Software Alternatives, Accelerators & Startups

Apify VS PyTorch

Compare Apify VS PyTorch 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.

Apify logo Apify

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

PyTorch logo PyTorch

Open source deep learning platform that provides a seamless path from research prototyping to...
  • Apify Landing page
    Landing page //
    2023-09-30

Apify is a JavaScript & Node.js based data extraction tool for websites that crawls lists of URLs and automates workflows on the web. With Apify you can manage and automatically scale a pool of headless Chrome / Puppeteer instances, maintain queues of URLs to crawl, store crawling results locally or in the cloud, rotate proxies and much more.

  • PyTorch Landing page
    Landing page //
    2023-07-15

Apify features and specs

  • Ease of Use
    Apify provides a user-friendly interface that makes it easy for users of all technical levels to create and manage web scraping tasks.
  • Scalability
    Apify is built to handle tasks of various sizes, from small-scale projects to enterprise-level operations, making it a scalable solution.
  • Integration and API Support
    It offers extensive API support, allowing for seamless integration with other tools and systems to enhance automated workflows.
  • Customizability
    Users can customize their scraping bots (actors) with different settings and scripts to fit specific needs and requirements.
  • Cloud-based
    Being a cloud-based platform, Apify allows users to run their scraping tasks without needing local resources, which is convenient and efficient.
  • Comprehensive Documentation
    Apify provides thorough documentation and tutorials, which help users get started quickly and solve issues efficiently.
  • Community and Support
    Apify has an active community and solid customer support to assist users with their needs and enhance their overall experience.

Possible disadvantages of Apify

  • Learning Curve
    While the interface is user-friendly, there may still be a learning curve for those new to web scraping and automation.
  • Cost
    Apify can be expensive compared to other web scraping tools, particularly for extensive use cases that require high volumes of data.
  • Dependency on External Factors
    Web scraping often depends on the stability of the target websites. Changes in website structures can break scripts, requiring ongoing maintenance.
  • Performance Limitations
    The performance of cloud-based scraping tasks can be affected by network latency and other external factors beyond user control.
  • Potential Legal Issues
    Web scraping can raise legal concerns, particularly when scraping data from websites that restrict such activities in their terms of service.
  • Resource Intensity
    Complex scraping tasks can be resource-intensive, potentially requiring higher-tier subscriptions and more computing resources, driving up costs.

PyTorch features and specs

  • Dynamic Computation Graph
    PyTorch uses a dynamic computation graph, which allows for interactive and flexible model building. This is particularly beneficial for researchers who need to modify the network architecture on-the-fly.
  • Pythonic Nature
    PyTorch is designed to be deeply integrated with Python, making it very intuitive for Python developers. The framework feels more 'native' to Python, which improves the ease of learning and use.
  • Strong Community Support
    PyTorch has a large, active, and growing community. This means abundant resources such as tutorials, forums, and third-party tools are available to help developers solve problems and share solutions.
  • Flexibility and Control
    PyTorch offers granular control over computations and provides extensive debugging capabilities. This level of control is beneficial for tasks that require precise tuning and custom implementations.
  • Support for GPU Acceleration
    PyTorch offers seamless integration with GPU hardware, which significantly accelerates the computation process. This makes it highly efficient for deep learning tasks.
  • Rich Ecosystem
    PyTorch has a rich ecosystem including libraries like torchvision, torchaudio, and torchtext, which are specialized for different data types and can significantly shorten development times.

Possible disadvantages of PyTorch

  • Limited Production Deployment Tools
    PyTorch is primarily designed for research rather than production. While deployment tools like TorchServe exist, they are not as mature or integrated as solutions offered by other frameworks like TensorFlow.
  • Lesser Adoption in Industry
    While PyTorch is popular among researchers, it has historically seen less adoption in industry compared to TensorFlow, which means there might be fewer resources for large-scale production deployments.
  • Inconsistent API Changes
    As PyTorch continues to evolve rapidly, occasionally there are breaking changes or inconsistent API updates. This can create maintenance challenges for existing codebases.
  • Steeper Learning Curve for Beginners
    Despite its Pythonic design, PyTorch's focus on flexibility and control can make it slightly harder for beginners to get started compared to some other high-level libraries and frameworks.
  • Less Mature Documentation
    Although the documentation is improving, it has been historically less comprehensive and mature compared to other frameworks like TensorFlow, which can make it difficult to find detailed, clear information.

Apify videos

Apify product news - 2019/01/30

PyTorch videos

PyTorch in 5 Minutes

More videos:

  • Review - Jeremy Howard: Deep Learning Frameworks - TensorFlow, PyTorch, fast.ai | AI Podcast Clips
  • Review - PyTorch at Tesla - Andrej Karpathy, Tesla

Category Popularity

0-100% (relative to Apify and PyTorch)
Web Scraping
100 100%
0% 0
Data Science And Machine Learning
Data Extraction
100 100%
0% 0
Data Science Tools
0 0%
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Apify and PyTorch

Apify Reviews

Top 15 Best TinyTask Alternatives in 2022
This is another tinytask alternative. For you to link various web services and APIs, Apify has provided many web integration options. You can add data processing and customised computation processes in addition to letting the data flow between them. With the data that is freely accessible on the web, you may provide crucial insights, and easy lead creation allows you to...

