Level-test: inject Temporary & Isolated Level Stores Into Your Tests

level-test

Inject temporary and isolated level stores (leveldown, level-js, memdown or custom) into your tests.

If you are upgrading: please see UPGRADING.md.

Usage

Create a fresh db, without refering to any file system or DOM specifics, so that the same test can be used in the server or the browser! Use whatever test framework you like.

const level = require('level-test')()
const db = level({ valueEncoding: 'json' })

In node it defaults to leveldown for storage, using a unique temporary directory. In the browser it defaults to level-js.

No database name is needed since level-test generates unique random names. For disk-based systems it uses tempy and in the browser it uses uuid/v4.

const level = require('level-test')()
const db = level()

In either environment use of memdown can be forced with options.mem:

const level = require('level-test')({ mem: true })
const db = level({ valueEncoding: 'json' })

Or use any abstract-leveldown compliant store! In this case level-test assumes the storage is on disk and will thus create a unique temporary directory, unless you pass mem: true.

const rocksdb = require('rocksdb')
const level = require('level-test')(rocksdb)
const db = level({ valueEncoding: 'json' })

API

`ctor = levelTest([store][, options])`

Returns a function ctor that creates preconfigured levelup instances with temporary storage. The store if provided must be a function and abstract-leveldown compliant. Options:

mem: use memdown as store (or assume that store is memdown), default false.
Any other option will be merged into ctor options, the latter taking precedence.

These are equal:

const db1 = require('level-test')({ valueEncoding: 'json' })()
const db2 = require('level-test')()({ valueEncoding: 'json' })

`db = ctor([options][, callback])`

Returns a levelup instance via level-packager which wraps the underlying store with encoding-down. In short: the db is functionally equivalent to level. You get deferred open, encodings, Promise support, readable streams and more!

Options are passed to levelup (which in turn passes them on to the store when opened) as well as encoding-down.

Please refer to the levelup documentation for usage of the optional callback.

Contributing

Level/level-test is an OPEN Open Source Project. This means that:

Individuals making significant and valuable contributions are given commit-access to the project to contribute as they see fit. This project is more like an open wiki than a standard guarded open source project.

See the Contribution Guide for more details.

Author: Level
Source Code: https://github.com/Level/level-test
License: MIT license

#javascript #node #test

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Buddha Community

Level-test: inject Temporary & Isolated Level Stores Into Your Tests

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

Nicolette Zboncak

1620983255

Software Testing 101: Regression Tests, Unit Tests, Integration Tests

Automation and segregation can help you build better software
If you write automated tests and deliver them to the customer, he can make sure the software is working properly. And, at the end of the day, he paid for it.

Ok. We can segregate or separate the tests according to some criteria. For example, “white box” tests are used to measure the internal quality of the software, in addition to the expected results. They are very useful to know the percentage of lines of code executed, the cyclomatic complexity and several other software metrics. Unit tests are white box tests.

#testing #software testing #regression tests #unit tests #integration tests

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

Aurelie Block

1598916060

Top 10 Automation Testing Tools: 2020 Edition

The demand for delivering quality software faster — or “Quality at Speed” — requires organizations to search for solutions in Agile, continuous integration (CI), and DevOps methodologies. Test automation is an essential part of these aspects. The latest World Quality Report 2018–2019 suggests that test automation is the biggest bottleneck to deliver “Quality at Speed,” as it is an enabler of successful Agile and DevOps adoption.

Test automation cannot be realized without good tools; as they determine how automation is performed and whether the benefits of automation can be delivered. Test automation tools is a crucial component in the DevOps toolchain. The current test automation trends have increased in applying artificial intelligence and machine learning (AI/ML) to offer advanced capabilities for test optimization, intelligent test generation, execution, and reporting. It will be worthwhile to understand which tools are best poised to take advantage of these trends.****

#automation-testing #automation-testing-tools #testing #testing-tools #selenium #open-source #test-automation #automated-testing

Reid Rohan

1657694220