Merge pull request #8 from sptramer/pep8

Run PEP8 on content

Author: laurenhughes

src/batch_python_tutorial_ffmpeg.py

@@ -23,6 +23,7 @@
 # unique to your accounts. These are used when constructing connection strings
 # for the Batch and Storage client objects.
 
+
 def query_yes_no(question, default="yes"):
     """
     Prompts the user for yes/no input, displaying the specified question text.
@@ -92,11 +93,10 @@ def upload_file_to_container(block_blob_client, container_name, file_path):
     block_blob_client.create_blob_from_path(container_name,
                                             blob_name,
                                             file_path)
-    
+
     # Obtain the SAS token for the container.
     sas_token = get_container_sas_token(block_blob_client,
-                            container_name, azureblob.BlobPermissions.READ)
-    
+                                        container_name, azureblob.BlobPermissions.READ)
 
     sas_url = block_blob_client.make_blob_url(container_name,
                                               blob_name,
@@ -105,6 +105,7 @@ def upload_file_to_container(block_blob_client, container_name, file_path):
     return batchmodels.ResourceFile(file_path=blob_name,
                                     http_url=sas_url)
 
+
 def get_container_sas_token(block_blob_client,
                             container_name, blob_permissions):
     """
@@ -130,9 +131,8 @@ def get_container_sas_token(block_blob_client,
     return container_sas_token
 
 
-
 def get_container_sas_url(block_blob_client,
-                            container_name, blob_permissions):
+                          container_name, blob_permissions):
     """
     Obtains a shared access signature URL that provides write access to the 
     ouput container to which the tasks will upload their output.
@@ -146,10 +146,11 @@ def get_container_sas_url(block_blob_client,
     """
     # Obtain the SAS token for the container.
     sas_token = get_container_sas_token(block_blob_client,
-                            container_name, azureblob.BlobPermissions.WRITE)
+                                        container_name, azureblob.BlobPermissions.WRITE)
 
     # Construct SAS URL for the container
-    container_sas_url = "https://{}.blob.core.windows.net/{}?{}".format(config._STORAGE_ACCOUNT_NAME, container_name, sas_token)
+    container_sas_url = "https://{}.blob.core.windows.net/{}?{}".format(
+        config._STORAGE_ACCOUNT_NAME, container_name, sas_token)
 
     return container_sas_url
 
@@ -174,16 +175,16 @@ def create_pool(batch_service_client, pool_id):
 
     # The start task installs ffmpeg on each node from an available repository, using
     # an administrator user identity.
-  
+
     new_pool = batch.models.PoolAddParameter(
         id=pool_id,
         virtual_machine_configuration=batchmodels.VirtualMachineConfiguration(
             image_reference=batchmodels.ImageReference(
-        	    publisher="Canonical",
-        	    offer="UbuntuServer",
-        	    sku="18.04-LTS",
-        	    version="latest"
-                ),
+                publisher="Canonical",
+                offer="UbuntuServer",
+                sku="18.04-LTS",
+                version="latest"
+            ),
             node_agent_sku_id="batch.node.ubuntu 18.04"),
         vm_size=config._POOL_VM_SIZE,
         target_dedicated_nodes=config._DEDICATED_POOL_NODE_COUNT,
@@ -193,13 +194,14 @@ def create_pool(batch_service_client, pool_id):
             wait_for_success=True,
             user_identity=batchmodels.UserIdentity(
                 auto_user=batchmodels.AutoUserSpecification(
-                scope=batchmodels.AutoUserScope.pool,
-                elevation_level=batchmodels.ElevationLevel.admin)),
-         )
+                    scope=batchmodels.AutoUserScope.pool,
+                    elevation_level=batchmodels.ElevationLevel.admin)),
+        )
     )
 
     batch_service_client.pool.add(new_pool)
 
