The quickest way to get started with the Forge client library is to register as a Forge user and use our hosted Jupyter environment. Jupyter notebooks hosted on our service are pre-configured for Forge client library usage. No additional setup required.

If you would like to work with the Forge client library locally, read on.


To install with pip:

pip install qcware

To install from source, you must first install poetry. Then, execute the following:

git clone https://github.com/qcware/platform_client_library_python.git
cd platform_client_library_python
poetry build
cd dist
pip install qcware-7.0.0-py3-none-any.whl


To use the Forge client library, you will need an API key. You can sign up for one at https://forge.qcware.com.

To access your API key, log in to Forge and navigate to the API page. Your API key should be plainly visible there.

A Tiny Program

The following code snippet illustrates how you might run Forge client code locally. Please make sure that you have installed the client library and obtained an API key before running the Python code presented below.

# configuration
from qcware.forge.config import set_api_key, set_host

# specify the problem (for more details, see the "Getting Started" Jupyter notebook on Forge)
from qcware.forge import optimization
from qcware.types.optimization import PolynomialObjective, Constraints, BinaryProblem

qubo = {
    (0, 0): 1,
    (0, 1): 1,
    (1, 1): 1,
    (1, 2): 1,
    (2, 2): -1

qubo_objective = PolynomialObjective(

# run a CPU-powered brute force solution
results = optimization.brute_force_minimize(

If the client code has been properly installed and configured, the above code should display a result similar to the following:

Objective value: -1
Solution: [0, 0, 1]

Next Steps

For further guidance on running client code to solve machine learning problems, optimization problems, and more, we encourage you to read through the documentation on this site and the Jupyter notebooks made available on Forge.