Schema validator

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In a Google SEO Office Hours, Google’s Martin Splitt answered a question about structured data validation and how Google’s validator can show different results than the Schema.org validator. Structured Data Validation Both Google and Schema.org offer tools for validating if structured data is correct. Google’s tool is called the Schema.org’s tool is called the Google’s tool validates structured data and it also offers feedback on whether the tested structured data qualifies for rich results in the search engine results pages. Rich results are enhanced search listings that makes the listing stand out on the search results. The Schema.org Schema Markup Validator checks if the structured data is valid according to the official standards. Why Does Google’s Validator Differ From Schema.org? One would think that both structured data validators are validating by the same rules. So it’s a good question as to why both validators may show different results. The person asking the question noted that their structured data validated perfectly on the Schema.org but not with Google’s validator. They asked: “Why does structured data show errors on Google but not schema.org? Google Search Console is showing errors for invalid enum value in field ‘ returnFees‘ but our schema.org test says no error. Please advise.” Google’s Martin Splitt answered: “Schema.org is an open and vendor-independent entity that defines the data types and attributes for structured data. Google, as a vendor however, ...

Google's Martin Splitt responded to a query on structured data validation and how Google's validator can produce different findings than the Schema.org validator at a Google SEO Office Hours. What is Structured Data Validation? Tools are available from both Google and Schema.org to ensure that structured data is accurate. The Rich Results Test is the name of Google's tool. The Schema Markup Validator is a tool created by Schema.org. The Google tool checks structured data for accuracy and provides comments on whether the data meets the requirements for rich results in the search engine results pages. Rich results are search results that have been upgraded so that the listing stands out more. The structured data is examined to see if it complies with recognised standards using the Schema.org Schema Markup Validator. Why Do Google's Validator and Schema.org Differ? One can assume that both structured data validators use the same standards for verifying data. So, it seems sensible to wonder why the findings from the two validators may be different. The user who posed the query remarked that while Google's validator failed to validate their structured data, it did so flawlessly on Schema.org. They asked, “Why does structured data show errors on Google but not schema.org? Google Search Console is showing errors for invalid enum value in field ‘returnFees’ but our schema.org test says no error. Please advice.” Google’s Martin Splitt answered, “Schema.org is an open and vendor-ind...

I am still a little confused. @cheesus just to clarify, when you say "works like a charm" are you saying you converted YAML in to JSON and then validated it with JSON schema tools (like ajv) or are those tools somehow meant to work directly with YAML? (They don't in my experience, and I would not expect them either. Just the phrase "JSON Schema can be used with most YAML documents" reads like they should?!?) Could someone please clarify. Thank you. @McKrassy, yes, JSON Schema can indeed be used with YAML files, without converting them to JSON. When thinking about this, you should regard both JSON and YAML files as tree structures. JSON Schema place constraints on these tree structures, so they apply to both JSON and YAML files. Here's an example of a JSON schema used for YAML: I wonder if it would make sense to reuse JSON schema for this. YAML can be easily converted to JSON without loosing any information (?), so in theory YAML could be validated by the same tool chain, allowing open source community to concentrate on one good schema tool chain. The schema itself could also be written in YAML and converted to JSON. Good idea. Googled this up because I was looking for the same. It's possible to convert YAML to XML in a defined manner (similarly to JSON XML) and validate with a standard XML validator. Depending on your platform, there are tools or snippets for that conversion: If done using an API, the error positions can even be mapped back to the original YAML file. @Aka...

What is Yup? Yup is a JavaScript schema builder, parser, and validator. You define an object schema, which you can then use to either validate the shape of an existing value or transform an existing value to match the schema. Yup email validation allows you to perform client side validation of emails, passwords, phone numbers, and other form elements. What is Yup Formik? Yup and Formik are both packages that can be installed into a React application. Formik is built specifically to work with React, but Yup can be used with any front-end framework. Formik is a form-building library. It provides you with out-of-the-box React form elements that can be quickly added to your React app. It takes care of the boilerplate, and automates the repetitive tasks of form-building, like error handling, validation, and visited/required fields. Yup is a validation library that can be used in tandem with Formik. Yup provides the schema to validate the form fields you’ve built with Formik. Together, they are a powerful tool for quickly building robust, performant React forms. Can You Use Yup Without Formik? Yes, you can use Yup without Formik, and you can use Formik without Yup. However, if you're building a React application, ‍ Don’t reinvent the wheel, use Abstract’s suite of Yup Email Validation: JavaScript Email Validation Example Using Yup for email validation is straightforward. Yup provides two email validation methods: the string.email object and the string.matches object. Let’s use a...

Use our XML validator to syntax-check your XML. Well Formed XML Documents An XML document with correct syntax is called "Well Formed". The syntax rules were described in the previous chapters: • XML documents must have a root element • XML elements must have a closing tag • XML tags are case sensitive • XML elements must be properly nested • XML attribute values must be quoted Tove Jani Reminder Don't forget me this weekend! XML Errors Will Stop You Errors in XML documents will stop your XML applications. The W3C XML specification states that a program should stop processing an XML document if it finds an error. The reason is that XML software should be small, fast, and compatible. HTML browsers are allowed to display HTML documents with errors (like missing end tags). With XML, errors are not allowed. Syntax-Check Your XML To help you syntax-check your XML, we have created an XML validator. Try to syntax-check correct XML : ToveJaniReminderDon't forget me this weekend! Try to syntax-check incorrect XML : ToveJaniReminderDon't forget me this weekend! Try to syntax-check your own XML : Valid XML Documents A "well formed" XML document is not the same as a "valid" XML document. A "valid" XML document must be well formed. In addition, it must conform to a document type definition. There are two different document type definitions that can be used with XML: • DTD - The original Document Type Definition • XML Schema - An XML-based alternative to DTD A document type definitio...

npm install ajv@6 See Ajv takes a schema for your JSON data and converts it into a very efficient JavaScript code that validates your data according to the schema. To create a schema you can use either For example, to validate an object that has a required property "foo" (an integer number), an optional property "bar" (a string) and no other properties: Ajv compiles schemas to functions and caches them in all cases (using the schema itself as a key in a Map), so that the next time the same schema object is used it won't be compiled again. Best performance: compile and getSchema methods The best performance is achieved when using compiled functions returned by compile or getSchema methods. While execution of the compiled validation function is very fast, its compilation is relatively slow, so you need to make sure that you compile schemas only once and re-use compiled validation functions. See Save errors property Every time a validation function (or ajv.validate) is called the errors property is overwritten. You need to copy the errors array reference to another variable if you want to use it later (e.g. in the callback). See New Ajv can compile efficient parsers and serializers from Serializing the data with a function specialized to your data shape can be more than 10x compared with JSON.stringify. Parsing the data replaces the need for separate validation after generic parsing with JSON.parse (although validation itself is usually much faster than parsing). In case your...