
ASP.NET
Ruby on Rails
Django
Node.js
Laravel
ExpressJS
Flask
Meteor
DocParser
Nanonets
Parseur.com
Rossum
Docsumo
FlexiCapture
Amazon Textract
Parsio.io
ASP.NET
DocParser{"enterprises" => "Ideal for enterprise-level applications requiring high security, performance, and scalability.", "developers_with_c#" => "Highly suitable for developers with a background in C#, offering seamless integration with existing .NET applications.", "large_web_applications" => "Perfect for developing large web applications, API services, and microservices.", "teams_using_microsoft_stack" => "Best for development teams already using the Microsoft technology stack, including Azure services."}
Based on our record, ASP.NET should be more popular than DocParser. It has been mentiond 26 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.
Based on libuv, the library that significantly influenced Node.js, Microsoft modernized the aging ASP.NET with ASP.NET Core starting in 2014. Later, Kestrel, a .NET-based engine, was added as a modern foundation. Minimal APIs marked ASP.NET Coreโs arrival in modern web development in 2021. - Source: dev.to / 7 months ago
Learn how to integrate n8n workflows into ASP.NET Core applications. API integration guide for triggering automations from your C# backend. - Source: dev.to / 7 months ago
In the Microsoft world, it is the direct equivalent of ASP.NET Core. Phoenix is known for high developer productivity and exceptional application performance. - Source: dev.to / 8 months ago
Why Use .NET for Microservices? There are many reasons why .NET is a solid choice for microservices development. Cross-platform support: Using .NET Core and the newer .NET versions (6, 7, and 8), you can deploy your services across Windows, Linux, and macOS platforms. This is useful when deploying to cloud environments like Azure, AWS, or even on-premises. Performance: .NET is known for its high performance. It... - Source: dev.to / 12 months ago
Most of the books teach C# and .NET, ASP.NET, Blazor, or T-SQL. I also found some .NET-specific coverage of wider topics: architecture and design, concurrency, automated tests, functional programming, and dependency injection. - Source: dev.to / over 1 year ago
You could try an online service like https://extract-io.web.app/ or https://docparser.com/. Source: about 3 years ago
DocParser: DocParser simplifies the extraction of structured data from various file formats, such as PDFs and scanned documents, directly into Google Sheets. By automating this process, DocParser saves valuable time and effort otherwise spent on manual data entry. Link to DocParser. Source: about 3 years ago
There are several tools available today that can help you extract tables from PDF files (such as Tabula), or even parse PDFs into structured JSON using AI (like Parsio -> I'm the founder) or without AI (like Docparser). Source: over 3 years ago
Thank you for sharing those! I didn't know them I've only checked this one https://docparser.com/ and I think my solution could be better because it will be easier for the user. Source: over 3 years ago
As previously suggested, if the layout of your PDFs never changes (consistent column widths in tables and placement), you can use a zonal PDF parser like DocParser. Alternatively, an AI-powered parser may be a better choice. Source: over 3 years ago
Ruby on Rails - Ruby on Rails is an open source full-stack web application framework for the Ruby programming...
Nanonets - Worlds best image recognition, object detection and OCR APIs. NanoNetsโ platform makes it straightforward and fast to create highly accurate Deep Learning models.
Django - The Web framework for perfectionists with deadlines
Parseur.com - Automate text extraction from emails and PDFs by using our powerful email and document parser.
Node.js - Node.js is a platform built on Chrome's JavaScript runtime for easily building fast, scalable network applications
Rossum - Rossum is AI-powered, cloud-based invoice data capture service that speeds up invoice processing 6x, with up to 98% accuracy. It can be easily customized, integrated and scaled according to your company needs.