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From r...@apache.org
Subject git commit: [SPARK-3361] Expand PEP 8 checks to include EC2 script and Python examples
Date Sat, 06 Sep 2014 06:08:59 GMT
Repository: spark
Updated Branches:
  refs/heads/master 19f61c165 -> 9422c4ee0


[SPARK-3361] Expand PEP 8 checks to include EC2 script and Python examples

This PR resolves [SPARK-3361](https://issues.apache.org/jira/browse/SPARK-3361) by expanding
the PEP 8 checks to cover the remaining Python code base:
* The EC2 script
* All Python / PySpark examples

Author: Nicholas Chammas <nicholas.chammas@gmail.com>

Closes #2297 from nchammas/pep8-rulez and squashes the following commits:

1e5ac9a [Nicholas Chammas] PEP 8 fixes to Python examples
c3dbeff [Nicholas Chammas] PEP 8 fixes to EC2 script
65ef6e8 [Nicholas Chammas] expand PEP 8 checks


Project: http://git-wip-us.apache.org/repos/asf/spark/repo
Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/9422c4ee
Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/9422c4ee
Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/9422c4ee

Branch: refs/heads/master
Commit: 9422c4ee0eaf4a32d2ed7c96799feac2f5f79d40
Parents: 19f61c1
Author: Nicholas Chammas <nicholas.chammas@gmail.com>
Authored: Fri Sep 5 23:08:54 2014 -0700
Committer: Reynold Xin <rxin@apache.org>
Committed: Fri Sep 5 23:08:54 2014 -0700

----------------------------------------------------------------------
 dev/lint-python                                 |  5 +++--
 ec2/spark_ec2.py                                | 20 ++++++++++++-----
 examples/src/main/python/avro_inputformat.py    | 17 ++++++++++-----
 .../src/main/python/cassandra_inputformat.py    | 15 +++++++------
 .../src/main/python/cassandra_outputformat.py   | 23 ++++++++++----------
 examples/src/main/python/hbase_inputformat.py   | 10 ++++++---
 examples/src/main/python/hbase_outputformat.py  | 18 +++++++++------
 examples/src/main/python/mllib/correlations.py  |  2 +-
 .../main/python/mllib/decision_tree_runner.py   |  6 +++--
 .../main/python/mllib/random_rdd_generation.py  |  6 ++---
 examples/src/main/python/mllib/sampled_rdds.py  |  8 +++----
 examples/src/main/python/pi.py                  |  2 +-
 12 files changed, 79 insertions(+), 53 deletions(-)
----------------------------------------------------------------------


http://git-wip-us.apache.org/repos/asf/spark/blob/9422c4ee/dev/lint-python
----------------------------------------------------------------------
diff --git a/dev/lint-python b/dev/lint-python
index a1e890f..79bf70f 100755
--- a/dev/lint-python
+++ b/dev/lint-python
@@ -30,6 +30,7 @@ cd $SPARK_ROOT_DIR
 #+  - Download this from a more reliable source. (GitHub raw can be flaky, apparently. (?))
 PEP8_SCRIPT_PATH="$SPARK_ROOT_DIR/dev/pep8.py"
 PEP8_SCRIPT_REMOTE_PATH="https://raw.githubusercontent.com/jcrocholl/pep8/1.5.7/pep8.py"
+PEP8_PATHS_TO_CHECK="./python/pyspark/ ./ec2/spark_ec2.py ./examples/src/main/python/"
 
 curl --silent -o "$PEP8_SCRIPT_PATH" "$PEP8_SCRIPT_REMOTE_PATH"    
 curl_status=$?
@@ -44,7 +45,7 @@ fi
 #+ first, but we do so so that the check status can
 #+ be output before the report, like with the
 #+ scalastyle and RAT checks.
-python $PEP8_SCRIPT_PATH ./python/pyspark > "$PEP8_REPORT_PATH"
+python $PEP8_SCRIPT_PATH $PEP8_PATHS_TO_CHECK > "$PEP8_REPORT_PATH"
 pep8_status=${PIPESTATUS[0]} #$?
 
