Build from Source in a Docker Container
Referring to this example, we create a canonical dev environment for Go and Python developers using Docker images.
Editing on Host
When we use this Docker image for daily development work, the source code relies
on the host computer instead of the container. The source code includes this repo
and all its dependencies, for example, the Go package
Code-on-the-host allows us to run our favorite editors (Emacs, VIM, Eclipse, and more)
on the host. Please free to rely on editors add-ons to analyze the source code
Building in Container
We build a Docker image that contains development tools below.
- Python Interpreter
- Go compiler
- Protobuf compiler
- Protobuf to Go compiler extension
- Protobuf to Python compiler extension
Because this repo contains Go code, please make sure that you have the directory structure required by Go. On my computer, I have GOPATH set to $Home/go, you can have your
$GOPATH pointing to any directory as you like.
$GOPATH$ is set, we could git clone the source code of our project by running:
go get github.com/sql-machine-learning/sqlflow
Change the directory to our project root, and we can use
go get to retrieve
and update Go dependencies. Note
-t instructs get to also download the packages required to build
the tests for the specified packages. As all Git users would do, we run
git pull from time to time to sync up with
others’ work. If somebody added new dependencies, we might need to run
go -u ./...
git pull to update dependencies.
cd $GOPATH/src/github.com/sql-machine-learning/sqlflow go get -u -t ./...
To build the project, we need protobuf compiler, Go compiler, Python interpreter and gRPC extension to protobuf compiler. To prepare our dev environment with these tools, the easist way is to pull latest image from DockerHub by running command below and give it an alias sqlflow:latest. Alternatively, we provide a Dockerfile where can build image from. Note it will take a while to build from Dockerfile, especially when the network is unpredictable.
docker pull sqlflow/sqlflow:latest docker tag sqlflow/sqlflow:latest sqlflow:latest
docker build -t sqlflow:latest .
Build and Test
We build and test the project inside the docker container. To run the container, we need to map the
$GOPATH directory on the host into the
/go directory in the container, because the Dockerfile configures
$GOPATH in the container:
docker run --rm -it -v $GOPATH:/go \ -w /go/src/github.com/sql-machine-learning/sqlflow \ sqlflow:latest bash
Inside the Docker container, start a MySQL server in the background
service mysql start
run all the tests as
go generate ./... go test -v ./...
go generate invokes the
protoc command to translate
go test -v builds and run unit tests.
Demo: Command line Prompt
The demo requires a MySQL server instance with populated data. If you don’t, please follow example/datasets/ to start one on the host. After setting up MySQL, run the following inside the Docker container
go run cmd/demo/demo.go --datasource="mysql://root:root@tcp(host.docker.internal:3306)/?maxAllowedPacket=0"
You should be able to see the following prompt