PyTorch Reviews

10 Python Libraries for Computer Vision
Similar to TensorFlow and Keras, PyTorch and torchvision offer powerful tools for computer vision tasks. PyTorch’s dynamic computation graph and torchvision’s datasets and pre-trained models make it easy to implement tasks such as image classification, object detection, and style transfer.
Source: clouddevs.com
25 Python Frameworks to Master
Along with TensorFlow, PyTorch (developed by Facebook’s AI research group) is one of the most used tools for building deep learning models. It can be used for a variety of tasks such as computer vision, natural language processing, and generative models.
Source: kinsta.com
Top 8 Alternatives to OpenCV for Computer Vision and Image Processing
PyTorch is another open-source machine learning framework that is widely used in academia and industry. PyTorch provides excellent support for building deep learning models, and it has several pre-trained models for computer vision tasks, making it the ideal tool for several computer vision applications. PyTorch offers a user-friendly interface that makes it easier for...
Source: www.uubyte.com
PyTorch vs TensorFlow in 2022
When we compare HuggingFace model availability for PyTorch vs TensorFlow, the results are staggering. Below we see a chart of the total number of models available on HuggingFace that are either PyTorch or TensorFlow exclusive, or available for both frameworks. As we can see, the number of models available for use exclusively in PyTorch absolutely blows the competition out of...
15 data science tools to consider using in 2021
First released publicly in 2017, PyTorch uses arraylike tensors to encode model inputs, outputs and parameters. Its tensors are similar to the multidimensional arrays supported by NumPy, another Python library for scientific computing, but PyTorch adds built-in support for running models on GPUs. NumPy arrays can be converted into tensors for processing in PyTorch, and vice...

Social recommendations and mentions

Based on our record, PyTorch should be more popular than Apify. It has been mentiond 133 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.

Apify mentions (26)

  • How to scrape TikTok using Python
    For deployment, we'll use the Apify platform. It's a simple and effective environment for cloud deployment, allowing efficient interaction with your crawler. Call it via API, schedule tasks, integrate with various services, and much more. - Source: dev.to / 24 days ago
  • How to scrape Bluesky with Python
    We already have a fully functional implementation for local execution. Let us explore how to adapt it for running on the Apify Platform and transform in Apify Actor. - Source: dev.to / 2 months ago
  • Web scraping with GPT-4o: powerful but expensive
    We've had the best success by first converting the HTML to a simpler format (i.e. markdown) before passing it to the LLM. There are a few ways to do this that we've tried, namely Extractus[0] and dom-to-semantic-markdown[1]. Internally we use Apify[2] and Firecrawl[3] for Magic Loops[4] that run in the cloud, both of which have options for simplifying pages built-in, but for our Chrome Extension we use... - Source: Hacker News / 9 months ago
  • Current problems and mistakes of web scraping in Python and tricks to solve them!
    Developed by Apify, it is a Python adaptation of their famous JS framework crawlee, first released on Jul 9, 2019. - Source: dev.to / 9 months ago
  • Show HN: Crawlee for Python – a web scraping and browser automation library
    Hey all, This is Jan, the founder of [Apify](https://apify.com/)—a full-stack web scraping platform. After the success of [Crawlee for JavaScript](https://github.com/apify/crawlee/) today! The main features are: - A unified programming interface for both HTTP (HTTPX with BeautifulSoup) & headless browser crawling (Playwright). - Source: Hacker News / 11 months ago
View more

PyTorch mentions (133)

  • Grasping Computer Vision Fundamentals Using Python
    To aspiring innovators: Dive into open-source frameworks like OpenCV or PyTorch, experiment with custom object detection models, or contribute to projects tackling bias mitigation in training datasets. Computer vision isn’t just a tool, it’s a bridge between the physical and digital worlds, inviting collaborative solutions to global challenges. The next frontier? Systems that don’t just interpret visuals, but... - Source: dev.to / 12 days ago
  • Top Programming Languages for AI Development in 2025
    With the quick emergence of new frameworks, libraries, and tools, the area of artificial intelligence is always changing. Programming language selection. We're not only discussing current trends; we're also anticipating what AI will require in 2025 and beyond. - Source: dev.to / 25 days ago
  • Fine-tuning LLMs locally: A step-by-step guide
    Next, we define a training loop that uses our prepared data and optimizes the weights of the model. Here's an example using PyTorch:. - Source: dev.to / about 2 months ago
  • 10 Must-Have AI Tools to Supercharge Your Software Development
    8. TensorFlow and PyTorch: These frameworks support AI and machine learning integrations, allowing developers to build and deploy intelligent models and workflows. TensorFlow is widely used for deep learning applications, offering pre-trained models and extensive documentation. PyTorch provides flexibility and ease of use, making it ideal for research and experimentation. Both frameworks support neural network... - Source: dev.to / 3 months ago
  • Automating Enhanced Due Diligence in Regulated Applications
    Frameworks like TensorFlow and PyTorch can help you build and train models for various tasks, such as risk scoring, anomaly detection, and pattern recognition. - Source: dev.to / 3 months ago
View more

What are some alternatives?

When comparing Apify and PyTorch, you can also consider the following products

import.io - Import. io helps its users find the internet data they need, organize and store it, and transform it into a format that provides them with the context they need.

TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.

Scrapy - Scrapy | A Fast and Powerful Scraping and Web Crawling Framework

Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.

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

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.