Software Alternatives, Accelerators & Startups

Deployment.io VS Scrapy

Compare Deployment.io VS Scrapy and see what are their differences

Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

Deployment.io logo Deployment.io

Deployment.io makes it super easy for startups and agile engineering teams to automate application deployments on AWS cloud.

Scrapy logo Scrapy

Scrapy | A Fast and Powerful Scraping and Web Crawling Framework
  • Deployment.io deployment home
    deployment home //
    2024-03-23
  • Deployment.io deployment repositories
    deployment repositories //
    2024-03-23
  • Deployment.io deployment environments
    deployment environments //
    2024-03-23
  • Deployment.io deployment deployments
    deployment deployments //
    2024-03-23

Deployment simplifies continuous code integration and delivery automation for startups and agile engineering teams on the AWS cloud, eliminating the need for DevOps engineering. A developer can deploy static sites, web services, and environments without knowledge of AWS or DevOps. Deployment supports previews on pull requests and automatic deployments on code push without manual setup or scripting. It enables engineering teams to focus on tasks that add customer value instead of worrying about DevOps-related grunt work.

  • Scrapy Landing page
    Landing page //
    2021-10-11

Deployment.io

$ Details
freemium
Platforms
AWS GitHub GitLab
Release Date
2024 February

Scrapy

Website
scrapy.org
Pricing URL
-
$ Details
Platforms
-
Release Date
-

Deployment.io features and specs

  • Automatic Deployments
    Automated deployments to AWS cloud
  • Previews
    Previews deployed to AWS on pull requests
  • Slack Alerts
    Slack alerts for for any updates to deployments
  • Unlimited static sites
    Deploy static sites with one click without any AWS setup
  • Unlimited web services
    Deploy web services and backend APIs without any AWS setup
  • Unlimited environments
    Create development, staging, and production environments on the fly on your AWS account
  • Unlimited repositories
    Connect your GitHub and GitLab repositories for automated CI/CD

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.

Deployment.io videos

Deploying a Golang API on AWS using deployment.io

Scrapy videos

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 Deployment.io and Scrapy)
DevOps Tools
100 100%
0% 0
Web Scraping
0 0%
100% 100
Cloud Computing
100 100%
0% 0
Data Extraction
0 0%
100% 100

Questions and Answers

As answered by people managing Deployment.io and Scrapy.

What's the story behind your product?

Deployment.io's answer

I led engineering teams at early-stage startups and realized that startups waste 70% of valuable engineering time on tedious, non-coding tasks that they can easily automate.

To solve this problem, we've built Deployment.io so engineering teams at startups can focus on writing more code that adds value and helps them achieve PMF faster.

Which are the primary technologies used for building your product?

Deployment.io's answer

ReactJs using Typescript, GatsbyJs using Typescript, GoLang, and AWS

What makes your product unique?

Deployment.io's answer

Deployment.io is built and designed for startups. Our customers can onboard in 5 minutes and start deploying apps to AWS without any DevOps or AWS knowledge. Other platforms are complex and require scripting or DevOps knowledge. They are built for bigger companies with a lot of resources.

Why should a person choose your product over its competitors?

Deployment.io's answer

Startups and agile engineering teams should choose Deployment.io for the simplicity and ease of use. Our competitors are complex and are designed for bigger companies.

How would you describe your primary audience?

Deployment.io's answer

For startups, speed and focus are crucial. Our primary audience is engineering teams at startups that want to focus on building code that adds value and not on DevOps related grunt work.

User comments

Share your experience with using Deployment.io 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 Deployment.io and Scrapy

Deployment.io Reviews

  1. Super easy deployments to AWS

    Deploying web apps on AWS has never been this easy and it also takes care of scaling based on usage.

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.

Social recommendations and mentions

Based on our record, Scrapy seems to be a lot more popular than Deployment.io. While we know about 97 links to Scrapy, we've tracked only 1 mention of Deployment.io. 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.

Deployment.io mentions (1)

  • Easily automate Rust web service deployments on AWS without DevOps
    Deployment.io is an AI-powered, self-serve developer platform that simplifies deployment of complex backend services on AWS. - Source: dev.to / 9 months ago

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 / 11 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 Deployment.io and Scrapy, you can also consider the following products

Harness - Automated Tests For Your Web App

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

Jenkins - Jenkins is an open-source continuous integration server with 300+ plugins to support all kinds of software development

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

Render UIKit - React-inspired Swift library for writing UIKit UIs

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