Skip to main content

Dependency Injection for Common Global Dependencies

The use of singletons can often be replaced by simply adjusting scoping of objects. The vast majority of dependencies fit this pattern, with a few exceptions such as DateTime instances, or logging.

Sometimes you just need these dependencies everywhere. You can find yourself passing these dependencies down into the deep depths of your code base. Such changes are often dangerous, time consuming and undesirable.

DateTime

For a while the use of some date/time abstraction was my default approach to handling dates and times. This fake clock or calendar instance when combined with DI at the lowest level does actually work. However if we stop and think about the abstraction it is clearly unnecessary in many cases. Unless your domain is dealing with date and times explicitly, you don't really need an abstraction. In other words, other than the system where the code is running when or why would you provide a different implementation?

The approach taken as part of the example within the Dependency Elimination Principle is my current solution to date/times and DI. This is still dependency injection, except the value is provided, not the method of obtaining the value. This is essentially one of the benefits of functional programming.

Logging

All systems need some form of logging. Commonly either the standard library or a highly rated logging framework is used. The general advice has been to use the logging component directly, rather than providing your own abstraction. Most frameworks already provide interfaces or base classes that make this easy to achieve.

Even so logging suffers the same issue as date/times when it comes to DI. You often need the logging component everywhere, whether it is simply to pass on to other services.

Logging and DI generally do not go well together. Instead simple use the logging instance directly. A good logging framework would be fast, so any automated tests will not notice the difference. Likewise whether logging is configured or not, this should not cause tests to fail. In summary, not every object has to be provided via dependency injection. Loggers being a prime example.

Due to this directly using a logging instance is the preferred approach. Do not rely on DI. However semantic or structured logging does change this suggestion as the use of a domain explicit interface can provide benefits. Semantic logging will be expanded in a future post.

Others

Date/Time and Logging are the two most common global dependencies. The majority of all other dependencies can and probably should be satisfied by traditional DI where possible. As always each dependency should be validated prior to introduction. It may be possible to either eliminate or replace the component in question.

Comments

Popular posts from this blog

Constant Object Anti Pattern

Most constants are used to remove magic numbers or variables that lack context. A classic example would be code littered with the number 7. What does this refer to exactly? If this was replaced with DaysInWeek or similar, much clarity is provided. You can determine that code performing offsets would be adding days, rather than a mysterious number seven.Sadly a common pattern which uses constants is the use of a single constant file or object. The beauty of constants is clarity, and the obvious fact such variables are fixed. When a constant container is used, constants are simply lumped together. These can grow in size and often become a dumping ground for all values within the application.A disadvantage of this pattern is the actual value is hidden. While a friendly variable name is great, there will come a time where you will want to know the actual value. This forces you to navigate, if only to peek at the value within the constant object. A solution is to simple perform a refactor …

Three Steps to Code Quality via TDD

Common complaints and problems that I've both encountered and hear other developers raise when it comes to the practice of Test Driven Development are: Impossible to refactor without all the tests breakingMinor changes require hours of changes to test codeTest setup is huge, slow to write and difficult to understandThe use of test doubles (mocks, stubs and fakes is confusing)Over the next three posts I will demonstrate three easy steps that can resolve the problems above. In turn this will allow developers to gain one of the benefits that TDD promises - the ability to refactor your code mercifully in order to improve code quality.StepsStop Making Everything PublicLimit the Amount of Dependencies you Use A Unit is Not Always a Method or ClassCode quality is a tricky subject and highly subjective, however if you follow the three guidelines above you should have the ability to radically change implementation details and therefore improve code quality when needed.

DRY vs DAMP in Tests

In the previous post I mentioned that duplication in tests is not always bad. Sometimes duplication becomes a problem. Tests can become large or virtually identically excluding a few lines. Changes to these tests can take a while and increase the maintenance overhead. At this point, DRY violations need to be resolved.SolutionsTest HelpersA common solution is to extract common functionality into setup methods or other helper utilities. While this will remove and reduce duplication this can make tests a bit harder to read as the test is now split amongst unrelated components. There is a limit to how useful such extractions can help as each test may need to do something slightly differently.DAMP - Descriptive and Meaningful PhrasesDescriptive and Meaningful Phrases is the alter ego of DRY. DAMP tests often use the builder pattern to construct the System Under Test. This allows calls to be chained in a fluent API style, similar to the Page Object Pattern. Internally the implementation wil…