1. Installation

Sinergym relies on several dependencies, the specifics of which vary by version. The table below provides a summary of the versions supported by Sinergym across its releases:

Sinergym version	Ubuntu version	Python version	EnergyPlus version	Building model file
0.0	18.04 LTS	3.6	8.3.0	IDF
1.1.0	18.04 LTS	3.6	9.5.0	IDF
1.7.0	18.04 LTS	3.9	9.5.0	IDF
1.9.5	22.04 LTS	3.10.6	9.5.0	IDF
2.4.0	22.04 LTS	3.10.6	9.5.0	epJSON
2.5.0	22.04 LTS	3.10.6	23.1.0	epJSON
3.3.6	24.04 LTS	3.12.3	23.1.0	epJSON
3.5.8	24.04 LTS	3.12.3	24.1.0	epJSON

Important

Starting from version 3.6.0, Sinergym begins to work with Poetry, although installation with pip is still available.

We recommend always using the latest version of Sinergym that is supported by the container. This approach helps you avoid the complexities of the installation process. However, if you prefer to manually install Sinergym on your computer, we provide the necessary documentation in the subsequent sections.

1.1. Docker container

We provide a Dockerfile to install all dependencies and prepare the image for running Sinergym. This is the recommended option, since it ensures that all dependencies and versions are correctly installed and configured.

In essence, this Dockerfile installs the compatible operating system, EnergyPlus, Python, and Sinergym, along with the necessary dependencies for its proper functioning. If you have cloned the repository, it can be used as follows:

$ docker build -t <tag_name> .

However, Sinergym has a set of optional dependencies that enhance the tool’s usage. These dependencies can be installed in the following way when building the image:

$ docker build -t <tag_name> --build-arg SINERGYM_EXTRAS=format,test,doc,DRL,gcloud .

These optional dependencies allow you to format code, run tests, generate documentation, have pre-existing DRL algorithms available, etc. For more information, please refer to the pyproject.toml file at the root of the repository. If you desire to install all optional packages, you can use dev directly in the SINERGYM_EXTRAS argument.

Note

Our container can also be directly installed from the Docker Hub repository. It contains all the project’s releases with secondary dependencies or lite versions.

Once the container image is ready, you can execute any command as follows:

$ docker run -it --rm <tag_name> <command>

By default, the command executed is python scripts/try_env.py, which is a minimal working example.

If you want to run a DRL experiment, for example, you can do it like this:

$ docker build -t example/sinergym:latest --build-arg SINERGYM_EXTRAS=DRL,platforms .
$ docker run -e WANDB_API_KEY=$WANDB_API_KEY -it --rm example/sinergym:latest python scripts/train/train_agent.py -conf scripts/train/train_agent_PPO.json

If the script you want to use requires a WandB account, remember to include the environment variable in the container with the token.

It’s also possible to keep a session open in the image to copy and run your own scripts. For more information, please refer to the Docker documentation. This can be useful when you want to run your own scripts in the container.

$ docker run -it <tag_name> /bin/bash

Note

For Visual Studio Code users, simply open the root directory and click on the Reopen in container pop-up button. This action will automatically install all dependencies and enable you to run Sinergym in an isolated environment. For more details on this feature, refer to the VSCode Containers extension documentation.

1.2. Manual installation

If you prefer not to use containers and have everything installed natively on your system, we’ll explain how to do it.

First, make sure that you meet the compatibility matrix; otherwise, no support or guarantees of functionality will be provided by the development team.

1.2.1. Configure Python Environment

Start by installing the desired version of Python and pip. It is recommended to set up a working environment for Python (multiple options are available). Finally, install the necessary dependencies for Sinergym in that environment:

$ pip install sinergym

You can also install the optional packages from here, just like in the Docker container:

$ pip install sinergym[format,test,doc,DRL,gcloud]

If you want to install the cloned repository directly, you can do so by running the following command in its root.

$ poetry install --with format,test,doc,DRL,gcloud

With this, you have the correct Python version and the necessary modules to run Sinergym. Let’s proceed with the installation of other required programs outside of Python to run the simulations.

1.2.2. Install EnergyPlus 24.1.0

You need to install EnergyPlus. We have tested and confirmed compatibility with version 24.1.0. The code might work with other versions, but we have not tested them.

Follow the instructions here to install it for Linux (we only support Ubuntu). You can choose any location for the installation. After installation, a folder named Energyplus-24-1-0 should appear in the chosen location.

1.2.3. Include Energyplus Python API in Python Path

Sinergym uses the Energyplus Python API as its backend. The modules of this API are located in the Energyplus folder that you installed in the previous step. You must add this installation path to the PYTHONPATH environment variable so that the interpreter can access these modules.

1.3. Verify Installation

This project is automatically monitored using tests specifically developed for it. To verify that Sinergym has been installed correctly, execute pytest tests/ -vv in the repository root.

Furthermore, each time the Sinergym repository is updated, the tests are automatically executed in a remote container built using the Dockerfile. This task is performed by Github Action (refer to the Github Actions section for more details).

1.4. Cloud Computing

You also have the option to run your experiments in the Cloud. We utilize Google Cloud for this purpose. Our team is working on setting up an account to run our Sinergym container with remote storage and Weights&Biases tracking. For more information on installation and preparing the Google Cloud SDK to run your experiments, please visit our Preparing Google Cloud section.