Tianqi-Dotes commented on a change in pull request #713:
URL: 
https://github.com/apache/dolphinscheduler-website/pull/713#discussion_r840433761



##########
File path: docs/en-us/dev/user_doc/guide/task/python.md
##########
@@ -1,15 +1,55 @@
 # Python Node
 
-- Using python nodes, you can directly execute python scripts. For python 
nodes, workers use `python **` to submit tasks.
+## Overview
 
-> Drag from the toolbar 
![PNG](https://analysys.github.io/easyscheduler_docs_cn/images/toolbar_PYTHON.png)
 task node to the canvas, as shown in the following figure:
+`Python Task` is used to create a python-type task and execute python scripts. 
When the worker execute `Python Task`,
+a temporary python script is generated, and the Linux user with the same name 
as the tenant executes the script.

Review comment:
       better
   a temporary python script is generated,
   change to 
   will generate a temporary python script,

##########
File path: docs/en-us/dev/user_doc/guide/task/python.md
##########
@@ -1,15 +1,55 @@
 # Python Node
 
-- Using python nodes, you can directly execute python scripts. For python 
nodes, workers use `python **` to submit tasks.
+## Overview
 
-> Drag from the toolbar 
![PNG](https://analysys.github.io/easyscheduler_docs_cn/images/toolbar_PYTHON.png)
 task node to the canvas, as shown in the following figure:
+`Python Task` is used to create a python-type task and execute python scripts. 
When the worker execute `Python Task`,

Review comment:
       better
   `Python Task` is used to create
   change to
   Use `Python Task` to create

##########
File path: docs/en-us/dev/user_doc/guide/task/python.md
##########
@@ -1,15 +1,55 @@
 # Python Node
 
-- Using python nodes, you can directly execute python scripts. For python 
nodes, workers use `python **` to submit tasks.
+## Overview
 
-> Drag from the toolbar 
![PNG](https://analysys.github.io/easyscheduler_docs_cn/images/toolbar_PYTHON.png)
 task node to the canvas, as shown in the following figure:
+`Python Task` is used to create a python-type task and execute python scripts. 
When the worker execute `Python Task`,

Review comment:
       When the worker execute
   change to 
   When the worker executes

##########
File path: docs/en-us/dev/user_doc/guide/task/python.md
##########
@@ -1,15 +1,55 @@
 # Python Node
 
-- Using python nodes, you can directly execute python scripts. For python 
nodes, workers use `python **` to submit tasks.
+## Overview
 
-> Drag from the toolbar 
![PNG](https://analysys.github.io/easyscheduler_docs_cn/images/toolbar_PYTHON.png)
 task node to the canvas, as shown in the following figure:
+`Python Task` is used to create a python-type task and execute python scripts. 
When the worker execute `Python Task`,
+a temporary python script is generated, and the Linux user with the same name 
as the tenant executes the script.

Review comment:
       ', and the Linux user with the same name as the tenant executes the 
script.' 
   should be 
   ', and executes the script by the Linux user with the same name as the 
tenant .'

##########
File path: docs/en-us/dev/user_doc/guide/task/python.md
##########
@@ -1,15 +1,55 @@
 # Python Node
 
-- Using python nodes, you can directly execute python scripts. For python 
nodes, workers use `python **` to submit tasks.
+## Overview
 
-> Drag from the toolbar 
![PNG](https://analysys.github.io/easyscheduler_docs_cn/images/toolbar_PYTHON.png)
 task node to the canvas, as shown in the following figure:
+`Python Task` is used to create a python-type task and execute python scripts. 
When the worker execute `Python Task`,
+a temporary python script is generated, and the Linux user with the same name 
as the tenant executes the script.
 
