![]() And finally generate a bunch of fake data from Synth and back into Mongo.Next will ingest data from MongoDB into Synth.Then we'll initialize a Synth workspace in our repo to host our data model.In the following section we will cover how Synth fits into the Web App development workflow: Ok, so now that we have a couple of movies, let's get started with Synth! ![]() So, let's add a couple of movies manually using the Web UI. Otherwise we would have to write the entire data definition (what we call a Schema) by hand. Well, by adding a little bit of test data by hand, we can then use Synth to infer the structure of the data and create as many movies as we want for us. Why are we adding movies by hand since we have a tool to generate data for us? For our purposes, we don't really need to build it from scratch, so let's just clone the repo and avoid writing any code ourselves.Įnter fullscreen mode Exit fullscreen modeĬool! If you navigate to you should see the React App running □ I picked this example because it shows how to get started quickly with a MERN stack, where the end product is a usable app you can write in 10 minutes. Īs a template, we'll use a repository which will give us scaffolding for the MERN app. I'm going to assuming you're working on MacOS or Linux (Windows support coming soon □) and you have NodeJS, Yarn and Docker installed.įor this example we'll be running Synth version 0.3.2. This tutorial is going to use a simple MERN ( Mongo Express React Node) web-app as our test subject, but really Synth is not married to any specific stack. Synth is a state-of-the-art declarative data generator - you tell Synth what you want your data to look like and Synth will generate that data for you. In this post we're going to explore how we can solve this problem using the open-source project Synth. You're building a Web App, you're super productive in your stack and you can go quickly - however generating lot's of data to see what your app will look like with enough users and traffic is a pain.Įither you're going to spend a lot of time manually inputting data or you're going to write some scripts to generate that data for you. If you sign in using your Google account, you can download random data programmatically by saving your schemas and using curl to download data in a shell script via a RESTful url.So we've all been in this situation. Mockaroo allows you to quickly and easily to download large amounts of randomly generated test data based on your own specs which you can then load directly into your test environment using SQL or CSV formats. But not everyone is a programmer or has time to learn a new framework. There are plenty of great data mocking libraries available for almost every language and platform. Testing with realistic data will make your app more robust because you'll catch errors that are likely to occur in production before release day. Real data is varied and will contain characters that may not play nice with your code, such as apostrophes, or unicode characters from other languages. When you demonstrate new features to others, they'll understand them faster. When your test database is filled with realistic looking data, you'll be more engaged as a tester. Worse, the data you enter will be biased towards your own usage patterns and won't match real-world usage, leaving important bugs undiscovered. ![]() If you're hand-entering data into a test environment one record at a time using the UI, you're never going to build up the volume and variety of data that your app will accumulate in a few days in production. In production, you'll have an army of users banging away at your app and filling your database with data, which puts stress on your code. If you're developing an application, you'll want to make sure you're testing it under conditions that closely simulate a production environment. Paralellize UI and API development and start delivering better applications faster today! Why is test data important? With Mockaroo, you can design your own mock APIs, You control the URLs, responses, and error conditions. By making real requests, you'll uncover problems with application flow, timing, and API design early, improving the quality of both the user experience and API. ![]() It's hard to put together a meaningful UI prototype without making real requests to an API. Mock your back-end API and start coding your UI today. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |