Detailed information on devloping in the webrtc github repo can be found in the WebRTC GitHub repo developer's guide.
The development AppRTC server can be accessed by visiting http://localhost:8080.
Running AppRTC locally requires the Google App Engine SDK for Python and Grunt.
Detailed instructions for running on Ubuntu Linux are provided below.
Install grunt by first installing npm. npm is distributed as part of nodejs.
sudo apt-get install nodejs
sudo npm install -g npm
On Ubuntu 14.04 the default packages installs /usr/bin/nodejs
but the /usr/bin/node
executable is required for grunt. This is installed on some Ubuntu package sets; if it is missing, you can add this by installing the nodejs-legacy
package,
sudo apt-get install nodejs-legacy
It is easiest to install a shared version of grunt-cli
from npm
using the -g
flag. This will allow you access the grunt
command from /usr/local/bin
. More information can be found on gruntjs
Getting Started.
sudo npm -g install grunt-cli
Omitting the -g
flag will install grunt-cli
to the current directory under the node_modules
directory.
Finally, you will want to install grunt and required grunt dependencies. This can be done from any directory under your checkout of the webrtc/apprtc repository.
npm install
On Ubuntu, you will also need to install the webtest package:
sudo apt-get install python-webtest
Before you start the AppRTC dev server and *everytime you update the source code you need to recompile the App Engine package by running,
grunt build
Start the AppRTC dev server from the out/app_engine
directory by running the Google App Engine SDK dev server,
<path to sdk>/dev_appserver.py ./out/app_engine
Then navigate to http://localhost:8080 in your browser (given it's on the same machine).
All tests by running grunt
.
To run only the Python tests you can call,
grunt runPythonTests
Note that logging is automatically enabled when running on Google App Engine using an implicit service account.
By default, logging to a BigQuery from the development server is disabled. Log information is presented on the console. Unless you are modifying the analytics API you will not need to enable remote logging.
Logging to BigQuery when running LOCALLY requires a secrets.json
containing Service Account credentials to a Google Developer project where BigQuery is enabled. DO NOT COMMIT secrets.json
TO THE REPOSITORY.
To generate a secrets.json
file in the Google Developers Console for your project:
- Go to the project page.
- Under APIs & auth select Credentials.
- Confirm a Service Account already exists or create it by selecting Create new Client ID.
- Select Generate new JSON key from the Service Account area to create and download JSON credentials.
- Rename the downloaded file to
secrets.json
and place in the directory containinganalytics.py
.
When the Analytics
class detects that AppRTC is running locally, all data is logged to analytics
table in the dev
dataset. You can bootstrap the dev
dataset by following the instructions in the Bootstrapping/Updating BigQuery.
When running on App Engine the Analytics
class will log to analytics
table in the prod
dataset for whatever project is defined in app.yaml
.
bigquery/analytics_schema.json
contains the fields used in the BigQuery table. New fields can be added to the schema and the table updated. However, fields cannot be renamed or removed. Caution should be taken when updating the production table as reverting schema updates is difficult.
Update the BigQuery table from the schema by running,
bq update -t prod.analytics bigquery/analytics_schema.json
Initialize the required BigQuery datasets and tables with the following,
bq mk prod
bq mk -t prod.analytics bigquery/analytics_schema.json
In order to deploy your own AppRTC instance you need a TURN/ICE server and a signaling server, in addition to AppRTC itself. The signaling server (Collider) is part of this repository and can be found here) while the TURN server used is rfc5766-turn-server. Credentials and TURN server instances are provided by a CEOD service that generates TURN servers on demand in form of a JSON response.
This means you need to either set-up a web server that returns TURN credentials and IP addresses (basically mimic the CEOD server) in a JSON response, or replace the CEOD details with your own TURN server provider details, and then change https://github.com/webrtc/apprtc/blob/master/src/app_engine/apprtc.py#L256 to turn_url = constants.TURN_URL_TEMPLATE.
You can test using your own TURN server by appending the ?ts=serverUrl parameter, details on AppRTC URL parameters can be found at https://appr.tc/params.html.