-<p align="center">
-   <img src="/img/python-en.png" width="80%" />
- </p>
+## Create Task
 
-- Script: Python program developed by the user.
-- Environment Name: Specific Python interpreter path for running the script. 
If you need to use Python **virtualenv**, you should create multiply 
environments for each **virtualenv**.  
-- Resources: Refers to the list of resource files that need to be called in 
the script.
-- User-defined parameter: It is a user-defined local parameter of Python, and 
will replace the content with `${variable}` in the script.
-- Note: If you import the python file under the resource directory tree, you 
need to add the `__init__.py` file.
+- Click Project Management-Project Name-Workflow Definition, and click the 
"Create Workflow" button to enter the DAG editing page.
+- Drag <img src="/img/tasks/icons/python.png" width="15"/> from the toolbar to 
the drawing board.
+
+## Task Parameter
+
+- Node name: The node name in a workflow definition is unique.
+- Run flag: Identifies whether this node can be scheduled normally, if it does 
not need to be executed, you can turn on the prohibition switch.
+- Descriptive information: describe the function of the node.
+- Task priority: When the number of worker threads is insufficient, they are 
executed in order from high to low, and when the priority is the same, they are 
executed according to the first-in first-out principle.

Review comment:
       When the number of worker threads is insufficient, execute in the order 
of priority from high to low, and tasks with the same priority will execute in 
a first-in first-out order.
   should be better
   

##########
File path: docs/en-us/dev/user_doc/guide/task/python.md
##########
@@ -1,15 +1,55 @@
 # Python Node
 
-- Using python nodes, you can directly execute python scripts. For python 
nodes, workers use `python **` to submit tasks.
+## Overview
 
-> Drag from the toolbar 
![PNG](https://analysys.github.io/easyscheduler_docs_cn/images/toolbar_PYTHON.png)
 task node to the canvas, as shown in the following figure:
+`Python Task` is used to create a python-type task and execute python scripts. 
When the worker execute `Python Task`,
+a temporary python script is generated, and the Linux user with the same name 
as the tenant executes the script.
 
-<p align="center">
-   <img src="/img/python-en.png" width="80%" />
- </p>
+## Create Task
 
-- Script: Python program developed by the user.
-- Environment Name: Specific Python interpreter path for running the script. 
If you need to use Python **virtualenv**, you should create multiply 
environments for each **virtualenv**.  
-- Resources: Refers to the list of resource files that need to be called in 
the script.
-- User-defined parameter: It is a user-defined local parameter of Python, and 
will replace the content with `${variable}` in the script.
-- Note: If you import the python file under the resource directory tree, you 
need to add the `__init__.py` file.
+- Click Project Management-Project Name-Workflow Definition, and click the 
"Create Workflow" button to enter the DAG editing page.
+- Drag <img src="/img/tasks/icons/python.png" width="15"/> from the toolbar to 
the drawing board.
+
+## Task Parameter
+
+- Node name: The node name in a workflow definition is unique.
+- Run flag: Identifies whether this node can be scheduled normally, if it does 
not need to be executed, you can turn on the prohibition switch.
+- Descriptive information: describe the function of the node.
+- Task priority: When the number of worker threads is insufficient, they are 
executed in order from high to low, and when the priority is the same, they are 
executed according to the first-in first-out principle.
+- Worker grouping: Tasks are assigned to the machines of the worker group to 
execute. If Default is selected, a worker machine will be randomly selected for 
execution.

Review comment:
       Assign tasks to the machines of the worker group to execute. If 
`Default` is selected, randomly select a worker machine for execution.
   should be better

##########
File path: docs/en-us/dev/user_doc/guide/task/python.md
##########
@@ -1,15 +1,55 @@
 # Python Node
 
-- Using python nodes, you can directly execute python scripts. For python 
nodes, workers use `python **` to submit tasks.
+## Overview
 
-> Drag from the toolbar 
![PNG](https://analysys.github.io/easyscheduler_docs_cn/images/toolbar_PYTHON.png)
 task node to the canvas, as shown in the following figure:
+`Python Task` is used to create a python-type task and execute python scripts. 
When the worker execute `Python Task`,
+a temporary python script is generated, and the Linux user with the same name 
as the tenant executes the script.
 
