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new 4b5c6a2 [Feature-8023][Document] Add example and notice about task
type Python (#8023) (#713)
4b5c6a2 is described below
commit 4b5c6a259ba4395fae7ce3f575dae92d6ef8a117
Author: Eric Gao <[email protected]>
AuthorDate: Fri Apr 1 22:35:11 2022 +0800
[Feature-8023][Document] Add example and notice about task type Python
(#8023) (#713)
---
docs/en-us/2.0.5/user_doc/guide/task/python.md | 62 +++++++++++++++++++-----
docs/en-us/dev/user_doc/guide/task/python.md | 58 +++++++++++++++++++----
docs/zh-cn/2.0.5/user_doc/guide/task/python.md | 63 ++++++++++++++++++++-----
docs/zh-cn/dev/user_doc/guide/task/python.md | 63 ++++++++++++++++++++-----
img/tasks/demo/python.jpg | Bin 0 -> 235373 bytes
img/tasks/demo/python_custom_param.jpg | Bin 0 -> 230867 bytes
img/tasks/demo/python_custom_param_ui_next.jpg | Bin 0 -> 396899 bytes
img/tasks/demo/python_ui_next.jpg | Bin 0 -> 450888 bytes
img/tasks/icons/python.png | Bin 0 -> 34066 bytes
9 files changed, 204 insertions(+), 42 deletions(-)
diff --git a/docs/en-us/2.0.5/user_doc/guide/task/python.md
b/docs/en-us/2.0.5/user_doc/guide/task/python.md
index d70ef5c..6edb29d 100644
--- a/docs/en-us/2.0.5/user_doc/guide/task/python.md
+++ b/docs/en-us/2.0.5/user_doc/guide/task/python.md
@@ -1,15 +1,55 @@
-# Python
+# Python Node
-- Using python nodes, you can directly execute python scripts. For python
nodes, workers will use `python **` to submit tasks.
+## Overview
-> Drag in the
toolbarThe
task node to the drawing board, as shown in the following figure:
+Use `Python Task` to create a python-type task and execute python scripts.
When the worker executes `Python Task`,
+it will generate a temporary python script, and executes the script by the
Linux user with the same name as the tenant.
-<p align="center">
- <img src="/img/python-en.png" width="80%" />
- </p>
+## Create Task
-- Script: Python program developed by the user
-- Environment Name: Specific which Python interpreter would be use and run
`Script`. If you want 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 local user-defined parameter of Python,
which 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 canvas.
+
+## 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, 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.
+- Worker grouping: Assign tasks to the machines of the worker group to
execute. If `Default` is selected, randomly select a worker machine for
execution.
+- Environment Name: Configure the environment name in which to run the script.
+- Number of failed retry attempts: The failure task resubmitting times. 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 send and the task execution
will fail.
+- Script: Python program developed by the user.
+- 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 the user-defined parameters of Python, which will
replace the content with \${variable} in the script.
+
+## Task Example
+
+### Simply Print
+
+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".
+
+
+
+```python
+print("This is a demo of python task")
+```
+
+### Custom Parameters
+
+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 "${param_key}" we just declared.
+After running this example, we would see "param_val" print in the log.
+
+
+
+```python
+print("${param_key}")
+```
+
+## Notice
+
+None
diff --git a/docs/en-us/dev/user_doc/guide/task/python.md
b/docs/en-us/dev/user_doc/guide/task/python.md
index 56df104..31ea986 100644
--- a/docs/en-us/dev/user_doc/guide/task/python.md
+++ b/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
task node to the canvas, as shown in the following figure:
+Use `Python Task` to create a python-type task and execute python scripts.
When the worker executes `Python Task`,
+it will generate a temporary python script, and executes the script by the
Linux user with the same name as the tenant.
-<p align="center">
- <img src="/img/python-en.png" width="80%" />
- </p>
+## Create Task
+- 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 canvas.
+
+## 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, 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.
+- Worker grouping: Assign tasks to the machines of the worker group to
execute. If `Default` is selected, randomly select a worker machine for
execution.
+- Environment Name: Configure the environment name in which to run the script.
+- Number of failed retry attempts: The failure task resubmitting times. 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 send and the task execution
will fail.
- 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 `${variable}` in the script.
-- Note: If you import the python file under the resource directory tree, you
need to add the `__init__.py` file.
