#Original
def output_json_log_data_to_file(filename, record_dictionary_list):
    with open(filename, 'w') as outputFile:
        for record in record_dictionary_list:
            json.dump(record, outputFile)
            outputFile.write('\n')


#Atomic
def output_json_log_data_to_file(filename, record_dictionary_list):
    # Use atomic file operations to prevent race conditions with readers
    # Write to temporary file first, then atomically rename to target file
    tmp_filename = filename + '.tmp'
    with open(tmp_filename, 'w') as outputFile:
        for record in record_dictionary_list:
            json.dump(record, outputFile)
            outputFile.write('\n')
    # Atomic rename - this prevents readers from seeing partial writes
    shutil.move(tmp_filename, filename)

# Python program for implementation of Bogo Sort
import random

# Sorts array a[0..n-1] using Bogo sort
def bogoSort(a):
	n = len(a)
	while (is_sorted(a)== False):
		shuffle(a)

# To check if array is sorted or not
def is_sorted(a):
	n = len(a)
	for i in range(0, n-1):
		if (a[i] > a[i+1] ):
			return False
	return True

# To generate permuatation of the array
def shuffle(a):
	n = len(a)
	for i in range (0,n):
		r = random.randint(0,n-1)
		a[i], a[r] = a[r], a[i]

# Driver code to test above
a = [3, 2, 4, 1, 0, 5]
bogoSort(a)
print("Sorted array :")
for i in range(len(a)):
	print ("%d" %a[i]),

print(123)

print("hellur")

#Python program to print topological sorting of a DAG
from collections import defaultdict
  
#Class to represent a graph
class Graph:
    def __init__(self,vertices):
        self.graph = defaultdict(list) #dictionary containing adjacency List
        self.V = vertices #No. of vertices
  
    # function to add an edge to graph
    def addEdge(self,u,v):
        self.graph[u].append(v)
  
    # A recursive function used by topologicalSort
    def topologicalSortUtil(self,v,visited,stack):
  
        # Mark the current node as visited.
        visited[v] = True
  
        # Recur for all the vertices adjacent to this vertex
        for i in self.graph[v]:
            if visited[i] == False:
                self.topologicalSortUtil(i,visited,stack)
  
        # Push current vertex to stack which stores result
        stack.insert(0,v)
  
    # The function to do Topological Sort. It uses recursive 
    # topologicalSortUtil()
    def topologicalSort(self):
        # Mark all the vertices as not visited
        visited = [False]*self.V
        stack =[]
  
        # Call the recursive helper function to store Topological
        # Sort starting from all vertices one by one
        for i in range(self.V):
            if visited[i] == False:
                self.topologicalSortUtil(i,visited,stack)
  
        # Print contents of stack
        print(stack)
  
g= Graph(6)
g.addEdge(5, 2);
g.addEdge(5, 0);
g.addEdge(4, 0);
g.addEdge(4, 1);
g.addEdge(2, 3);
g.addEdge(3, 1);
  
print("Following is a Topological Sort of the given graph")
g.topologicalSort()

# List
lst = [1, 2, 3, 'Alice', 'Alice']

# One-Liner
indices = [i for i in range(len(lst)) if lst[i]=='Alice']

# Result
print(indices)
# [3, 4]