-<p align="center">
-   <img src="/img/python-en.png" width="80%" />
- </p>
+## Create Task
 
-- Script: Python program developed by the user.
-- Environment Name: Specific Python interpreter path for running the script. 
If you need to use Python **virtualenv**, you should create multiply 
environments for each **virtualenv**.  
-- Resources: Refers to the list of resource files that need to be called in 
the script.
-- User-defined parameter: It is a user-defined local parameter of Python, and 
will replace the content with `${variable}` in the script.
-- Note: If you import the python file under the resource directory tree, you 
need to add the `__init__.py` file.
+- Click Project Management-Project Name-Workflow Definition, and click the 
"Create Workflow" button to enter the DAG editing page.
+- Drag <img src="/img/tasks/icons/python.png" width="15"/> from the toolbar to 
the drawing board.
+
+## Task Parameter
+
+- Node name: The node name in a workflow definition is unique.
+- Run flag: Identifies whether this node can be scheduled normally, if it does 
not need to be executed, you can turn on the prohibition switch.
+- Descriptive information: describe the function of the node.
+- Task priority: When the number of worker threads is insufficient, they are 
executed in order from high to low, and when the priority is the same, they are 
executed according to the first-in first-out principle.
+- Worker grouping: Tasks are assigned to the machines of the worker group to 
execute. If Default is selected, a worker machine will be randomly selected for 
execution.
+- Environment Name: Configure the environment name in which to run the script.
+- Number of failed retry attempts: The number of times the task failed to be 
resubmitted. It supports drop-down and hand-filling.
+- Failed retry interval: The time interval for resubmitting the task after a 
failed task. It supports drop-down and hand-filling.
+- Timeout alarm: Check the timeout alarm and timeout failure. When the task 
exceeds the "timeout period", an alarm email will be sent and the task 
execution will fail.
+- Script: PYTHON program developed by users.
+- Resource: Refers to the list of resource files that need to be called in the 
script, and the files uploaded or created by the resource center-file 
management.
+- Custom parameters: It is a user-defined parameter that is part of PYTHON, 
which will replace the content with \${variable} in the script.

Review comment:
       It is a user-defined parameter that is part of PYTHON
   to
   It is the user-defined parameters of Python,

##########
File path: docs/en-us/dev/user_doc/guide/task/python.md
##########
@@ -1,15 +1,55 @@
 # Python Node
 
-- Using python nodes, you can directly execute python scripts. For python 
nodes, workers use `python **` to submit tasks.
+## Overview
 
-> Drag from the toolbar 
![PNG](https://analysys.github.io/easyscheduler_docs_cn/images/toolbar_PYTHON.png)
 task node to the canvas, as shown in the following figure:
+`Python Task` is used to create a python-type task and execute python scripts. 
When the worker execute `Python Task`,
+a temporary python script is generated, and the Linux user with the same name 
as the tenant executes the script.
 
-<p align="center">
-   <img src="/img/python-en.png" width="80%" />
- </p>
+## Create Task
 
-- Script: Python program developed by the user.
-- Environment Name: Specific Python interpreter path for running the script. 
If you need to use Python **virtualenv**, you should create multiply 
environments for each **virtualenv**.  
-- Resources: Refers to the list of resource files that need to be called in 
the script.
-- User-defined parameter: It is a user-defined local parameter of Python, and 
will replace the content with `${variable}` in the script.
-- Note: If you import the python file under the resource directory tree, you 
need to add the `__init__.py` file.
+- Click Project Management-Project Name-Workflow Definition, and click the 
"Create Workflow" button to enter the DAG editing page.
+- Drag <img src="/img/tasks/icons/python.png" width="15"/> from the toolbar to 
the drawing board.
+
+## Task Parameter
+
+- Node name: The node name in a workflow definition is unique.
+- Run flag: Identifies whether this node can be scheduled normally, if it does 
not need to be executed, you can turn on the prohibition switch.
+- Descriptive information: describe the function of the node.
+- Task priority: When the number of worker threads is insufficient, they are 
executed in order from high to low, and when the priority is the same, they are 
executed according to the first-in first-out principle.
+- Worker grouping: Tasks are assigned to the machines of the worker group to 
execute. If Default is selected, a worker machine will be randomly selected for 
execution.
+- Environment Name: Configure the environment name in which to run the script.
+- Number of failed retry attempts: The number of times the task failed to be 
resubmitted. It supports drop-down and hand-filling.
+- Failed retry interval: The time interval for resubmitting the task after a 
failed task. It supports drop-down and hand-filling.
+- Timeout alarm: Check the timeout alarm and timeout failure. When the task 
exceeds the "timeout period", an alarm email will be sent and the task 
execution will fail.