 if [ $pep8_status -ne 0 ]; then
@@ -54,7 +55,7 @@ else
     echo "PEP 8 checks passed."
 fi
 
-rm -f "$PEP8_REPORT_PATH"
+rm "$PEP8_REPORT_PATH"
 rm "$PEP8_SCRIPT_PATH"
 
 exit $pep8_status

http://git-wip-us.apache.org/repos/asf/spark/blob/9422c4ee/ec2/spark_ec2.py
----------------------------------------------------------------------
diff --git a/ec2/spark_ec2.py b/ec2/spark_ec2.py
index 1670fac..8ec88d9 100755
--- a/ec2/spark_ec2.py
+++ b/ec2/spark_ec2.py
@@ -41,6 +41,7 @@ from boto import ec2
 # A URL prefix from which to fetch AMI information
 AMI_PREFIX = "https://raw.github.com/mesos/spark-ec2/v2/ami-list"
 
+
 class UsageError(Exception):
     pass
 
@@ -342,7 +343,6 @@ def launch_cluster(conn, opts, cluster_name):
     if opts.ami is None:
         opts.ami = get_spark_ami(opts)
 
-
     additional_groups = []
     if opts.additional_security_group:
         additional_groups = [sg
@@ -363,7 +363,7 @@ def launch_cluster(conn, opts, cluster_name):
         for i in range(opts.ebs_vol_num):
             device = EBSBlockDeviceType()
             device.size = opts.ebs_vol_size
-            device.volume_type=opts.ebs_vol_type
+            device.volume_type = opts.ebs_vol_type
             device.delete_on_termination = True
             block_map["/dev/sd" + chr(ord('s') + i)] = device
 
@@ -495,6 +495,7 @@ def launch_cluster(conn, opts, cluster_name):
     # Return all the instances
     return (master_nodes, slave_nodes)
 
+
 def tag_instance(instance, name):
     for i in range(0, 5):
         try:
@@ -507,9 +508,12 @@ def tag_instance(instance, name):
 
 # Get the EC2 instances in an existing cluster if available.
 # Returns a tuple of lists of EC2 instance objects for the masters and slaves
+
+
 def get_existing_cluster(conn, opts, cluster_name, die_on_error=True):
     print "Searching for existing cluster " + cluster_name + "..."
-    # Search all the spot instance requests, and copy any tags from the spot instance request
to the cluster.
+    # Search all the spot instance requests, and copy any tags from the spot
+    # instance request to the cluster.
     spot_instance_requests = conn.get_all_spot_instance_requests()
     for req in spot_instance_requests:
         if req.state != u'active':
@@ -520,7 +524,7 @@ def get_existing_cluster(conn, opts, cluster_name, die_on_error=True):
             for res in reservations:
                 active = [i for i in res.instances if is_active(i)]
                 for instance in active:
-                    if (instance.tags.get(u'Name') == None):
+                    if (instance.tags.get(u'Name') is None):
                         tag_instance(instance, name)
     # Now proceed to detect master and slaves instances.
     reservations = conn.get_all_instances()
@@ -540,13 +544,16 @@ def get_existing_cluster(conn, opts, cluster_name, die_on_error=True):
         return (master_nodes, slave_nodes)
     else:
         if master_nodes == [] and slave_nodes != []:
-            print >> sys.stderr, "ERROR: Could not find master in with name " + cluster_name
+ "-master"
+            print >> sys.stderr, "ERROR: Could not find master in with name " + \
+                cluster_name + "-master"
         else:
             print >> sys.stderr, "ERROR: Could not find any existing cluster"
         sys.exit(1)
 