+
 def create_job(batch_service_client, job_id, pool_id):
     """
     Creates a job with the specified ID, associated with the specified pool.
@@ -216,7 +218,8 @@ def create_job(batch_service_client, job_id, pool_id):
         pool_info=batch.models.PoolInformation(pool_id=pool_id))
 
     batch_service_client.job.add(job)
-    
+
+
 def add_tasks(batch_service_client, job_id, input_files, output_container_sas_url):
     """
     Adds a task for each input file in the collection to the specified job.
@@ -234,26 +237,26 @@ def add_tasks(batch_service_client, job_id, input_files, output_container_sas_ur
 
     tasks = list()
 
-    for idx, input_file in enumerate(input_files): 
-        input_file_path=input_file.file_path
-        output_file_path="".join((input_file_path).split('.')[:-1]) + '.mp3'
-        command = "/bin/bash -c \"ffmpeg -i {} {} \"".format(input_file_path, output_file_path)
+    for idx, input_file in enumerate(input_files):
+        input_file_path = input_file.file_path
+        output_file_path = "".join((input_file_path).split('.')[:-1]) + '.mp3'
+        command = "/bin/bash -c \"ffmpeg -i {} {} \"".format(
+            input_file_path, output_file_path)
         tasks.append(batch.models.TaskAddParameter(
             id='Task{}'.format(idx),
             command_line=command,
             resource_files=[input_file],
             output_files=[batchmodels.OutputFile(
-                      file_pattern=output_file_path,
-                      destination=batchmodels.OutputFileDestination(
-                        container=batchmodels.OutputFileBlobContainerDestination(
-                            container_url=output_container_sas_url)),
-                      upload_options=batchmodels.OutputFileUploadOptions(
-                        upload_condition=batchmodels.OutputFileUploadCondition.task_success))]
-            )
-     )
+                file_pattern=output_file_path,
+                destination=batchmodels.OutputFileDestination(
+                          container=batchmodels.OutputFileBlobContainerDestination(
+                              container_url=output_container_sas_url)),
+                upload_options=batchmodels.OutputFileUploadOptions(
+                    upload_condition=batchmodels.OutputFileUploadCondition.task_success))]
+        )
+        )
     batch_service_client.task.add_collection(job_id, tasks)
 
-    
 
 def wait_for_tasks_to_complete(batch_service_client, job_id, timeout):
     """
@@ -289,7 +292,6 @@ def wait_for_tasks_to_complete(batch_service_client, job_id, timeout):
                        "timeout period of " + str(timeout))
 
 
-
 if __name__ == '__main__':
 
     start_time = datetime.datetime.now().replace(microsecond=0)
@@ -299,37 +301,37 @@ def wait_for_tasks_to_complete(batch_service_client, job_id, timeout):
     # Create the blob client, for use in obtaining references to
     # blob storage containers and uploading files to containers.
 
-    
     blob_client = azureblob.BlockBlobService(
         account_name=config._STORAGE_ACCOUNT_NAME,
         account_key=config._STORAGE_ACCOUNT_KEY)
 
     # Use the blob client to create the containers in Azure Storage if they
     # don't yet exist.
- 
+
     input_container_name = 'input'
     output_container_name = 'output'
     blob_client.create_container(input_container_name, fail_on_exist=False)
     blob_client.create_container(output_container_name, fail_on_exist=False)
     print('Container [{}] created.'.format(input_container_name))
     print('Container [{}] created.'.format(output_container_name))
 
-    # Create a list of all MP4 files in the InputFiles directory. 
+    # Create a list of all MP4 files in the InputFiles directory.
     input_file_paths = []
-    
-    for folder, subs, files in os.walk(os.path.join(sys.path[0],'InputFiles')):
+
+    for folder, subs, files in os.walk(os.path.join(sys.path[0], 'InputFiles')):
         for filename in files:
             if filename.endswith(".mp4"):
-                input_file_paths.append(os.path.abspath(os.path.join(folder, filename)))
+                input_file_paths.append(os.path.abspath(
+                    os.path.join(folder, filename)))
 
