Analyzing Production Build Size in Loklak Search

Loklak search being a web application it is critical to keep the size of the application in check to ensure that we are not transferring any non-essential bytes to the user so that application load is faster, and we are able to get the minimal first paint time. This requires a mechanism for the ability to check the size of the build files which are generated and served to the user. Alongside the ability to check sizes it is also critically important to analyze the distribution of the modules along with their sizes in various chunks. In this blog post, I discuss the analysis of the application code of loklak search and the generated build files.

Importance of Analysis

The chunk size analysis is critical to any application, as the chunk size of any application directly determines the performance of any application, at any scale. The smaller the application the lesser is the load time, thus faster it becomes usable at the user side. The time to first-paint is the most important metric to keep in mind while analyzing any web application for performance, though the first paint time consists of many critical parts from loading, parsing, layout and paint, but still the size of any chunk determines all the time it will take to render it on the screen.

Also as we use the 3rd party libraries and components it becomes crucially important to inspect the impact on the size of the application upon the inclusion of those libraries and components.

Development Phase Checking

Angular CLI provides a clean mechanism to track and check the size of all the chunks always at the runtime, these stats simply show the size of each chunk in the application in the terminal on every successful compilation, and this provides us a broad idea about the chunks to look and address.

Deep Analysis using Webpack Bundle Analyzer

The angular cli while generating the production build provides us with an option to generates the statistics about the chunks including the size and namespaces of the each module which is part of that chunk. These stats are directly generated by the webpack at the time of bundling, code splitting, and tree shaking. These statistics thus provide us to peek into the actual deeper level of chunk creation in webpack to analyze sizes of its various components. To generate the statistics we just need to enable the –stats-json flag while building.

ng serve --prod --aot --stats-json

This will generate the statistics file for the application in the /dist directory, alongside all the bundles. Now to have the visual and graphical analysis of these statistics we can use a tool like webpack-bundle-analyzer to analyze the statistics. We can install the webpack-bundle-analyzer via npm,

npm install --save-dev webpack-bundle-analyzer

Now, to our package.json we can add a script, running this script will open up a web page which contains graphical visualization of all the chunks build in the application

// package.json

{
   …
   …
   {
      “scripts”: {
         …
         …
         "analyze": "webpack-bundle-analyzer dist/stats.json"
      }
   }
}

These block diagrams also contain the information about the sub modules contained in each chunk, and thus we can easily analyze and compare the size of each component we add in the application.

Now, we can see in the above distribution, the main.bundle is of the largest size among all the other chunks. And the major part of it is being occupied by, moment.js, this analysis provides us with a deeper insight into the impact of a module like moment.js on the application size. This helps us to reason about the analyze which part of the application is worth, and which parts of the application can be replaced with lighter alternatives and which parts of the application are worth the size they are consuming, as for a 3rd party module which consumes a lot of sizes but is used in some insignificant feature, must be replaced with a lightweight alternative.

Conclusion

Thus being able to see the description of modules in each and every chunk provides us with a method to reason about, and compare the alternative approaches for a particular solution to a problem, in terms of the effect of those approaches on the size of the application so we are able to make the best decision.

Resources and Links

  • Analyzing the builds blog by hackernoon
  • Bundle analysis for webpack applications blog by Nimesh