There are a few things that will make managing your pico engine and writing KRL code easier. 

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Update to the Latest Version

You also use the npm install command to get the latest version, or the variant shown above if you want a specific version rather than the latest, using the command:

npm install -g pico-engine

Check Your Version

You can see which version you are using near the bottom-right corner of the developer UI page (localhost:3000):

Image Modified

or by running the command:

npm ls -g pico-engine

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PORT=3001 PICO_ENGINE_HOME=~/.pico-engine-1 pico-engine

Using Docker

The pico engine repository contains a Dockerfile that can be used to build a Docker image for use locally or in a cloud service like AWS Fargate. 

To build a container use docker build:

docker build -t <username>/<container-name> github.com/picolab/pico-engine

For example:

docker build -t pjw/pico-engine github.com/picolab/pico-engine

builds a container named pjw/pico-engine for your use. 

To run the image use docker run:

docker run -p <port>:3000 -v <mount-point>:/var/pico-image -d <username>/container-name>

For example:

docker run -p 3001:3000 -v ~/images/pico-image:/var/pico-image -d pjw/pico-engine

runs the docker with a port of 3001 and the image files located at ~/tmp/pico-image on the local machine.

If you need to set the URL for your engine, you can add the PICO_ENGINE_BASE_URL env variable. For example:

docker run -p 80:3000 -v ~/images/pico-image:/var/pico-image -d pjw/pico-engine -e PICO_ENGINE_BASE_URL=https://picos.picolabs.io

would use https://picos.picolabs.io and the engine URL. 

You can run the same container multiple times with different ports and mount points to have multiple engines running at the same time.

docker run -p 3000:3000 -v ~/images/dnd_game_image:/var/pico-image -d pjw/pico-engine
docker run -p 3001:3000 -v ~/images/iot_image:/var/pico-image -d pjw/pico-engine

would run two different pico engines, each with their own collection of picos, one on port 3000 and one on port 3001. 

Hosting Code

Because the rules engine reads your KRL program from the Web, it has to be available online. You can host it anywhere. There are a few options:

1. GitHub works well, with one caveat. See these instructions for more information about how to use GitHub to host KRL. The caveat is that GitHub caches the resources on raw URLs for about 5 minutes. If you're making frequent changes, it can be frustrating to wait out the cache. Alternatively, GitLab should give you fewer caching problems. (raw URLs to rulesets in private repositories need an account access token)
2. AWS S3 works well. Be sure to make the URL for the ruleset is readable by the engine. 

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To validate using the second method, Install the KRL Compiler using this command:

npm install -g krl-compiler
krl-compiler -v                # v1.0.1

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