AutoExecFlow

An API for cross-platform custom orchestration of execution steps without any third-party dependencies. Based on DAG , it implements the scheduling function of sequential execution of dependent steps and concurrent execution of non-dependent steps.

It provides API remote operation mode, batch execution of Shell , Powershell , Python and other commands, and easily completes common management tasks such as running automated operation and maintenance scripts, polling processes, installing or uninstalling software, updating applications, and installing patches.

Operating system remote execution interface

Feature

• support Windows / Linux / Mac
• Dynamically adjust the number of workers
• Orchestrating execution based on directed acyclic graph ( DAG )
• Supports forced termination of tasks or steps
• Supports suspension and resumption of tasks or steps
• Support timeout for tasks or steps
• Task-level Workspace isolation
• Browse, upload, and download tasks in Workspace
• Self-update, use parameter --self_url
• WebShell
• Support delayed Task
• Send events before/after a task or step is executed
• Task or step plugin implementation

Help

Usage:
  AutoExecFlow_linux_amd64_v1 [command]

Available Commands:
  client      a self-sufficient executor
  help        Help about any command
  server      start server

Flags:
      --help      Print usage
  -v, --version   Print version information and quit

Use "AutoExecFlow_linux_amd64_v1 [command] --help" for more information about a command.

How to use

Windows

Open PowerShell in management mode to add services

New-Service -Name AutoExecFlow -BinaryPathName "C:\AutoExecFlow\bin\AutoExecFlow_windows_amd64_v1.exe server" -DisplayName  "AutoExecFlow " -StartupType Automatic
sc.exe failure AutoExecFlow reset= 0 actions= restart/0/restart/0/restart/0
sc.exe start AutoExecFlow

Linux

echo > /etc/systemd/system/AutoExecFlow.service <<EOF
[Unit]
Description=Operating system remote execution interface
Documentation=https://github.com/busybox-org/AutoExecFlow.git
After=network.target nss-lookup.target

[Service]
NoNewPrivileges=true
ExecStart=/usr/local/AutoExecFlow/bin/AutoExecFlow_linux_amd64_v1 server
Restart=on-failure
RestartSec=10s
LimitNOFILE=infinity

[Install]
WantedBy=multi-user.target
EOF

systemctl daemon-reload
systemctl enable --now AutoExecFlow.service

Local compilation (Linux)

• Depends on the Docker environment

git clone https://github.com/xmapst/AutoExecFlow.git
cd AutoExecFlow
make

Request Example

name: 测试
desc: 这是一段任务描述
async: true
timeout: 2m
env:
  - name: GLOBAL_NAME
    value: "全局变量"
step:
  - name: shell
    desc: 执行shell脚本
    timeout: 2m
    env:
      - name: Test
        value: "test_env"
    type: sh
    content: |-
      ping -c 4 1.1.1.1
  - name: python
    desc: 执行python脚本
    timeout: 2m
    env:
      - name: Test
        value: "test_env"
    depends:
      - shell
    type: py3
    content: |-
      import subprocess
      command = ["ping", "-c", "4", "1.1.1.1"]
      try:
          result = subprocess.run(command, stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True, check=True)
          print("Ping 命令的输出：")
          print(result.stdout)
      except subprocess.CalledProcessError as e:
          print("执行 ping 命令时发生错误：")
          print(e.stderr)
  - name: lua
    desc: 执行lua脚本
    timeout: 2m
    env:
      - name: Test
        value: "test_env"
    depends:
      - shell
    type: lua
    content: |-
      local cmd = require("cmd")
      function EvalCall(params)
        print(params)
        local command = "ping -c 4 1.1.1.1"
        local result, err = cmd.exec(command)
        if err then
          print("Error executing command:", err)
          return
        end
        if not(result.status == 0) then
          print("Ping failed with status:", result.status)
          return
        end
        
