Pre-installed software and custom configurations

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This document describes the pre-installed software in the secure environment and explains how to install custom software.

Pre-installed software

  1. WPS.

  2. Notepad++.

  3. Anaconda with Python 3.6 and 3.9: Includes common Python packages for modeling. To install additional packages, follow the instructions in the "Custom software installation" section.

We recommend using the Python 3.9 environment, as it includes a more comprehensive set of Python packages.

Usage: Open Jupyter Notebook from the desktop. When creating a new notebook, select the py3 kernel.

  1. When modeling, we recommend using sklearn APIs, such as XGBClassifier.fit() or LGBMClassifier.fit(), to train your model. This simplifies saving the model as a PMML file.

Custom software installation

1. Installing Python packages

  • By default, the system environment provides two Python versions: 3.6 and 3.9. Both include common Python packages for modeling.

  • If you need other packages, you can download them locally, then upload and install them. Follow these steps:

    1. Open Anaconda Prompt and activate the environment where you want to install the package. For example: conda activate py3

    2. Run the installation command. For example: pip install pandas -i https://mirrors.aliyun.com/pypi/simple

2. Installing a custom kernel

If your organization has a pre-configured Anaconda kernel from a Windows environment, you can copy its folder directly into the secure environment.

  • Follow these steps:

    1. Copy the configured kernel folder to the following location in the secure environment: C:\Anaconda3\envs

    2. Open Anaconda Prompt and run conda info -e to view the available kernels.

    3. Activate the corresponding kernel by running conda activate $kernel_folder_name

    4. Run the following command to register the kernel with Jupyter: python -m ipykernel install --user --name=$kernel_folder_name --display-name "$display_name_in_Jupyter"

    5. Start Jupyter Notebook by running jupyter notebook or by opening it from the desktop. When creating a new notebook, select the display name that you set in the previous step from the kernel list.