dianfu commented on a change in pull request #14041:
URL: https://github.com/apache/flink/pull/14041#discussion_r521771064
##########
File path: docs/dev/python/index.zh.md
##########
@@ -22,3 +23,43 @@ KIND, either express or implied. See the License for the
specific language governing permissions and limitations
under the License.
-->
+
+<img src="{% link /fig/pyflink.svg %}" alt="PyFlink" class="offset"
width="50%" />
+
+PyFlink is a language for building unified batch and streaming workloads.
+This means real-time streaming pipelines, performing exploratory data
+analysis at scale, building machine learning pipelines, and creating ETLs for
a data platform.
+If you're already familiar with Python and libraries such as Pandas, then
PyFlink makes it simple
+to leverage the full capabilities of the Apache Flink ecosystem.
+
+The PyFlink Table API makes it simple to write powerful relational queries for
building reports and
+ETL pipelines.
+At the same time, the PyFlink DataStream API gives developers access to
low-level control over
+state and time, unlocking the full power of stream processing.
+
+<div class="row">
+<div class="col-sm-6" markdown="1">
+
+### Try PyFlink
+
+If you’re interested in playing around with Flink, try one of our tutorials:
+
+* [Intro to PyFlink Table API]({% link dev/python/table_api_tutorial.md %})
+* [Intro to PyFlink DataStream API]({% link dev/python/datastream_tutorial.md
%})
Review comment:
```suggestion
* [Intro to PyFlink DataStream API]({% link
dev/python/datastream_tutorial.zh.md %})
```
##########
File path: docs/dev/python/index.zh.md
##########
@@ -22,3 +23,43 @@ KIND, either express or implied. See the License for the
specific language governing permissions and limitations
under the License.
-->
+
+<img src="{% link /fig/pyflink.svg %}" alt="PyFlink" class="offset"
width="50%" />
+
+PyFlink is a language for building unified batch and streaming workloads.
+This means real-time streaming pipelines, performing exploratory data
+analysis at scale, building machine learning pipelines, and creating ETLs for
a data platform.
+If you're already familiar with Python and libraries such as Pandas, then
PyFlink makes it simple
+to leverage the full capabilities of the Apache Flink ecosystem.
+
+The PyFlink Table API makes it simple to write powerful relational queries for
building reports and
+ETL pipelines.
+At the same time, the PyFlink DataStream API gives developers access to
low-level control over
+state and time, unlocking the full power of stream processing.
+
+<div class="row">
+<div class="col-sm-6" markdown="1">
+
+### Try PyFlink
+
+If you’re interested in playing around with Flink, try one of our tutorials:
+
+* [Intro to PyFlink Table API]({% link dev/python/table_api_tutorial.md %})
+* [Intro to PyFlink DataStream API]({% link dev/python/datastream_tutorial.md
%})
+
+</div>
+<div class="col-sm-6" markdown="1">
+
+### Explore PyFlink
+
+The reference documentation covers all the details. Some starting points:
+
+* [PyFlink DataStream API]({% link dev/python/table-api-users-guide/index.md
%})
Review comment:
```suggestion
* [PyFlink DataStream API]({% link
dev/python/table-api-users-guide/index.zh.md %})
```
##########
File path: docs/dev/python/index.zh.md
##########
@@ -22,3 +23,43 @@ KIND, either express or implied. See the License for the
specific language governing permissions and limitations
under the License.
-->
+
+<img src="{% link /fig/pyflink.svg %}" alt="PyFlink" class="offset"
width="50%" />
+
+PyFlink is a language for building unified batch and streaming workloads.
+This means real-time streaming pipelines, performing exploratory data
+analysis at scale, building machine learning pipelines, and creating ETLs for
a data platform.
+If you're already familiar with Python and libraries such as Pandas, then
PyFlink makes it simple
+to leverage the full capabilities of the Apache Flink ecosystem.
+
+The PyFlink Table API makes it simple to write powerful relational queries for
building reports and
+ETL pipelines.
