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Real Estate Scraper API VS Scrapy

Compare Real Estate Scraper API VS Scrapy and see what are their differences

Piloterr
Piloterr web scraping API handles headless browsers, rotates proxies for you, and offers a library featured
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Real Estate Scraper API logo Real Estate Scraper API

Real Estate Scraper API for easy property data extraction: gather data from popular real estate websites, easily bypass advanced anti-bot systems, pay only for successfully delivered results.

Scrapy logo Scrapy

Scrapy | A Fast and Powerful Scraping and Web Crawling Framework
  • Real Estate Scraper API Landing page
    Landing page //
    2023-07-17

Gather property data from leading real estate websites

Real Estate Scraper API ensures consistent data flow of accurate information from the most popular real estate websites. Collect pricing, location, property type, amenities, and other data - our API will deliver it to you as a raw HTML in real-time or to your cloud storage bucket.

Easily bypass advanced anti-bot systems

Benefit from our top-tier real estate data collection infrastructure that is ready-to-use right away. Oxylabs’ built-in patented proxy rotator, auto-retry system, JavaScript rendering, and other smart solutions will ensure a quick and reliable data gathering process.

  • Easy access to difficult real estate targets
  • No CAPTCHAs or IP blocks
  • No need to develop or maintain your own web scrapers

Pay only for successfully delivered results

Be confident you pay for only quality results from your chosen real estate website. Oxylabs ML-based response recognition module validates the response and triggers retry logic if needed. Save your time, resources, and money on more important tasks.

  • Fair pricing and cost optimization
  • No need to spend time checking the response status
  • Scrapy Landing page
    Landing page //
    2021-10-11

Real Estate Scraper API features and specs

  • Custom Parser
  • Web Crawler
  • Scheduler

Scrapy features and specs

  • Efficiency
    Scrapy is designed to be efficient and robust, capable of handling multiple tasks simultaneously and scraping large websites in a fast and reliable manner.
  • Built-in Tooling
    Scrapy comes with built-in tools for handling common tasks such as following links, extracting data using XPath and CSS, and exporting data in a variety of formats.
  • Customization
    Scrapy offers extensive customization options, allowing users to build complex spiders and modify their behavior through middleware and pipelines.
  • Python Integration
    Being a Python framework, Scrapy integrates seamlessly with the Python ecosystem, enabling the use of libraries like Pandas, NumPy, and others to process and analyze scraped data.
  • Community Support
    Scrapy has a large and active community, providing extensive documentation, tutorials, and third-party extensions to enhance functionality.
  • Asynchronous Processing
    Scrapy’s asynchronous processing model enhances performance by allowing multiple concurrent requests, reducing the time required for crawling sites.

Possible disadvantages of Scrapy

  • Steep Learning Curve
    For beginners, Scrapy's comprehensive feature set and the need for understanding concepts like XPath and CSS selectors can be challenging.
  • Resource Intensive
    Scrapy can be resource-intensive, potentially consuming significant memory and CPU, which can be problematic for scraping very large websites or running multiple spiders simultaneously.
  • Debugging Complexity
    Debugging Scrapy projects can be complex due to its asynchronous nature and the multiple layers of middleware and pipelines that need to be understood.
  • Overhead for Small Projects
    For simple or small-scale scraping tasks, the overhead of setting up and configuring a Scrapy project might be excessive, with simpler alternatives being more suitable.
  • Limited JavaScript Support
    Scrapy's out-of-the-box support for JavaScript-heavy websites is limited, requiring additional tools like Splash or Selenium, which can complicate the setup.
  • Dependency Management
    Managing Scrapy's dependencies and compatibility with other Python packages can sometimes be challenging, leading to potential conflicts and maintenance overhead.

Analysis of Scrapy

Overall verdict

  • Yes, Scrapy is a good option for those looking to implement web scraping projects due to its robust set of features, active community, and comprehensive documentation. It is particularly well-suited for projects that require scraping from multiple websites and processing large volumes of data efficiently.

Why this product is good

  • Scrapy is a popular open-source web crawling framework for Python that's designed for extensive, flexible, and efficient web scraping. Its built-in tools and features make it easy to extract data from websites quickly and automatically. Key advantages include its ability to handle requests asynchronously, its support for multiple protocols, its item pipeline feature that allows for data cleaning and storage, and its ease of integration with other Python libraries and databases.