 # Deploy configuration files and run setup scripts on a newly launched
 # or started EC2 cluster.
+
+
 def setup_cluster(conn, master_nodes, slave_nodes, opts, deploy_ssh_key):
     master = master_nodes[0].public_dns_name
     if deploy_ssh_key:
@@ -890,7 +897,8 @@ def real_main():
                 if opts.security_group_prefix is None:
                     group_names = [cluster_name + "-master", cluster_name + "-slaves"]
                 else:
-                    group_names = [opts.security_group_prefix + "-master", opts.security_group_prefix
+ "-slaves"]
+                    group_names = [opts.security_group_prefix + "-master",
+                                   opts.security_group_prefix + "-slaves"]
 
                 attempt = 1
                 while attempt <= 3:

http://git-wip-us.apache.org/repos/asf/spark/blob/9422c4ee/examples/src/main/python/avro_inputformat.py
----------------------------------------------------------------------
diff --git a/examples/src/main/python/avro_inputformat.py b/examples/src/main/python/avro_inputformat.py
index e902ae2..cfda8d8 100644
--- a/examples/src/main/python/avro_inputformat.py
+++ b/examples/src/main/python/avro_inputformat.py
@@ -23,7 +23,8 @@ from pyspark import SparkContext
 Read data file users.avro in local Spark distro:
 
 $ cd $SPARK_HOME
-$ ./bin/spark-submit --driver-class-path /path/to/example/jar ./examples/src/main/python/avro_inputformat.py
\
+$ ./bin/spark-submit --driver-class-path /path/to/example/jar \
+> ./examples/src/main/python/avro_inputformat.py \
 > examples/src/main/resources/users.avro
 {u'favorite_color': None, u'name': u'Alyssa', u'favorite_numbers': [3, 9, 15, 20]}
 {u'favorite_color': u'red', u'name': u'Ben', u'favorite_numbers': []}
@@ -40,7 +41,8 @@ $ cat examples/src/main/resources/user.avsc
  ]
 }
 
-$ ./bin/spark-submit --driver-class-path /path/to/example/jar ./examples/src/main/python/avro_inputformat.py
\
+$ ./bin/spark-submit --driver-class-path /path/to/example/jar \
+> ./examples/src/main/python/avro_inputformat.py \
 > examples/src/main/resources/users.avro examples/src/main/resources/user.avsc
 {u'favorite_color': None, u'name': u'Alyssa'}
 {u'favorite_color': u'red', u'name': u'Ben'}
@@ -51,8 +53,10 @@ if __name__ == "__main__":
         Usage: avro_inputformat <data_file> [reader_schema_file]
 
         Run with example jar:
-        ./bin/spark-submit --driver-class-path /path/to/example/jar /path/to/examples/avro_inputformat.py
<data_file> [reader_schema_file]
-        Assumes you have Avro data stored in <data_file>. Reader schema can be optionally
specified in [reader_schema_file].
+        ./bin/spark-submit --driver-class-path /path/to/example/jar \
+        /path/to/examples/avro_inputformat.py <data_file> [reader_schema_file]
+        Assumes you have Avro data stored in <data_file>. Reader schema can be optionally
specified
+        in [reader_schema_file].
         """
         exit(-1)
 
@@ -62,9 +66,10 @@ if __name__ == "__main__":
     conf = None
     if len(sys.argv) == 3:
         schema_rdd = sc.textFile(sys.argv[2], 1).collect()
-        conf = {"avro.schema.input.key" : reduce(lambda x, y: x+y, schema_rdd)}
+        conf = {"avro.schema.input.key": reduce(lambda x, y: x + y, schema_rdd)}
 
-    avro_rdd = sc.newAPIHadoopFile(path,
+    avro_rdd = sc.newAPIHadoopFile(
+        path,
         "org.apache.avro.mapreduce.AvroKeyInputFormat",
         "org.apache.avro.mapred.AvroKey",
         "org.apache.hadoop.io.NullWritable",

http://git-wip-us.apache.org/repos/asf/spark/blob/9422c4ee/examples/src/main/python/cassandra_inputformat.py
----------------------------------------------------------------------
diff --git a/examples/src/main/python/cassandra_inputformat.py b/examples/src/main/python/cassandra_inputformat.py
index e4a897f..05f34b7 100644
--- a/examples/src/main/python/cassandra_inputformat.py
+++ b/examples/src/main/python/cassandra_inputformat.py
@@ -51,7 +51,8 @@ if __name__ == "__main__":
         Usage: cassandra_inputformat <host> <keyspace> <cf>
 
