mdoc
JMH
| mdoc | JMH | |
|---|---|---|
| 4 | 3 | |
| 387 | 783 | |
| 0.5% | 0.1% | |
| 8.4 | 7.0 | |
| 15 days ago | 2 days ago | |
| Scala | Scala | |
| Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
mdoc
- Optimal decision-making with examples built using scala
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Friction-less scala - Tell us what is causing friction in your day-to-day life with Scala
Literally what scaladoc is, it comes with sbt. Although, it's better when enhanced with mdoc so that you get the standard microsite template like these. It would be nice to have an sbt serveDocs and if everyone would host their docs for external linking, but javadoc doesn't do that either.
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A Scala rant
The good news is that scaladoc is produced by default by sbt and published by default. So you can often pull it from the same repository your library jar came from, extract it with zip, and read the docs. But that's also totally unnecessary - javadoc.io allows you to put in your module info and serves the docs for you, so if there's an older version you can access the documentation this way. Rely on the type signatures, since they can't lie, whilst comments (including scaladoc comments) can. Honestly, library authors should be using mdoc and including examples on every public method, and that type of documentation is something you can almost always contribute to a project for a quick pr kudos.
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The future of Scaladoc
I know it's not new but the "Snippet validation and results (mdoc)" features in mdoc are so cool. Really takes some of the tedium out of working with documentation since you can know that as you evolve your code the compiler will make sure you keep the docs in sync. Whole new level of Readme-Driven Development
JMH
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Scala collections benchmark - revisited
Also, it has an amazing SBT plugin integration.
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Why is Scala so much slower than JavaScript/Node at running iterations?
Take a look at sbt-jhm for doing benchmarks. Java in particular is hard to measure because of optimizations that happen at run-time. jhm runs multiple iterations and gives tools to ensure that function calls and loops that may be optimized away are kept around and tested. You may also find some cases that are faster in node.js because the Javascript V8 engine is highly optimized.
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Help with making backtracking more efficient
Also, if you really want to know what the performance characteristics are you should use JMH (sbt plugin https://github.com/sbt/sbt-jmh). Not sure how you are evaluating the performance but things like JVM startup and warming can make a big difference. JMH will give you a better idea of real world performance when the JVM is already started and any relevant hot code has been JIT compiled.
What are some alternatives?
sbt-unidoc - sbt plugin to create a unified Scaladoc or Javadoc API document across multiple subprojects.
JITWatch - Log analyser / visualiser for Java HotSpot JIT compiler. Inspect inlining decisions, hot methods, bytecode, and assembly. View results in the JavaFX user interface.
sbt-mima-plugin - A tool for catching binary incompatibility in Scala
honest-profiler - A sampling JVM profiler without the safepoint sample bias
sbt-revolver - An SBT plugin for dangerously fast development turnaround in Scala
Sniffy - Sniffy - interactive profiler, testing and chaos engineering tool for Java
sbt-pack - A sbt plugin for creating distributable Scala packages.
LatencyUtils - Utilities for latency measurement and reporting
coursier - Pure Scala Artifact Fetching
sbt-sonatype - A sbt plugin for publishing Scala/Java projects to the Maven central.
sbt-updates - sbt plugin that can check Maven and Ivy repositories for dependency updates
jHiccup - jHiccup is a non-intrusive instrumentation tool that logs and records platform "hiccups" - including the JVM stalls that often happen when Java applications are executed and/or any OS or hardware platform noise that may cause the running application to not be continuously runnable.