Review comment:
       will be sent
   to
   will send

##########
File path: docs/en-us/dev/user_doc/guide/task/python.md
##########
@@ -1,15 +1,55 @@
 # Python Node
 
-- Using python nodes, you can directly execute python scripts. For python 
nodes, workers use `python **` to submit tasks.
+## Overview
 
-> Drag from the toolbar 
![PNG](https://analysys.github.io/easyscheduler_docs_cn/images/toolbar_PYTHON.png)
 task node to the canvas, as shown in the following figure:
+`Python Task` is used to create a python-type task and execute python scripts. 
When the worker execute `Python Task`,
+a temporary python script is generated, and the Linux user with the same name 
as the tenant executes the script.
 
-<p align="center">
-   <img src="/img/python-en.png" width="80%" />
- </p>
+## Create Task
 
-- Script: Python program developed by the user.
-- Environment Name: Specific Python interpreter path for running the script. 
If you need to use Python **virtualenv**, you should create multiply 
environments for each **virtualenv**.  
-- Resources: Refers to the list of resource files that need to be called in 
the script.
-- User-defined parameter: It is a user-defined local parameter of Python, and 
will replace the content with `${variable}` in the script.
-- Note: If you import the python file under the resource directory tree, you 
need to add the `__init__.py` file.
+- Click Project Management-Project Name-Workflow Definition, and click the 
"Create Workflow" button to enter the DAG editing page.
+- Drag <img src="/img/tasks/icons/python.png" width="15"/> from the toolbar to 
the drawing board.
+
+## Task Parameter
+
+- Node name: The node name in a workflow definition is unique.
+- Run flag: Identifies whether this node can be scheduled normally, if it does 
not need to be executed, you can turn on the prohibition switch.
+- Descriptive information: describe the function of the node.
+- Task priority: When the number of worker threads is insufficient, they are 
executed in order from high to low, and when the priority is the same, they are 
executed according to the first-in first-out principle.
+- Worker grouping: Tasks are assigned to the machines of the worker group to 
execute. If Default is selected, a worker machine will be randomly selected for 
execution.
+- Environment Name: Configure the environment name in which to run the script.
+- Number of failed retry attempts: The number of times the task failed to be 
resubmitted. It supports drop-down and hand-filling.
+- Failed retry interval: The time interval for resubmitting the task after a 
failed task. It supports drop-down and hand-filling.
+- Timeout alarm: Check the timeout alarm and timeout failure. When the task 
exceeds the "timeout period", an alarm email will be sent and the task 
execution will fail.
+- Script: PYTHON program developed by users.
+- Resource: Refers to the list of resource files that need to be called in the 
script, and the files uploaded or created by the resource center-file 
management.
+- Custom parameters: It is a user-defined parameter that is part of PYTHON, 
which will replace the content with \${variable} in the script.
+
+## Task Example
+
+### Simply Print
+
+This example is a sample print task which only print one line in the log file, 
including the content
+"This is a demo of python task". If your task only run one or two python 
command, you could add task based on this example.

Review comment:
       This is different from the original meaning.
   should be 
   This example simulates a common task that runs by a simple command. The 
example is to print one line in the log file, as shown in the following figure:
   "This is a demo of python task".
   