         Run with example jar:
-        ./bin/spark-submit --driver-class-path /path/to/example/jar /path/to/examples/cassandra_inputformat.py
<host> <keyspace> <cf>
+        ./bin/spark-submit --driver-class-path /path/to/example/jar \
+        /path/to/examples/cassandra_inputformat.py <host> <keyspace> <cf>
         Assumes you have some data in Cassandra already, running on <host>, in <keyspace>
and <cf>
         """
         exit(-1)
@@ -61,12 +62,12 @@ if __name__ == "__main__":
     cf = sys.argv[3]
     sc = SparkContext(appName="CassandraInputFormat")
 
-    conf = {"cassandra.input.thrift.address":host,
-            "cassandra.input.thrift.port":"9160",
-            "cassandra.input.keyspace":keyspace,
-            "cassandra.input.columnfamily":cf,
-            "cassandra.input.partitioner.class":"Murmur3Partitioner",
-            "cassandra.input.page.row.size":"3"}
+    conf = {"cassandra.input.thrift.address": host,
+            "cassandra.input.thrift.port": "9160",
+            "cassandra.input.keyspace": keyspace,
+            "cassandra.input.columnfamily": cf,
+            "cassandra.input.partitioner.class": "Murmur3Partitioner",
+            "cassandra.input.page.row.size": "3"}
     cass_rdd = sc.newAPIHadoopRDD(
         "org.apache.cassandra.hadoop.cql3.CqlPagingInputFormat",
         "java.util.Map",

http://git-wip-us.apache.org/repos/asf/spark/blob/9422c4ee/examples/src/main/python/cassandra_outputformat.py
----------------------------------------------------------------------
diff --git a/examples/src/main/python/cassandra_outputformat.py b/examples/src/main/python/cassandra_outputformat.py
index 836c35b..d144539 100644
--- a/examples/src/main/python/cassandra_outputformat.py
+++ b/examples/src/main/python/cassandra_outputformat.py
@@ -50,7 +50,8 @@ if __name__ == "__main__":
         Usage: cassandra_outputformat <host> <keyspace> <cf> <user_id>
<fname> <lname>
 
         Run with example jar:
-        ./bin/spark-submit --driver-class-path /path/to/example/jar /path/to/examples/cassandra_outputformat.py
<args>
+        ./bin/spark-submit --driver-class-path /path/to/example/jar \
+        /path/to/examples/cassandra_outputformat.py <args>
         Assumes you have created the following table <cf> in Cassandra already,
         running on <host>, in <keyspace>.
 
@@ -67,16 +68,16 @@ if __name__ == "__main__":
     cf = sys.argv[3]
     sc = SparkContext(appName="CassandraOutputFormat")
 
-    conf = {"cassandra.output.thrift.address":host,
-            "cassandra.output.thrift.port":"9160",
-            "cassandra.output.keyspace":keyspace,
-            "cassandra.output.partitioner.class":"Murmur3Partitioner",
-            "cassandra.output.cql":"UPDATE " + keyspace + "." + cf + " SET fname = ?, lname
= ?",
-            "mapreduce.output.basename":cf,
-            "mapreduce.outputformat.class":"org.apache.cassandra.hadoop.cql3.CqlOutputFormat",
-            "mapreduce.job.output.key.class":"java.util.Map",
-            "mapreduce.job.output.value.class":"java.util.List"}
-    key = {"user_id" : int(sys.argv[4])}
+    conf = {"cassandra.output.thrift.address": host,
+            "cassandra.output.thrift.port": "9160",
+            "cassandra.output.keyspace": keyspace,
+            "cassandra.output.partitioner.class": "Murmur3Partitioner",
+            "cassandra.output.cql": "UPDATE " + keyspace + "." + cf + " SET fname = ?, lname
= ?",
+            "mapreduce.output.basename": cf,
+            "mapreduce.outputformat.class": "org.apache.cassandra.hadoop.cql3.CqlOutputFormat",
+            "mapreduce.job.output.key.class": "java.util.Map",
+            "mapreduce.job.output.value.class": "java.util.List"}
+    key = {"user_id": int(sys.argv[4])}
     sc.parallelize([(key, sys.argv[5:])]).saveAsNewAPIHadoopDataset(
         conf=conf,
         keyConverter="org.apache.spark.examples.pythonconverters.ToCassandraCQLKeyConverter",

