How To Fix Schema Validation Errors?

To help prevent schema validation Errors, please check the information below in your return.

  1. Update to the current version of the tax program.
  2. Avoid using government form overrides.
  3. Avoid using the special characters: ‘#’, ‘[‘and ‘]’ in your data entry.

How do I fix a schema error?

The process for fixing schema errors using other schema types (Microdata or RDFa) may differ, but the steps to find them are the same. Different Ways to Use Google’s Structured Data Tool

  1. Help create your schema.
  2. Fix schema code for errors.
  3. Check web page for errors after inserting schema.
  4. Check competitors schema.

How do you validate a schema?

Each schema has an associated checkbox, which you can use to select the schema to validate the incoming message. Note: If you have a WSDL file that contains an XML Schema, and you want to use this schema to validate the message, you can import the WSDL file into the Web Services Repository.

What are schema errors?

Schema errors occur where there is a problem with the structure or order of the file, or an invalid character is included. Schema errors prevent the validation being run in full because the file cannot be read. This means that errors cannot be traced to a particular record.

What causes validation error?

It is precisely because validation errors can be caused by such a wide range of reasons (i.e. the input’s content, length, formatting, etc ) that it is so important to let the user know exactly why their input failed because they’ll otherwise have to try and work it out themselves.

What is schema validation error?

A schema validation error is an error in the required formatting of the electronic file established by the taxing authority which can be caused by missing or invalid information. This return contains one or more eFile schema validation errors.

How do I find schema errors?

How do I find errors in my schema markup? The first step is to make sure that your markup is on the page using the Schema Markup Validator (SMV). You can also use Google Search Console to report on the rich results or features tied to certain structured data.

What is schema validation in API?

JSON Schema is a vocabulary that allows you to annotate and validate JSON documents. It describes your existing data format with clear, human- and machine-readable documentation for complete structural validation, useful for automated testing and validating client-submitted data.

What is JSON Schema validation?

Overview. JSON Schema validation asserts constraints on the structure of instance data. An instance location that satisfies all asserted constraints is then annotated with any keywords that contain non-assertion information, such as descriptive metadata and usage hints.

What is schema validation in SQL?

Database schema validation is related to check whether a database schema correctly and adequately describes the user intended needs and requirements. This is an increasingly important problem in database engineering, particularly since database schemas are becoming more complex.

What is schema in XML example?

XML Schema is commonly known as XML Schema Definition (XSD). It is used to describe and validate the structure and the content of XML data. XML schema defines the elements, attributes and data types. It is similar to a database schema that describes the data in a database.

What is XML schema invalid?

You can get an ‘invalid XML error’ message if you have altered or edited the XML file generated from the ITR utility/form before uploading the same to the portal. If using the Excel utility to file ITR, the computer used for generating the XML does not have the. Net 3.5 framework installed or enabled.

What is the purpose of schema?

The purpose of a schema is to define and describe a class of XML documents by using these constructs to constrain and document the meaning, usage and relationships of their constituent parts: datatypes, elements and their content, attributes and their values, entities and their contents and notations.

How do I fix validation error in GST?

Taxpayer must verify the Name and Date of Birth related details submitted by him in Promoter /Partner and Auth. signatory tab. Put these details from taxpayers Income Tax Profile and not as printed on copy of PAN Card.

What is meant by validation error?

Validations errors are errors when users do not respond to mandatory questions. A validation error occurs when you have validation/response checking turned on for one of the questions and the respondent fails to answer the question correctly (for numeric formatting, required response).

What is training and validation error?

Your performance on the training data/the training error does not tell you how well your model is overall, but only how well it has learned the training data. The validation error tells you how well your learned model generalises, that means how well it fits to data that it has not been trained on.

Understanding schema errors

  • So, what exactly is a schema error? Recognizing and correcting schema problems
  • Examples of schema flaws for the DLHE record that have been worked out
  • Identifying and correcting the mistake

What is a schema error?

It explains the structure of the XML document (number of elements, whether an element can be empty, default/fixed values, and so on), as well as the entries that are valid in the document. The XSD is responsible for defining the schema. An error in the file’s structure or order occurs when an invalid character is included, or when the file’s structure or order is incorrect. Because the file cannot be read, schema flaws prohibit the validation from being completed in its entirety. This implies that errors can’t be traced back to a specific piece of information.

Tip: If you open the raw data in a text editing application, the line numbers will be visible.

Understanding schema errors

First-time users may find it challenging to comprehend the terminology used to explain a schema problem due to its complexity. A glossary of words has been provided below to aid you in detecting and correcting any problems that may have occurred.

Expression Meaning
Schema The schema describes the structure of the XML document (number of elements, whether an element can be empty, default/fixed values, etc.) and valid entries. The schema is defined by the XSD.
Entity A single entity name groups together a set of fields which have the same relationship.
Field A field is an attribute (data item) of an entity. This refers to the short field name as shown in the coding manual.
Reason for null Used to describe a field requiring an explanation for a null value. It must be accompanied by a reason code, for example. 2: not sought, 3: refused or 9: not applicable.
Parent element XML is made up of elements. Entities are known as the ‘parent elements’.
Child element XML is made up of elements. Fields are known as ‘child elements’ as they belong to a ‘parent element’ (i.e. entity).
Nested Elements (fields and entities) can belong to one each other and thus are nested.

