Execute container commands in parallel

Commands able to use this parallelisation are `stop`, `kill` and `rm`.

We're using a backported function from python 3, to allow us to make
the most of a pool of threads without having to write the low level
code for managing this ourselves.

A default value for number of threads is a low enough number so it
shouldn't cause performance problems but if someone knows the
capability of their system and wants to increase it, they can via
an environment variable DEFAULT_MAX_WORKERS

Signed-off-by: Mazz Mosley <mazz@houseofmnowster.com>

compose/utils.py

@@ -1,5 +1,39 @@
-import json
 import hashlib
+import json
+import logging
+import os
+
+import concurrent.futures
+
+from .const import DEFAULT_MAX_WORKERS
+
+
+log = logging.getLogger(__name__)
+
+
+def parallel_execute(command, containers, doing_msg, done_msg, **options):
+    """
+    Execute a given command upon a list of containers in parallel.
+    """
+    max_workers = os.environ.get('MAX_WORKERS', DEFAULT_MAX_WORKERS)
+
+    def container_command_execute(container, command, **options):
+        log.info("{} {}...".format(doing_msg, container.name))
+        return getattr(container, command)(**options)
+
+    with concurrent.futures.ThreadPoolExecutor(max_workers=max_workers) as executor:
+        future_container = {
+            executor.submit(
+                container_command_execute,
+                container,
+                command,
+                **options
+            ): container for container in containers
+        }
+
+        for future in concurrent.futures.as_completed(future_container):
+            container = future_container[future]
+            log.info("{} {}".format(done_msg, container.name))
 
 
 def json_hash(obj):