Building a Search Engine with Scrapy and Python


Building a Search Engine with Scrapy and Python: A blog about building a search engine. Information on how to parse web pages using Scrapy and the python programming language.

Building a Search Engine with Scrapy and Python: A blog about building a search engine. Information on how to parse web pages using Scrapy and the python programming language.

https://blog.hartleybrody.com/python-search-engine/

Building a Search Engine with Scrapy and Python: A blog about building a search engine. Information on how to parse web pages using Scrapy and the python programming language.

Building a Search Engine with Scrapy and Python: A blog about building a search engine. Information on how to parse web pages using Scrapy and the python programming language.

I hope you had a great summer! Mine was quite busy, I spent most of it preparing for the launch of [my new course]() to create web crawlers and web scrapers in Python Scrapy.

In order to make the course practical, I decided to create a real-world project together with the students: a search engine. The idea is that, after completing the project, we will have built a real search engine that can be used by anyone!

In this article I want to talk about how we are doing it and why.

Building a Search Engine with Scrapy and Python: A blog about building a search engine. Information on how to parse web pages using Scrapy and the python programming language

After installing scrapy, go ahead and create your first scrapy project. To do this, navigate to the directory you would like to save your project in, and run:

scrapy startproject mynewspider

This will give us a boilerplate for our spider. It will create a folder with the name of our spider (mynewspider in this case), with various configuration files and folders inside.

We will want to keep track of which URLs we have already seen in our crawler, so that we don’t crawl the same URL twice or more. Let’s create a cache for this purpose:

class UrlCache(object):

“””A simple cache where we store the URLs already seen”””

def __init__(self):

self.seen_urls = set()

def add_url(self, url):

self.seen_urls.add(url)

def has_url(self, url):

return url in self.seen_urls

A few weeks ago I embarked on a project to build a basic search engine with Python and the Scrapy framework. I wanted to learn how to build a simple search engine that could index and rank pages by content. I also wanted to learn Scrapy, so this seemed like a good project for me. The idea is simple: get a web page, extract the links from the page, and crawl any new links until you have enough pages in your index.

The first thing I did was figure out what Scrapy does for you and what it doesn’t do for you. From everything I’ve read about it, it seems like it’s really good at getting data out of web pages, but not as good at storing data or searching data. So that meant my first task was going to be building my own database to store the indexed pages.

The second step was figuring out how to get Scrapy to parse a page and return all of the links on the page. It turned out this was pretty easy. The hardest part was figuring out how Scrapy parses URLs: it uses python’s urlparse module which has some oddities I didn’t understand at first (for example, if a URL starts with //www.google.com it

In this section we are going to build a search engine in python. The first step to building a search engine is creating a web crawler. A web crawler will crawl the internet and index information from the web pages it finds. This information can be used in many ways. For example you could use this data for marketing purposes or for adding search functionality to your own website.

The first thing we need to do is install Scrapy. In order to install Scrapy you will need Python installed on your computer. If you do not have Python installed, download it here: https://www.python.org/downloads/

Once you have Python installed, open up a terminal window and type: pip install scrapy

The next thing we need to do is create a directory for our project and then create a project within that directory. To create the directory type: mkdir search_engine && cd search_engine

Next we need to run the command scrapy startproject wscraper in order to create our project folder structure which should look like this:

![Image](https://cdn-images-1.medium.com/max/800/1*uD6UiM0Ea1x

In this post I’ll be describing how to create a search engine using Scrapy and Python. This tutorial was written for Python 3.6. I’ll be implementing it in Visual Studio Code, but any IDE will do.

Requirements

This tutorial will walk you through these tasks:

1. Creating a new Scrapy project

2. Defining the Items you will extract

3. Writing a spider to crawl a site and extract Items

4. Exporting the scraped data using the command line

5. Storing the scraped data in MongoDB


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