        print("Ping 命令的输出：")
        print(result.stdout)
      end
  - name: star
    desc: 执行starlark脚本
    env:
      - name: Test
        value: "test_env"
    depends:
      - lua
    type: star
    content: |-
      def EvalCall(params):
        print(params)
        cmd = "ping -c 4 1.1.1.1"
        exit_code, stdout, stderr = exec_command(cmd)
        if exit_code != 0:
          print("Ping 命令执行失败 (退出码: %d)" % exit_code)
          if stderr:
            print("错误输出: %s" % stderr)
          return
        print("Ping 命令的输出：")
        print(stdout)
  - name: yaegi
    desc: 执行yaegi脚本
    env:
      - name: Test
        value: "test_env"
    depends:
      - python
    type: yaegi
    content: |-
      import (
        "fmt"
        "os/exec"
      )
      func EvalCall(params map[string]interface{}) {
        fmt.Println(params)
        cmd := exec.Command("ping", "-c", "4", "1.1.1.1")
        output, err := cmd.CombinedOutput()
        if err != nil {
          fmt.Println("执行 ping 命令时发生错误：", err)
          return
        }
        fmt.Println("Ping 命令的输出：")
        fmt.Println(string(output))
      }
  - name: 聚合测试
    desc: 等待所有脚本执行完成
    env:
      - name: Test
        value: "test_env"
    depends:
      - yaegi
      - star
    type: sh
    content: |-
      echo "done done"
  - name: 测试lua-http
    desc: 测试lua执行http获取内容
    env:
      - name: Test
        value: "test_env"
    depends:
      - shell
    type: lua
    content: |-
      local http = require("http")
      local client = http.client()
      function EvalCall(params)
        local request = http.request("GET", "https://www.baidu.com")
        local result, err = client:do_request(request)
        if err then
          error(err)
          return
        end
        print(result)
      end
  - name: 多分支执行
    desc: 测试多分支执行
    env:
      - name: Test
        value: "test_env"
    type: star
    content: |-
      load('http.star', 'http')
      def EvalCall(params):
        result = http.get("https://www.baidu.com")
        if result.status_code != 200:
          log.error(result.status_code)
          return
        print(result.body())
  - name: 多分支执行2
    desc: 测试多分支执行
    env:
      - name: Test
        value: "test_env"
    depends:
      - 多分支执行
    type: yaegi
    content: |-
      import (
        "fmt"
        "io"
        "log"
        "net/http"
      )
      func EvalCall(params map[string]interface{}) {
        resp, err := http.Get("https://www.baidu.com")
        if err != nil {
          log.Fatalf("HTTP 请求失败: %v", err)
          return
        }
        defer resp.Body.Close()
        if resp.StatusCode != http.StatusOK {
          log.Printf("HTTP 请求失败，状态码: %d", resp.StatusCode)
          return
        }
        // 读取响应体
        body, err := io.ReadAll(resp.Body)
        if err != nil {
        	log.Fatalf("读取响应体失败: %v", err)
        	return
        }
        
        // 打印响应内容
        fmt.Println("HTTP 响应内容:")
        fmt.Println(string(body))
      }

Create a task

# By default, the execution is in order.
curl -X POST -H "Content-Type:application/json" -d '"name": "test",
"timeout": "10m",
"env": [
  {
    "name": "TEST_SITE",
    "value" : "www.google.com"
  }
],
"step": [
  {
    "type": "bash", # support[python2,python3,bash,sh,cmd,powershell]
    "content": "env", # Script content
    "env": [ # Environment variable injection
      {
        "name": "TEST_SITE",
        "value" : "www.google.com"
      }
    ]
  },
  {
    "type": "bash", # support[python2,python3,bash,sh,cmd,powershell]
    "content": "curl ${TEST_SITE}", # Script content
    "env": [ # Environment variable injection
      {
        "name": "TEST_SITE",
        "value" : "www.baidu.com"
      }
    ]
  }
]' 'http://localhost:2376/api/v1/task' 