http://git-wip-us.apache.org/repos/asf/spark/blob/9422c4ee/examples/src/main/python/hbase_inputformat.py
----------------------------------------------------------------------
diff --git a/examples/src/main/python/hbase_inputformat.py b/examples/src/main/python/hbase_inputformat.py
index befacee..3b16010 100644
--- a/examples/src/main/python/hbase_inputformat.py
+++ b/examples/src/main/python/hbase_inputformat.py
@@ -51,7 +51,8 @@ if __name__ == "__main__":
         Usage: hbase_inputformat <host> <table>
 
         Run with example jar:
-        ./bin/spark-submit --driver-class-path /path/to/example/jar /path/to/examples/hbase_inputformat.py
<host> <table>
+        ./bin/spark-submit --driver-class-path /path/to/example/jar \
+        /path/to/examples/hbase_inputformat.py <host> <table>
         Assumes you have some data in HBase already, running on <host>, in <table>
         """
         exit(-1)
@@ -61,12 +62,15 @@ if __name__ == "__main__":
     sc = SparkContext(appName="HBaseInputFormat")
 
     conf = {"hbase.zookeeper.quorum": host, "hbase.mapreduce.inputtable": table}
+    keyConv = "org.apache.spark.examples.pythonconverters.ImmutableBytesWritableToStringConverter"
+    valueConv = "org.apache.spark.examples.pythonconverters.HBaseResultToStringConverter"
+
     hbase_rdd = sc.newAPIHadoopRDD(
         "org.apache.hadoop.hbase.mapreduce.TableInputFormat",
         "org.apache.hadoop.hbase.io.ImmutableBytesWritable",
         "org.apache.hadoop.hbase.client.Result",
-        keyConverter="org.apache.spark.examples.pythonconverters.ImmutableBytesWritableToStringConverter",
-        valueConverter="org.apache.spark.examples.pythonconverters.HBaseResultToStringConverter",
+        keyConverter=keyConv,
+        valueConverter=valueConv,
         conf=conf)
     output = hbase_rdd.collect()
     for (k, v) in output:

http://git-wip-us.apache.org/repos/asf/spark/blob/9422c4ee/examples/src/main/python/hbase_outputformat.py
----------------------------------------------------------------------
diff --git a/examples/src/main/python/hbase_outputformat.py b/examples/src/main/python/hbase_outputformat.py
index 49bbc5a..abb425b 100644
--- a/examples/src/main/python/hbase_outputformat.py
+++ b/examples/src/main/python/hbase_outputformat.py
@@ -44,8 +44,10 @@ if __name__ == "__main__":
         Usage: hbase_outputformat <host> <table> <row> <family> <qualifier>
<value>
 
         Run with example jar:
-        ./bin/spark-submit --driver-class-path /path/to/example/jar /path/to/examples/hbase_outputformat.py
<args>
-        Assumes you have created <table> with column family <family> in HBase
running on <host> already
+        ./bin/spark-submit --driver-class-path /path/to/example/jar \
+        /path/to/examples/hbase_outputformat.py <args>
+        Assumes you have created <table> with column family <family> in HBase
+        running on <host> already
         """
         exit(-1)
 
