Enhancing Monolog

Configuring loggers effortlessly with
Monolog Cascade

Monolog is awesome! We’ve been using it for quite some time and it clearly made our life easier at The Orchard given our hybrid infrastructure (cloud/on premise).

We use many available handlers: syslog, streams, Loggly, etc. One thing we noticed though is that configuring all those loggers and handlers was tedious and accessing those logger objects from different locations of our code base was also a bit cumbersome.

Introducing Monolog Cascade, a Monolog extension to configure and access your loggers from anywhere.

Excessive Boilerplate code

There were 2 main issues with our use of bare-bones Monolog:

  • accessing the logger objects was difficult as you often had to pass those objects around in order to use them at the desired locations unless duplicating a lot of code to set them up.
  • configuring all the formatters, handlers and loggers was a lot of code to include into some bootstrap script wherever you needed to log.

Here is what your life was like before Cascade:

Configuring Formatters, Handlers and Loggers was a long process and you had to pass logger objects around

In the example above we set up a single logger with 3 handlers and one formatter. Imagine if you had 3 times what’s above to set up…

Ease the pain

The genesis of that project came during one of our monthly fixathon/hackathon. The first iteration of the project was a small wrapper around Monolog’s Registry class so we could instantiate a Logger object on the fly and access it from anywhere. That would take care of the first pain point.

The Cascade class wraps Monolog’s Registry and adds lazy loading.

Here, the first call to getLogger actually instantiates a Logger object and pushes it to Monolog’s Registry.

This was nice but did only alleviate a tiny bit of the hassle of configuring your handlers, formatters, etc. You still needed to so “manually”.

Stronger painkiller

As our Engineering team was diving deeper into writing Python code, a lot of ideas were borrowed from by the logging.config Python module.

Having a single config file where you can define options for your loggers was the goal. Not only you can define your components but with a hierarchical structure offered by Yaml or JSON formats, you can define dependencies between those and reuse them — i.e. handlers can share the same formatter — multiple times.

Here is a sample Yaml config file that is parseable by Monolog Cascade:

Formatters and Handlers are defined once and shared by Loggers

The immediate benefit is that the config file (whether it is Yaml or JSON) is much easier to read and to understand than plain Php code. Adding a few loggers or handlers takes no time and the file is still clean.

Then setting up your loggers becomes much shorter.

Cascade will read the file, parse it and work its magic to load all required objects in sequence and eventually set up you loggers and stick them into Monolog’s Registry.

Now let’s see what’s under the hood…

Loading, Parsing, Resolving

Let’s dive into some implementation details. The main idea behind this project was to provide a library that is simple to use and could support most of Monolog’s features. The simplicity factor resides in the fact that by only checking out the constructor declaration in a formatter or handler class, you were able to write a valid config file and get the ball rolling within minutes.

Like mentioned above this project was a side project and although the need for that package was real from an engineering perspective, it was hard to make a business case and allocate lots of resources on such project. So, with that in mind we wanted to implement something simple but yet quite robust. Thus we leveraged a few proven and well tested Php libraries.

Symfony to the rescue

Symfony is a very mature and well known MVC framework in the Php community. Since version 2.0, they have broken down the library into standalone usable components. Better yet, they are all independently Composer-installable. It turned out Symfony already had a lot of what was needed for Monolog Cascade to take form: loaders, parsers and option resolvers.

Having those components right off the bat helped a lot not only getting the first version emerged in a timely manner but also keeping each layer of the package nicely separated and therefore easier to reuse and test.

Most of the challenges of the implementation were around extracting constructor parameters of handler and formatter classes to then feed option resolvers in order to validate those parameters coming from the config file.

Mirror, Mirror on the Wall

Figuring out whether or not parameter name and value were valid was essential to the robustness and the maintainability of the package. This is the part where I had wished Php had something similar to Python’s kwargs. It would have been so much easier… Php arrays kind of emulates that behavior, but Monolog’s formatters and handlers have real arguments (value only), not just a single associative array with a bunch of key/value options.

