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Installing Packages
Pip #
The pip
package installer is available and working when using a GraalPy virtual environment.
The GraalPy pip
module ships some patches for packages that the project test internally, these will be applied automatically where necessary.
Support for as many extension modules as possible is a high priority for the project.
The project is actively adding support for the Python C API to make extensions such as NumPy, SciPy, Scikit-learn, Pandas, and TensorFlow work fully.
This means that some might already work, but the project is still working on compatibility, especially with native extensions.
Including packages in a Java application #
When using Python from Java via the GraalVM embedder APIs, some preparation is required to make packages available to the runtime.
After you have created a venv
virtual environment and installed your required packages, the virtual environment is made available to the Python embedded in Java by setting a context option.
A good idea is to include the entire virtual environment directory as a resource, and use Java’s resource API:
String venvExePath = getClass().
getClassLoader().
getResource(Paths.get("venv", "bin", "graalpy").toString()).
getPath();
Context ctx = Context.newBuilder("python").
allowIO(true).
option("python.Executable", venvExePath).
build();
ctx.eval("python", "import site");
The initial import site
instruction loads the Python standard library module site
, which sets up the library paths.
To do so, it uses the path of the Python executable that is currently running.
For a language such as Python, which is built around the filesystem, this makes sense, but in a Java embedding context, there is no Python executable running.
This is what the python.Executable
option is for: it reports which executable would be running if we were running Python directly inside your virtual environment.
That is enough to make the machinery work and any packages inside the virtual environment available to the Python embedded in Java.
A simple virtual environment is already quite heavy, because it comes with the machinery to install more packages. For a Java distribution, you can strip down the virtual environment. Just run these inside the top-level virtual environment directory:
find . -type d -name "__pycache__" -exec rm -rf "{}" ";"
rmdir include
rm bin/*
rmdir bin
rm lib/python3.*/site-packages/easy_install.py
rm -rf lib/python3.*/site-packages/pip*
Some packages may require the following, but most do not, so you can also remove these, but be aware that it may break a few packages:
rm -rf lib/python3.*/site-packages/setuptools*
rm -rf lib/python3.*/site-packages/pkg_resources*