In this task you have to code process planner.

You will be given initial thing, target thing and a set of processes to turn one thing into another (in the form of _[process\_name, start\_thing, end\_thing]_). You must return  names of shortest sequence of processes to turn initial thing into target thing, or empty sequence if it's impossible.

If start already equals end, return [], since no path is required.

Example: 

```python
test_processes = [
        ['gather', 'field', 'wheat'],
        ['bake', 'flour', 'bread'],
        ['mill', 'wheat', 'flour']
];

processes('field', 'bread', test_processes) # should return ['gather', 'mill', 'bake']
processes('field', 'ferrari', test_processes) # should return []
processes('field', 'field', test_processes) # should return [], since no processes are needed
```

Good luck!

Difficulty: EASY

Starter code:
def processes(start, end, processes):
	

Solutions:
def processes(start, end, processes):
	q = [(start, [])]
	visited = set()
	while q:
		(s, path) = q.pop(0)
		if s == end:
			return path
		visited.add(s)
		for p in [x for x in processes if x[1] == s]:
			if not p[2] in visited:
				q.append((p[2], path + [p[0]]))
	return []


from collections import deque

def processes(start, end, graph):
	Q = deque([[i, []] for i in graph if i[1] == start])
	visited = set()
	while Q:
		((p, s, e), path) = Q.popleft()
		path.append(p)
		visited.add((s, e))
		if e == end:
			return path
		for k in graph:
			if k[1] == e and tuple(k[1:]) not in visited:
				Q.append([k, path[:]])
	return []


from collections import defaultdict, deque

def processes(start, end, processes):
	(D, L, S) = (defaultdict(dict), deque([(start, [])]), set())
	for (a, b, c) in processes:
		D[b][a] = c
	while L:
		(current, path) = L.pop()
		if current == end:
			return path
		if current not in S:
			S.add(current)
			for (k, v) in D[current].items():
				L.appendleft((v, path + [k]))
	return []


def processes(start, end, processes):
	if start == end:
		return []
	result = check(start, end, processes, [])
	if result == None:
		return []
	return result

def check(start, end, processes, result):
	if start == end:
		return result
	results = []
	for i in processes:
		if i[1] == start:
			try:
				tmp = result.copy()
				tmp.append(i[0])
				tmp2 = check(i[2], end, processes, tmp)
				if tmp2 != None:
					results.append(tmp2)
			except:
				return None
	if len(results) > 0:
		return min(results, key=len)
	else:
		return None


from collections import defaultdict, namedtuple
Edge = namedtuple('Edge', ['process_name', 'to'])
State = namedtuple('State', ['stack', 'visited', 'min_stack'])

def dfs(graph, cur_node, end_node, state):
	if cur_node in state.visited:
		return
	if len(state.min_stack) and len(state.stack) >= len(state.min_stack):
		return
	if cur_node == end_node:
		state.min_stack.clear()
		state.min_stack.extend(state.stack)
		return
	state.visited.add(cur_node)
	for (process, node) in graph[cur_node]:
		state.stack.append(process)
		dfs(graph, node, end_node, state)
		state.stack.pop()
	state.visited.remove(cur_node)

def processes(start, end, processes):
	if start == end:
		return []
	graph = defaultdict(list)
	for (process_name, start_node, end_node) in processes:
		graph[start_node].append(Edge(process_name, end_node))
	state = State([], set(), [])
	dfs(graph, start, end, state)
	return state.min_stack


def processes(start, end, procs):

	def _p(start, end, procs, re_):
		for step in procs:
			res = re_[:]
			if step[1] == start:
				res.append(step[0])
				_p(step[2], end, [x for x in procs if x != step], res)
				if step[2] == end:
					_p.gres.append(res)
	_p.gres = []
	_p(start, end, procs, [])
	return min(_p.gres, key=lambda x: len(x)) if _p.gres else []


def processes(start, end, processes):
	sequences = [[start, []]]
	while len(sequences) > 0:
		k = sequences[0]
		del sequences[0]
		node = k[0]
		path = k[1]
		if node == end:
			return path
		for n in processes:
			if n[1] == node and n[0] not in path:
				sequences.append([n[2], path + [n[0]]])
	return []


def processes(start, end, processes):
	pss = []

	def proc(start, end, ps, l=[]):
		[pss.append(l + [ps[i][0]]) if ps[i][-1] == end else proc(ps[i][-1], end, ps[:i] + ps[i + 1:], l + [ps[i][0]]) for i in range(len(ps)) if ps[i][1] == start]
	return proc(start, end, processes) or (min(pss, key=len) if pss else [])


from collections import defaultdict

def processes(start, end, processes):
	d = defaultdict(list)
	for (process, x, y) in processes:
		d[x].append((y, process))
	(visited, nodes) = (set(), [(start, [])])
	while nodes:
		next = []
		for (node, path) in nodes:
			if node in visited:
				continue
			if node == end:
				return path
			visited.add(node)
			for (y, process) in d[node]:
				next.append((y, path + [process]))
		nodes = next
	return []


from collections import defaultdict

def prcs(start, end, procs, path):
	if start == end:
		return path
	paths = []
	try:
		for p in procs[start]:
			if p in path:
				continue
			paths.append(prcs(p[1], end, procs, path + [p]))
		return min([a for a in paths if a and a[-1][1] == end], key=len)
	except (KeyError, ValueError):
		return []

def processes(start, end, procs):
	dd = defaultdict(list)
	for (n, s, e) in procs:
		dd[s].append((n, e))
	return [n for (n, _) in prcs(start, end, dd, [])]