Moq.ILogger
Moq.Contrib.HttpClient
Moq.ILogger | Moq.Contrib.HttpClient | |
---|---|---|
2 | - | |
66 | 184 | |
- | - | |
0.0 | 0.0 | |
10 months ago | over 1 year ago | |
C# | C# | |
Apache License 2.0 | MIT License |
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Moq.ILogger
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Library to easily verify calls to ILogger with Moq
So something like https://github.com/adrianiftode/Moq.ILogger what are the main pros for using your library instead of this one?
Cool stuff! I've used this in the past https://github.com/adrianiftode/Moq.ILogger, but more contributions in this area are always welcome. As you correctly put it, verifying the ILogger is a pain in the ***!
Moq.Contrib.HttpClient
We haven't tracked posts mentioning Moq.Contrib.HttpClient yet.
Tracking mentions began in Dec 2020.
What are some alternatives?
opentelemetry-dotnet - The OpenTelemetry .NET Client
Moq - Repo for managing Moq 4.x [Moved to: https://github.com/moq/moq]
ILogger.UnitTest.Verifier - Verify ILogger calls more easily.
Bogus - :card_index: A simple fake data generator for C#, F#, and VB.NET. Based on and ported from the famed faker.js.
MELT - MELT is a free, open source, testing library for the .NET Standard Microsoft Extensions Logging library. It is a solution to easily test logs.
Machine.Specifications - Machine.Specifications is a Context/Specification framework for .NET that removes language noise and simplifies tests.
WireMock.Net - WireMock.Net is a flexible product for stubbing and mocking web HTTP responses using advanced request matching and response templating. Based on the functionality from http://WireMock.org, but extended with more functionality.
Rhino Mocks
LightBDD - BDD framework allowing to create easy to read and maintain tests.
SpecFlow - #1 .NET BDD Framework. SpecFlow automates your testing & works with your existing code. Find Bugs before they happen. Behavior Driven Development helps developers, testers, and business representatives to get a better understanding of their collaboration
should - Should Assertion Library
GenFu - GenFu is a library you can use to generate realistic test data. It is composed of several property fillers that can populate commonly named properties through reflection using an internal database of values or randomly created data. You can override any of the fillers, give GenFu hints on how to fill them.