Web Crawler - Iterating over Postgres database result with Scrapy-CodePudding

I'm trying to write a scraper that gets domains from database result. I'm able to get data from database but I can't wrap my head around how to feed it to Scrapy. I've looked here and found many suggestions but none is really what I'm doing. When I run my codes below, nothing happens not even an error.

scaper.py

#import json
import json

#import database library
import psycopg2

#import scrapy library
import scrapy

#create database connection
conn = psycopg2.connect(
    host="localhost",
    database="mydb",
    user="dbuser",
    password="postgres",
    port=5432
)

#create cursor from database
#cursor() is python equivalent to query() to fetch the rows
query = conn.cursor()

#execute query from database
query.execute('SELECT info FROM domains')

#create scrapy class
class MySpider(scrapy.Spider):  
    name = "scrap_domains"

    #start_requests with scrapy
    def start_requests(self):

        #iterate over database result
        for url in query:

            #iterate over each json object
            for item in url:

                #get domain name
                domain_name = item['domain']

                #grab information from url
                yield scrapy.Request()

        #print response
        def parse(self, response):
            print(response)

# we close the cursor and conn both
query.close()
conn.close()

CodePudding user response：

I finally got my scraper working. The problem was caused by closing the cursor and database connection on every iteration. Python is not async like Node, as I've been learning. A function should be written to detect when the iteration is finished then proceed with further tasks but for the purpose of this example, we just comment them out like we did at the bottom of the file. I'm posting a detailed answer for future references.

Notes : I use this scraper to scrape through a list of 300 millions records stored in my database. Just change your limit per page and the code below will do the rest for you until it's all done. When it' finished, just grab your json file and upload to your database. I suffered so that you don't have to.

I'm using PostgreSQL and store the data in JSONB. My table only has 2 columns and looks like this :

id (int) | info (jsonb)
1        | {"domain": "weerstation-aarschot.be","timestamp":1646106745}
2        | {"domain": "wereldvakanties.be","timestamp":1646106746}
3        | {"domain": "welzijnscentrum.be","timestamp":1646106747}

As per the scrapy documents, copy/paste codes below and run this command in your terminal to write all domains to a json file :

scrapy runspider scraper.py -o domains.json

Use the Selectors to extract HTML data from the body

scraper.py

#import datetime
from datetime import datetime

#calendar
import calendar
from email import header;
import time;

#import json
import json
from urllib import request
from wsgiref import headers

#import database library
import psycopg2

#import scrapy library
import scrapy

#create database connection
conn = psycopg2.connect(
    host="localhost",
    database="mydb",
    user="username",
    password="postgres",
    port=5432
)

#create cursor from database
#cursor() is python equivalent to query() to fetch the rows
query = conn.cursor()

#spiderclass
class MySpider(scrapy.Spider):  
    name = "domains"

    def start_requests(self):

            #database pagination
            #loop through extremely large datasets automatically
            current_page = ""
            offset = 0
            limit = 1000000
            flag = True

            #while its true
            while flag:

                #execute query from database
                query.execute("SELECT info FROM domains ORDER BY id ASC LIMIT " str(limit) " OFFSET " str(offset))

                # query db with start and offset, example: select * from domains limit %start% offset %offset%
                unique_domains = query.fetchone()

                #condition
                if not unique_domains:
                    flag = False
                else:

                    # do processing with your data
                    offset  = limit

                    #iterate over database result
                    for url in query:

                        #iterate over each json object
                        for item in url:

                            #variables from result
                            hostname = item['domain']
                            https_url = "https://" hostname
                            http_url = "http://" hostname

                            #fetch http request
                            yield scrapy.Request(url=https_url, callback=self.parse)

    #print response
    def parse(self, response):

        #current date
        currDate = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
        timestamp = calendar.timegm(time.gmtime())
        date_created = currDate

        #variables from response
        url = response.url
        status = response.status
        headers = response.headers
        request = response.request
        body = response.body

        #header information
        content_language = ""
        protocol = ""

        #meta tags
        favicon = response.css('link::attr(href)').get()
        title = response.xpath('//title/text()').get()
        description = response.xpath('//description/text()').get()
        keywords = response.xpath('//keywords/text()').get()
        author = response.xpath('//author/text()').get()
        type = response.xpath('//content-type/text()').get()

