Lawrence  Lesch

Lawrence Lesch

1623836280

Using Playwright to Test Next.js Applications

The testing setup of my dreams is finally a reality

In its  latest release,  Playwright has gained a new feature called Playwright Test. This newly added test runner for Playwright enables the smoothest testing experience in Next.js applications I have ever seen. Once set up, it allows testing with real browsers across multiple device sizes. We’ll be able to mock requests made by the frontend. And, we’ll be able to mock the backend’s requests as well. All from the test spec itself.

And to top it all off, we’ll even be able to do Visual Regression Testing which the Playwright team calls Visual Comparisons. This allows you to basically take a screenshot of your application and fail your test in case the next screenshot does not match the current one.

This is incredibly exciting as you’ll be able to make your tests reflect the way a real user would use your application.

In this article, I’ll walk you through the setup of Playwright for Next.js applications. We’ll also use msw to mock requests made by the Next.js server.

Note that this setup is brand new and pretty experimental. Consider this as me sharing something cool I’ve sort of stumbled into. There might be some unresolved hurdles down the road that can’t yet be foreseen and might lead to a change in the taken approach.

Let’s first take a look at the  official release notes to learn about Playwright Test: Playwright Test_ is a new test runner built from scratch by Playwright team specifically to accommodate end-to-end testing needs:_

  • Run tests across all browsers.
  • Execute tests in parallel.
  • Enjoy context isolation and sensible defaults out of the box.
  • Capture traces, videos, screenshots and other artefacts on failure.
  • Infinitely extensible with fixtures.

This sounded incredibly exciting and is what lead me to try to use Playwright to test my Next.js applications. As a side note, I am building a service called happykit.dev which allows you to use  Feature Flags in your Next.js applications. I plan to use this Playwright setup for HappyKit. But let’s get back to the setup now :)

Note that Playwright itself can be used in many different ways. The following is just my approach at integrating it with Next.js. I am not saying that this is the ultimate solution for everyone, but it works really well for me. I hope it will at least inspire.

#testing #javascript #nextjs #typescript

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Using Playwright to Test Next.js Applications

NBB: Ad-hoc CLJS Scripting on Node.js

Nbb

Not babashka. Node.js babashka!?

Ad-hoc CLJS scripting on Node.js.

Status

Experimental. Please report issues here.

Goals and features

Nbb's main goal is to make it easy to get started with ad hoc CLJS scripting on Node.js.

Additional goals and features are:

  • Fast startup without relying on a custom version of Node.js.
  • Small artifact (current size is around 1.2MB).
  • First class macros.
  • Support building small TUI apps using Reagent.
  • Complement babashka with libraries from the Node.js ecosystem.

Requirements

Nbb requires Node.js v12 or newer.

How does this tool work?

CLJS code is evaluated through SCI, the same interpreter that powers babashka. Because SCI works with advanced compilation, the bundle size, especially when combined with other dependencies, is smaller than what you get with self-hosted CLJS. That makes startup faster. The trade-off is that execution is less performant and that only a subset of CLJS is available (e.g. no deftype, yet).

Usage

Install nbb from NPM:

$ npm install nbb -g

Omit -g for a local install.

Try out an expression:

$ nbb -e '(+ 1 2 3)'
6

And then install some other NPM libraries to use in the script. E.g.:

$ npm install csv-parse shelljs zx

Create a script which uses the NPM libraries:

(ns script
  (:require ["csv-parse/lib/sync$default" :as csv-parse]
            ["fs" :as fs]
            ["path" :as path]
            ["shelljs$default" :as sh]
            ["term-size$default" :as term-size]
            ["zx$default" :as zx]
            ["zx$fs" :as zxfs]
            [nbb.core :refer [*file*]]))

(prn (path/resolve "."))

(prn (term-size))

(println (count (str (fs/readFileSync *file*))))

(prn (sh/ls "."))

(prn (csv-parse "foo,bar"))

(prn (zxfs/existsSync *file*))

(zx/$ #js ["ls"])

Call the script:

$ nbb script.cljs
"/private/tmp/test-script"
#js {:columns 216, :rows 47}
510
#js ["node_modules" "package-lock.json" "package.json" "script.cljs"]
#js [#js ["foo" "bar"]]
true
$ ls
node_modules
package-lock.json
package.json
script.cljs

Macros

Nbb has first class support for macros: you can define them right inside your .cljs file, like you are used to from JVM Clojure. Consider the plet macro to make working with promises more palatable:

