The repository for all your experiments

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Cubyc is an open-source experiment tracking library for data scientists. With Cubyc, you can easily track, version, and analyze your experiments using Git and SQL, all without ever leaving your Python environment.

Install Cubyc:

pip install cubyc

Initialize a new project in your current directory:

cubyc init

Start tracking your experiments:

import numpy as np
from cubyc import Run

@Run(tags=["linear_algebra"])
def matrix_multiplication(n_size: int):
    A = np.random.rand(n_size, n_size)
    B = np.random.rand(n_size, n_size)

    _ = np.dot(A, B)

for n_size in [10, 20, 40, 80, 160, 320, 640]:
    matrix_multiplication(n_size=n_size)

Analyze your runs with SQL:

from cubyc import query

statement = """
                SELECT config.n_size, metadata.runtime
                FROM config
                INNER JOIN metadata ON config.id = metadata.id
                ORDER BY metadata.runtime ASC
            """
            
print(query(statement=statement))

Output:

>>>    n_size   runtime
... 0      10  0.012209
... 1      20  1.455673
... 2      40  2.768197
... 3      80  4.073367
... 4     160  5.336599
... 5     320  6.663631
... 6     640  8.028414

For more information and examples on how to use Cubyc, please refer to our documentation.

We welcome contributions from the community! If you'd like to contribute to Cubyc, please read our contributing guidelines and code of conduct.

Cubyc is released under the LGPL-3.0 License.

If you have any questions, feedback, or suggestions, please feel free to open an issue or join our community.