Worked examples of schema errors for the DLHE record

In these situations, the error message indicates that the value returned is invalid, which is correct. This indicates that it does not correspond to the valid entries listed in the field descriptions. ” indicates that the value is absent, and as a result, the file has an empty field in the location where the value is referred as ” This is what the file would look like within it: EMPBASIS/EMPBASISorEMPBASIS/EMPBASIS There are no blank values permitted in the XML format; thus, each field in the file must have an acceptable code.

If, on the other hand, no value can be determined and the field is not necessary for the record, you should consider removing the field from the file completely.

In this version of the error message, a code has been returned; however, the code does not adhere to the schema and is thus considered to be invalid.

If you see this error message, you must go back through your submission and make any necessary changes.

2)Invalid child elements

Inside the schema, a parent element refers to the entity or set of fields, and a child element refers to a single field within the entity. The DLHE record, for example, contains an element called ‘Employment,’ which is an entity and hence a parent element, but the field ‘SALARY’ is a child element. It signifies that the fields inside an entity in the file are not in the right sequence as prescribed by the schema when the error message relates to an incorrect child element (XSD). This might indicate that a field is missing entirely, or that existing fields are not located in the proper location.

This is illustrated in the following example, where the problem appears at line 11 of the file and is related to the Employment entity: In this case, the SALARY field is the unexpected field because the EMPBASIS field was predicted by validation.

Review the raw data file and examine the fields in this entity, making any required modifications before resubmitting the data to address the problem. In some cases, the schema tree diagram can aid you in determining the right sequence and, as a result, in correcting the problem with the file.

The raw data contains: Looking at the schema for this collection, it can be seen that the following fields are in the wrong order: Therefore the correct structure would be:

3)Incomplete content

Similarly to the invalid child element issue described above, this sort of error occurs when fields from the parent element or entity are missing from the child element or entity. A compulsory or mandatory field that has been omitted from the record because the value is unknown may result in this error. In this scenario, you would need to track down the missing information and make certain that it is included in the XML extract that was provided. As seen in the error message above, when the ALLACT field validation was completed, the entity was expecting to see the HEWORKEXP field in the file, however as shown in the extract below, the entity ended without this field being present:

The raw data contains: Looking at the schema for this collection, it can be seen that the following fields are missing: Therefore the correct structure would be:

4)Invalid character

When an unusual character is encountered in a file, this sort of error will occur. This might be something that does not belong under the data type, such as a character that is not in the UTF-8 encoding. It can be seen in the sample below that a tag is missing from one of the fields, resulting in the validation failing.

5)Missing closing tag

This sort of error happens when a closing tag is absent from an object or field. It’s important to remember that each field or entity must be opened and closed appropriately in order for validation to read the file correctly. If, for example, the final closing tag of/DLHERecordis absent in this error, it signifies that the file structure does not conform to the schema description, as seen in the following example.

Locating the error

It is possible to locate information in the ‘location’ part of the error notice to aid institutions in locating the problem inside the file using the validation kit. Often, this will be little more than a line reference (as in the example below). When you open the raw data in a text editor, you will be able to see line references that will allow you to locate the affected line of data. Keep in mind, however, that schema errors mean that the validation kit cannot read the file, and so once something wrong is discovered, validation will stop because it will be unable to proceed any further.

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Schema errors are intended to provide as much location information as feasible; nevertheless, the quantity of information given may vary depending on how far within the file the validation program has progressed and the nature of the problem encountered.

Schema Validation

The following settings are available on theAdvanced tab:Allow RPC Schema Validation:When theAllow RPC Schema Validationcheckbox ischecked, the filter will make abest attemptto validate an RPC encoded SOAP message.An RPC encoded message is defined in the WSDL as having an operation with the following characteristics:
  • A value of “document” has been assigned to the styleattribute of thesoap:operationelement. Use of the rpc property on the soap:body element is specified.

Please refer to Section 3.5 of the WSDL standard, which outlines the various values that can be assigned to these characteristics. According to the WSDL specification, the difficulty with RPC encoded SOAP messages in terms of schema validation is that the schema included inside the WSDL file does not necessarily specify the structure of the SOAP message, as is the case with “document-literal” style messages, for instance. When sending a message via an RPC encoded operation, the message format can be determined by a mix of the SOAP operation name, WSDL message elements, and schema-defined types.

Another issue with RPC-encoded messages is that type information is supplied in each element that appears inside the SOAP message, which causes confusion.

It eliminates the type declarations from the message and then performs the most reasonable attempt to validate it.

A binary data attachment (similar to SOAP with Attachments) can be sent as a MIME attachment (similar to SOAP with Attachments) to a SOAP message using the include technique given by XOP (XML Optimized Packaging).

Through the use of thexop:Includeelement, the binary data may subsequently be accessed from within the SOAP message. As an example, consider the following SOAP request, which contains a binary image that has been base64-encoded in order to be used as the content of theimageelement:

?xml version=”1.0″ encoding=”UTF-8″?soap:Envelope xmlns_soap=”soap:BodyuploadGraphic application/xop+xml”; start=” [email protected] “; start-info=”text/xml”-MIME_boundary Content-Type: application/xop+xml;charset=UTF-8;type=”text/xml” Content-Transfer-Encoding: 8bit Content-ID:[email protected]?xml version=”1.0″ encoding=”UTF-8″?soap:Envelope xmlns_soap=”soap:BodyuploadGraphic image” maxOccurs=”1″ minOccurs=”1″ type=”xsd:base64Binary”xmime:expectedContentTypes=”*/*”xsi:schemaLocation=”xmlns:xmime=”
In this case, the XML Schema validator will expect the contents of the imageelement to bebase64Binary.However, if the message has been formatted as an MTOM message, theimageelement will contain a child element,xop:Includethat the Schema know nothing about.This will, of course, cause the schema validator to report an error and the schema validation will fail.To resolve this issue, you can check theInline MTOM Attachments into Messagecheckbox on the Advancedtab.At run-time, the schema validator willreplace the value of thexop:Includeelement with thebase64-encoded contents of the MIME part to which it refers.This means that the message will now adhere to the definition of theimage element in the XML Schema, i.e. the element will contain data of type base64Binary.This standard procedure of interpreting XOP messages is described inSection 3.2 Interpreting XOP Packagesof the XML-binary OptimizedPackaging (XOP) specification.