(defmacro plet
  [bindings & body]
  (let [binding-pairs (reverse (partition 2 bindings))
        body (cons 'do body)]
    (reduce (fn [body [sym expr]]
              (let [expr (list '.resolve 'js/Promise expr)]
                (list '.then expr (list 'clojure.core/fn (vector sym)
                                        body))))
            body
            binding-pairs)))

Using this macro we can look async code more like sync code. Consider this puppeteer example:

(-> (.launch puppeteer)
      (.then (fn [browser]
               (-> (.newPage browser)
                   (.then (fn [page]
                            (-> (.goto page "https://clojure.org")
                                (.then #(.screenshot page #js{:path "screenshot.png"}))
                                (.catch #(js/console.log %))
                                (.then #(.close browser)))))))))

Using plet this becomes:

(plet [browser (.launch puppeteer)
       page (.newPage browser)
       _ (.goto page "https://clojure.org")
       _ (-> (.screenshot page #js{:path "screenshot.png"})
             (.catch #(js/console.log %)))]
      (.close browser))

See the puppeteer example for the full code.

Since v0.0.36, nbb includes promesa which is a library to deal with promises. The above plet macro is similar to promesa.core/let.

Startup time

$ time nbb -e '(+ 1 2 3)'
6
nbb -e '(+ 1 2 3)'   0.17s  user 0.02s system 109% cpu 0.168 total

The baseline startup time for a script is about 170ms seconds on my laptop. When invoked via npx this adds another 300ms or so, so for faster startup, either use a globally installed nbb or use $(npm bin)/nbb script.cljs to bypass npx.

Dependencies

NPM dependencies

Nbb does not depend on any NPM dependencies. All NPM libraries loaded by a script are resolved relative to that script. When using the Reagent module, React is resolved in the same way as any other NPM library.

Classpath

To load .cljs files from local paths or dependencies, you can use the --classpath argument. The current dir is added to the classpath automatically. So if there is a file foo/bar.cljs relative to your current dir, then you can load it via (:require [foo.bar :as fb]). Note that nbb uses the same naming conventions for namespaces and directories as other Clojure tools: foo-bar in the namespace name becomes foo_bar in the directory name.

To load dependencies from the Clojure ecosystem, you can use the Clojure CLI or babashka to download them and produce a classpath:

$ classpath="$(clojure -A:nbb -Spath -Sdeps '{:aliases {:nbb {:replace-deps {com.github.seancorfield/honeysql {:git/tag "v2.0.0-rc5" :git/sha "01c3a55"}}}}}')"

and then feed it to the --classpath argument:

$ nbb --classpath "$classpath" -e "(require '[honey.sql :as sql]) (sql/format {:select :foo :from :bar :where [:= :baz 2]})"
["SELECT foo FROM bar WHERE baz = ?" 2]

Currently nbb only reads from directories, not jar files, so you are encouraged to use git libs. Support for .jar files will be added later.

Current file

The name of the file that is currently being executed is available via nbb.core/*file* or on the metadata of vars:

(ns foo
  (:require [nbb.core :refer [*file*]]))

(prn *file*) ;; "/private/tmp/foo.cljs"

(defn f [])
(prn (:file (meta #'f))) ;; "/private/tmp/foo.cljs"

Reagent

Nbb includes reagent.core which will be lazily loaded when required. You can use this together with ink to create a TUI application:

$ npm install ink

ink-demo.cljs:

(ns ink-demo
  (:require ["ink" :refer [render Text]]
            [reagent.core :as r]))

(defonce state (r/atom 0))

(doseq [n (range 1 11)]
  (js/setTimeout #(swap! state inc) (* n 500)))

(defn hello []
  [:> Text {:color "green"} "Hello, world! " @state])

(render (r/as-element [hello]))

Promesa

Working with callbacks and promises can become tedious. Since nbb v0.0.36 the promesa.core namespace is included with the let and do! macros. An example:

(ns prom
  (:require [promesa.core :as p]))

(defn sleep [ms]
  (js/Promise.
   (fn [resolve _]
     (js/setTimeout resolve ms))))

(defn do-stuff
  []
  (p/do!
   (println "Doing stuff which takes a while")
   (sleep 1000)
   1))

(p/let [a (do-stuff)
        b (inc a)
        c (do-stuff)
        d (+ b c)]
  (prn d))
$ nbb prom.cljs
Doing stuff which takes a while
Doing stuff which takes a while
3

Also see API docs.

Js-interop

Since nbb v0.0.75 applied-science/js-interop is available:

(ns example
  (:require [applied-science.js-interop :as j]))

(def o (j/lit {:a 1 :b 2 :c {:d 1}}))

(prn (j/select-keys o [:a :b])) ;; #js {:a 1, :b 2}
(prn (j/get-in o [:c :d])) ;; 1

Most of this library is supported in nbb, except the following:

  • destructuring using :syms
  • property access using .-x notation. In nbb, you must use keywords.