##########
File path: docs/en-us/dev/user_doc/guide/task/python.md
##########
@@ -1,15 +1,55 @@
 # Python Node
 
-- Using python nodes, you can directly execute python scripts. For python 
nodes, workers use `python **` to submit tasks.
+## Overview
 
-> Drag from the toolbar 
![PNG](https://analysys.github.io/easyscheduler_docs_cn/images/toolbar_PYTHON.png)
 task node to the canvas, as shown in the following figure:
+`Python Task` is used to create a python-type task and execute python scripts. 
When the worker execute `Python Task`,
+a temporary python script is generated, and the Linux user with the same name 
as the tenant executes the script.
 
-<p align="center">
-   <img src="/img/python-en.png" width="80%" />
- </p>
+## Create Task
 
-- Script: Python program developed by the user.
-- Environment Name: Specific Python interpreter path for running the script. 
If you need to use Python **virtualenv**, you should create multiply 
environments for each **virtualenv**.  
-- Resources: Refers to the list of resource files that need to be called in 
the script.
-- User-defined parameter: It is a user-defined local parameter of Python, and 
will replace the content with `${variable}` in the script.
-- Note: If you import the python file under the resource directory tree, you 
need to add the `__init__.py` file.
+- Click Project Management-Project Name-Workflow Definition, and click the 
"Create Workflow" button to enter the DAG editing page.
+- Drag <img src="/img/tasks/icons/python.png" width="15"/> from the toolbar to 
the drawing board.
+
+## Task Parameter
+
+- Node name: The node name in a workflow definition is unique.
+- Run flag: Identifies whether this node can be scheduled normally, if it does 
not need to be executed, you can turn on the prohibition switch.
+- Descriptive information: describe the function of the node.

Review comment:
       describe -> Describe 

##########
File path: docs/en-us/dev/user_doc/guide/task/python.md
##########
@@ -1,15 +1,55 @@
 # Python Node
 
-- Using python nodes, you can directly execute python scripts. For python 
nodes, workers use `python **` to submit tasks.
+## Overview
 
-> Drag from the toolbar 
![PNG](https://analysys.github.io/easyscheduler_docs_cn/images/toolbar_PYTHON.png)
 task node to the canvas, as shown in the following figure:
+`Python Task` is used to create a python-type task and execute python scripts. 
When the worker execute `Python Task`,
+a temporary python script is generated, and the Linux user with the same name 
as the tenant executes the script.
 
-<p align="center">
-   <img src="/img/python-en.png" width="80%" />
- </p>
+## Create Task
 
-- Script: Python program developed by the user.
-- Environment Name: Specific Python interpreter path for running the script. 
If you need to use Python **virtualenv**, you should create multiply 
environments for each **virtualenv**.  
-- Resources: Refers to the list of resource files that need to be called in 
the script.
-- User-defined parameter: It is a user-defined local parameter of Python, and 
will replace the content with `${variable}` in the script.
-- Note: If you import the python file under the resource directory tree, you 
need to add the `__init__.py` file.
+- Click Project Management-Project Name-Workflow Definition, and click the 
"Create Workflow" button to enter the DAG editing page.
+- Drag <img src="/img/tasks/icons/python.png" width="15"/> from the toolbar to 
the drawing board.
+
+## Task Parameter
+
+- Node name: The node name in a workflow definition is unique.
+- Run flag: Identifies whether this node can be scheduled normally, if it does 
not need to be executed, you can turn on the prohibition switch.
+- Descriptive information: describe the function of the node.
+- Task priority: When the number of worker threads is insufficient, they are 
executed in order from high to low, and when the priority is the same, they are 
executed according to the first-in first-out principle.
+- Worker grouping: Tasks are assigned to the machines of the worker group to 
execute. If Default is selected, a worker machine will be randomly selected for 
execution.
+- Environment Name: Configure the environment name in which to run the script.
+- Number of failed retry attempts: The number of times the task failed to be 
resubmitted. It supports drop-down and hand-filling.
+- Failed retry interval: The time interval for resubmitting the task after a 
failed task. It supports drop-down and hand-filling.
+- Timeout alarm: Check the timeout alarm and timeout failure. When the task 
exceeds the "timeout period", an alarm email will be sent and the task 
execution will fail.
+- Script: PYTHON program developed by users.

