scipy為python提供了矩陣的運算，還有功能：最優化、線性代數、積分、插值、擬合、特殊函數、快速傅里葉變換、信號和圖像處理、常微分方程的求解等等。安裝scipy之前必須安裝numpy。

例子如下，python3在pycharm中編譯：

from scipy.optimize import fsolve #導入求解方程組的函數def f(x): x1 = x[0] x2 = x[1] return [2*x1 - x2**2 - 1, x1**2 - x2 - 2]result = fsolve(f, [1,1]) #輸入初始值并求解PRint(result)# 數值積分from scipy import integratedef g(x): return (1 - x**2)**0.5pi_2, err = integrate.quad(g, -1, 1)print(pi_2 * 2)

from scipy.optimize import fsolve  # 導入求解方程組的函數def f(x):    x1 = x[0]    x2 = x[1]    return [2*x1 - x2**2 - 1, x1**2 - x2 - 2]result = fsolve(f, [1, 1])  # 輸入初始值并求解print(result)# 數值積分from scipy import integratedef g(x):    return (1 - x**2)**0.5pi_2, err = integrate.quad(g, -1, 1)print(pi_2 * 2)