Found 95 packages
This is an agile HTML parser that builds a read/write DOM and supports plain XPATH or XSLT (you actually don't HAVE to understand XPATH nor XSLT to use it, don't worry...). It is a .NET code library that allows you to parse "out of the web" HTML files. The parser is very tolerant with "real world" malformed HTML. The object model is very similar to what proposes System.Xml, but for HTML documents (or streams). --------------------------------------- This library is sponsored by ZZZ Projects: https://entityframework-extensions.net/ https://eval-expression.net/ https://dapper-plus.net/ --------------------------------------- HAP is trusted by companies worldwide with over 150 million downloads.
Classes to represent, construct, parse, serialize and validate entity data models. Supports OData v4 and v4.01. Targets .NET 8 or above. OData .NET library is open source at http://github.com/OData/odata.net. Documentation for the library can be found at https://docs.microsoft.com/en-us/odata/.
Deprecated as there's new maintainer for original HAP project. Please check the new repo at https://github.com/zzzprojects/html-agility-pack. This is a port of HtmlAgilityPack library created by Simon Mourrier and Jeff Klawiter for .NET Core platform. This NuGet package supports can be used with Universal Windows Platform, ASP.NET 5 (using .NET Core) and full .NET Framework 4.6. Original description: This is an agile HTML parser that builds a read/write DOM and supports plain XPATH or XSLT (you actually don't HAVE to understand XPATH nor XSLT to use it, don't worry...). It is a .NET code library that allows you to parse "out of the web" HTML files. The parser is very tolerant with "real world" malformed HTML. The object model is very similar to what proposes System.Xml, but for HTML documents (or streams).
Document .Net is 100% C# managed library which gives you API to create, parse, load, modify, convert, edit, generate pie charts, merge, do mail merge and digitally sign documents in PDF, DOCX, RTF, HTML and Text formats. Rasterize documents to Images and render to WPF Framework Element. + Completely created in managed C#. No Microsoft Office automation. + Has own DOCX parser and writer according to ECMA-376 specification. + Has own RTF parser and writer according to RTF 1.8 specification. + Has own PDF parser and writer according to PDF reference 1.7. + Has own HTML writer according to HTML5 reference. + Create PDF/A compliance documents. + Digitally sign PDF documents. + Multi-platform: Windows / macOS / Linux.
The Universal Device Detection library for .NET that parses User Agents and detects devices (desktop, tablet, mobile, tv, cars, console, etc.), clients (browsers, feed readers, media players, PIMs, ...), operating systems, brands and models. This is a port of the popular PHP device-detector library to C#. For the most part you can just follow the documentation for device-detector with no issue.
ByteScout Document Parser SDK for .NET, ASP.NET, ActiveX - parse data from PDF documents and images.
Recommended Google client library to access the Google Document AI API (v1), which is a service to parse structured information from unstructured or semi-structured documents using state-of-the-art Google AI such as natural language, computer vision, translation, and AutoML.
The Universal Device Detection library for .NET that parses User Agents and detects devices (desktop, tablet, mobile, tv, cars, console, etc.), clients (browsers, feed readers, media players, PIMs, ...), operating systems, brands and models. This is a port of the popular PHP device-detector library to C#. For the most part you can just follow the documentation for device-detector with no issue.
This is an agile HTML parser that builds a read/write DOM and supports plain XPATH or XSLT (you actually don't HAVE to understand XPATH nor XSLT to use it, don't worry...). It is a .NET code library that allows you to parse "out of the web" HTML files. The parser is very tolerant with "real world" malformed HTML. The object model is very similar to what proposes System.Xml, but for HTML documents (or streams).
MimeKit is an Open Source library for creating and parsing MIME, S/MIME and PGP messages on desktop and mobile platforms. It also supports parsing of Unix mbox files. Unlike any other .NET MIME parser, MimeKit's parser does not need to parse string input nor does it use a TextReader. Instead, it parses raw byte streams, thus allowing it to better support undeclared 8bit text in headers as well as message bodies. It also means that MimeKit's parser is significantly faster than other .NET MIME parsers. MimeKit's parser also uses a real tokenizer when parsing the headers rather than regex or string.Split() like most other .NET MIME parsers. This means that MimeKit is much more RFC-compliant than any other .NET MIME parser out there, including the commercial implementations. In addition to having a far superior parser implementation, MimeKit's object tree is not a derivative of System.Net.Mail objects and thus does not suffer from System.Net.Mail's limitations. API documentation can be found on the web at http://www.mimekit.net/docs For those that need SMTP, POP3 or IMAP support, check out https://github.com/jstedfast/MailKit
Event Tracing for Windows (ETW) is a powerful logging mechanism built into the Windows OS and is used extensively in Windows. You can also log ETW events yourself code using the System.Diagnostics.Tracing.EventSource class. The TraceEvent library conains the classes needed to control ETW providers (including .NET EventSources) and parse the events they emit. The library includes -- TraceEventSession which can enable ETW providers, -- EtwTraceEventSource which lets you read the stream of ETW events, and -- TraceLog which is is digested form of ETW events which include decoded stack traces associated with the events. See https://github.com/Microsoft/perfview/blob/master/documentation/TraceEvent/TraceEventLibrary.md for more.