The simplest way to address that issue was using Php’s Reflection API. Reflection is a strategy for metaprogramming. It allows type introspections of interfaces, classes, and methods so you can reverse-engineer those components and instantiate objects with proper arguments at runtime dynamically for instance.

Reflection allows us to find out what argument is required or optional and pull the default value from the constructor declaration (if any)

Reflection is used extensively in Cascade to inspect constructor declarations and build an array of valid parameters out of the parsed config file before instantiating the object. That works pretty well. This approach was intended to minimize updating the package every time a new Formatter or Handler is added to Monolog. Cascade will just pick it up as long as the class exists in Monolog. Your config file just has to follow basic rules.

From constructor declaration to config file

The Formatter section must have a class parameter. Cascade will then try to match all the other parameters against the constructor args it has found. Parameters will be placed into 2 buckets: constructor parameters and extra parameters (i.e. everything else that is not constructor’s).

Let’s go over Monolog’s LineFormatter class to see how it would be configured using Cascade. Here is the constructor declaration along with the corresponding Yaml section to configure that formatter:

You would know how to build your configuration file just by looking up the constructor declaration of you handler/formatter class.

As you can see in the code samples above the formatters section of the Yaml file matches the constructor declaration. Note that Cascade will convert underscore separated param names (if this is your preferred syntax) to camel case internally and then figure out param positions to call the constructor method appropriately.

Configuring Handlers works the same way. There is only an additional “formatter” reserved keyword if you would like your handler to use a specific formatter.

Processors will work pretty much the same way but are not yet implemented.
Update (09/02/2015): implemented as of 0.1.0

Would You Like to Know More?

There is one thing we left off in the previous section. This is those mysterious extra parameters. While solely using constructor args will take care of 90% of your use cases, there are times when you want to do additional things with your loggers prior to using them. Those things include calling a method to set some values (that are not “settable” from the constructor) or you have a more complex case where you would like to use custom handlers and formatters and call a bunch of other things before using you logger objects.

Cascade adds the ability to implement those custom behaviors at runtime if needed. Here is an example of configuring a custom Formatter using an extra parameter:

By adding an extra parameter, Cascade will try to resolve it in that order:

  • it will look for a public method in the formatter class with the name of that parameter and call that method with the parameter value
  • it will look for a public member and set it with the parameter value
  • it will look for a custom handler (like the closure in the code sample above) and execute it passing the instance (Formatter or Handler) along with the parameter value.

Although this implementation is not perfect, it is a cheap way of introducing more flexible behavior should you need them.

Note to Symfony users:
You might want to use MonologBundle as it integrates better with your favorite framework.

Limitations

Some Handlers use Dependency Injection upon instantiation (most of the Database and Key/Value store do). This scenario is a bit hard to support with a simple config file and would require some more head scratching to figure out.
Update (08/24/2015): this has been fixed in 0.2.0

What’s Next?

This first release is still green and early stage. As we get more usage, we’ll continue to add support for more Handlers, Formatters and Processors and other features that Monolog introduces.

Coming Up

  • support for more config file formats: .ini, etc.
  • support for namespaced Loggers with message propagation (through handler inheritance) so children Loggers can log messages using parent’s Handlers

Feedback / Contributions

If you have feedback, questions, or simply want to contribute, we’d love to hear from you. You can send pull request directly through Github.

Raphaël
Currently listening Roses, dEUS

The Orchard Technology

The Orchard is a music, video and film distribution company…

Thanks to Michael Ortali

Raphaël Antonmattei

Written by

CTO at PathMotion

The Orchard Technology

The Orchard is a music, video and film distribution company operating globally. We provide the tools and technology needed to empower independent creators.

Raphaël Antonmattei

Written by

CTO at PathMotion

The Orchard Technology

The Orchard is a music, video and film distribution company operating globally. We provide the tools and technology needed to empower independent creators.

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