Recommended for

    Scrapy is recommended for developers, data scientists, and businesses that need to gather data from websites efficiently. It's particularly useful for projects involving data aggregation, market research, competitive analysis, and monitoring pricing changes across various platforms.

Real Estate Scraper API videos

+ Add

How to Gather Property Listing Data With Real Estate Scraper API? | Step-By-Step Guide

Scrapy videos

+ Add

Python Scrapy Tutorial - 22 - Web Scraping Amazon

More videos:

  • Demo - Scrapy - Overview and Demo (web crawling and scraping)
  • Review - GFuel LemoNADE Taste Test & Review! | Scrapy

Category Popularity

0-100% (relative to Real Estate Scraper API and Scrapy)

Real Estate Scraper API

Scrapy

Data Extraction
3 3%
Data Extraction
97% 97
Web Scraping
3 3%
Web Scraping
97% 97
Web Data Extraction
100 100%
Web Data Extraction
0% 0
Data
0 0%
Data
100% 100

User comments

Share your experience with using Real Estate Scraper API and Scrapy. For example, how are they different and which one is better?
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Reviews

These are some of the external sources and on-site user reviews we've used to compare Real Estate Scraper API and Scrapy

Real Estate Scraper API Reviews

We have no reviews of Real Estate Scraper API yet.
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Scrapy Reviews

Top 15 Best TinyTask Alternatives in 2022
The software is simply deployable via the cloud, or you can host the spiders on your server using Scrapy. Only the rules need to be written; Scrapy will take care of the rest to separate the facts. With Scrapy’s portability and ability to run on Windows, Linux, Mac, and BSD platforms, new features can be added without affecting the program’s core.
Source: www.dashtech.org

Social recommendations and mentions

Based on our record, Scrapy seems to be more popular. It has been mentiond 97 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Real Estate Scraper API mentions (0)

We have not tracked any mentions of Real Estate Scraper API yet. Tracking of Real Estate Scraper API recommendations started around Jan 2023.

Scrapy mentions (97)

  • Current problems and mistakes of web scraping in Python and tricks to solve them!
    One might ask, what about Scrapy? I'll be honest: I don't really keep up with their updates. But I haven't heard about Zyte doing anything to bypass TLS fingerprinting. So out of the box Scrapy will also be blocked, but nothing is stopping you from using curl_cffi in your Scrapy Spider. - Source: dev.to / 10 months ago
  • Automate Spider Creation in Scrapy with Jinja2 and JSON
    Install scrapy (Offical website) either using pip or conda (Follow for detailed instructions):. - Source: dev.to / 10 months ago
  • Analyzing Svenskalag Data using DBT and DuckDB
    Using Scrapy I fetched the data needed (activities and attendance). Scrapy handled authentication using a form request in a very simple way:. - Source: dev.to / 12 months ago
  • Scrapy Vs. Crawlee
    Scrapy is an open-source Python-based web scraping framework that extracts data from websites. With Scrapy, you create spiders, which are autonomous scripts to download and process web content. The limitation of Scrapy is that it does not work very well with JavaScript rendered websites, as it was designed for static HTML pages. We will do a comparison later in the article about this. - Source: dev.to / about 1 year ago
  • What is SERP? Meaning, Use Cases and Approaches
    While there is no specific library for SERP, there are some web scraping libraries that can do the Google Search Page Ranking. One of them which is quite famous is Scrapy - It is a fast high-level web crawling and web scraping framework, used to crawl websites and extract structured data from their pages. It offers rich developer community support and has been used by more than 50+ projects. - Source: dev.to / over 1 year ago
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What are some alternatives?

When comparing Real Estate Scraper API and Scrapy, you can also consider the following products

Crawlbase - A Platform for Data Crawling and Scraping For Business Developers

Apify - Apify is a web scraping and automation platform that can turn any website into an API.

Zyte - We're Zyte (formerly Scrapinghub), the central point of entry for all your web data needs.

ParseHub - ParseHub is a free web scraping tool. With our advanced web scraper, extracting data is as easy as clicking the data you need.

Octoparse - Octoparse provides easy web scraping for anyone. Our advanced web crawler, allows users to turn web pages into structured spreadsheets within clicks.

Smartproxy - Smartproxy is perhaps the most user-friendly way to access local data anywhere. It has global coverage with 195 locations, offers more than 55M residential proxies worldwide and a great deal of scraping solutions.

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