Launching Unity Environment From Python

It is possible to launch and terminate the environment from Python.

This provide additional level of fexibilty where you will not have to lauch environment manually everytime.

from airctrl import environment
from airctrl import sample_generator
from airctrl.utils import unity
from airctrl import sample_generator
port=8999
sample = sample_generator.samples()

Use Launch() class from unity subpackage to create and object

env =  environment.Trigger()
L = unity.Launch()

Now call method .get_connected(port=<Default 8053>) to get connected


Use function launch_executable() to launch an environment. launch_executable() takes path where the executable is located. Use suitable path according to OS.

process = L.launch_executable("/home/supatel/Games/AirControl_2021/Build/1.3.0/Linux/v1.3.0-AirControl.x86_64", server_port=port)
env.get_connected(port=port)

Loading environment from /home/supatel/Games/AirControl_2021/Build/1.3.0/Linux/v1.3.0-AirControl.x86_64 at port 8999 client ip 127.0.1.1 client port 8999

['/home/supatel/Games/AirControl_2021/Build/1.3.0/Linux/v1.3.0-AirControl.x86_64', '--serverPort', '8999', '--clientIP', '127.0.1.1', '--clientPort', '8999']
Sleeping for 5 seconds to allow environment load

[UnityMemory] Configuration Parameters - Can be set up in boot.config
    "memorysetup-bucket-allocator-granularity=16"
    "memorysetup-bucket-allocator-bucket-count=8"
    "memorysetup-bucket-allocator-block-size=4194304"
    "memorysetup-bucket-allocator-block-count=1"
    "memorysetup-main-allocator-block-size=16777216"
    "memorysetup-thread-allocator-block-size=16777216"
    "memorysetup-gfx-main-allocator-block-size=16777216"
    "memorysetup-gfx-thread-allocator-block-size=16777216"
    "memorysetup-cache-allocator-block-size=4194304"
    "memorysetup-typetree-allocator-block-size=2097152"
    "memorysetup-profiler-bucket-allocator-granularity=16"
    "memorysetup-profiler-bucket-allocator-bucket-count=8"
    "memorysetup-profiler-bucket-allocator-block-size=4194304"
    "memorysetup-profiler-bucket-allocator-block-count=1"
    "memorysetup-profiler-allocator-block-size=16777216"
    "memorysetup-profiler-editor-allocator-block-size=1048576"
    "memorysetup-temp-allocator-size-main=4194304"
    "memorysetup-job-temp-allocator-block-size=2097152"
    "memorysetup-job-temp-allocator-block-size-background=1048576"
    "memorysetup-job-temp-allocator-reduction-small-platforms=262144"
    "memorysetup-temp-allocator-size-background-worker=32768"
    "memorysetup-temp-allocator-size-job-worker=262144"
    "memorysetup-temp-allocator-size-preload-manager=262144"
    "memorysetup-temp-allocator-size-nav-mesh-worker=65536"
    "memorysetup-temp-allocator-size-audio-worker=65536"
    "memorysetup-temp-allocator-size-cloud-worker=32768"
    "memorysetup-temp-allocator-size-gfx=262144"
Connecting with port 8999


Once done you can call terminate() function call to kill the environment.

process.terminate()