@@ -55,13 +57,15 @@ if __name__ == "__main__":
 
     conf = {"hbase.zookeeper.quorum": host,
             "hbase.mapred.outputtable": table,
-            "mapreduce.outputformat.class" : "org.apache.hadoop.hbase.mapreduce.TableOutputFormat",
-            "mapreduce.job.output.key.class" : "org.apache.hadoop.hbase.io.ImmutableBytesWritable",
-            "mapreduce.job.output.value.class" : "org.apache.hadoop.io.Writable"}
+            "mapreduce.outputformat.class": "org.apache.hadoop.hbase.mapreduce.TableOutputFormat",
+            "mapreduce.job.output.key.class": "org.apache.hadoop.hbase.io.ImmutableBytesWritable",
+            "mapreduce.job.output.value.class": "org.apache.hadoop.io.Writable"}
+    keyConv = "org.apache.spark.examples.pythonconverters.StringToImmutableBytesWritableConverter"
+    valueConv = "org.apache.spark.examples.pythonconverters.StringListToPutConverter"
 
     sc.parallelize([sys.argv[3:]]).map(lambda x: (x[0], x)).saveAsNewAPIHadoopDataset(
         conf=conf,
-        keyConverter="org.apache.spark.examples.pythonconverters.StringToImmutableBytesWritableConverter",
-        valueConverter="org.apache.spark.examples.pythonconverters.StringListToPutConverter")
+        keyConverter=keyConv,
+        valueConverter=valueConv)
 
     sc.stop()

http://git-wip-us.apache.org/repos/asf/spark/blob/9422c4ee/examples/src/main/python/mllib/correlations.py
----------------------------------------------------------------------
diff --git a/examples/src/main/python/mllib/correlations.py b/examples/src/main/python/mllib/correlations.py
index 6b16a56..4218eca 100755
--- a/examples/src/main/python/mllib/correlations.py
+++ b/examples/src/main/python/mllib/correlations.py
@@ -28,7 +28,7 @@ from pyspark.mllib.util import MLUtils
 
 
 if __name__ == "__main__":
-    if len(sys.argv) not in [1,2]:
+    if len(sys.argv) not in [1, 2]:
         print >> sys.stderr, "Usage: correlations (<file>)"
         exit(-1)
     sc = SparkContext(appName="PythonCorrelations")

http://git-wip-us.apache.org/repos/asf/spark/blob/9422c4ee/examples/src/main/python/mllib/decision_tree_runner.py
----------------------------------------------------------------------
diff --git a/examples/src/main/python/mllib/decision_tree_runner.py b/examples/src/main/python/mllib/decision_tree_runner.py
index 6e4a4a0..61ea4e0 100755
--- a/examples/src/main/python/mllib/decision_tree_runner.py
+++ b/examples/src/main/python/mllib/decision_tree_runner.py
@@ -21,7 +21,9 @@ Decision tree classification and regression using MLlib.
 This example requires NumPy (http://www.numpy.org/).
 """
 
-import numpy, os, sys
+import numpy
+import os
+import sys
 
 from operator import add
 
@@ -127,7 +129,7 @@ if __name__ == "__main__":
     (reindexedData, origToNewLabels) = reindexClassLabels(points)
 
     # Train a classifier.
-    categoricalFeaturesInfo={} # no categorical features
+    categoricalFeaturesInfo = {}  # no categorical features
     model = DecisionTree.trainClassifier(reindexedData, numClasses=2,
                                          categoricalFeaturesInfo=categoricalFeaturesInfo)
     # Print learned tree and stats.

http://git-wip-us.apache.org/repos/asf/spark/blob/9422c4ee/examples/src/main/python/mllib/random_rdd_generation.py
----------------------------------------------------------------------
diff --git a/examples/src/main/python/mllib/random_rdd_generation.py b/examples/src/main/python/mllib/random_rdd_generation.py
index b388d8d..1e88927 100755
--- a/examples/src/main/python/mllib/random_rdd_generation.py
+++ b/examples/src/main/python/mllib/random_rdd_generation.py
@@ -32,8 +32,8 @@ if __name__ == "__main__":
 
     sc = SparkContext(appName="PythonRandomRDDGeneration")
 
