Forge Client Library

This package contains functions for easily interfacing with Forge.

Installation

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

API Key

To use the 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
set_api_key('YOUR-API-KEY-HERE')
set_host('https://api.forge.qcware.com')

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

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

qubo_objective = PolynomialObjective(
    polynomial=qubo,
    num_variables=3,
    domain='boolean'
)

# run a CPU-powered brute force solution
results = optimization.brute_force_minimize(
    objective=qubo_objective,
    backend='qcware/cpu'
)
print(results)

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]

For further guidance on running client code to solve machine learning problems, optimization problems, and more, please read through the documentation made available at https://qcware.readthedocs.io as well as the Jupyter notebooks made available on Forge.