+- Resource: Refers to the list of resource files that need to be called in the
script, and the files uploaded or created by the resource center-file
management.
+- Custom parameters: It is the user-defined parameters of Python, which will
replace the content with \${variable} in the script.
+
+## Task Example
+
+### Simply Print
+
+This example simulates a common task that runs by a simple command. The
example is to print one line in the log file, as shown in the following figure:
+"This is a demo of python task".
+
+
+
+```python
+print("This is a demo of python task")
+```
+
+### Custom Parameters
+
+This example simulates a custom parameter task. We use parameters for reusing
existing tasks as template or coping with the dynamic task. In this case,
+we declare a custom parameter named "param_key", with the value "param_val".
Then we use echo to print the parameter "${param_key}" we just declared.
+After running this example, we would see "param_val" print in the log.
+
+
+
+```python
+print("${param_key}")
+```
+
+## Notice
+
+None
diff --git a/docs/zh-cn/2.0.5/user_doc/guide/task/python.md
b/docs/zh-cn/2.0.5/user_doc/guide/task/python.md
index ec01f2f..b851acf 100644
--- a/docs/zh-cn/2.0.5/user_doc/guide/task/python.md
+++ b/docs/zh-cn/2.0.5/user_doc/guide/task/python.md
@@ -1,15 +1,56 @@
-# Python节点
+# Python 节点
-- 使用python节点，可以直接执行python脚本，对于python节点，worker会使用`python **`方式提交任务。
+## Overview
->
拖动工具栏中的任务节点到画板中，如下图所示：
+Python 任务类型，用于创建 Python 类型的任务并执行一系列的 Python 脚本。worker 执行该任务的时候，会生成一个临时python脚本，
+并使用与租户同名的 linux 用户执行这个脚本。
-<p align="center">
- <img src="/img/python_edit.png" width="80%" />
- </p>
+## Create Task
-- 脚本：用户开发的Python程序
-- 环境名称：执行Python程序的解释器路径，指定运行脚本的解释器。当你需要使用 Python **虚拟环境** 时，可以通过创建不同的环境名称来实现。
-- 资源：是指脚本中需要调用的资源文件列表
-- 自定义参数：是Python局部的用户自定义参数，会替换脚本中以${变量}的内容
-- 注意：若引入资源目录树下的python文件，需添加 `__init__.py` 文件
+- 点击项目管理-项目名称-工作流定义，点击"创建工作流"按钮，进入DAG编辑页面。
+- 工具栏中拖动 <img src="/img/tasks/icons/python.png" width="15"/> 到画板中，即可完成创建。
+
+## Task Parameter
+
+- 任务名称：设置任务的名称。一个工作流定义中的节点名称是唯一的。
+- 运行标志：标识这个节点是否能正常调度,如果不需要执行，可以打开禁止执行开关。
+- 描述：描述该节点的功能。
+- 任务优先级：worker线程数不足时，根据优先级从高到低依次执行，优先级一样时根据先进先出原则执行。
+- Worker分组：任务分配给worker组的机器机执行，选择Default，会随机选择一台worker机执行。
+- 环境名称：配置运行脚本的环境。
+- 失败重试次数：任务失败重新提交的次数，支持下拉和手填。
+- 失败重试间隔：任务失败重新提交任务的时间间隔，支持下拉和手填。
+- 超时告警：勾选超时告警、超时失败，当任务超过"超时时长"后，会发送告警邮件并且任务执行失败.
