The Environment Manager is a streamlined quantum software package and virtual environment management system provided to qBraid end-users through a simple, intuitive graphical user interface. It offers curated development environments in Python, Julia, C++, and Q# over a range of quantum applications.

Click on the ENVS tab in the upper-right of the Lab console to expand the Environment Manager sidebar and view a list of your currently installed environments. The qBraid “Default” Python environment is pre-installed for all users.

Install environment

  1. In the Environment Manager sidebar, click Add to view the environments available to install.

  2. Choose an environment, expand its panel, and click Install. Once the installation has started, the panel is moved to the Environments tab. Click Browse Environments to return to the Environments tab and view its progress.

  1. When the installation is complete, the environment panel’s action button will switch from Installing… to Add kernel.

Create environment

  1. In the Environment Manager sidebar, click Add, then click Create Environment.

  2. Give your custom environment a name, description, add tags, upload a logo, and specify any packages to install using a requirements.txt format.

After clicking Create, a new environment panel is created for your custom environment. You can view the environment’s install progress by returning to My Environments.

  1. Once the environment has been created and any package installations have finished, the environment panel’s action button will switch from Installing… to Add kernel, and the installed packages number will be updated.

  2. Click on More to verify/view the environment’s list of installed packages. You can use the search bar or scroll through the Python package (pip) list to find the exact versions of all packages and package dependencies that were installed. From the More pop-out, you can also install additional packages, remove packages, add/delete tags, and edit the environment’s description.

Share environment

In qBraid Lab, you can share your custom environments with other users. This will make your environment visible under their Add environment list. They can then install it, and run code using an exact copy of your environment. This includes support for quantum jobs and any additional configurations.

Although modifications to pre-packaged environments can’t be directly shared, you can export a requirements.txt from any environment to use in creating a new custom environment “copy”, which can then be shared with other users.

To share a custom environment, first click the More button in the drop-down to open the environment editor. Then, under ‘Share Environment’, enter the qBraid user email, and click Share.

When you share an environment on qBraid, you’re creating a snapshot of your Python virtual environment with its specific configurations and installed packages. This snapshot is uploaded to the qBraid cloud, creating a static version accessible to other users. This shared version remains unchanged, even if you make updates to your local environment. To reflect any changes, you’d need to re-share and overwrite the existing version in the cloud.

Overwriting a globally shared environment doesn’t affect versions that other users have already downloaded. Instead, an indicator notifies them of the availability of an updated version. Currently, users must manually check for this indicator. Also, before installing an updated version, users must uninstall their current one as maintaining multiple versions of a shared environment isn’t supported. Sharing or overwriting globally doesn’t impact your local environment.

Uninstall / cancel install environment

To uninstall an environment or cancel the installation of an environment, click on More, and then Uninstall or Cancel Installation.

Install new package

Find the environment into which you want to install the package, expand the environment panel using the carrot drop-down, and then click More.

At the bottom of the Python packages list, click Add a package. Type in the exact name of the package you wish to install into the “Add package…” search bar, and then hit Enter (or click the search icon on the right). This will do a direct search through PyPI, and return the latest version available to install. To accept, click on the packge, and then click Add.

package installation

While installing, the environment action button will indicate Installing…. Once complete, Lab will notify with a pop-up.

Activate environment (kernel)

Clicking Add kernel creates a new ipykernel, see Add/remove kernels for more.

access key
  • Pennylane Lighting GPU: Environment for developing with the Pennylane quantum machine learning library with support for GPU-accelerated circuit simulation.
  • Qiskit Aer GPU: Environment for developing with Qiskit Aer using GPU supported simulators: statevector, density matrix, and unitary.
  • Bloqade: Environment and dedicated qBraid Lab instance for developing with Bloqade: an SDK for quantum computation and quantum dynamics based on neutral-atom architectures, developed by QuEra.
  • Intel® Quantum SDK: Environment for developing with the Intel Quantum SDK, a C++ based API that allows users to write software targeted for Intel quantum hardware.
  • Fire Opal: Environment for developing with Fire Opal, a Python package containing a large suite of error suppression techniques intended to improve the quality of quantum algorithm results.