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.
Based on our record, NumPy should be more popular than Apify. It has been mentiond 119 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.
The AI Service will be built using aiohttp (asynchronous Python web server) and integrates PyTorch, Hugging Face Transformers, numpy, pandas, and scikit-learn for financial data analysis. - Source: dev.to / 4 months ago
This library provides functions for working in domain of linear algebra, fourier transform, matrices and arrays. - Source: dev.to / 8 months ago
The Python Library components of Ray could be considered analogous to solutions like numpy, scipy, and pandas (which is most analogous to the Ray Data library specifically). As a framework and distributed computing solution, Ray could be used in place of a tool like Apache Spark or Python Dask. It’s also worthwhile to note that Ray Clusters can be used as a distributed computing solution within Kubernetes, as... - Source: dev.to / 8 months ago
It's compatible with a wide range of data libraries, including Pandas, NumPy, and Altair. Streamlit integrates with all the latest tools in generative AI, such as any LLM, vector database, or various AI frameworks like LangChain, LlamaIndex, or Weights & Biases. Streamlit’s chat elements make it especially easy to interact with AI so you can build chatbots that “talk to your data.”. - Source: dev.to / 9 months ago
The OpenCV image is a regular NumPy array. You can see it shape:. - Source: dev.to / 9 months ago
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
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
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
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
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
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
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.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Scrapy - Scrapy | A Fast and Powerful Scraping and Web Crawling Framework
OpenCV - OpenCV is the world's biggest computer vision library
ParseHub - ParseHub is a free web scraping tool. With our advanced web scraper, extracting data is as easy as clicking the data you need.