![]() ![]() Please forward all queries about this project to the issue tracker. ![]() Can assign custom weights for each parser to provide a fallback priority sytem However this one tries to be more general. This library is inspired by open_graph_parser. Var data = MetadataParser.parse(document, url:myURL) get aggregated metadata, supplying a fallback URL import 'package:metadata_fetch/metadata_fetch.dart' This URL will be added in the final Metadata structure, and is used to resolve images with relative URLs (non-absolute URLs). If the parsers cannot extract a URL from the document, you may optionally provide a URL in MetadataFetch.parse(). Provide a fallback url when manually parsing Var twitterCardData = MetadataParser.TwitterCard(document) Var structuredData = MetadataParser.JsonLdSchema(document) Var htmlData = MetadataParser.HtmlMeta(document) Var ogData = MetadataParser.OpenGraph(document) Var document = responseToDocument(response) The utility function `responseToDocument` is provided or you can use own decoder/parser. Manually specify which Metadata parser to use import 'package:metadata_fetch/metadata_fetch.dart' Var data = MetadataParser.parse(document) Var document = MetadataFetch.responseToDocument(response) The utility function `MetadataFetch.responseToDocument` is provided or you can use own decoder/parser. This method prioritizes Open Graph data, followed by Twitter Card, JSON-LD and finally falls back to HTML metadata. Parsing Manually # Get aggregated Metadata from a document Print(scription) // Flutter is Google's UI toolkit for crafting beautiful. Print(data.title) // Flutter - Beautiful native apps in record time Var data = await MetadataFetch.extract(myURL) ![]() Use the `MetadataFetch.extract()` function to fetch data from the url Usage # Extract Metadata for a given URL # import 'package:metadata_fetch/metadata_fetch.dart' Supports OpenGraph, Meta, Twitter Cards, and Structured Data (Json-LD) This feature is also useful to identify spammy pages that have been “stuffed” with hundreds of Meta Keywords or long Meta Descriptions that was common practice in SEO many years ago but now may be harming your rankings.Īlso the Meta harvester is ideal to use to harvest all the keywords for your competitors pages, then transfer these to the ScrapeBox keyword scraper to get further keyword suggestions from Google Suggest,, YouTube etc for further analysis and promotion.A dart library for extracting metadata in web pages. So poorly created Titles and Descriptions can impact click through’s from the engines. We store them temporarily for the only purpose: extract and visualize metadata. The page Title and Description are extremely important page attributes, because search engines display this information in the search result pages. We respect your privacy and never share your uploads with others. When exporting you also have the option to export URL’s, Titles, Descriptions, Keywords or any combination of one or more of these fields.īeing able to harvest meta information is great for competitor research, or auditing your own websites Titles and Descriptions to ensure they are optimal for your webpages as many CMS platforms auto-generate these fields. This feature is multi-threaded and can harvest the data from hundreds of pages per minute, once finished you can filter the data by removing urls with errors, or for example urls without meta keywords. ScrapeBox offers a Meta Grabber feature, this enables you to load a list of urls and extract the page Titles, Descriptions and Keywords for every URL in the list. ![]()
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