doc

README.md

@@ -5,19 +5,19 @@
 [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
 ![GitHub last commit](https://img.shields.io/github/last-commit/danionella/dejaq)
 
-# DéjàQueue
+# Déjà Queue
 
-A fast drop-in replacement for `multiprocessing.Queue` taking advantage of a [shared memory](https://docs.python.org/3/library/multiprocessing.html#multiprocessing.Array) ring buffer and [pickle protocol 5 with out-of-band data](https://peps.python.org/pep-0574/). As with other queues in Python, data is transmitted via `put` and `get` calls.
+A fast drop-in replacement for `multiprocessing.Queue` taking advantage of a [shared memory](https://docs.python.org/3/library/multiprocessing.html#multiprocessing.Array) ring buffer and [pickle protocol 5 out-of-band data](https://peps.python.org/pep-0574/) to minimize copies. As with other queues in Python, data is transmitted via `put` and `get` calls.
 
-DejaQueue supports any type of picklable Python object, including numpy arrays or nested dictionaries with mixed content. It uses locks to support more than one producer and comsumer process.
+`dejaq.DejaQueue` supports any type of picklable Python object, including numpy arrays or nested dictionaries with mixed content. It uses locks to support more than one producer and comsumer process.
 
 Auto-generated API documentation: https://danionella.github.io/dejaq
 
 ## Usage example
 ```python
 import numpy as np
 from multiprocessing import Process
-from dqjaq import DejaQueue
+from dejaq import DejaQueue
 
 def produce(queue):
     for i in range(20):

dejaq/__init__.py

@@ -6,6 +6,7 @@
 
 @dataclasses.dataclass
 class FrameInfo:
+    ''' A class to store metadata about a frame in a FIFO queue.'''
     nbytes: int
     head: int
     tail: int
@@ -207,7 +208,7 @@ def callback_wrapper(array_bytes, meta):
         return array, meta
 
 class DejaQueue(ByteFIFO):
-    """ A fast queue for Python objects. The queue is implemented as a ring buffer in shared memory.
+    """ A fast queue for arbitrary (picklable) Python objects. The queue is implemented as a ring buffer in shared memory.
 
     Args:
         buffer_size (int): The size of the buffer in bytes.