See the example of what is currently supported.

Examples

See the examples directory for small examples.

Also check out these projects built with nbb:

API

See API documentation.

Migrating to shadow-cljs

See this gist on how to convert an nbb script or project to shadow-cljs.

Build

Prequisites:

  • babashka >= 0.4.0
  • Clojure CLI >= 1.10.3.933
  • Node.js 16.5.0 (lower version may work, but this is the one I used to build)

To build:

  • Clone and cd into this repo
  • bb release

Run bb tasks for more project-related tasks.

Download Details:
Author: borkdude
Download Link: Download The Source Code
Official Website: https://github.com/borkdude/nbb 
License: EPL-1.0

#node #javascript

Eva  Murphy

Eva Murphy

1625674200

Google analytics Setup with Next JS, React JS using Router Events - 14

In this video, we are going to implement Google Analytics to our Next JS application. Tracking page views of an application is very important.

Google analytics will allow us to track analytics information.

Frontend: https://github.com/amitavroy/video-reviews
API: https://github.com/amitavdevzone/video-review-api
App link: https://video-reviews.vercel.app

You can find me on:
Twitter: https://twitter.com/amitavroy7​
Discord: https://discord.gg/Em4nuvQk

#next js #js #react js #react #next #google analytics

Tamia  Walter

Tamia Walter

1596754901

Testing Microservices Applications

The shift towards microservices and modular applications makes testing more important and more challenging at the same time. You have to make sure that the microservices running in containers perform well and as intended, but you can no longer rely on conventional testing strategies to get the job done.

This is where new testing approaches are needed. Testing your microservices applications require the right approach, a suitable set of tools, and immense attention to details. This article will guide you through the process of testing your microservices and talk about the challenges you will have to overcome along the way. Let’s get started, shall we?

A Brave New World

Traditionally, testing a monolith application meant configuring a test environment and setting up all of the application components in a way that matched the production environment. It took time to set up the testing environment, and there were a lot of complexities around the process.

Testing also requires the application to run in full. It is not possible to test monolith apps on a per-component basis, mainly because there is usually a base code that ties everything together, and the app is designed to run as a complete app to work properly.

Microservices running in containers offer one particular advantage: universal compatibility. You don’t have to match the testing environment with the deployment architecture exactly, and you can get away with testing individual components rather than the full app in some situations.

Of course, you will have to embrace the new cloud-native approach across the pipeline. Rather than creating critical dependencies between microservices, you need to treat each one as a semi-independent module.

The only monolith or centralized portion of the application is the database, but this too is an easy challenge to overcome. As long as you have a persistent database running on your test environment, you can perform tests at any time.

Keep in mind that there are additional things to focus on when testing microservices.

  • Microservices rely on network communications to talk to each other, so network reliability and requirements must be part of the testing.
  • Automation and infrastructure elements are now added as codes, and you have to make sure that they also run properly when microservices are pushed through the pipeline
  • While containerization is universal, you still have to pay attention to specific dependencies and create a testing strategy that allows for those dependencies to be included

Test containers are the method of choice for many developers. Unlike monolith apps, which lets you use stubs and mocks for testing, microservices need to be tested in test containers. Many CI/CD pipelines actually integrate production microservices as part of the testing process.

Contract Testing as an Approach

As mentioned before, there are many ways to test microservices effectively, but the one approach that developers now use reliably is contract testing. Loosely coupled microservices can be tested in an effective and efficient way using contract testing, mainly because this testing approach focuses on contracts; in other words, it focuses on how components or microservices communicate with each other.

Syntax and semantics construct how components communicate with each other. By defining syntax and semantics in a standardized way and testing microservices based on their ability to generate the right message formats and meet behavioral expectations, you can rest assured knowing that the microservices will behave as intended when deployed.

Ways to Test Microservices

It is easy to fall into the trap of making testing microservices complicated, but there are ways to avoid this problem. Testing microservices doesn’t have to be complicated at all when you have the right strategy in place.

There are several ways to test microservices too, including:

  • Unit testing: Which allows developers to test microservices in a granular way. It doesn’t limit testing to individual microservices, but rather allows developers to take a more granular approach such as testing individual features or runtimes.
  • Integration testing: Which handles the testing of microservices in an interactive way. Microservices still need to work with each other when they are deployed, and integration testing is a key process in making sure that they do.
  • End-to-end testing: Which⁠—as the name suggests⁠—tests microservices as a complete app. This type of testing enables the testing of features, UI, communications, and other components that construct the app.

