Scrapy Reviews

Qdrant Reviews

Scrapy mentions (94)

• 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 / 16 days 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 / 6 months ago

• Creating an advanced search engine with PostgreSQL

  If you're looking for a turn-key solution, I'd have to dig a little. I generally write a scraper in python that dumps into a database or flat file (depending on number of records I'm hunting). Scraping is a separate subject, but once you write one you can generally reuse relevant portions for many others. If you can get adept at a scraping framework like Scrapy you can do it fairly quickly, but there aren't many... - Source: Hacker News / 11 months ago

• What do .NET devs use for web scraping these days?

  I know this might not be a good answer, as it's not .NET, but we use https://scrapy.org/ (Python). Source: 12 months ago

• BeutifulSoup and getting URLs

  Take a look at Scrapy. It has a fairly advanced throttling mechanism for you to not get banned. Source: 12 months ago

Qdrant mentions (39)

• How to Build a Chat App with Your Postgres Data using Agent Cloud

  AgentCloud uses Qdrant as the vector store to efficiently store and manage large sets of vector embeddings. For a given user query the RAG application fetches relevant documents from vector store by analyzing how similar their vector representation is compared to the query vector. - Source: dev.to / 19 days ago

• Hindi-Language AI Chatbot for Enterprises Using Qdrant, MLFlow, and LangChain

  Great. Now that we have the embeddings, we need to store them in a vector database. We will be using Qdrant for this purpose. Qdrant is an open-source vector database that allows you to store and query high-dimensional vectors. The easiest way to get started with the Qdrant database is using the docker. - Source: dev.to / 29 days ago

• Boost Your Code's Efficiency: Introducing Semantic Cache with Qdrant

  I took Qdrant for this project. The reason was that Qdrant stands for high-performance vector search, the best choice against use cases like finding similar function calls based on semantic similarity. Qdrant is not only powerful but also scalable to support a variety of advanced search features that are greatly useful to nuanced caching mechanisms like ours. - Source: dev.to / about 1 month ago

• Ask HN: Has Anyone Trained a personal LLM using their personal notes?

  I'm currently looking to implement locally, using QDrant [1] for instance. I'm just playing around, but it makes sense to have a runnable example for our users at work too :) [2]. [1]. https://qdrant.tech/. - Source: Hacker News / about 2 months ago

• Open-source Rust-based RAG

  There are much better known examples, such as https://qdrant.tech/ and https://github.com/lancedb/lancedb. - Source: Hacker News / 3 months ago