SurveyJS
SurveyJS is a product family of four open-source JavaScript libraries that provide you with all the advantages of a custom-built in-house survey application while significantly reducing time-to-market and resources required to get the system up and running. The libraries are compatible with most popular JavaScript frameworks and can communicate with any server that can post and get a request in JSON format, which makes them server- and database-agnostic.
The product family is composed of:
> An open-source MIT-licensed rendering library that renders dynamic JSON-based forms in your web application, and collects responses.
> An self-hosted drag-and-drop form builder that features an integrated CSS-based theme editor and a GUI for conditional rules.
> PDF Generator, a library that renders SurveyJS surveys and forms as PDF files in a browser.
> The Dashboard library that allows you to simplify survey data analysis with interactive and customizable charts and tables.
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Apify
Apify is a full-stack web scraping and automation platform helping anyone get value from the web. At its core is Apify Store, a marketplace with over 10,000 Actors where developers build, publish, and monetize automation tools.
Actors are serverless cloud programs that extract data, automate web tasks, and run AI agents. Developers build them using JavaScript, Python, or Crawlee, Apify's open-source library. Build once, publish to Store, and earn when others use it. Thousands of developers do this - Apify handles infrastructure, billing, and monthly payouts.
Apify Store has ready-made Actors for scraping Amazon, Google Maps, social media, tracking prices, lead-gen, and more.
Actors handle proxies, CAPTCHAs, JavaScript rendering, headless browsers, and scaling. Everything runs on Apify's cloud with 99.95% uptime. SOC2, GDPR, and CCPA compliant.
Integrate with Zapier, Make, n8n, and LangChain. Apify's MCP server lets AI like Claude dynamically discover and use Actors
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Mako
It provides a familiar, non-XML syntax that compiles into Python modules for maximum performance. Mako's syntax and API borrows from the best ideas of many others, including Django and Jinja2 templates, Cheetah, Myghty, and Genshi. Conceptually, Mako is an embedded Python (i.e. Python Server Page) language, which refines the familiar ideas of componentized layout and inheritance to produce one of the most straightforward and flexible models available, while also maintaining close ties to Python calling and scoping semantics. As templates are ultimately compiled into Python bytecode, Mako's approach is extremely efficient and was originally written to be just as fast as Cheetah. Today, Mako is very close in speed to Jinja2, which uses a similar approach and for which Mako was an inspiration. Can access variables from their enclosing scope as well as the template's request context
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