Review comment:
       Python program developed by the user.

##########
File path: docs/en-us/dev/user_doc/guide/task/python.md
##########
@@ -1,15 +1,55 @@
 # Python Node
 
-- Using python nodes, you can directly execute python scripts. For python 
nodes, workers use `python **` to submit tasks.
+## Overview
 
-> Drag from the toolbar 
![PNG](https://analysys.github.io/easyscheduler_docs_cn/images/toolbar_PYTHON.png)
 task node to the canvas, as shown in the following figure:
+`Python Task` is used to create a python-type task and execute python scripts. 
When the worker execute `Python Task`,
+a temporary python script is generated, and the Linux user with the same name 
as the tenant executes the script.
 
-<p align="center">
-   <img src="/img/python-en.png" width="80%" />
- </p>
+## Create Task
 
-- Script: Python program developed by the user.
-- Environment Name: Specific Python interpreter path for running the script. 
If you need to use Python **virtualenv**, you should create multiply 
environments for each **virtualenv**.  
-- Resources: Refers to the list of resource files that need to be called in 
the script.
-- User-defined parameter: It is a user-defined local parameter of Python, and 
will replace the content with `${variable}` in the script.
-- Note: If you import the python file under the resource directory tree, you 
need to add the `__init__.py` file.
+- Click Project Management-Project Name-Workflow Definition, and click the 
"Create Workflow" button to enter the DAG editing page.
+- Drag <img src="/img/tasks/icons/python.png" width="15"/> from the toolbar to 
the drawing board.

Review comment:
       drawing board
   to 
   canvas

##########
File path: docs/en-us/dev/user_doc/guide/task/python.md
##########
@@ -1,15 +1,55 @@
 # Python Node
 
-- Using python nodes, you can directly execute python scripts. For python 
nodes, workers use `python **` to submit tasks.
+## Overview
 
-> Drag from the toolbar 
![PNG](https://analysys.github.io/easyscheduler_docs_cn/images/toolbar_PYTHON.png)
 task node to the canvas, as shown in the following figure:
+`Python Task` is used to create a python-type task and execute python scripts. 
When the worker execute `Python Task`,
+a temporary python script is generated, and the Linux user with the same name 
as the tenant executes the script.
 
-<p align="center">
-   <img src="/img/python-en.png" width="80%" />
- </p>
+## Create Task
 
-- Script: Python program developed by the user.
-- Environment Name: Specific Python interpreter path for running the script. 
If you need to use Python **virtualenv**, you should create multiply 
environments for each **virtualenv**.  
-- Resources: Refers to the list of resource files that need to be called in 
the script.
-- User-defined parameter: It is a user-defined local parameter of Python, and 
will replace the content with `${variable}` in the script.
-- Note: If you import the python file under the resource directory tree, you 
need to add the `__init__.py` file.
+- Click Project Management-Project Name-Workflow Definition, and click the 
"Create Workflow" button to enter the DAG editing page.
+- Drag <img src="/img/tasks/icons/python.png" width="15"/> from the toolbar to 
the drawing board.
+
+## Task Parameter
+
+- Node name: The node name in a workflow definition is unique.
+- Run flag: Identifies whether this node can be scheduled normally, if it does 
not need to be executed, you can turn on the prohibition switch.
+- Descriptive information: describe the function of the node.
+- Task priority: When the number of worker threads is insufficient, they are 
executed in order from high to low, and when the priority is the same, they are 
executed according to the first-in first-out principle.
+- Worker grouping: Tasks are assigned to the machines of the worker group to 
execute. If Default is selected, a worker machine will be randomly selected for 
execution.
+- Environment Name: Configure the environment name in which to run the script.
+- Number of failed retry attempts: The number of times the task failed to be 
resubmitted. It supports drop-down and hand-filling.

