[SW-2095][FollowUp] Remove and replace remaining reference in example…

…s tests (#1990) (#1994)

py/examples/ChicagoCrimeDemo.py

@@ -4,7 +4,6 @@
 from pyspark.sql import Row, SparkSession
 import os
 from pysparkling import *
-import sys
 
 
 # Refine date column
@@ -80,8 +79,7 @@ def crime(date,
 
 # This is just helper function returning path to data-files
 def _locate(file_name):
-        basedir = sys.argv[1]
-        return os.path.abspath(basedir + "./../examples/smalldata/chicago/" + file_name)
+        return os.path.abspath("../examples/smalldata/chicago/" + file_name)
 
 spark = SparkSession.builder.appName("ChicagoCrimeTest").getOrCreate()
 # Start H2O services

py/examples/HamOrSpamMultiAlgorithmDemo.py

@@ -1,5 +1,4 @@
 import os
-import sys
 
 from pyspark.ml import Pipeline, PipelineModel
 from pyspark.ml.feature import HashingTF, RegexTokenizer, StopWordsRemover, IDF
@@ -15,8 +14,7 @@
 
 ## This method loads the data, perform some basic filtering and create Spark's dataframe
 def load():
-    basedir = sys.argv[1]
-    dataPath = "file://" + os.path.abspath(basedir + "./../examples/smalldata/smsData.txt")
+    dataPath = "file://" + os.path.abspath("../examples/smalldata/smsData.txt")
     row_rdd = spark.sparkContext.textFile(dataPath).map(lambda x: x.split("\t", 1)).filter(lambda r: r[0].strip())
     return spark.createDataFrame(row_rdd, ["label", "text"])
 
@@ -82,13 +80,13 @@ def trainPipelineModel(idf, hashingTF, stopWordsRemover, tokenizer, algoStage, d
     ## Test exporting and importing the pipeline. On Systems where HDFS & Hadoop is not available, this call store the pipeline
     ## to local file in the current directory. In case HDFS & Hadoop is available, this call stores the pipeline to HDFS home
     ## directory for the current user. Absolute paths can be used as wells. The same holds for the model import/export bellow.
-    pipeline.write().overwrite().save("../../build/pipeline")
-    loaded_pipeline = Pipeline.load("../../build/pipeline")
+    pipeline.write().overwrite().save("../build/pipeline")
+    loaded_pipeline = Pipeline.load("../build/pipeline")
 
     ## Train the pipeline model
     model = loaded_pipeline.fit(data)
-    model.write().overwrite().save("../../build/model")
-    return PipelineModel.load("../../build/model")
+    model.write().overwrite().save("../build/model")
+    return PipelineModel.load("../build/model")
 
 
 def isSpam(smsText, model):

py/tests/integration/integ_test_utils.py

@@ -18,7 +18,6 @@
 
 import subprocess
 import sys
-import os
 
 
 def get_default_spark_conf(additional_conf=None):
@@ -55,9 +54,6 @@ def launch(conf, script_name):
     # Add path to test script
     cmd_line.append(script_name)
 
-    # Add current dir to script as parameter
-    cmd_line.append( os.getcwd())
-
     # Launch it via command line
     return_code = subprocess.call(cmd_line)