stephanie-wang

import ray
from ray.util.dask import ray_dask_get

import dask
import dask.dataframe as dd 
import pandas as pd
import numpy as np

dask.config.set(scheduler=ray_dask_get) # Sets Ray as the default backend.

stephanie-wang

import ray
import dask
import dask.dataframe as dd
import json
import pandas as pd
import numpy as np
from ray.util.dask import ray_dask_get
import os.path
import csv
import fastparquet

stephanie-wang

import dask
import dask.dataframe as dd
import json
import pandas as pd
import numpy as np
import os.path
import csv
import fastparquet

from dask.distributed import Client

stephanie-wang

import ray

import numpy as np
import time


ray.init(address="auto")

@ray.remote
def f(x):

stephanie-wang

import ray
from ray.test_utils import SignalActor

@ray.remote
class Driver:
  def __init__(self):
    pass

  def start(self, signal):
    signal.send.remote()

stephanie-wang

import ray
import time


@ray.remote
def foo(arg):
    return


@ray.remote

stephanie-wang

@ray.remote
def f():
  return 1
  
@ray.remote
def g(x):
  return x + 1

x_id = f.remote()  # ({'CPU': 1}, args=[])
g.remote(x_id)  # ({'CPU': 1}, args=[x]) --> ({'CPU': 1}, args=[])

stephanie-wang

import subprocess
import cv2
import os.path
import numpy as np
import time
import json
import threading
import tempfile

import ray

stephanie-wang

Keybase proof

I hereby claim:

• I am stephanie-wang on github.
• I am swangster (https://keybase.io/swangster) on keybase.
• I have a public key whose fingerprint is CCCD 57CE 7B21 D165 B132 632B D26B 31FD FDFF A3DB

To claim this, I am signing this object:

stephanie-wang

import time
import ray
from ray.tests.cluster_utils import Cluster

# Create a cluster with some worker nodes with 1 CPU each, to force colocated
# tasks to run one at a time.
cluster = Cluster(initialize_head=True, connect=True, head_node_args={'num_cpus': 0})
num_nodes = 3
for _ in range(num_nodes):
    cluster.add_node(num_cpus=1)