# Concurrent Execution
curl -X POST -H "Content-Type:application/json" -d '"name": "test",
"timeout": "10m",
"env": [
  {
    "name": "TEST_SITE",
    "value" : "www.google.com"
  }
],
"async: true,
"step": [
  {
    "type": "bash", # support[python2,python3,bash,sh,cmd,powershell]
    "content": "env", # Script content
    "env": [ # Environment variable injection
      {
        "name": "TEST_SITE",
        "value" : "www.google.com"
      }
    ]
  },
  {
    "type": "bash", # support[python2,python3,bash,sh,cmd,powershell]
    "content": "curl ${TEST_SITE}", # Script content
    "env": [ # Environment variable injection
      {
        "name": "TEST_SITE",
        "value" : "www.baidu.com"
      }
    ]
  }
]' 'http://localhost:2376/api/v1/task'

# Customized orchestration execution
curl -X POST -H "Content-Type:application/json" -d '"name": "test",
"timeout": "10m",
"env": [
  {
    "name": "TEST_SITE",
    "value" : "www.google.com"
  }
],
"async: true,
"step": [
  {
    "name": "step0",
    "type": "bash", # support[python2,python3,bash,sh,cmd,powershell]
    "content": "env", # Script content
    "env": [ # Environment variable injection
      {
        "name": "TEST_SITE",
        "value" : "www.google.com"
      }
    ]
  },
  {
    "name": "step1",
    "type": "bash", # support[python2,python3,bash,sh,cmd,powershell]
    "content": "curl ${TEST_SITE}", # Script content
    "env": [ # Environment variable injection
      {
        "name": "TEST_SITE",
        "value" : "www.baidu.com"
      }
    ],
    "depends": [
      "step1"
    ]
  }
]' 'http://localhost:2376/api/v1/task'

Get the task list

curl -X GET -H "Content-Type:application/json" 'http://localhost:2376/api/v1/task'

Get task details

curl -X GET -H "Content-Type:application/json" http://localhost:2376/api/v1/task/{task name}

Get task step list

curl -X GET -H "Content-Type:application/json" http://localhost:2376/api/v1/task/{task name}/step

Get the task working directory

curl -X GET -H "Content-Type:application/json" http://localhost:2376/api/v1/task/{task name}/workspace

Task Control

# Task to force kill
curl -X PUT -H "Content-Type:application/json" http://localhost:2376/api/v1/task/{task name}?action=kill

# Pause task execution [Only pending tasks can be paused]
curl -X PUT -H "Content-Type:application/json" http://localhost:2376/api/v1/task/{task name}?action=pause

# Pause task execution (pause for 5 minutes) [Only tasks to be run can be paused]
curl -X PUT -H "Content-Type:application/json" http://localhost:2376/api/v1/task/{task name}?action=pause&duration=5m

# Continue the task
curl -X PUT -H "Content-Type:application/json" http://localhost:2376/api/v1/task/{task name}?action=resume

Get step console output

curl -X GET -H "Content-Type:application/json" http://localhost:2376/api/v1/task/{task name}/step/{step name}

Step Control

# Steps to force kill
curl -X PUT -H "Content-Type:application/json" http://localhost:2376/api/v1/task/{task name}/step/{step name}?action=kill

# Pause step execution [Only pending steps can be paused]
curl -X PUT -H "Content-Type:application/json" http://localhost:2376/api/v1/task/{task name}/step/{step name}?action=pause

# Pause step execution (pause for 5 minutes) [Only steps to be run can be paused]
curl -X PUT -H "Content-Type:application/json" http://localhost:2376/api/v1/task/{task name}/step/{step name}?action=pause&duration=5m

# Continue to step
curl -X PUT -H "Content-Type:application/json" http://localhost:2376/api/v1/task/{task name}/step/{step name}?action=resume

[Notes]

• code:
  • 0: success
  • 1001: running
  • 1002: failed
  • 1003: not found
  • 1004: pending
  • 1005: paused

Script language support

• bash/sh/ps1/bat/python2/python3
• lua
• starlark
• yaegi

Swagger API documentation

Swagger API documentation

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