Javadoc vs Scalene
Javadoc
oracle.comScalene
github.comSide by side
| Figure | Javadoc | Scalene |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | Yes |
| Windows | Yes | Yes |
| macOS | Yes | Yes |
| Linux | Yes | Yes |
| Plans published | 1 | 1 |
| Spec score · Profiling Software | 7.9 (#9) | 7.6 (#17) |
| Purpose | Javadoc generates HTML API documentation pages from Java source files. | Scalene profiles Python programs for CPU, GPU, and memory use and provides AI-powered optimization proposals. |
| Support | Oracle directs customers with active support contracts to My Oracle Support for technical questions and service requests. | The project links to a Scalene community Slack for community discussion. |
Plans
In their own words
Javadoc
Javadoc creates HTML API documentation from Java source files and is installed with the Java Development Kit (JDK). Its standard doclet describes public and protected Java types and members, including classes, interfaces, constructors, methods, and fields. It can process packages, individual source files, or both, with an option to include subpackages recursively. Alternate doclets can change the content and format of the generated output, while taglets add support for custom tags in documentation comments. The standard doclet includes DocLint to help identify common comment problems, but DocLint does not check conformance or repair errors. Oracle cautions that generated output may pose issues if it is non-conformant or contains executable content such as JavaScript. JDK 25 downloads are listed for Linux, macOS, and Windows. JDK 25 binaries are free under Oracle No-Fee Terms and Conditions through September 2028; later updates use a license that may require fees for production use beyond limited free grants.
Scalene
Scalene is a free, open-source profiler for Python programs that reports CPU, GPU and memory use and offers AI-powered optimization proposals. Its line- and function-level reports separate Python time from native-code and system time. Memory analysis shows per-line use, distinguishes Python from native allocations and flags lines with likely memory leaks. GPU profiling reports time on NVIDIA-based systems. Async profiling attributes wall-clock await time to the suspended coroutine line and reports mean and peak concurrent waiters. Its graphical interface can display stitched Python and native call stacks, memory flame charts and a timeline. Scalene is usable from the command line, a web-based GUI, a Visual Studio Code extension or Jupyter notebooks. The web interface processes profiles locally and works offline. For optimization suggestions, listed AI providers include Amazon Bedrock, Microsoft Azure, OpenAI and local models through Ollama. The project reports typical profiling overhead of no more than 10–20%, often less. Scalene is available for free under the Apache-2.0 license, with installations listed for macOS, Linux, Windows and Windows Subsystem for Linux 2.