-    numExamples = 10000 # number of examples to generate
-    fraction = 0.1 # fraction of data to sample
+    numExamples = 10000  # number of examples to generate
+    fraction = 0.1  # fraction of data to sample
 
     # Example: RandomRDDs.normalRDD
     normalRDD = RandomRDDs.normalRDD(sc, numExamples)
@@ -45,7 +45,7 @@ if __name__ == "__main__":
     print
 
     # Example: RandomRDDs.normalVectorRDD
-    normalVectorRDD = RandomRDDs.normalVectorRDD(sc, numRows = numExamples, numCols = 2)
+    normalVectorRDD = RandomRDDs.normalVectorRDD(sc, numRows=numExamples, numCols=2)
     print 'Generated RDD of %d examples of length-2 vectors.' % normalVectorRDD.count()
     print '  First 5 samples:'
     for sample in normalVectorRDD.take(5):

http://git-wip-us.apache.org/repos/asf/spark/blob/9422c4ee/examples/src/main/python/mllib/sampled_rdds.py
----------------------------------------------------------------------
diff --git a/examples/src/main/python/mllib/sampled_rdds.py b/examples/src/main/python/mllib/sampled_rdds.py
index ec64a59..92af3af 100755
--- a/examples/src/main/python/mllib/sampled_rdds.py
+++ b/examples/src/main/python/mllib/sampled_rdds.py
@@ -36,7 +36,7 @@ if __name__ == "__main__":
 
     sc = SparkContext(appName="PythonSampledRDDs")
 
-    fraction = 0.1 # fraction of data to sample
+    fraction = 0.1  # fraction of data to sample
 
     examples = MLUtils.loadLibSVMFile(sc, datapath)
     numExamples = examples.count()
@@ -49,9 +49,9 @@ if __name__ == "__main__":
     expectedSampleSize = int(numExamples * fraction)
     print 'Sampling RDD using fraction %g.  Expected sample size = %d.' \
         % (fraction, expectedSampleSize)
-    sampledRDD = examples.sample(withReplacement = True, fraction = fraction)
+    sampledRDD = examples.sample(withReplacement=True, fraction=fraction)
     print '  RDD.sample(): sample has %d examples' % sampledRDD.count()
-    sampledArray = examples.takeSample(withReplacement = True, num = expectedSampleSize)
+    sampledArray = examples.takeSample(withReplacement=True, num=expectedSampleSize)
     print '  RDD.takeSample(): sample has %d examples' % len(sampledArray)
 
     print
@@ -66,7 +66,7 @@ if __name__ == "__main__":
     fractions = {}
     for k in keyCountsA.keys():
         fractions[k] = fraction
-    sampledByKeyRDD = keyedRDD.sampleByKey(withReplacement = True, fractions = fractions)
+    sampledByKeyRDD = keyedRDD.sampleByKey(withReplacement=True, fractions=fractions)
     keyCountsB = sampledByKeyRDD.countByKey()
     sizeB = sum(keyCountsB.values())
     print '  Sampled %d examples using approximate stratified sampling (by label). ==>
Sample' \

http://git-wip-us.apache.org/repos/asf/spark/blob/9422c4ee/examples/src/main/python/pi.py
----------------------------------------------------------------------
diff --git a/examples/src/main/python/pi.py b/examples/src/main/python/pi.py
index fc37459..ee9036a 100755
--- a/examples/src/main/python/pi.py
+++ b/examples/src/main/python/pi.py
@@ -35,7 +35,7 @@ if __name__ == "__main__":
         y = random() * 2 - 1
         return 1 if x ** 2 + y ** 2 < 1 else 0
 
-    count = sc.parallelize(xrange(1, n+1), slices).map(f).reduce(add)
+    count = sc.parallelize(xrange(1, n + 1), slices).map(f).reduce(add)
     print "Pi is roughly %f" % (4.0 * count / n)
 
     sc.stop()


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