Aspose.HTML for .NET is a cross-platform class library that works as a headless browser, seamlessly integrating with .NET, C#, VB.NET, and ASP.NET applications. It supports HTML5, CSS3, SVG, and Canvas while building a Document Object Model (DOM) based on the WHATWG standard. Developers can navigate and manipulate HTML documents using DOM traversal, XPath, CSS selectors, or JavaScript. Along with a wide range of functions for programmatic work with HTML content, the library allows users to load, read, convert, and render SVG, MHTML, Markdown, and EPUB documents. Aspose.HTML for .NET provides robust data extraction capabilities, enabling you to parse and extract information from HTML documents. It also supports binding data from XML or JSON sources to HTML templates, making it ideal for generating dynamic content. Additional features include CSS extraction, document sandboxing, SVG file management, support for asynchronous operations, custom output stream handling, real-time DOM observation using MutationObserver, an HTML form editor, comprehensive web accessibility testing, and more. Aspose.HTML for .NET provides comprehensive format conversion support, enabling your applications to convert from HTML, XHTML, SVG, EPUB, MHTML, and Markdown documents to various formats, including PDF, XPS, DOCX, images, etc. It is optimized for handling complex and large-scale documents, making it ideal for web automation, content creation and management.
This library allows our fellow programmers to easily parse some command line arguments without having spend hours reading the documentation. SimpleArgParse is inspired by the python module 'argparse' and was created due to the lack of easy-to-use argument parsers.
Create and parse UBL documents in C# with UblSharp.
MultiParse is a mathematical expression parser written in the .NET framework. The focus of the project is building a highly customizable expression parser. This involves custom types, custom operators and custom functions. Also dynamic/static variables are perfectly feasible. Find the project with more documentation at http://multiparse.codeplex.com/! Features: - Custom user-defined data types C# native data types have been implemented Boolean/bool Byte/byte, Char/char, SByte/sbyte Int16/short, UInt16/ushort, Int32/int, UInt32/uint, Int64/long, UInt64/ulong, Decimal/decimal String/string (supports C# escape sequences including unicode \xX(XXX) \uXXXX and \UXXXXXXXX) Single/float, Double/double DateTime is not implemented as it does not have a literal format in C#. But it can be implemented by the user. - Variables, static and dynamic. - Custom user-defined operators Default C# binary operators have been implemented for all native data types Arithmetic operators: +, -, *, /, % Relational operators: <=, >=, <, >, ==, != Logical operators: &, |, ^ Conditional operators: ||, && Default C# unary operators have been implemented for all native data types Arithmetic operators: +, - Logical operators: ~ Conditional operators: ! Explicit type casts: eg. (Boolean), (int), etc. - Customizable functions Default C# Math functions have been implemented Generic functions: Abs(), Ceiling(), Exp(), Floor(), Log(), Log10(), Max(), Min(), Pow(), Round(), Sign(), Sqrt(), Truncate() Trigometric functions: Acos(), Asin(), Atan(), Atan2(), Cos(), Sin(), Tan() Hyperbolic functions: Cosh(), Sinh(), Tanh() - Compilation at first evaluation Subsequent evaluations will use the compiled action queue.
Complete document processing library for AI, ML, and analytics. DocumentAtom provides a light, fast library for breaking input documents into constituent parts (atoms), useful for AI, machine learning, processing, analytics, and general analysis.
Best xml comment document parse utility for .NET Core and .NET 4.6+
DocumentAtom provides a light, fast library for breaking input images into constituent text parts (atoms), useful for AI, machine learning, processing, analytics, and general analysis.
ByteScout Invoice Parser SDK for .NET, ASP.NET, ActiveX - parse common data from invoices in PDF and raster image formats.
DocumentAtom provides a light, fast library for breaking input Excel (xlsx) documents into constituent parts (atoms), useful for AI, machine learning, processing, analytics, and general analysis.