+- 脚本：用户开发的PYTHON程序。
+- 资源：是指脚本中需要调用的资源文件列表，资源中心-文件管理上传或创建的文件。
+- 自定义参数：是PYTHON局部的用户自定义参数，会替换脚本中以${变量}的内容。
+- 前置任务：选择当前任务的前置任务，会将被选择的前置任务设置为当前任务的上游。
+
+## Task Example
+
+### Simply Print
+
+该样例模拟了常见的简单任务，这些任务只需要简单的一两行命令就能运行起来。我们以打印一行日志为例，该任务仅会在日志文件中打印一行
+"This is a demo of python task"
+
+
+
+```python
+print("This is a demo of python task")
+```
+
+### Custom Parameters
+
+该样例模拟了自定义参数任务，为了更方便的复用已有的任务，或者面对动态的需求时，我们会使用变量保证脚本的复用性。本例中，我们先在自定义脚本
+中定义了参数 "param_key"，并将他的值设置为 "param_val"。接着在"脚本"中使用了 print 函数，将参数 "param_key"
打印了出来。当我们保存
+并运行任务后，在日志中会看到将参数 "param_key" 对应的值 "param_val" 打印出来。
+
+
+
+```python
+print("${param_key}")
+```
+
+## Notice
+
+None
diff --git a/docs/zh-cn/dev/user_doc/guide/task/python.md
b/docs/zh-cn/dev/user_doc/guide/task/python.md
index 7b4a8f4..e4316ae 100644
--- a/docs/zh-cn/dev/user_doc/guide/task/python.md
+++ b/docs/zh-cn/dev/user_doc/guide/task/python.md
@@ -1,15 +1,56 @@
-# Python节点
+# Python 节点
-- 使用python节点，可以直接执行python脚本，对于python节点，worker会使用`python **`方式提交任务。
+## Overview
->
拖动工具栏中的任务节点到画板中，如下图所示：
+Python 任务类型，用于创建 Python 类型的任务并执行一系列的 Python 脚本。worker 执行该任务的时候，会生成一个临时python脚本，
+并使用与租户同名的 linux 用户执行这个脚本。
-<p align="center">
- <img src="/img/python_edit.png" width="80%" />
- </p>
+## Create Task
-- 脚本：用户开发的Python程序
-- 环境名称：执行Python程序的解释器路径，指定运行脚本的解释器。当你需要使用 Python **虚拟环境** 时，可以通过创建不同的环境名称来实现。
-- 资源：是指脚本中需要调用的资源文件列表
-- 自定义参数：是Python局部的用户自定义参数，会替换脚本中以${变量}的内容
-- 注意：若引入资源目录树下的python文件，需添加 `__init__.py` 文件
+- 点击项目管理-项目名称-工作流定义，点击"创建工作流"按钮，进入DAG编辑页面。
+- 工具栏中拖动 <img src="/img/tasks/icons/python.png" width="15"/> 到画板中，即可完成创建。
+
+## Task Parameter
+
+- 任务名称：设置任务的名称。一个工作流定义中的节点名称是唯一的。
+- 运行标志：标识这个节点是否能正常调度,如果不需要执行，可以打开禁止执行开关。
+- 描述：描述该节点的功能。
+- 任务优先级：worker线程数不足时，根据优先级从高到低依次执行，优先级一样时根据先进先出原则执行。
+- Worker分组：任务分配给worker组的机器机执行，选择Default，会随机选择一台worker机执行。
+- 环境名称：配置运行脚本的环境。
+- 失败重试次数：任务失败重新提交的次数，支持下拉和手填。
+- 失败重试间隔：任务失败重新提交任务的时间间隔，支持下拉和手填。
+- 超时告警：勾选超时告警、超时失败，当任务超过"超时时长"后，会发送告警邮件并且任务执行失败.
+- 脚本：用户开发的PYTHON程序。
+- 资源：是指脚本中需要调用的资源文件列表，资源中心-文件管理上传或创建的文件。
+- 自定义参数：是PYTHON局部的用户自定义参数，会替换脚本中以${变量}的内容。
+- 前置任务：选择当前任务的前置任务，会将被选择的前置任务设置为当前任务的上游。
+
+## Task Example
+
+### Simply Print
+
+该样例模拟了常见的简单任务，这些任务只需要简单的一两行命令就能运行起来。我们以打印一行日志为例，该任务仅会在日志文件中打印一行
+"This is a demo of python task"
+
+
+
+```python
+print("This is a demo of python task")
+```
+
+### Custom Parameters
+
+该样例模拟了自定义参数任务，为了更方便的复用已有的任务，或者面对动态的需求时，我们会使用变量保证脚本的复用性。本例中，我们先在自定义脚本
+中定义了参数 "param_key"，并将他的值设置为 "param_val"。接着在"脚本"中使用了 print 函数，将参数 "param_key"
打印了出来。当我们保存
+并运行任务后，在日志中会看到将参数 "param_key" 对应的值 "param_val" 打印出来。
+
+
+
+```python
+print("${param_key}")
+```
+
+## Notice
+
+None
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