Version 0.1

Author: dkumor

examples/basics/README.md

@@ -94,7 +94,7 @@ The `camera.subscribe` function allows you to subscribe to video frames incoming
 firing the `onFrame` function 30 times a second with [numpy](https://en.wikipedia.org/wiki/NumPy) arrays containing BGR images captured by the camera.
 The `put_nowait` function is then used to send the frame to the window where the image is displayed.
 
-These two functions form the core of RTCBot's abilities. Every producer of data (like `CVCamera`) has a `subscribe()` method, and every consumer of data (like `CVDisplay`) has a `put_nowait` method to insert data.
+These two functions are part of RTCBot's core abilities. Every producer of data (like `CVCamera`) has a `subscribe()` method, and every consumer of data (like `CVDisplay`) has a `put_nowait` method to insert data.
 
 ```eval_rst
 .. note::
@@ -108,19 +108,25 @@ These two functions form the core of RTCBot's abilities. Every producer of data
 
 ## Subscriptions
 
-In RTCBot, a subscription is any object with a `put_nowait` method, and a `get` coroutine:
+Using a callback function with the `subscribe` method is not the only way to 
+get data out of a data-producing object. The `subscribe` method is also able
+to create what is called a `subscription`.
+
+To understand subscriptions, let's take a quick detour to python Queues:
 
 ```python
 import asyncio
 
-# An asyncio Queue is a subscription
+# An asyncio Queue has put_nowait and get coroutine
 q = asyncio.Queue()
 
+# Sends data each second
 async def sender():
     while True:
         await asyncio.sleep(1)
         q.put_nowait("hi!")
 
+# Receives the data
 async def receiver():
     while True:
         data = await q.get()
@@ -131,10 +137,9 @@ asyncio.ensure_future(receiver())
 asyncio.get_event_loop().run_forever()
 ```
 
-Here, the `sender` function sends data, and the `receiver` awaits for incoming data, and prints it.
+Here, the `sender` function sends data, and the `receiver` awaits for incoming data, and prints it. Notice how the queue had a `get` coroutine from which data could be awaited.
 
-In the example where we viewed a video feed, `subscribe` was used as a decorator for a callback function.
-This is just a small part of the actual power of the `subscribe` method. When run without an argument, it actually returns a subscription, which `CVCamera` automatically keeps updated with new video frames as they come in:
+We can use the `subscribe` method in a similar way to the above code snippet. When run without an argument, `subscribe` actually returns a subscription, which `CVCamera` automatically keeps updated with new video frames as they come in:
 
 ```python
 import asyncio
@@ -200,7 +205,7 @@ finally:
 
 ## Generalizing to Audio
 
-The above code examples created a video stream, and displayed it in a window. RTCBot uses _exactly the same_ API for **everything**. This means that we can trivially add audio to the previous example:
+The above code examples all created a video stream, and displayed it in a window. RTCBot uses _exactly the same_ API for **everything**. This means that we can trivially add audio to the previous example:
 
 ```python
 import asyncio
@@ -223,7 +228,7 @@ finally:
     speaker.close()
 ```
 
-With this example, a video stream should be displayed in a window, and all microphone input should be playing in your headphones (or speakers).
+Here, a video stream should be displayed in a window, and all microphone input should be playing in your headphones (or speakers).
 
 ## Summary
 

examples/offloading/README.md

@@ -131,12 +131,3 @@ Control message: {'timestamp': 1553379217.004892, 'code': 'ABS_X', 'state': -125
    The output for the `Gamepad` object is currently different in Javascript and in Python. Make sure you don't mix them up!
 ```
 
-## Machine Learning a Controller
-
-This portion of the tutorial focuses on modifying the desktop code from the previous portion to include
-a neural network which is trained exploiting the computational power available on a desktop PC.
-
-This is an _advanced_ topic, requiring a working knowledge of machine learning basics. It is also assumed
-that you are using linux on your desktop, and that you have an nvidia graphics card compatible with [pytorch](https://pytorch.org). If you choose to attempt this part on a windows desktop or on a mac, be aware that you might run into some problems that might require some googling skills to solve.
-
-### Under Construction...

examples/remotecontrol/README.md

@@ -214,7 +214,7 @@ key press {'value': -0.8708761930465698, 'type': 'axis2'}
 key press {'value': -0.7945494055747986, 'type': 'axis2'}
 ```
 
-The controller's buttons give boolean values, and the joysticks give float values between -1 and 1. By default, the controller is polled at 10Hz as not to overwhelm an embedded computer like the Pi with tons of data each time a joystick is moved.
+The controller's buttons give boolean values, and the joysticks give float values between -1 and 1. By default, the controller is polled at 10Hz as not to overwhelm a Pi 3 with tons of data each time a joystick is moved.
 
 ## Remote Control
 

js/package.json

@@ -1,6 +1,6 @@
 {
   "name": "rtcbot",
-  "version": "0.0.9",
+  "version": "0.1.0",
   "description": "",
   "main": "dist/rtcbot.cjs.js",
   "module": "dist/rtcbot.esm.js",

rtcbot/__init__.py

@@ -10,4 +10,4 @@
 from .devices import *
 
 
-__version__="0.0.9"
+__version__="0.1.0"

setup.py

@@ -10,7 +10,7 @@
 # This call to setup() does all the work
 setuptools.setup(
     name="rtcbot",
-    version="0.0.9",
+    version="0.1.0",
     description="An asyncio-focused library for webrtc robot control",
     long_description=README,
     long_description_content_type="text/markdown",