docs: Update Docker instructions

README.md

@@ -58,21 +58,32 @@ the Django app must be running**.
 
 The easiest way to get started is by deploying both Docker containers on your
 local machine. For help installing Docker, [reference the documentation for your
-specific system](https://docs.docker.com/get-docker/). Once Docker is installed,
-from the root directory of the repository, run
+specific system](https://docs.docker.com/get-docker/).
 
-`docker-compose up`
+The Docker container for PyWorkflow is built from 2 images: the `front-end` and
+the `back-end`. The `docker-compose.yml` defines how to combine and run the two.
 
-This builds both the front- and back-end Docker images and runs them with
-networking between the images. To use the GUI, open http://localhost:3000 in your
-web-browser. To use the CLI...
+In order to build each image individually, from the root of the application:
+- `docker build front-end --tag FE_IMAGE[:TAG]`
+- `docker build back-end --tag BE_IMAGE[:TAG]`
+  ex. - `docker build back-end --tag backendtest:2.0`
 
-**Installing new Python packages**
-If you write custom nodes that require additional packages, you can add these
-to the Docker image by running:
-```
-docker exec pipenv install [package-name]
-```
+Each individual image can be run by changing to the `front-end` or `back-end` directory and running:
+- `docker run -p 3000:3000 --name FE_CONTAINER_NAME FE_IMAGE[:TAG]`
+- `docker run -p 8000:8000 --name BE_CONTAINER_NAME BE_IMAGE[:TAG]`
+  ex. - `docker run -p 8000:8000 --name pyworkflow-be backendtest:2.0`
+
+Note: there [is a known issue with `react-scripts` v3.4.1](https://github.com/facebook/create-react-app/issues/8688)
+that may cause the front-end container to exit with code 0. If this happens,
+you can add `-e CI=true` to the `docker-run` command above for the front-end.
+
+To compose and run the entire application container, from the root of the application:
+- `docker-compose up`
+
+You can then kill the container gracefully with:
+- `docker-compose down`
+
+NOTE: For development, change ./front-end/package.json from "proxy": "http://back-end:8000" to "http://localhost:8000" to work.
 
 
 ## Serve locally

docs/custom_nodes.md

@@ -174,11 +174,6 @@ in PyWorkflow's `Pipfile`, your custom node won't know how to use the package.
 All you have to do is install the package in PyWorkflow and you'll be good to
 go!
 
-**Docker**:
-```
-docker exec pipenv install [package-name]
-```
-
 **Running locally**:
 ```
 # Go to wherever the back-end code is located