram = session.query(NGrams).filter_by(ngram=word).first()
#
# if matching_token is None:
# if matching_ngram is None:
# continue
# for document_token in matching_token.document_tokens:
# if document_token.document.url in result.keys():
# result[document_token.document.url] += 1
# for document_ngram in matching_ngram.document_ngrams:
# if document_ngram.document.url in result.keys():
# result[document_ngram.document.url] += 1
# else:
# result[document_token.document.url] = 1
# result[document_ngram.document.url] = 1
# print(str((time.time_ns() - start_time) // 1_000_000) + "ms")
# return sorted(result.items(), key=lambda x: x[1], reverse=True)[:10]

4
todo
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@ -6,6 +6,6 @@
[x] Add clustered index to document_ngrams table model
[x] Add clustered index to document_tokens table model
[ ] Add ddl command to create partition tables
[ ] Investigate whether or not robots.txt is as aggressive as I'm making ito ut to be
[ ] Instead of starting from a random page on the site, go to root and find site map and crawl that
[x] Investigate whether or not robots.txt is as aggressive as I'm making ito ut to be
[x] Instead of starting from a random page on the site, go to root and find site map and crawl that