canopy VS Playwright

Pinecone: A scalable vector database service that facilitates efficient similarity search in high-dimensional spaces. Ideal for building real-time applications in AI, such as personalized recommendation engines and content-based retrieval systems.

In this post we’ll build a Python script that uses StripeDocs Reader, a loader on LlamaIndex, that creates vector embeddings of Stripe's documentation in Pinecone. This allows a user to ask questions about Stripe Docs to an LLM, in this case OpenAI, and receive a generated response.

Pinecone is a managed vector database service that simplifies the process of building and scaling vector search applications. It offers a simple API for embedding vector search into applications, providing accurate, scalable similarity search with minimal setup and maintenance.

In case of AIMD, I am doing this all in-memory, but you could also do this in a database (e.g. Pinecone). It all depends on how much data you have and how much compute you have available.

A RAG implementation's quality and performance highly depend on the similarity-based search of embeddings. The challenge arises from the fact that embeddings are usually high-dimensional vectors, and the knowledge base may have many documents. It's not surprising that the popularity of LLM catalyzed the development of specialized vector databases like Pinecone and Weaviate. However, SQL databases are also evolving to meet the new challenge.

In the dynamic world of web development, Python has emerged as a dominant force, especially in backend development – the primary focus of this blog post. Although it's worth mentioning that there are ongoing efforts to use Python for the frontend as well, like Reflex (previously known as Pynecone, they presumably had to change their name because of Pinecone vector database), which even garnered support from Y Combinator. Samuel Colvin (creator of Pydantic) is also working on FastUI (he literally just released the first version in December 2023).

Playwright is a powerful tool developed by Microsoft, it allows developers to write reliable end-to-end tests and perform browser automation tasks with ease. What sets Playwright apart is its ability to work seamlessly across multiple browsers (Chrome, Firefox, and WebKit), it provides a consistent and efficient way to interact with web pages, extract data, and automate repetitive tasks. Moreover, it supports various programming languages such as Node.js, Python, Java, and .NET, that’s making it a versatile choice for web scraping projects. Whether you're scraping public data for analysis, building a web crawler, or automating manual workflows, Playwright has you covered.

The consensus I could gather is either use playwright or use a workaround to solve it in the puppeteer layer. The root cause of the bug is a websocket size limitation on the CDP protocol for chromium.

With the advent of tools like Puppeteer and now Playwright, end-to-end testing has become much easier and more reliable. For anyone who's used Selenium in the past, you know what I'm talking about. Puppeteer has opened the way in terms of E2E tooling, but Playwright has taken it to the next level and made it easier to await for certain selectors or conditions to be fulfilled (via locators), thus making tests more reliable and less flaky. Also, it's a game changer that it introduced a test-runner - this made the integration between the headless browser and the actual test code much smoother.

In this tutorial, our main focus will be on Playwright web scraping. So what is Playwright? It’s a handy framework created by Microsoft. It's known for making web interactions more streamlined and works reliably with all the latest browsers like WebKit, Chromium, and Firefox. You can also run tests in headless or headed mode and emulate native mobile environments like Google Chrome for Android and Mobile Safari.

// playwright.config.ts import { defineConfig } from "@playwright/test"; /** * See https://playwright.dev/docs/test-configuration. */ export default defineConfig({ testDir: "./src/pages", reporter: "list", use: { baseURL: "http://localhost:5432/", }, timeout: process.env.CI ? 10000 : 4000, // ... more options });

Issues with Playwright

Fast and reliable end-to-end testing for modern web apps | Playwright

This means you cannot place test files outside of this directory, which was brought up as a question on Github some time ago. Initially, I thought it would be nice to add another folder in the repo called "scripts", but Playwright does not allow multiple testDir values.

4.Playwright: Playwright is a browser automation library by Microsoft. Key Features: Supports Chromium, Firefox, and WebKit. Provides cross-browser testing capabilities. Allows automating web, mobile, and desktop applications

HTML to PDF conversion is a common requirement in modern web applications. It allows users to save web pages, reports, and other content in a format that is easy to share and print. There are many libraries and services available for converting HTML to PDF, each with its own strengths and weaknesses. In this article, we will compare some of the most popular HTML to PDF renderers in Node.js, including Puppeteer, Playwright, node-html-pdf, and Onedoc.