Review comment:
       better
   The number of times the task failed to be resubmitted. It supports drop-down 
and hand-filling.
   to
   The failure task resubmitting times.

##########
File path: docs/en-us/dev/user_doc/guide/task/python.md
##########
@@ -1,15 +1,55 @@
 # Python Node
 
-- Using python nodes, you can directly execute python scripts. For python 
nodes, workers use `python **` to submit tasks.
+## Overview
 
-> Drag from the toolbar 
![PNG](https://analysys.github.io/easyscheduler_docs_cn/images/toolbar_PYTHON.png)
 task node to the canvas, as shown in the following figure:
+`Python Task` is used to create a python-type task and execute python scripts. 
When the worker execute `Python Task`,
+a temporary python script is generated, and the Linux user with the same name 
as the tenant executes the script.
 
-<p align="center">
-   <img src="/img/python-en.png" width="80%" />
- </p>
+## Create Task
 
-- Script: Python program developed by the user.
-- Environment Name: Specific Python interpreter path for running the script. 
If you need to use Python **virtualenv**, you should create multiply 
environments for each **virtualenv**.  
-- Resources: Refers to the list of resource files that need to be called in 
the script.
-- User-defined parameter: It is a user-defined local parameter of Python, and 
will replace the content with `${variable}` in the script.
-- Note: If you import the python file under the resource directory tree, you 
need to add the `__init__.py` file.
+- Click Project Management-Project Name-Workflow Definition, and click the 
"Create Workflow" button to enter the DAG editing page.
+- Drag <img src="/img/tasks/icons/python.png" width="15"/> from the toolbar to 
the drawing board.
+
+## Task Parameter
+
+- Node name: The node name in a workflow definition is unique.
+- Run flag: Identifies whether this node can be scheduled normally, if it does 
not need to be executed, you can turn on the prohibition switch.
+- Descriptive information: describe the function of the node.
+- Task priority: When the number of worker threads is insufficient, they are 
executed in order from high to low, and when the priority is the same, they are 
executed according to the first-in first-out principle.
+- Worker grouping: Tasks are assigned to the machines of the worker group to 
execute. If Default is selected, a worker machine will be randomly selected for 
execution.
+- Environment Name: Configure the environment name in which to run the script.
+- Number of failed retry attempts: The number of times the task failed to be 
resubmitted. It supports drop-down and hand-filling.
+- Failed retry interval: The time interval for resubmitting the task after a 
failed task. It supports drop-down and hand-filling.
+- Timeout alarm: Check the timeout alarm and timeout failure. When the task 
exceeds the "timeout period", an alarm email will be sent and the task 
execution will fail.
+- Script: PYTHON program developed by users.
+- Resource: Refers to the list of resource files that need to be called in the 
script, and the files uploaded or created by the resource center-file 
management.
+- Custom parameters: It is a user-defined parameter that is part of PYTHON, 
which will replace the content with \${variable} in the script.
+
+## Task Example
+
+### Simply Print
+
+This example is a sample print task which only print one line in the log file, 
including the content
+"This is a demo of python task". If your task only run one or two python 
command, you could add task based on this example.
+
+![demo-python-simple](/img/tasks/demo/python_ui_next.jpg)
+
+```python
+print("This is a demo of python task")
+```
+
+### Custom Parameters
+
+This example is a sample custom parameter task which could reuse existing as 
template, or for dynamic task. First of all,
+we should declare a custom parameter named "param_key", with the value as 
"param_val". Then we using keyword "${param_key}"
+to using the parameter we just declared. After this example is being run, we 
would see "param_val" print in the log

Review comment:
       better change to
   This example simulates a custom parameter task. We use parameters for 
reusing existing tasks as template or coping with the dynamic task. In this 
case,
   we declare a custom parameter named "param_key", with the value "param_val". 
Then we use `echo` to print the parameter "${param_key}" we just declared. 
   After running this example, we would see "param_val" print in the log.




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