Merge pull request #122 from Peefy/split-code-block-cmd-output

feat: split code block cmd input and output for the convenience of copying commands.

Author: Peefy

blog/2022-12-06-kcl-0.4.4-release-blog/index.md

@@ -128,8 +128,13 @@ x1 = Person {
 
 Execute the following command and get the output:
 
-```bash
-$ python3 -m kclvm hello.k
+```shell
+python3 -m kclvm hello.k
+```
+
+The expect output is
+
+```yaml
 name: kcl
 age: 1
 x0:
@@ -155,8 +160,13 @@ print(planner.plan(kclvm_exec.Run(["hello.k"]).filter_by_path_selector()))
 
 Execute the following command and get the output:
 
-```bash
-$ python3 main.py
+```shell
+python3 main.py
+```
+
+The expect output is
+
+```yaml
 name: kcl
 age: 1
 x0:

blog/2023-04-14-kcl-0.4.6-release/index.md

@@ -49,7 +49,12 @@ metadata = {
 Execute the following KCL command, then you can see the syntax errors including the unterminated string and the brace mismatch errors.
 
 ```shell
-$ kcl main.k
+kcl main.k
+```
+
+The output is
+
+```shell
 error[E1001]: InvalidSyntax
  --> main.k:2:21
   |
@@ -121,7 +126,12 @@ person = Person {
 We run the following command:
 
 ```shell
-$ kcl main.k -S person
+kcl main.k -S person
+```
+
+The output is
+
+```yaml
 name: Alice
 age: 18
 ```
@@ -215,7 +225,12 @@ apps.Deployment {
 Execute the following command to run the KCL code to obtain an nginx deployment YAML output.
 
 ```shell
-$ kpm run
+kpm run
+```
+
+The output is
+
+```yaml
 apiVersion: apps/v1
 kind: Deployment
 metadata:

blog/2023-04-27-new-version-feature-interpretation-kclvm-go-feature-overview/index.md

@@ -58,8 +58,13 @@ spec = {
 
 And then execute the KCL directly from the command line with:
 
-```bash
-$ kcl-go run ./hello.k
+```shell
+kcl-go run ./hello.k
+```
+
+The output is
+
+```yaml
 apiVersion: apps/v1
 kind: Deployment
 metadata:
@@ -112,8 +117,13 @@ go get kusionstack.io/kclvm-go@main
 
 The following command runs the Go program:
 
-```bash
-$ go run main.go      
+```shell
+go run main.go
+```
+
+The output is
+
+```yaml
 apiVersion: apps/v1
 kind: Deployment
 metadata:

blog/2023-05-20-vs-kustomize/index.md

@@ -111,8 +111,13 @@ The base directory stores the basic deployment configuration, and the prod envir
 
 We can display the real deployment configuration of the prod environment through the following command.
 
-```bash
-$ kubectl kustomize ./prod
+```shell
+kubectl kustomize ./prod
+```
+
+The output is
+
+```yaml
 apiVersion: apps/v1
 kind: Deployment
 metadata:
@@ -149,9 +154,13 @@ spec:
 
 We can also directly apply the configuration to the cluster through the following command.
 
-```bash
-$ kubectl apply -k ./prod
+```shell
+kubectl apply -k ./prod
+```
+
+The output is
 
+```shell
 deployment.apps/ldap created
 ```
 
@@ -244,17 +253,25 @@ diff prod-deployment.yaml deployment.yaml
 
 Of course, we can also use KCL tools together with kubectl and other tools to apply the configuration of the production environment to the cluster
 
-```bash
-$ kcl main.k -D env=prod | kubectl apply -f -
+```shell
+kcl main.k -D env=prod | kubectl apply -f -
+```
+
+The output is
 
+```shell
 deployment.apps/ldap created
 ```
 
 Finally, check the deployment status through kubectl
 
-```bash
-$ kubectl get deploy
+```shell
+kubectl get deploy
+```
+
+The output is
 
+```shell
 NAME   READY   UP-TO-DATE   AVAILABLE   AGE
 ldap   0/6     6            0           15s
 ```

blog/2023-05-30-vs-helm/index.md

@@ -364,8 +364,13 @@ We can get the `Deployment` and `Service` resources throw the following command:
 
 + `Deployment`
 
-```bash
-$ kcl workload-kcl/deployment.k -Y workload-kcl/kcl.yaml
+```shell
+kcl workload-kcl/deployment.k -Y workload-kcl/kcl.yaml
+```
+
+The output is
+
+```yaml
 apiVersion: apps/v1
 kind: Deployment
 metadata:
@@ -401,8 +406,13 @@ spec:
 
 + `Service`
 
-```bash
-$ kcl workload-kcl/service.k -Y workload-kcl/kcl.yaml
+```shell
+kcl workload-kcl/service.k -Y workload-kcl/kcl.yaml
+```
+
+The output is
+
+```yaml
 apiVersion: v1
 kind: Service
 metadata:
@@ -425,8 +435,13 @@ spec:
 
 In addition, we can overwrite the value in the `kcl.yaml` file with the `-D` parameter, such as executing the following command.
 
-```bash
-$ kcl workload-kcl/service.k -Y workload-kcl/kcl.yaml -D service=None
+```shell
+kcl workload-kcl/service.k -Y workload-kcl/kcl.yaml -D service=None
+```
+
+The output is
+
+```yaml
 apiVersion: v1
 kind: Service
 metadata:

blog/2023-06-05-k8s-sidecar-1/index.md

@@ -36,7 +36,7 @@ spec:
 
 The `Pod` is then created via the kubectl, and then the `Pod` execution status is viewed via `kubectl get po`.
 
-```bash
+```shell
 $ kubectl create -f pod.yaml
 $ kubectl get po
 NAME READY STATUS RESTARTS AGE
@@ -45,7 +45,7 @@ web-app 1/1 Running 0 45m
 
 You can see that a `Pod` named `web-app` is up and running properly, containing the `Nginx` service. To configure port forwarding for external access, the port 3999 of the host corresponds to port 80 of the master container:
 
-```bash
+```shell
 $ kubectl port-forward web-app 3999:80
 Forwarding from 127.0.0.1:3999 ->80
 Forwarding from [::1]:3999 -> 80
@@ -59,7 +59,7 @@ Port forwarding is a blocking procedure, keep the command line open. Then open t
 
 In this section, we try to add the ability to customize web pages to the `Nginx` service via Sidecar without modifying the original `Nginx` container image. Before we start, remove the previously started `Pod`:
 
-```bash
+```shell
 $ kubectl delete po web-app
 pod "web-app" deleted
 ```
@@ -113,7 +113,7 @@ The `Busybox` has only one function: it overwrites the `/var/log/index.html` fil
 
