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Walmart Review Crawler
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Extract all reviews from each review page. For each review, capture and output the following information: URL, product name, product link, total number of reviews, average product rating, review location, review rating, publication date, review text, review title, author name, and original source.
BeautifulSoup and HTTPX template
A template for web scraping data from websites enqueued from starting URL using Python. The URL of the web page is passed in via input, which is defined by the input schema. The template uses the HTTPX to get the HTML of the page and the Beautiful Soup to parse the data from it. Enqueued URLs are available in request queue. The data are then stored in a dataset where you can easily access them.
Included features
- Apify SDK for Python - a toolkit for building Apify Actors and scrapers in Python
- Input schema - define and easily validate a schema for your Actor's input
- Request queue - queues into which you can put the URLs you want to scrape
- Dataset - store structured data where each object stored has the same attributes
- HTTPX - library for making asynchronous HTTP requests in Python
- Beautiful Soup - a Python library for pulling data out of HTML and XML files
How it works
This code is a Python script that uses HTTPX and Beautiful Soup to scrape web pages and extract data from them. Here's a brief overview of how it works:
- The script reads the input data from the Actor instance, which is expected to contain a
start_urls
key with a list of URLs to scrape and amax_depth
key with the maximum depth of nested links to follow. - The script enqueues the starting URLs in the default request queue and sets their depth to 0.
- The script processes the requests in the queue one by one, fetching the URL using HTTPX and parsing it using BeautifulSoup.
- If the depth of the current request is less than the maximum depth, the script looks for nested links in the page and enqueues their targets in the request queue with an incremented depth.
- The script extracts the desired data from the page (in this case, all the links) and pushes it to the default dataset using the
push_data
method of the Actor instance. - The script catches any exceptions that occur during the scraping process and logs an error message using the
Actor.log.exception
method. - This code demonstrates how to use Python and the Apify SDK to scrape web pages and extract specific data from them.
Resources
- BeautifulSoup Scraper
- Beautifulsoup Scraper tutorial
- Python tutorials in Academy
- Web scraping with Beautiful Soup and Requests
- Beautiful Soup vs. Scrapy for web scraping
- Integration with Make, GitHub, Zapier, Google Drive, and other apps
- Video guide on getting scraped data using Apify API
- Video introduction to Python SDK
- A short guide on how to build web scrapers using code templates:
Getting started
For complete information see this article. In short, you will:
- Build the Actor
- Run the Actor
Pull the Actor for local development
If you would like to develop locally, you can pull the existing Actor from Apify console using Apify CLI:
-
Install
apify-cli
Using Homebrew
brew install apify-cli
Using NPM
npm -g install apify-cli
-
Pull the Actor by its unique
<ActorId>
, which is one of the following:- unique name of the Actor to pull (e.g. "apify/hello-world")
- or ID of the Actor to pull (e.g. "E2jjCZBezvAZnX8Rb")
You can find both by clicking on the Actor title at the top of the page, which will open a modal containing both Actor unique name and Actor ID.
This command will copy the Actor into the current directory on your local machine.
apify pull <ActorId>
Documentation reference
To learn more about Apify and Actors, take a look at the following resources:
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- Created in Apr 2024
- Modified 4 months ago