How to fix xsd schema validation errors? (rephrased)

596 times it has been asked and seen After making a complete mess of my earlier question, here is another shot at it. I’m attempting to construct an XSD schema based on an example from the Microsoft Developer Network. Instead of using a namespace, I’ve adjusted the example such that the XSD is local to the xml file and does not reference any other XSDs. The XML, on the other hand, does not pass validation. The following XSD file (leda sys params.xsd) is included:xs:schema xmlns_xs=” targetNamespace=”qualified” xmlns_xs=” targetNamespace=”qualified” xs:annotation xs:documentation xml_lang=”en”’s purchase order structure is shown below.

Copyright 2000 is a trademark of Microsoft Corporation.

/xs:documentation xs:appinfoApplication information.

/xs /xs:element name=”zip” type=”xs:decimal” /xs:element name=”zip” type=”xs:decimal” /xs:sequencexs:attribute name=”country” type=”xs:NMTOKEN” fixed=”US” /xs:sequencexs:attribute name=”country” type=”xs:NMTOKEN” fixed=”US” /xs:complex Typexs:complex Name of the type “Items” “item” is the name of an xs:sequencexs:element in a sequence.

-xs:simple name=”SKU” is a kind of identifier.

version=”1.0″ in the xml encoding=”UTF-8″?

/commentitemsitem partNum=”872-AA”productName Lawnmower /productNamequantity 1 /quantityUS/commentitemsitem partNum=”872-AA”productNamequantityUS/commentitemsitem partNum=”872-AA”productNamequantityUS/commentitemsitem partNum=”872-AA”productNamequantityUS/commentitemsitem part Price: 148.95 dollars (US).

Comments and itemitems with partNum=”926-AA”productName Baby Monitor and quantity 1 and quantity US are accepted.

Priceship Date: May 21st, 1999 /ship: Date/item/items/purchase Order The XML fails to pass validation because it contains the following errors: 3 145: Error: The target namespace of the schema document ‘leda sys params.xsd’ differs from the target namespace of the instance document “, which is defined in the instance document “.

Line 3 contains all of the mistakes.

asked At 13:23 on July 11, 2016, DavidADavidA has received 1,6956 gold badges.

You must have an XML instance with elements in the same namespace as the elements you defined in the targetNamespace (as shown by the URL in the attachment).

At 13:55 on July 11, 2016, potamepotame6,9774 gold badges22 silver badges31 bronze badges potamepotame6,9774 gold badges 4

Not the answer you’re looking for? Browse other questions taggedxmlxsdorask your own question.

Toggle the table of contents sidebar on or off. An incorrect instance will cause a ValidationError to be thrown or returned, depending on which method or function is being used to handle the situation. exceptionjsonschema.exceptions. ValidationError(message,validator= unset,path=(),cause=None,context=(),validator value= unset,instance= unset,schema= unset,schema path=(),parent=None): a validation error has occurred. An instance was found to be invalid under the schema that was given. The information carried by an error may be broken down into the following categories: message¶ A message that can be understood by humans describing the mistake.

  • In the schema, the value for the failed validator is specified.
  • Depending on how a$refwas followed, this might be a subschema from inside the schema that was handed in initially, or it could be a totally other schema.
  • absolute schema path¶ There is an acollections.deque storing the route to any failed validator within the schema, but it is always relative to the original schema and not to any subschema (i.e.
  • schema path¶ The same as relative schema path.relative path.relative path.
  • If the issue occurred at the root of the instance, the deque may be completely empty.
  • In all cases, the absolute path is measured in relation to the initial instance that was verified (i.e.
  • If the issue occurred at the root of the instance, the deque may be completely empty.

path¶ The same as the instance of relative path.

If the validator object was in the midst of verifying a (potentially nested) element within the top-level instance, the instance passed intovalidate will be different from the instance passed intovalidate originally.

context¶ If the problem was caused by mistakes in subschemas, the list of errors from the subschemas will be available on this property if the issue was caused by faults in the parent scheme.

These mistakes will be positioned in relation to the original error.

For the time being, this is solely utilized for the exception caused by a failed format checker in the jsonschema framework.

If there wasn’t one, there was none.


A schema was found to be invalid under the conditions of its related metaschema.

These characteristics can be better understood via the use of a brief illustration: schema={“items”:{“anyOf”:[,]}} instance=v=Draft7Validator(schema)errors=sorted(v.iter errors(instance),key=lambdae:e.path) As a stand-alone, the error messages in this case are not particularly useful.

‘foo’ is not valid under any of the schemas that have been provided.

For the sake of this example, ValidationError.path will have only one element, which will be the index in our list.

Using the ValidationError.instance and ValidationError.schemaattributes, we can see that this is the case.

Because these errors originated in two different subschemas, it may be beneficial to examine theValidationError.schema pathattribute as well to determine precisely where in the schema each of these problems originated.

the mistake originating from the parent 3 is not of the type’string’, 3 is less than the minimum of 5, ‘foo’ is too long, ‘foo’ is not of the type ‘integer’, 3 is not of the type’string’, 3 is not of the type ‘integer’, 3 is less than the minimum of 5, In order to make debugging errors easier, the string representation of an error incorporates some of these properties.

