adding pylint (ray-project#233)

lib/python/ray/array/distributed/core.py

@@ -192,7 +192,7 @@ def subblocks(a, *ranges):
     if ranges[i][0] < 0:
       raise Exception("Values in the ranges passed to sub_blocks must be at least 0, but the {}th range is {}.".format(i, ranges[i]))
     if ranges[i][-1] >= a.num_blocks[i]:
-        raise Exception("Values in the ranges passed to sub_blocks must be less than the relevant number of blocks, but the {}th range is {}, and a.num_blocks = {}.".format(i, ranges[i], a.num_blocks))
+      raise Exception("Values in the ranges passed to sub_blocks must be less than the relevant number of blocks, but the {}th range is {}, and a.num_blocks = {}.".format(i, ranges[i], a.num_blocks))
   last_index = [r[-1] for r in ranges]
   last_block_shape = DistArray.compute_block_shape(last_index, a.shape)
   shape = [(len(ranges[i]) - 1) * BLOCK_SIZE + last_block_shape[i] for i in range(a.ndim)]

lib/python/ray/array/distributed/linalg.py

@@ -1,5 +1,3 @@
-from typing import List
-
 import numpy as np
 import ray.array.remote as ra
 import ray

lib/python/ray/datasets/imagenet.py

@@ -52,7 +52,7 @@ def load_tarfile_from_s3(bucket, s3_key, size=[]):
     output.write(chunk)
     chunk = response["Body"].read(1024 * 8)
   output.seek(0) # go to the beginning of the .tar file
-  tar = tarfile.open(mode= "r", fileobj=output)
+  tar = tarfile.open(mode="r", fileobj=output)
   return load_chunk(tar, size=size if size != [] else None)
 
 @ray.remote([str, List[str], List[int]], [List[ray.ObjRef]])

lib/python/ray/serialization.py

@@ -51,7 +51,7 @@ def from_primitive(primitive_obj):
   return obj
 
 def is_arrow_serializable(value):
-  return type(value) == np.ndarray and value.dtype.name in ["int8", "int16", "int32", "int64", "uint8", "uint16", "uint32", "uint64", "float32", "float64"]
+  return isinstance(value, np.ndarray) and value.dtype.name in ["int8", "int16", "int32", "int64", "uint8", "uint16", "uint32", "uint64", "float32", "float64"]
 
 def serialize(worker_capsule, obj):
   primitive_obj = to_primitive(obj)

lib/python/ray/services.py

@@ -1,8 +1,7 @@
-import subprocess32 as subprocess
 import os
-import atexit
 import time
-import datetime
+import atexit
+import subprocess32 as subprocess
 
 import ray
 import worker
@@ -196,7 +195,7 @@ def start_services_local(num_objstores=1, num_workers_per_objstore=0, worker_pat
   time.sleep(0.1)
   objstore_addresses = []
   # create objstores
-  for i in range(num_objstores):
+  for _ in range(num_objstores):
     objstore_address = address(IP_ADDRESS, new_objstore_port())
     objstore_addresses.append(objstore_address)
     start_objstore(scheduler_address, objstore_address, local=True)

lib/python/ray/worker.py

@@ -1,14 +1,13 @@
+import os
 import time
-import datetime
+import traceback
+import copy
 import logging
-import os
 from types import ModuleType
 import typing
 import funcsigs
 import numpy as np
 import colorama
-import copy
-import traceback
 
 import ray
 import ray.config as config
@@ -147,7 +146,7 @@ def print_task_info(task_data, mode):
       print ", ".join(info_strings)
 
 def scheduler_info(worker=global_worker):
-  return ray.lib.scheduler_info(worker.handle);
+  return ray.lib.scheduler_info(worker.handle)
 
 def visualize_computation_graph(file_path=None, view=False, worker=global_worker):
   """
@@ -188,7 +187,7 @@ def visualize_computation_graph(file_path=None, view=False, worker=global_worker
 
 def task_info(worker=global_worker):
   """Tell the scheduler to return task information. Currently includes a list of all failed tasks since the start of the cluster."""
-  return ray.lib.task_info(worker.handle);
+  return ray.lib.task_info(worker.handle)
 
 def register_module(module, worker=global_worker):
   """
@@ -258,7 +257,7 @@ def kill_workers(worker=global_worker):
   """
   success = ray.lib.kill_workers(worker.handle)
   if not success:
-    print "Could not kill all workers; check that there are no tasks currently running."
+    print "Could not kill all workers. Check that there are no tasks currently running."
   return success
 
 def restart_workers_local(num_workers, worker_path, worker=global_worker):
@@ -301,7 +300,7 @@ def process_task(task): # wrapping these lines in a function should cause the lo
       outputs = worker.functions[func_name].executor(arguments) # execute the function
       if len(return_objrefs) == 1:
         outputs = (outputs,)
-    except Exception as e:
+    except Exception:
       exception_message = format_error_message(traceback.format_exc())
       # Here we are storing RayFailedObjects in the object store to indicate
       # failure (this is only interpreted by the worker).
@@ -374,7 +373,7 @@ def check_signature_supported(function):
   if function.has_kwargs_param:
     raise "Function {} has a **kwargs argument, which is currently not supported.".format(function.__name__)
   # check if the user specified a variable number of arguments and any keyword arguments
-  if function.has_vararg_param and any([d != funcsigs._empty for k, d in function.keyword_defaults]):
+  if function.has_vararg_param and any([d != funcsigs._empty for _, d in function.keyword_defaults]):
     raise "Function {} has a *args argument as well as a keyword argument, which is currently not supported.".format(function.__name__)