In [2]:

    

from math import sqrt

def fibo1(n): # Recursive Fibonacci number
    if n == 0:
        return 0
    elif n == 1:
        return 1
    return fibo1(n-1) + fibo1(n-2)

def fibo2(n): # Closed Form
    return ((1+sqrt(5))**n-(1-sqrt(5))**n)/(2**n*sqrt(5))


    

In [3]:

    

%timeit fibo1(20)


    

    




100 loops, best of 3: 3.55 ms per loop

In [4]:

    

%timeit fibo2(20)


    

    




The slowest run took 14.23 times longer than the fastest. This could mean that an intermediate result is being cached.
1000000 loops, best of 3: 921 ns per loop

In [6]:

    

import random


    

In [7]:

    

%%timeit
prize = 0
for ii in range(100):
    # roll a die
    roll = random.randint(1, 6)
    if roll % 2 == 0:
        prize += roll
    else:
        prize -= 1


    

    




10000 loops, best of 3: 152 µs per loop

In [8]:

    

%%timeit
rolls = (random.randint(1, 6) for _ in range(100))
prize = sum(roll if roll % 2 == 0 else -1 for roll in rolls)


    

    




10000 loops, best of 3: 158 µs per loop

In [10]:

    

%matplotlib inline
%config InlineBackend.figure_format = 'retina'

import matplotlib.pyplot as plt
import numpy as np


    

In [11]:

    

x = np.linspace(0, 1, 300)
for w in range(2, 6, 2):
    plt.plot(x, np.sin(np.pi*x) * np.sin(2*w*np.pi*x))


    

In [12]:

    

%pdb


    

    




Automatic pdb calling has been turned ON

In [ ]:

    

numbers = 'hello'
sum(numbers)


    

    




---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-13-7a179164921f> in <module>()
      1 numbers = 'hello'
----> 2 sum(numbers)

TypeError: unsupported operand type(s) for +: 'int' and 'str'





    




> <ipython-input-13-7a179164921f>(2)<module>()
      1 numbers = 'hello'
----> 2 sum(numbers)