3 is not valid under any of the schemas that have been provided. Validating ‘anyOf’ in schema:,]On instance: 3 failed due to an error.

ErrorTrees ¶

If you want to be able to query whether properties or validators failed while validating a specific instance programmatically, you will most likely want to do it using the jsonschema.exceptions function. ErrorTreeobjects.classjsonschema.exceptions.ErrorTree(errors=())¶ The use of ErrorTrees makes it easy to determine which validations were unsuccessful. errors ¶ At this level of the tree, the mapping of validator names to error objects (typically jsonschema.exceptions.ValidationErrors) is defined.

  • _getitem (index)¶ Retrieve the child tree one level below at the specified index by using getchildtree(index).
  • _getitem_ will be propagated (typically, this is a subclass of LookupError.
  • Iterate (non-recursively) across the indices in the instance containing errors to find the root cause.
  • return repr() (self).

In the whole tree, including children, the total number of mistakes is calculated as Consider the following illustration: schema={“type”:”array”,”items”:,”minItems”:3,} instance=For the interest of clarity, the following three faults can be found in the supplied instance under this schema: v=Draft3Validator(schema)forerrorinsorted(v.iter errors(),key=str): print(error.message)’spam’ is not of the type ‘number,’ according to the error message.

  1. ‘spam’ is not one of them since it is too short.
  2. tree=ErrorTree (v.iter errors(instance)) As you can see, jsonschema.exceptions is a kind of exception.
  3. Validator.iter errorsmethod.
  4. Checking whether a certain piece in our instance failed validation is the first task we would wish to do in this section.
  5. it was valid).
  6. (tree.errors) We can see that theenumandtypevalidators failed for index0 in this section of the code.
  7. It is not of type ‘number’, as shown by print(tree.errors.message).
  8. That’s because minItemsis a fault that applies to the whole instance, not just to a single item.
  9. “minItems”intree.errors True That’s all there is to it when it comes to using error trees.

ErrorTree.errors is a dict that translates the failed validator name to the associated validation error for each tree and child in the tree and child hierarchy.

best_match and relevance ¶

Thebest match function is a straightforward yet helpful function for attempting to identify the most relevant error from a collection of errors. fromjsonschemaimportDraft7Validatorfromjsonschema.exceptionsimportbest matchschema= {.”type”:”array”,.”minItems”:3,.} print(best match (Draft7Validator(schema).iter errors(11)). message)11 does not belong to the ‘array’ type. match The key is (errors,key= functionby relevance,locals.relevance) in this case. Look for a mistake that looks to be the best fit among the errors that have been provided.

for which ValidationError.pathis shorter) are generally regarded better matches, because they suggest that “more” is wrong with the instance.

the deepest error is selected.

  • Errors( – a collection of errors from which to choose. You should avoid providing a combination of failures from separate validation efforts (for example, from different instances or schemas) since the resulting output will not be meaningful
  • Key( – the key to use for sorting faults in the collection. For additional information, see relevance and transitivelyby relevance (the default is to sort with the defaults of that function). This feature is only relevant if you wish to alter the function that rates errors but still require the error context descent performed by this function
  • Otherwise, this feature is not useful.

If the iterable was empty, it returns the best matching error, else it returns None. Note This function is only a heuristic in nature. In certain cases, the return value for a particular set of inputs may change from one version to the next when improved heuristics are added to the algorithm. jsonschema.exceptions.relevance(validation error)¶ A critical function that organizes mistakes according to their heuristic importance. Use this method if you wish to sort a large number of mistakes in the same direction.

This function considers anyOfandoneOfto beweakvalidation faults among the many validators that might fail, and it will order them lower in the instance than other validators at the same level that have the same chance of failing.

schema=,”properties”:,”name”:,.”phones”:,”properties”:.”home”:.,.,.,.instance=.”properties”:.”name”:,.”phones”:.”properties”:.”home”:.,.,.,.instance=.”properties”:.”name”:,.”phones”:.”properties”:.”home”:.,.,.,.instance= errors=Draft7Validator(schema).iter errors(instance) In the following example, [path.foreinsorted(errors,key=exceptions,relevance)] relevance(weak=frozenset(),strong=frozenset())¶ Create a key function that may be used to sort errors based on their relevance to the current situation.


  • Validator names that should be considered “weak” are collected into a set called Weak(set). Whenever there are two errors occurring at the same level of the instance, and one of them is contained inside the list of weak validator names, the other error will be given priority over the first. By default, anyOfandoneOfare regarded weak validators, and their mistakes will be substituted by other validation faults of the same level. The term “strong(set)” refers to a group of validator names that are considered to be “strong.”

Unexpected schema validation error received using Validate action to validate SOAP body

While submitting a request to a DataPower service that is specified with the XML or Non-XML request type, when using the Validate action with SOAP Validation set to body, an unexpected schema validation error may result.


According to the DataPower logs, the following problems have occurred:

  • 09:27:54multisteperror7716225 request
  • 0x80c00009mpgw (MyService MPG): request
  • MyService Policy Request Rule 06 validate: 0x80c00009mpgw (MyService MPG): request
  • MyService Policy Request Rule 06 validate: the ‘PIPE schema
  • Local:/MyService MPG/mySchema.xsd dpvar 1′ failed with the following errors: 2: unknown element
  • Envelope
  • The following problem occurred at 09:27:54: multisteperror7716225 request x.99.99.99.xx
  • 0x01d30003mpgw (MyService MPG): Schema Validation Error
  • 09:27:54schemaerror7716225 request
  • Mpgw (MyService MPG): The following error occurred at 09:27:54: ‘local:/My


The validate for “SOAP body” function is solely applicable to the SOAP request type itself.

