Comparing execution times of sorting methods

def bubble_sort(A):
    n = len(A)
    for j in range(0, n-1):
        for i in range(j+1, n):
            if A[i] > A[j]:
                A[i], A[j] = A[j], A[i]


def insertion_sort(A, p=None, r=None):
    if p is None:
        p = 0
    if r is None:
        r = len(A)-p
    for j in range(p+1, r):
        key = A[j]
        i = j - 1
        while i >= p and A[i] > key:
            A[i + 1] = A[i]
            i = i - 1
        A[i + 1] = key

def merge_sort(A, p=None, r=None):
    if p is None:
        p = 0
    if r is None:
        r = len(A)-1-p
    if p < r:
        q = (p + r) // 2
        merge_sort (A, p, q)
        merge_sort (A, q + 1, r)
        merge(A, p, q + 1, r)

def merge(A, p, q, r):
    n1 = q - p
    n2 = r - q + 1

    L = []
    R = []
    for i in range(0, n1):
        L.append(A[p + i])
    for j in range(0, n2):
        R.append(A[q + j])
    L.append(float("inf"))
    R.append(float("inf"))

    i = 0
    j = 0
    for k in range(p, r + 1):
        if L[i] <= R[j]:
            A[k] = L[i]
            i = i + 1
        else:
            A[k] = R[j]
            j = j + 1


# EXECUTION TIME
# MAIN FUNCTION
from timeit import default_timer as timer
import random
import matplotlib.pyplot as plt

def time(sort_alg, node_range=None):
    if node_range is None:
        node_range = range(10, 510, 10)
    times = []
    for n in node_range:
        A = [random.random() for _ in range(n)]
        start = timer()
        sort_alg(A) # run sorting algorithm
        times.append(timer()-start) # add time difference to time
    plt.plot(node_range, times, label=sort_alg.__name__)

time(merge_sort)
time(insertion_sort)
time(bubble_sort)
plt.legend()
plt.show()