+At the same time, the PyFlink DataStream API gives developers access to
low-level control over
+state and time, unlocking the full power of stream processing.
+
+<div class="row">
+<div class="col-sm-6" markdown="1">
+
+### Try PyFlink
+
+If you’re interested in playing around with Flink, try one of our tutorials:
+
+* [Intro to PyFlink Table API]({% link dev/python/table_api_tutorial.md %})
+* [Intro to PyFlink DataStream API]({% link dev/python/datastream_tutorial.md
%})
+
+</div>
+<div class="col-sm-6" markdown="1">
+
+### Explore PyFlink
+
+The reference documentation covers all the details. Some starting points:
+
+* [PyFlink DataStream API]({% link dev/python/table-api-users-guide/index.md
%})
+* [PyFlink Table API & SQL]({% link
dev/python/datastream-api-users-guide/index.md %})
Review comment:
```suggestion
* [PyFlink Table API & SQL]({% link
dev/python/datastream-api-users-guide/index.zh.md %})
```
##########
File path: docs/dev/python/index.zh.md
##########
@@ -22,3 +23,43 @@ KIND, either express or implied. See the License for the
specific language governing permissions and limitations
under the License.
-->
+
+<img src="{% link /fig/pyflink.svg %}" alt="PyFlink" class="offset"
width="50%" />
+
+PyFlink is a language for building unified batch and streaming workloads.
+This means real-time streaming pipelines, performing exploratory data
+analysis at scale, building machine learning pipelines, and creating ETLs for
a data platform.
+If you're already familiar with Python and libraries such as Pandas, then
PyFlink makes it simple
+to leverage the full capabilities of the Apache Flink ecosystem.
+
+The PyFlink Table API makes it simple to write powerful relational queries for
building reports and
+ETL pipelines.
+At the same time, the PyFlink DataStream API gives developers access to
low-level control over
+state and time, unlocking the full power of stream processing.
+
+<div class="row">
+<div class="col-sm-6" markdown="1">
+
+### Try PyFlink
+
+If you’re interested in playing around with Flink, try one of our tutorials:
+
+* [Intro to PyFlink Table API]({% link dev/python/table_api_tutorial.md %})
Review comment:
```suggestion
* [Intro to PyFlink Table API]({% link dev/python/table_api_tutorial.zh.md
%})
```
##########
File path: docs/dev/python/index.md
##########
@@ -22,3 +23,43 @@ KIND, either express or implied. See the License for the
specific language governing permissions and limitations
under the License.
-->
+
+<img src="{% link /fig/pyflink.svg %}" alt="PyFlink" class="offset"
width="50%" />
+
+PyFlink is a language for building unified batch and streaming workloads.
+This means real-time streaming pipelines, performing exploratory data
+analysis at scale, building machine learning pipelines, and creating ETLs for
a data platform.
+If you're already familiar with Python and libraries such as Pandas, then
PyFlink makes it simple
+to leverage the full capabilities of the Apache Flink ecosystem.
+
+The PyFlink Table API makes it simple to write powerful relational queries for
building reports and
+ETL pipelines.
+At the same time, the PyFlink DataStream API gives developers access to
low-level control over
+state and time, unlocking the full power of stream processing.
+
+<div class="row">
+<div class="col-sm-6" markdown="1">
+
+### Try PyFlink
+
+If you’re interested in playing around with Flink, try one of our tutorials:
+
+* [Intro to PyFlink Table API]({% link dev/python/table_api_tutorial.md %})
+* [Intro to PyFlink DataStream API]({% link dev/python/datastream_tutorial.md
%})
+
+</div>
+<div class="col-sm-6" markdown="1">
+
+### Explore PyFlink
+
+The reference documentation covers all the details. Some starting points:
+
+* [PyFlink DataStream API]({% link dev/python/table-api-users-guide/index.md
%})
Review comment:
Nit: *PyFlink Table API* is located before the *Python DataStream API*
in the *Try PyFlink* section. What about keeping the order consistent?
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