Diagnosing The Problem

When both of the following conditions are met, this problem may occur:

  • The service accepts two types of requests: XML and Non-XML. An action called Validate is included in the request rule, and it performs “SOAP body” validation.

Resolving The Problem

Remove the soap:Body content by including a “Extract Using XPath” action before the Validate operation in order to remedy this problem. Define the “Extract Using XPath” action with the following parameters:

  • PIPE is the input context
  • PIPE is the output context
  • The XPath expression is “/*/* /*”

Mongoose v6.1.5: Validation

To avoid confusion when discussing validation syntax, please keep the following guidelines in mind before continuing.

  • Validation is described in theSchemaType
  • Validation is a middleware component of the application. By default, Mongoose registers validation as a apre(‘save’)hook on every schema
  • However, this may be changed. By enabling thevalidateBeforeSaveoption, you may prevent automated validation before saving from occurring. The doc.validate(callback) and doc.validateSync() functions can be used to manually conduct validation. Using the doc.invalidate(.) function, you may manually declare a field as invalid, resulting in validation failing. Undefined values do not trigger the execution of validators. The only exception is the requiredvalidator
  • Otherwise, everything is OK. Asynchronous recursive validation is used
  • When you callModel save, sub-document validation is also carried out. If an error occurs, the error is sent to yourModel savecallback. Validation is adjustable

The following functions are defined: constschema = newSchema(name: String, required:true); constCat = db.model(‘Cat’, schema); constcat = newCat();;; (error) error = cat.validateSync(); assert.equal(error.errors.message, ‘Path ‘name’ is required.’); error = cat.validateSync(); assert.equal(error.errors.message, ‘Path ‘name’ is required.’); ); error = cat.validateSync(); assert.equal(error.errors.message, ‘Path ‘name’ is required.’);

Built-in Validators

Mongoose comes with a number of built-in validators.

  • AllSchemaTypesinclude the requiredvalidator, which is integrated into the schema. For the necessary validator, the checkRequired() method of theSchemaType is used to assess whether or not the value meets the required validator. Numbershaveminandmaxvalidators
  • Strings are validated using the enum, match, minLength, and maxLength validators.

Each of the validator URLs provided above provides further information on how to activate them and modify their error messages, among other things. db.model(‘Breakfast’, breakfastSchema);constbreakfast = newBreakfast(eggs: type:Number, min:, max:12; bacon: type:Number, required: ; drink: type:String, enum:, required:function (); returnthis.bacon3; constbadBreakfast = newBreakfast(eggs: 2, bacon:0, drink:’Milk’ BadBreakfast.bacon =5; badBreakfast.drink =null;error = badBreakfast.validateSync(); assert.equal(error.errors.message, ‘Too few eggs’); assert.ok(!error.errors); assert.equal(error.errors.message, “Milk’ is not a valid enum value for path ‘drink’);badBreakfast.

Custom Error Messages

Individual validators in your schema might have their error messages configured differently. There are two approaches to set the validator error message that are functionally equivalent:

  • There is no support for the array syntax:min
  • And the object syntax:enum: is not supported’.

Mongoose also allows rudimentary templating for error messages, which is particularly useful. Mongoose substitutes the value that is being verified with the value that is being replaced. constbreakfastSchema = newSchema(eggs: type:Number, min:, max:12, drink: type:String, enum: ‘values:, message:’is not supported’); constBreakfast = db.model(‘Breakfast’, breakfastSchema); constBreakfast = db.model(‘Breakfast’, breakfastSchema); constBreakfast = badBreakfast = newBreakfast(eggs:2, drink:’Milk’); constbadBreakfast = newBreakfast(eggs:2, drink:’Milk’); Allowing for errors, leterror = badBreakfast.validateSync(); asserting that error and error messages are equal; asserting that error and error messages are equal; asserting that error and error messages are equal; asserting that error and error messages are equal; and asserting that error and error messages are equal;

TheuniqueOption is Not a Validator

Beginners frequently run into the problem of the unique option for schemas not being a validator. It’s a handy aid for creating MongoDB unique indexes that you can use anywhere. For further information, please see theFAQ. db.model(‘U1’, uniqueUsernameSchema);constdup =; U1.create(dup, err =);U2.init(). then(()=U2.create(dup)). constuniqueUsernameSchema = newSchema(username: type:String, unique:true);constU2 = db.model(‘u2’, uniqueUsernameSchema);const catch(error=assert.ok(error); assert.ok(!error.errors); catch(error=assert.ok(error.message.index); catch(error=assert.ok(error.message.index); catch(error=assert.ok(error); catch(error=assert.ok(error.message.index); catch(error=assert.ok(error.message.index); catch(error=assert The value of of(‘duplicate key error’)!=-1);

Custom Validators

If the built-in validators aren’t sufficient, you may create custom validators to meet your specific requirements. Custom validation is declared by giving a validation function to the application. You may find extensive instructions on how to accomplish this in the API documentation for the SchemaType validate() method. phone: type:String, validate: validator:function (v) return/.test(v); constuserSchema =newSchema(phone: type:String, validate: validator:function (v) return/.test(v);, message_props=’$is not a valid phone number!’, required: ); User is defined as db.model(‘user, userSchema);constuser is defined as newUser();leterror; =’555.0123’; error = user.validateSync(); assert.equal(error.errors.message, ‘555.0123 is not a valid phone number!’); =’201-555-0123′; error = user.validateSync(); assert.equal(error.errors.mes

