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Installation

The aindo.rdml package is a Python package and is available for Linux and for a few versions of Python. It is recommended to have the venv module available, to install the package in an isolated virtual environment. The name of the provided wheel file has the following structure: aindo_rdml-{version}-cp{py_version}-cp{py_version}-linux_x86_64.whl, where {version} is the package version (e.g. 3.0.0) and {py_version} is the Python version (e.g. 310 for Python 3.10).

Once the wheel is located, open a terminal and move to the folder where to create the virtual environment, then type the following commands:

Terminal window
path/to/dir$ python -m venv venv
path/to/dir$ source venv/bin/activate
(venv) path/to/dir$ python -m pip install -U pip setuptools
(venv) path/to/dir$ python -m pip install -U "path/to/aindo_rdml-{version}-cp{py_version}-cp{py_version}-linux_x86_64.whl"

Note that in the above example the command python is used in the first line to create the virtual environment, but the user should specify the command to launch the required Python version (e.g. python3 for Python 3.10 in some Linux distributions). Once the virtual environment is activated, the command python will invoke the correct Python version.

Once the installation is complete, the package aindo.rdml will be available in the virtual environment:

Terminal window
path/to/dir$ source venv/bin/activate
(venv) path/to/dir$ python
Python 3.10.15 (main, Sep  7 2024, 18:35:33) [GCC 9.4.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> from aindo.rdml.relational import RelationalData
>>>

Optional dependencies

The procedure discussed above will install the library and its main dependencies. There are also a few optional dependencies that can be installed. They can be specified by adding them to the last command described above as follows:

Terminal window
(venv) path/to/dir$ python -m pip install -U "path/to/aindo_rdml-{version}-cp310-cp310-linux_x86_64.whl[opt1,opt2,...]"

The available optional dependencies are:

  • db: Allow for DB reading/writing (the supported dialects are the ones supported by sqlalchemy, but the user may have to install the appropriate DBAPI driver).
  • excel: Allow for reading from Excel files.
  • dev: Includes a few packages that may be useful to track the progression of the model training (e.g. tensorboard).