Joi validate file extension


  • Custom Validation with Joi — Annotations and Failover Values
  • Validate Image Content in ReactJS
  • Validate file upload with html5 file api
  • 34 joi.validate is not a function
  • Form Validation Using Custom React Hooks
  • Custom Validation with Joi — Annotations and Failover Values

    Daniel Testa When it comes to choosing a client-side object validation library, Yup has increasingly become the go-to choice. With its descriptive, yet powerful API, Yup can be bent to most use cases. On a recent project, we were using Formik with Yup to build out highly dynamic, schema-generated forms. For simple forms, this worked great, but as the forms became more complex and the data models behind them grew to include a variety of different data types, the lack of a clear approach to optional object validation in Yup became an issue.

    While looking into this, I came across several solutions that might work for you, depending on your requirements. The Problem The simple version of the problem we were grappling with was this — how do we define an object as optional, but allow the object to have required properties within it? Solution One? First, notRequired simply makes is so that undefined values do not fail validation.

    Both suggested similar solutions — in combination with notRequired, override the type default to be undefined. Note, the guidance on this approach comes from project author Jason Quense himself. This time, the underlying issue is our own. For many projects, this sort of approach should work, but in our case, it was time to get more hands-on.

    Solution Two — Lazy Validation Since it is our data making things difficult, we needed to get more involved in the validation process. While looking into how we might go about enforcing our own rules, I came across a blog post by Jason Brown at CodeDaily. While his final validation approach ends up being quite similar in function to using. With a working solution on hand, there was one more approach I wanted to try that might better fit with how we were dynamically creating our forms and Yup validation.

    Instead of swapping out the validation tests by using lazy, we can handle the noise that our custom defaults and form data is creating by applying our own transform function. This allows us to keep our actual validations much simpler to read and generate.

    End Result — Custom. When I started looking into this problem, I assumed a quick solution was to be found. Once again, code for most of the above examples, along with some unit tests, are running on this CodeSandbox — see which solution works for you! About the Author.

    Validate Image Content in ReactJS

    Given that schema, you can create the validation function that will be used in your code. The declaration of your schema will always depend on the library you are using; therefore, I always recommend checking the official docs.

    In the case of ajv, it forces you to declare in an object style, where each property has to provide its type. This method provides: A standardized way to create validators and checks: The idea behind the schema is to have only one way to check for specific conditions inside your application — especially in JavaScript, where there are many ways to accomplish the same task, such as checking the length of an array.

    This quality is great to improve communication and collaboration inside a team Improvement of error reporting: In case there is a mismatch on some property, the library will inform you of which one it is in a human-friendly way rather than just printing the stack trace This new way of creating validations presents the following drawbacks: Introduction of new syntax: When a team decides to add a new library, it becomes more difficult to understand the whole codebase.

    Every contributor has to know about the validator schema to understand how to make a change on it Validators and types are not in sync: The definition of the schema and ExampleType is disconnected, which means that every time you make a change inside the ExampleType, you have to manually reflect it inside the schema. Depending on how many validators you have, this task can be quite tedious One small comment regarding keeping validators and types in sync: some open-source projects address this issue, such as json-schema-to-typescript , which can generate a type definition from an existing schema.

    Dynamic type validator This is the method I want to talk about, and it represents a change in paradigm regarding how to create validators and keep types in sync. In the two other methods, the validator and the type can be seen as different entities: the validator will take the incoming object and check its properties, and the type statically belongs to the object. Combining both entities, the result is a validated type object.

    Dynamic type validation allows a type to generate a validator from its definition. Now they are related — a validator depends entirely on a type, preventing any mismatch between structures. Generation of validators To generate these validators, I found an amazing open-source project called typescript-json-validator , made by ForbesLindesay.

    Creating the ajv instance It also sets some default configuration for ajv. Definition of the schema from the type This is the key of this approach. Export validation function using the generated schema It also takes care of throwing an exception in case there is an error.

    These will be translated into ajv rules when the library generates the final schema. In the case of email, it will check whether the string value belongs to a valid email address.

    Fixing this issue is quite easy: you simply have to add a script that will be executed before your code will run. You can call it prebuild or prestart, and this is how your package. There is no point in committing these files to your repository since they are going to be generated every time you start your project. The project presents two main flows: Create the resume information: you will be asked to enter your Linked In credentials, then a crawler will open a new browser, read your profile values and finally save all this information inside a JSON file in your directory.

    After that, the project will transform the data extracted from the crawler into the structure for Json Resume. In the event that there is a change on the website, the output from the crawler can be altered. Local file with the resume information: This project allows you to change the content of your resume manually in case you want to skip the creation of the resume information and create it by yourself. After I set up my project to generate the validators from these types, checking the structure of the incoming object was a very easy task.

    The dynamic types approach grabs the best of the other methods, making it the recommended approach to validate your object.

    Validate file upload with html5 file api

    Solution Two — Lazy Validation Since it is our data making things difficult, we needed to get more involved in the validation process. While looking into how we might go about enforcing our own rules, I came across a blog post by Jason Brown at CodeDaily. While his final validation approach ends up being quite similar in function to using. With a working solution on hand, there was one more approach I wanted to try that might better fit with how we were dynamically creating our forms and Yup validation.

    Instead of swapping out the validation tests by using lazy, we can handle the noise that our custom defaults and form data is creating by applying our own transform function. This allows us to keep our actual validations much simpler to read and generate. End Result — Custom. Dynamic type validation allows a type to generate a validator from its definition. Now they are related — a validator depends entirely on a type, preventing any mismatch between structures.

    Generation of validators To generate these validators, I found an amazing open-source project called typescript-json-validatormade by ForbesLindesay.

    Creating the ajv instance It also sets some default configuration for ajv. Definition of the schema from the type This is the key of this approach.

    Export validation function using the generated schema It also takes care of throwing an exception in case there is an error. These will be translated into ajv rules when the library generates the final schema. In the case of email, it will check whether the string value belongs to a valid email address.

    34 joi.validate is not a function

    Fixing this issue is quite easy: you simply have to add a script that will be executed before your code will run. For the Form component to display a list of errors, our useForm custom React Hook needs to store them in its state. We need to add back the call to the callback function to our useForm Hook. But where? Enter the useEffect Hook.

    Form Validation Using Custom React Hooks

    Furthermore, by passing an array with a value inside as the second parameter to useEffect, we can tell that specific useEffect declaration to run whenever that value changes. This is because our useEffect Hook above is actually being run once when the component renders because the value of errors is initialized to an empty object.

    Set the initial state to false. Then setIsSubmitting to true inside handleSubmit. This is the final step to adding some proper form validation inside of any custom React Hooks. Homework as it were. If you want the solution, you can check out the entire code base for this tutorial. Wrapping Up So there you have it, form validation and initialization using custom React Hooks.

    As always, if you enjoyed the tutorial, please leave a message in the discussion below. If you have any issues or questions, leave a comment below or hit me up on Twitter.


    Joi validate file extension