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Author:
HappymathLabs
License:
MIT
Summary:
Happymath is a high-level mathematical modeling Python library. Its core philosophy lies in reducing users' learning costs through high-level encapsulation, enabling efficient mathematical modeling. It is particularly suitable for mathematical modeling competitions and applied mathematics fields.
Latest version:
0.2.0
Required dependencies:
catboost
|
dash
|
dash-bootstrap-components
|
ipykernel
|
ipython
|
jupyter_bokeh
|
matplotlib
|
numpy
|
pandas
|
panel
|
patsy
|
py-pde
|
pyarrow
|
pycaret
|
pymoo
|
pyomo
|
scikit-learn
|
scipy
|
seaborn
|
shap
|
statsmodels
|
sympy
|
timeout-decorator
|
umap-learn
|
watchfiles
|
xgboost
Optional dependencies:
black
|
cylp
|
flake8
|
lightgbm
|
mypy
|
pyscipopt
|
pytest
|
pytest-cov
|
sphinx
|
sphinx-autodoc-typehints
|
sphinx-rtd-theme
|
swiglpk
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