X-Git-Url: https://git.arvados.org/arvados.git/blobdiff_plain/18258f6a3762ba7d83b05260b3c22f71423c0373..6a5064852f67f11915dd0c956128a6363f1d83c8:/doc/_includes/_tutorial_hash_script_py.liquid

diff --git a/doc/_includes/_tutorial_hash_script_py.liquid b/doc/_includes/_tutorial_hash_script_py.liquid
index f9b2ec0948..b9c7f31532 100644
--- a/doc/_includes/_tutorial_hash_script_py.liquid
+++ b/doc/_includes/_tutorial_hash_script_py.liquid
@@ -1,63 +1,45 @@
 #!/usr/bin/env python
 
-# Import the hashlib module (part of the Python standard library) to compute md5.
-import hashlib
+import hashlib      # Import the hashlib module to compute MD5.
+import arvados      # Import the Arvados sdk module
 
-# Import the Arvados sdk module
-import arvados
+# Automatically parallelize this job by running one task per file.
+# This means that if the input consists of many files, each file will
+# be processed in parallel on different nodes enabling the job to 
+# be completed quicker.
+arvados.job_setup.one_task_per_input_file(if_sequence=0, and_end_task=True, 
+                                          input_as_path=True)
 
-# Get information about the task from the environment
-this_task = arvados.current_task()
-
-# Get the "input" field from "script_parameters" on the job creation object
-this_job_input = arvados.getjobparam('input')
-
-# Create the object access to the collection referred to in the input
-collection = arvados.CollectionReader(this_job_input)
-
-# Create an object to write a new collection as output
-out = arvados.CollectionWriter()
-
-# Set the name of output file within the collection
-out.set_current_file_name("md5sum.txt")
+# Create the message digest object that will compute the MD5 hash
+digestor = hashlib.new('md5')
 
-# Get an iterator over the files listed in the collection
-all_files = collection.all_files()
-
-# Iterate over each file
-for input_file in all_files:
-    # Create the object that will actually compute the md5 hash
-    digestor = hashlib.new('md5')
+# Get the input file for the task
+input_file = arvados.get_task_param_mount('input')
 
+# Open the input file for reading
+with open(input_file) as f:
     while True:
-        # read a 1 megabyte block from the file
-        buf = input_file.read(2**20)
-
-        # break when there is no more data left
-        if len(buf) == 0:
+        buf = f.read(2**20)      # read a 1 megabyte block from the file
+        if len(buf) == 0:        # break when there is no more data left
             break
+        digestor.update(buf)     # update the MD5 hash object
 
-        # update the md5 hash object
-        digestor.update(buf)
-
-    # Get the final hash code
-    hexdigest = digestor.hexdigest()
+# Get object representing the current task
+this_task = arvados.current_task()
 
-    # Get the file name from the StreamFileReader object
-    file_name = input_file.name()
+ # Write a new collection as output
+out = arvados.CollectionWriter()
 
-    # The "stream name" is the subdirectory inside the collection in which
-    # the file is located; '.' is the root of the collection.
-    if input_file.stream_name() != '.':
-        file_name = os.join(input_file.stream_name(), file_name)
+ # Set output file within the collection
+out.set_current_file_name("md5sum.txt")
 
-    # Write an output line with the md5 value and file name.
-    out.write("%s %s\n" % (hexdigest, file_name))
+# Write an output line with the MD5 value and input
+out.write("%s %s\n" % (digestor.hexdigest(), this_task['parameters']['input']))
 
-# Commit the output to keep.  This returns a Keep id.
+ # Commit the output to keep.  This returns a Keep id.
 output_id = out.finish()
 
 # Set the output for this task to the Keep id
-this_task.set_output(output_id)
+this_task.set_output(output_id) 
 
 # Done!