What’s important to note is the fact that these testing approaches allow for asynchronous testing. After all, asynchronous development is what makes developing microservices very appealing in the first place. By allowing for asynchronous testing, you can also make sure that components or microservices can be updated independently to one another.

#blog #microservices #testing #caylent #contract testing #end-to-end testing #hoverfly #integration testing #microservices #microservices architecture #pact #testing #unit testing #vagrant #vcr

Dejah  Reinger

Dejah Reinger

1599859380

How to Do API Testing?

Nowadays API testing is an integral part of testing. There are a lot of tools like postman, insomnia, etc. There are many articles that ask what is API, What is API testing, but the problem is How to do API testing? What I need to validate.

Note: In this article, I am going to use postman assertions for all the examples since it is the most popular tool. But this article is not intended only for the postman tool.

Let’s directly jump to the topic.

Let’s consider you have an API endpoint example http://dzone.com/getuserDetails/{{username}} when you send the get request to that URL it returns the JSON response.

My API endpoint is http://dzone.com/getuserDetails/{{username}}

The response is in JSON format like below

JSON

{
  "jobTitle": "string",
  "userid": "string",
  "phoneNumber": "string",
  "password": "string",
  "email": "user@example.com",
  "firstName": "string",
  "lastName": "string",
  "userName": "string",
  "country": "string",
  "region": "string",
  "city": "string",
  "department": "string",
  "userType": 0
}

In the JSON we can see there are properties and associated values.

Now, For example, if we need details of the user with the username ‘ganeshhegde’ we need to send a **GET **request to **http://dzone.com/getuserDetails/ganeshhegde **

dzone.com

Now there are two scenarios.

1. Valid Usecase: User is available in the database and it returns user details with status code 200

2. Invalid Usecase: User is Unavailable/Invalid user in this case it returns status with code 404 with not found message.

#tutorial #performance #api #test automation #api testing #testing and qa #application programming interface #testing as a service #testing tutorial #api test

Einar  Hintz

Einar Hintz

1599055326

Testing Microservices Applications

The shift towards microservices and modular applications makes testing more important and more challenging at the same time. You have to make sure that the microservices running in containers perform well and as intended, but you can no longer rely on conventional testing strategies to get the job done.

This is where new testing approaches are needed. Testing your microservices applications require the right approach, a suitable set of tools, and immense attention to details. This article will guide you through the process of testing your microservices and talk about the challenges you will have to overcome along the way. Let’s get started, shall we?

A Brave New World

Traditionally, testing a monolith application meant configuring a test environment and setting up all of the application components in a way that matched the production environment. It took time to set up the testing environment, and there were a lot of complexities around the process.

Testing also requires the application to run in full. It is not possible to test monolith apps on a per-component basis, mainly because there is usually a base code that ties everything together, and the app is designed to run as a complete app to work properly.

Microservices running in containers offer one particular advantage: universal compatibility. You don’t have to match the testing environment with the deployment architecture exactly, and you can get away with testing individual components rather than the full app in some situations.

Of course, you will have to embrace the new cloud-native approach across the pipeline. Rather than creating critical dependencies between microservices, you need to treat each one as a semi-independent module.

The only monolith or centralized portion of the application is the database, but this too is an easy challenge to overcome. As long as you have a persistent database running on your test environment, you can perform tests at any time.

Keep in mind that there are additional things to focus on when testing microservices.

  • Microservices rely on network communications to talk to each other, so network reliability and requirements must be part of the testing.
  • Automation and infrastructure elements are now added as codes, and you have to make sure that they also run properly when microservices are pushed through the pipeline
  • While containerization is universal, you still have to pay attention to specific dependencies and create a testing strategy that allows for those dependencies to be included

Test containers are the method of choice for many developers. Unlike monolith apps, which lets you use stubs and mocks for testing, microservices need to be tested in test containers. Many CI/CD pipelines actually integrate production microservices as part of the testing process.

Contract Testing as an Approach

As mentioned before, there are many ways to test microservices effectively, but the one approach that developers now use reliably is contract testing. Loosely coupled microservices can be tested in an effective and efficient way using contract testing, mainly because this testing approach focuses on contracts; in other words, it focuses on how components or microservices communicate with each other.

Syntax and semantics construct how components communicate with each other. By defining syntax and semantics in a standardized way and testing microservices based on their ability to generate the right message formats and meet behavioral expectations, you can rest assured knowing that the microservices will behave as intended when deployed.

#testing #software testing #test automation #microservice architecture #microservice #test #software test automation #microservice best practices #microservice deployment #microservice components