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"""Example for generating an arbitrary DAG as a dependency map.
This demo uses networkx to generate the graph.
Authors
-------
* MinRK
"""
from random import randint
import networkx as nx
import ipyparallel as parallel
def randomwait():
import time
from random import random
time.sleep(random())
return time.time()
def random_dag(nodes, edges):
"""Generate a random Directed Acyclic Graph (DAG) with a given number of nodes and edges."""
G = nx.DiGraph()
for i in range(nodes):
G.add_node(i)
while edges > 0:
a = randint(0, nodes - 1)
b = a
while b == a:
b = randint(0, nodes - 1)
G.add_edge(a, b)
if nx.is_directed_acyclic_graph(G):
edges -= 1
else:
# we closed a loop!
G.remove_edge(a, b)
return G
def add_children(G, parent, level, n=2):
"""Add children recursively to a binary tree."""
if level == 0:
return
for i in range(n):
child = parent + str(i)
G.add_node(child)
G.add_edge(parent, child)
add_children(G, child, level - 1, n)
def make_bintree(levels):
"""Make a symmetrical binary tree with @levels"""
G = nx.DiGraph()
root = '0'
G.add_node(root)
add_children(G, root, levels, 2)
return G
def submit_jobs(view, G, jobs):
"""Submit jobs via client where G describes the time dependencies."""
results = {}
for node in nx.topological_sort(G):
with view.temp_flags(after=[results[n] for n in G.predecessors(node)]):
results[node] = view.apply(jobs[node])
return results
def validate_tree(G, results):
"""Validate that jobs executed after their dependencies."""
for node in G:
started = results[node].metadata.started
for parent in G.predecessors(node):
finished = results[parent].metadata.completed
assert started > finished, f"{node} should have happened after {parent}"
def main(nodes, edges):
"""Generate a random graph, submit jobs, then validate that the
dependency order was enforced.
Finally, plot the graph, with time on the x-axis, and
in-degree on the y (just for spread). All arrows must
point at least slightly to the right if the graph is valid.
"""
from matplotlib import pyplot as plt
from matplotlib.cm import gist_rainbow
from matplotlib.dates import date2num
print("building DAG")
G = random_dag(nodes, edges)
jobs = {}
pos = {}
colors = {}
for node in G:
jobs[node] = randomwait
client = parallel.Client()
view = client.load_balanced_view()
print("submitting %i tasks with %i dependencies" % (nodes, edges))
results = submit_jobs(view, G, jobs)
print("waiting for results")
client.wait_interactive()
for node in G:
md = results[node].metadata
start = date2num(md.started)
runtime = date2num(md.completed) - start
pos[node] = (start, runtime)
colors[node] = md.engine_id
validate_tree(G, results)
nx.draw(
G,
pos,
node_list=list(colors.keys()),
node_color=list(colors.values()),
cmap=gist_rainbow,
with_labels=False,
)
x, y = zip(*pos.values())
xmin, ymin = map(min, (x, y))
xmax, ymax = map(max, (x, y))
xscale = xmax - xmin
yscale = ymax - ymin
plt.xlim(xmin - xscale * 0.1, xmax + xscale * 0.1)
plt.ylim(ymin - yscale * 0.1, ymax + yscale * 0.1)
return G, results
if __name__ == '__main__':
from matplotlib import pyplot as plt
# main(5,10)
main(32, 96)
plt.show()
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