It is recommended to use Ianvs on a Linux machine. But for quick algorithm development, the Windows platform is also planned to support, to reduce the configuration cost of the development environment.
This guide covers how to install Ianvs on a Linux environment.
- One machine is all you need, i.e., a laptop or a virtual machine is sufficient and a cluster is not necessary
- 2 CPUs or more
- 4GB+ free memory, depends on algorithm and simulation setting
- 10GB+ free disk space
- Internet connection for GitHub and pip, etc
- Python 3.6+ installed
you can check the python version by the following command:
python -V
after doing that, the output will be like this, which means your version fits the bill.
Python 3.6.9
sudo apt-get install -y virtualenv
mkdir ~/venv
virtualenv -p python3 ~/venv/ianvs
source ~/venv/ianvs/bin/activateIf you prefer conda, you can create a python environment by referring to the creating steps provided by conda.
cd ~
git clone https://github.com/kubeedge/ianvs.git
sudo apt-get update
sudo apt-get install libgl1-mesa-glx -y
python -m pip install --upgrade pip
cd ~/ianvs
python -m pip install ./examples/resources/third_party/*
python -m pip install -r requirements.txt
python setup.py install
ianvs -vIf the version information is printed, Ianvs is installed successfully.
At the time being, the package requirements of Ianvs are only applicable for Linux, to ensure comprehensive support from the Linux ecosystem and to ease the burden of manual installation for users in Windows.
If you are more used to developing on Windows, you can still do so with remote connections like SSH from Windows connecting to a Linux machine with ianvs installed. Such remote connection is already supported in common Python coding tools like VScode, Pycharm, etc. By doing so, it helps to provide efficient installation and robust functionality of Ianvs.