Async Custom Validators

Custom validators can also be used in an asynchronous fashion. If your validator function returns a promise (for example, anasyncfunction), mongoose will wait for the promise to be resolved before continuing to the next step. The returned promise will be considered invalid if it rejects, or if it fulfills with the value false. userSchema = newSchema constuserSchema ( user.validate().catch(error=’Oops!’);constUser = db.model(‘User’, userSchema);constUser = newUser();constUser = newUser();constUser = newUser(); = ‘[email protected]’; = ‘test’;user.validate().catch(error=’Oops assert.ok(error); assert.equal(error.errors.message,’Oops!’); assert.equal(error.errors.message,’Email validation failed’); ); assert.equal(error.errors.message,’Oops!’); assert.equal(error.errors.message,’Email validation failed’); );

Validation Errors

The errors returned after a failed validation contain anerrorsobject whose values areValidatorErrorobjects, which are the objects that caused the failure. EachValidatorError contains the following properties: kind, path, value, and message. A ValidatorError may additionally have an areaonproperty property. It will hold the error that was thrown if an error was encountered when validating a value in the validator. The constructor toySchema is defined as: newSchema(color:String, name:String); constvalidator is defined as: function (value) return/red|white|gold/i.test(value); toySchema.path(‘color’).

Cast Errors

Prior to running validators, Mongoose makes an effort to coerce values into the proper format. This procedure is referred to as “casting the document.” Casting will fail for a given route if the error.errorsobject contains an instance of theCastErrorobject. Casting takes place before validation, and validation does not take place if casting is unsuccessful. Because of this, your custom validators may make assumptions about the values ofvisnull and undefined, as well as instances of the types given in your schema db.model(‘Vehicle’, vehicleSchema);constVehicle = db.model(‘Vehicle’, vehicleSchema);constdoc = newVehicle();consterr = doc.validateSync();;err.errors.message; constdoc = newVehicle(); constdoc = newVehicle(); cons

Required Validators On Nested Objects

The definition of validators on nested objects in mongoose is difficult due to the fact that nested objects do not represent fully fledged pathways. Allowing personSchema to be equal to newSchema(“name: “first” String, “last” String);assert.throws (function ()personSchema.path(‘name’).required(true);, (function ()personSchema.path(‘name’).required(true); It is not possible to use the word’required’. constnameSchema = newSchema(first:String, last:String);personSchema = newSchema(name: type: nameSchema, required:true);constPerson = db.model(‘Person’, personSchema);constperson = newPerson();consterror = person.validateSync(); assert.ok(error.errors); constperson = newPerson(); consterror = person.

Update Validators

You learnt about document validation from the examples provided above. Mongoose additionally provides validation for the update(), updateOne(), updateMany(), and findOneAndUpdate() procedures, as well as for the findOneAndUpdate() operation. Update validators are disabled by default; to enable them, you must use therunValidatorsoption. The runValidatorsoption forupdate(), updateOne(), updateMany(), or findOneAndUpdate() must be set to true in order for validators to be enabled (). Keep in mind that update validators are turned off by default due to the fact that they have a number of drawbacks.

validate(function (value) return/red|green|blue/i.test(value);,’Invalid color’);constopts =; Toy.updateOne(, opts,function (err) assert.equal(err.errors.color.message, ‘Invalid color’);constopts =; Toy.updateOne(, opts,function (err) assert.equal(err.errors.color

Update Validators andthis

In terms of functionality, there are several significant distinctions between update validators and document validators. When employing document validation, the document being validated is referred to as the document being validated in the color validation function below. However, while performing update validators, it is possible that the document being updated is not now in the server’s memory, hence the value ofthis is not provided by default. consttoySchema =newSchema(color:String, name:String);toySchema.path(‘color’); consttoySchema =newSchema(color:String, name:String); consttoySchema =newSchema(color:String, name:String); If (‘red’)!=-1), then validate(function (value)!=-1) ‘red’ as the return value; ‘true’ as the return value; assert.ok(error.errors);constupdate =;conststopts =;Toy.updateOne(, update, opts, function (error)assert.ok(error););consterror = toy.validateSync(), assert.ok(error.errors);constupdate =;conststopts =;Toy.updateTwo(, update, opts, function (error)assert.ok(error););


Thecontextoption allows you to link the value ofthisin update validators to the query that is being validated. toySchema.path(‘color’). validate(function (value)if(this.getUpdate)) is equivalent to (). is a function that lowercases the name of a variable (). indexOf(‘red’)! = -1) = -1) = -1) returnstrue;);constToy = db.model(‘Figure’, toySchema);constupdate =;conststopts =;Toy.updateOne(, update, opts, function (error)););constupdateOne(, update, opts, function (error); assert.ok(error.errors); );) ;

Update Validators Only Run On Updated Paths

The other significant distinction is that update validators only operate on the pathways that have been defined in the update itself. For example, in the following example, because the parameter ‘name’ is not supplied in the update action, the update validation will proceed. The requiredvalidatorsonly fail when you try to explicitly$unsetthe key while utilizing update validators with requiredvalidators. db.model(‘Kitten’, kittenSchema); constkittenSchema = newSchema(name:, age:Number); constKitten = db.model(‘Kitten’, kittenSchema); constupdate =; conststopts =; Kitten.updateOne(, update, opts, function ()); constunset =; Kitten.updateOne (, unset, opts, function