 Then restart the Pod and remap the local host port to the container port.
 
-```bash
+```shell
 $ kubectl create -f pod.yaml 
 pod/web-app created
 $ kubectl port-forward web-app 3999:80

blog/2023-07-14-kcl-0.5.0-release/index.md

@@ -229,7 +229,7 @@ kcl-openapi generate model -f processed-${spec_path}
 
 The expected execution output of the script is the corresponding version of the KCL Kubernetes model, and the generated path is `<workspace path>/models/k8s`.
 
-```bash
+```shell
 $ tree models/k8s
 models/k8s
 ├── api
@@ -290,7 +290,7 @@ apps.Deployment {
 
 By combining the `kpm run` and `kubectl` command lines, we can directly distribute resource configurations to the cluster.
 
-```bash
+```shell
 $ kpm run | kubectl apply -f -
 
 deployment.apps/nginx-deployment configured
@@ -420,7 +420,7 @@ spec:
 
 In the above configuration, we used a Kubernetes web service application abstract model that has been predetermined on OCI `oci://ghcr.io/kcl-lang/web-service` and configured the required configuration fields for the model through the `params` field. The original Kubernetes YAML output can be obtained and applied by executing the following command:
 
-```bash
+```shell
 $ kubectl kcl apply -f krm-kcl-abstration.yaml
 
 deployment.apps/app created

docs/reference/package-management/command-reference/6.login.md

@@ -31,22 +31,37 @@ Show help for `kpm login` command.
 ### login to a registry with account and password
 
 ```shell
-$ kpm login -u <account_name> -p <password> <oci_registry>
+kpm login -u <account_name> -p <password> <oci_registry>
+```
+
+The output is
+
+```shell
 Login succeeded
 ```
 
 ### login to a registry with account, and enter the password interactively
 
 ```shell
-$ kpm login -u <account_name> <oci_registry>
+kpm login -u <account_name> <oci_registry>
+```
+
+The output is
+
+```shell
 Password:
 Login succeeded
 ```
 
 ### login to a registry, and enter the account and password interactively
 
 ```shell
-$ kpm login <oci_registry>
+kpm login <oci_registry>
+```
+
+The output is
+
+```shell
 Username: <account_name>
 Password:
 Login succeeded

docs/reference/xlang-api/overview.md

@@ -135,7 +135,7 @@ x1 = Person {
 
 Execute the following command and get the output:
 
-```bash
+```shell
 $ python3 -m kclvm hello.k
 name: kcl
 age: 1
@@ -162,7 +162,7 @@ print(planner.plan(kclvm_exec.Run(["hello.k"]).filter_by_path_selector()))
 
 Execute the following command and get the output:
 
-```bash
+```shell
 $ python3 main.py
 name: kcl
 age: 1

docs/tools/cli/kcl/vet.md

@@ -49,21 +49,21 @@ schema Data:
 
 Execute the following command:
 
-```bash
-$ kcl-vet data.json schema.k
+```shell
+kcl-vet data.json schema.k
 ```
 
 ## Specify the schema for validation
 
 When multiple schema definitions exist in the KCL file, by default, the KCL Validation tool will use the first schema to check. If you need to specify a schema for verification, you can use the `-d|--schema` parameter
 
-```bash
-$ kcl-vet data.json schema.k -d User
+```shell
+kcl-vet data.json schema.k -d User
 ```
 
 ## Args
 
-```bash
+```shell
 $ kcl-vet -h
 USAGE:
     kcl-vet [OPTIONS] [ARGS]

docs/user_docs/getting-started/kcl-quick-start.md

@@ -21,7 +21,13 @@ Set the `hello` attribute to the `"KCL"` string. Then save the code to the `hell
 How to execute this program depends on the specific development environment, we first assume that the local macOS or Linux system has installed the `kcl` command (or enter the **Docker** environment test by `docker run --rm -it kcllang/kcl`) and then run the following command:
 
 ```shell
-$ kcl hello.k
+kcl hello.k
+```
+
+The output is
+
+
+```yaml
 hello: KCL
 ```
 
@@ -123,7 +129,12 @@ database = DatabaseConfig {
 When executed, an error similar to the following will be generated (the displayed file path depends on the local environment):
 
 ```shell
-$ kcl server.k 
+kcl server.k 
+```
+
+The output is
+
+```shell
 error[E2G22]: TypeError
  --> /path/to/server.k:8:5
   |