        #open graph tags
        og_title = ""
        og_type = ""
        og_url = ""
        og_image = ""
        og_site_name = ""
        og_description = ""

        #get all the links to follow
        links = response.css('a::attr(href)').getall()

        #get text from every header tag (<h>)
        h1_text = response.css('h1::text').getall()
        h2_text = response.css('h2::text').getall()
        h3_text = response.css('h3::text').getall()

        #get span text
        span_text = response.css('span::text').getall();

        #get text from every paragraph tag (<p>)
        p_text = response.css('p::text').getall()

        #get text from every div tag (<div>)
        div_text = response.css('div::text').getall()

        #get every image
        images = response.css('img').xpath('@src').getall()

        #get every video
        videos = []

        #category, score
        websiteScore = ""

        #grab information from url
        result =  yield{
                    'url': url,
                    'status': status, 
                    "score" : websiteScore,
                    "type" : type,
                    "category" : "",
                    "industry" : "",
                    "timestamp" : timestamp,
                    "date_created" :date_created,
                    "headers" :{
                    "content_language" : content_language,
                    "protocol" : protocol,
                    },
                    "metas" : [
                    {
                    "favicon ": favicon,
                    "title" :title,
                    "description": description,
                    "keywords" :keywords,
                    "author" : author,
                    }
                    ],
                    "open_graph" : [
                    {
                    "og_title" :og_title,
                    "og_type" :og_type,
                    "og_url" :og_url,
                    "og_image" :og_image,
                    "og_site_name" :og_site_name,
                    "og_description" : og_description,
                    }
                    ],
                    "links": links,
                    "h1_text": h1_text,
                    "h2_text": h2_text,
                    "h3_text": h3_text,
                    "div_text": div_text,
                    "p_text": p_text,
                    "span_text": span_text,
                    "images ": images,
                    "videos" : videos

                    }

        #print result
        #print(request)

    # we close the cursor and conn both
    #query.close()
    #conn.close()
    #scrapy runspider scraper.py -o domains.json

domains.json (example output)

[
{"url": "https://weerstation-aarschot.be", "status": 200, "score": "", "page": "", "offset ": "", "per_page": "", "type": "", "category": "", "industry": "", "timestamp": 1646535167.804621, "date_created": "2022-03-05 21:52:47", "headers": {"content_language": "", "protocol": ""}, "metas": [{"favicon ": "", "title": "", "description": "", "keywords": "", "author": ""}], "open_graph": [{"og_title": "", "og_type": "", "og_url": "", "og_image": "", "og_site_name": "", "og_description": ""}], "links": [[]], "h_text": [[]], "div_text": [[]], "p_text": [[]], "images ": [[]], "videos": [[]]},
{"url": "https://wereldvakanties.be", "status": 200, "score": "", "page": "", "offset ": "", "per_page": "", "type": "", "category": "", "industry": "", "timestamp": 1646535168.069924, "date_created": "2022-03-05 21:52:48", "headers": {"content_language": "", "protocol": ""}, "metas": [{"favicon ": "", "title": "", "description": "", "keywords": "", "author": ""}], "open_graph": [{"og_title": "", "og_type": "", "og_url": "", "og_image": "", "og_site_name": "", "og_description": ""}], "links": [[]], "h_text": [[]], "div_text": [[]], "p_text": [[]], "images ": [[]], "videos": [[]]},
{"url": "https://welzijnscentrum.be", "status": 200, "score": "", "page": "", "offset ": "", "per_page": "", "type": "", "category": "", "industry": "", "timestamp": 1646535168.096689, "date_created": "2022-03-05 21:52:48", "headers": {"content_language": "", "protocol": ""}, "metas": [{"favicon ": "", "title": "", "description": "", "keywords": "", "author": ""}], "open_graph": [{"og_title": "", "og_type": "", "og_url": "", "og_image": "", "og_site_name": "", "og_description": ""}], "links": [[]], "h_text": [[]], "div_text": [[]], "p_text": [[]], "images ": [[]], "videos": [[]]},
]