Update Validators Only Run For Some Operations

One final point to mention is that update validators are only available for the following update operators:

  • $set
  • $unset
  • $push(= 4.8.0)
  • $addToSet(= 4.8.0)
  • $pull(= 4.12.0)
  • $pullAll(= 4.12.0)

For example, the change shown below will succeed regardless of the value ofnumber since update validators ignore$inc when validating updates. Additionally, the functions $push, $addToSet, $pull, and $pullAllvalidation do not do any validation on the array as a whole, just on the individual members in the array. testSchema = newSchema(number:, arr: ); testSchema.path(‘arr’); consttestSchema = newSchema(number:, arr: ); testSchema.path(‘arr’). validate(function (v) returnv.length2; );constTest = db.model(‘Test’, testSchema);letupdate =;constopts =; Test.updateOne(, update, opts,function ()update =,] ; Test.updateOne(, update, opts,function (error)); ); Test.updateOne(, update, opts,function (error)); );

How To Fix Schema Validation Error “Product Offers, Review or AggregateRating”

Have you gotten the following email from Google: “Google has begun assessing your site’s repair for the Products problems that you reported.” The phrase ‘Either “offers,” “review,” or” aggregateRating “shall be supplied” is being checked specifically, and it now impacts 327 pages. Validation may take several days; we will notify you when the procedure is complete.” You can keep track of the progress of the test by visiting the website provided below.” The following are the top five new issues discovered, listed in descending order by the number of impacted pages: Alternatively, you may have noticed the following message in your Google Search Console when you clicked on your product tab: “Either “offers,” “review,” or “aggregateRating” should be specified?” I’m sure that terrified the very daylights out of you, didn’t it?

You are not alone in your feelings.

But don’t be concerned.

The problem is a Schema Validation Error, which was generated by your Structured DataSchema and has been resolved.

“ Structured data, such as that provided by, provides context to your website content by utilizing a defined search engine “vocabulary.” When structured data is properly applied, it enhances the likelihood that search engines such as Google will display more information about your content directly on the search engine results pages (also known as SERPs) in the form of “rich snippets.” It allows yourWoocommerce Products to stand out more and rank higher in search results.

It is possible that an inaccuracy in your schema data will have an impact on your rankings. So, what are your options? Well, I’ve got the right structural code put up and running, and it’s been tried and tested with no issues.

*** If you want to know how to fix more website errors, go toSmazzit WordPress Support

NOTE: The presence of Schema Validation Warnings has no effect on your website. You can make them better if you wish, but it isn’t a significant issue. First and foremost, before I provide the right structural code, I’d want to mention a piece from Checkerboard on How To Fix “Either the word “offers,” the word “review,” or the word “aggregateRating” must be supplied.” According to Checkerboard, the following code should be included in yourfunctions.php file in order to assist in the resolution of this problem.

  • /** * /** * /** * /** * Remove the product schema markup that was created from the Product Category and Shop pages.
  • It could work for some people, but it didn’t work on any of the websites I tested using the code I provided.
  • On the home page of the website, a peculiar piece of code was shown in real time.
  • This was tried on three separate websites with no success.
  • Don’t go into your WordPress dashboard unless you are sure what you are doing or have a WordPress Developer on hand to guide you through it.

UPDATED SCHEMA VALIDATION CODE FOR Product Offers, Review or AggregateRating (September 28, 2021)

**IMPORTANT** The new code will assist in the correction of Google Product Warnings, including Brand and MPN warnings in the Google Search Console. PREFERABLY, CHECK TO SEE IF YOU HAVE ANY REVIEWS ON YOUR PRODUCTS BEFORE ADDING THE CODE AGAIN.

PLEASE REPLACE THE DUMMY DATA WITH YOUR REAL SCHEMA DATA (rating value, review count, description, name, image, availability url and your customer reviews)!

Script type=”application/ld+json” is defined as follows: “@context”: “”@type”: “Product”,”name”: “Dummy Title”,”image”: [“],”description”: “This description is only a dummy description, so replace it with your own”,”description”: “This description is simply a dummy description, so replace it with your own” ,”sku”: “None”,”mpn”: “None”,”brand”: “@type”: “Brand”,”name”: “Dummy Name”,”review”: “@type”: “Review”,”reviewRating”: “@type”: “Rating”,”ratingValue”: “5”,”bestRating”: “5”,”author”: “@type”: “Person”,”name”

Old Schema Validation Code but it still works~

Application/ld+json is the script type. This description is only a dummy description, so please replace it with your own.” “@context”: “This description is only a dummy description, so please replace it with your own.” “@type”: “Product”,”name”: “Dummy Title”,”image”: [“],”description”: “This description is only a dummy description, so please replace it with your own.” ,”sku”: “None”,”mpn”: “None”,”brand”: “Brand”,”name”: “Dummy Name”,”review”: “@type”: “Review”,”reviewRating”: “@type”: “Rating”,”ratingValue”: “5”,”bestRating”: “5”,”author”: “A.

Angie”,”aggregateRating”: “AggregateRating”,”ratingVal

UPDATE: 03/23/2021

Script type=”application/ld+json” is defined as follows: [“@context”: “”@type”: “Product”,”aggregateRating”: “@type”: “AggregateRating”,”ratingValue”: “5.0”,”reviewCount”: “2”,”description”: “Description of our services”,”name”: “My Best Services”,”image”: “”,”offers”: “@type”: “Offer”,”available”: “”price”: ”

Validating APIs

Using Postman, you can evaluate your API schema and the parts that make up your API (docs, test suites, mock servers, and monitors) against your schema. Keep your API well-defined, and make sure that your elements are consistent with your schema, by following these guidelines. If there is a validation error on the schema or if any of the elements do not fit the schema, Postman will provide a list of the issues that have been discovered, as well as possible solutions to the problems. After that, you may make any necessary adjustments to the API items and revalidate them.

