Overview
SciPy 1.15, released on February 1, 2025, works natively with NumPy 2.x and improves solver performance.
Main Features
Native NumPy 2.x support
SciPy 1.15 is natively built against NumPy 2.x, benefiting from performance improvements and the new type API.
python
import scipy
import numpy as np
print(f'SciPy {scipy.__version__}') # 1.15.0
print(f'NumPy {np.__version__}') # 2.x
# SciPy functions leverage NumPy 2.x
from scipy import linalg
A = np.random.randn(100, 100)
inv = linalg.inv(A)
print(f'Check: {np.allclose(A @ inv, np.eye(100))}')Optimized solvers
Differential equation and optimization solvers are faster thanks to improved underlying algorithms.
python
from scipy.optimize import minimize
import numpy as np
def rosenbrock(x):
return sum(100 * (x[1:] - x[:-1]**2)**2 + (1 - x[:-1])**2)
x0 = np.zeros(10)
result = minimize(rosenbrock, x0, method='L-BFGS-B')
print(f'Minimum: {result.fun:.6f}')
print(f'Iterations: {result.nit}')