-    # Upload the input files. This is the collection of files that are to be processed by the tasks. 
+    # Upload the input files. This is the collection of files that are to be processed by the tasks.
     input_files = [
         upload_file_to_container(blob_client, input_container_name, file_path)
         for file_path in input_file_paths]
 
     # Obtain a shared access signature URL that provides write access to the output
     # container to which the tasks will upload their output.
-    
+
     output_container_sas_url = get_container_sas_url(
         blob_client,
         output_container_name,
@@ -348,30 +350,30 @@ def wait_for_tasks_to_complete(batch_service_client, job_id, timeout):
         # Create the pool that will contain the compute nodes that will execute the
         # tasks.
         create_pool(batch_client, config._POOL_ID)
-        
+
         # Create the job that will run the tasks.
         create_job(batch_client, config._JOB_ID, config._POOL_ID)
 
-        # Add the tasks to the job. Pass the input files and a SAS URL 
+        # Add the tasks to the job. Pass the input files and a SAS URL
         # to the storage container for output files.
-        add_tasks(batch_client, config._JOB_ID, input_files, output_container_sas_url)
+        add_tasks(batch_client, config._JOB_ID,
+                  input_files, output_container_sas_url)
 
         # Pause execution until tasks reach Completed state.
         wait_for_tasks_to_complete(batch_client,
                                    config._JOB_ID,
                                    datetime.timedelta(minutes=30))
 
         print("  Success! All tasks reached the 'Completed' state within the "
-          "specified timeout period.")
+              "specified timeout period.")
 
     except batchmodels.BatchErrorException as err:
-            print_batch_exception(err)
-            raise
+        print_batch_exception(err)
+        raise
 
     # Delete input container in storage
     print('Deleting container [{}]...'.format(input_container_name))
     blob_client.delete_container(input_container_name)
-    
 
     # Print out some timing info
     end_time = datetime.datetime.now().replace(microsecond=0)

src/config.py

@@ -1,15 +1,15 @@
-#-------------------------------------------------------------------------
-# 
-# THIS CODE AND INFORMATION ARE PROVIDED "AS IS" WITHOUT WARRANTY OF ANY KIND, 
-# EITHER EXPRESSED OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE IMPLIED WARRANTIES 
+# -------------------------------------------------------------------------
+#
+# THIS CODE AND INFORMATION ARE PROVIDED "AS IS" WITHOUT WARRANTY OF ANY KIND,
+# EITHER EXPRESSED OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE IMPLIED WARRANTIES
 # OF MERCHANTABILITY AND/OR FITNESS FOR A PARTICULAR PURPOSE.
-#----------------------------------------------------------------------------------
+# ----------------------------------------------------------------------------------
 # The example companies, organizations, products, domain names,
 # e-mail addresses, logos, people, places, and events depicted
 # herein are fictitious. No association with any real company,
 # organization, product, domain name, email address, logo, person,
 # places, or events is intended or should be inferred.
-#--------------------------------------------------------------------------
+# --------------------------------------------------------------------------
 
 # Global constant variables (Azure Storage account/Batch details)
 
@@ -19,7 +19,7 @@
 # unique to your accounts. These are used when constructing connection strings
 # for the Batch and Storage client objects.
 
-_BATCH_ACCOUNT_NAME =''
+_BATCH_ACCOUNT_NAME = ''
 _BATCH_ACCOUNT_KEY = ''
 _BATCH_ACCOUNT_URL = ''
 _STORAGE_ACCOUNT_NAME = ''
@@ -28,4 +28,4 @@
 _DEDICATED_POOL_NODE_COUNT = 0
 _LOW_PRIORITY_POOL_NODE_COUNT = 5
 _POOL_VM_SIZE = 'STANDARD_A1_v2'
-_JOB_ID = 'LinuxFfmpegJob'
+_JOB_ID = 'LinuxFfmpegJob'