Validating schemas

Validation is offered for the OpenAPI 2.0 and 3.0 schemas, as well as the WSDL 1.1 and 2.0 schemas. As you change your API schema in the Definitiontab on the API version page, Postman will alert you to any validation failures that have occurred. The pane below the schema editing area will display errors; you may toggle between showing and hiding the error view as you work. Each error will include the type of mistake, the line number on which it occurs, and the specifics of the problem. You may also hover your cursor over an error inline in the editor to view more details as you enter it.

As you correct your mistakes, you will see that the validation problems disappear.

It is only if the JSON or YAML is well-formed that Postman will be able to validate the schema components included inside it.

Validating elements

In addition to the OpenAPI 2.0 and 3.0 schemas, the WSDL 1.1 and 2.0 schemas are also supported via schema validation. As you change your API schema in the Definitiontab on the API version page, Postman will alert you to any validation mistakes. Errors will be displayed in a pane below the schema editing area; you may hide and reveal the error view as needed while working on your schema. Each error will include the type of error, the line number on which it occurs, and the specifics of the problem with the code executing it.

Remember that a single problem in your schema might cause several issues to appear in the list at the same time.

The schema JSON or YAML syntax will be flagged as incompatible with the editor; search for issues in the editor and mouse over them for additional information.

It is only if the JSON or YAML is well-formed that Postman will be able to validate the schema items you have provided. If there are no issues, Postman will show that your schema is valid in the lower pane of the window.

  • Validation of OpenAPI 2.0 and 3.0 schemas, as well as WSDL 1.1 and 2.0 schemas, is offered. As you change your API schema under theDefinitiontab on the API version page, Postman will alert you to any validation issues that have occurred. The error view will be displayed below the schema editing area, and you may toggle between it and the editing area as you work. Each error will include the type of mistake, the line on which it occurs, and the specifics of the problem. If you hover over an error inline in the editor, you may view more details while you type. Remember that a single problem in your schema might cause more than one issue to show in the list at a time. As you correct your mistakes, you will see that the validation difficulties will disappear. A warning will appear if there is a problem with your schema’s JSON or YAML syntax
  • Search for issues highlighted in the editor and mouse over them for additional information. It is only if the JSON or YAML is well-formed that Postman will be able to validate the schema components included inside it. If there are no issues, Postman will show that your schema is valid in the lower pane.

Once the validation is complete, a status bar will show next to the element, with a checkmark indicating that no errors have been discovered and a warning message explaining that issues have been discovered. Every time you add a new element to an API, you must run it through a validation process to ensure that it conforms to the existing API schema. When the element is validated, the results will be shown next to it. Additionally, you may manually initiate a fresh validation of your element in the following situations:

  • After making changes to your schema or linked element, you should re-validate your changes. Adding a new schema to an API that already has items associated to it is known as schema expansion.

If you navigate to your element (for example,Test), click the validation status, then click Validate Again, you will be able to perform this action.

Validating requests

You must have a collection that is connected to an API if you want your queries to be verified. If you create a collection from a schema or add it as a relation to an existing API, that collection is connected to the API. When a request is made to Postman, it will be validated. If there are problems with your request, you will get a warning notice with the number of problems next to the name of the request. Version-specific validation is conducted against the schema of the particular version of the API associated with the collection, and the results are sent to the user.

Accessing issues

You can go over the issues that were discovered during validation and make changes to your collections or schemas. If an error occurs while processing a request, click the warning notice next to the request’s name to learn more about the problem (e.g.1 issue). This will open a side-panel on the right that contains extensive information about which component of the request is affected as well as the nature of the issue itself. For example:

  • A direct link to the API against which the request is being validated—clicking on the link will open the API in the Postman application
  • More specifics on where the problem is located inside the request

You may access the relevant request component by selecting a specific issue from the drop-down menu. For issues involving another element, browse to your API by selectingAPIsin the app sidebar and selecting an API version from the drop-down list. Open the tab containing the element for which you wish to see any problems (eitherOverview,TestorMonitoring). Next to each piece, you will notice a status bar showing whether or not any errors were discovered throughout the validation process. If there are any problems, you can see them by clickingIssues foundView problems.

Updating API elements

The report will include the specifics of each problem as well as changes that may be applied immediately to the associated API element.

Understanding the issue summary

The validation summary contains a list of all of the discrepancies that were discovered between the created collection and the API schema. You can make adjustments to the collection by selecting from a list of suggestions. You may travel straight to the problems associated with a request by clicking on the request name or the request element in the right-hand sidebar.

The evaluation offers specifics on the adjustments that must be performed in order for the API element to be brought back into alignment with the schema.

Applying changes to API elements

There were many errors discovered during validation between the created collection and the API schema, which are listed in detail in the validation report. It is possible to make modifications to the collection by selecting from a list of suggested adjustments. You may browse straight to the associated problems by clicking on the request name or the request element in the right sidebar. According to the assessment, specific adjustments must be performed in order for the API element to be back in sync with the schema.

Next steps

Along with maintaining your API pieces in sync with a schema, you can evaluate and report on the performance of your APIs to have a better knowledge of how well they are operating.

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