refine docs latest tag to make it ready as default.

docs/_static/css/custom.css

@@ -14,3 +14,18 @@ body {
 .sidebar-scroll {
 	margin-bottom: 175px;
 }
+
+.fa.fa-2x {
+    font-size: 36px;
+}
+
+/* Decrease the padding of button block in panels */
+div.card-body.card-body-less-padding {
+    padding: 0.25em;
+}
+
+/* Disable theme toggle */
+div.theme-toggle-container.theme-toggle-content {
+    display: none;
+}
+

docs/_templates/sidebar/rtd-versions.html

@@ -59,7 +59,7 @@
 
     <hr />
     <small>
-      <span>Hosted by <a href="https://pages.github.com/">Github Pages</a>.</span>
+      <span>Hosted on <a href="https://pages.cloudflare.com/">Cloudflare Pages</a>.</span>
     </small>
   </div>
 </div>

docs/conf.py

@@ -117,8 +117,8 @@
         {
             "name": "GitHub",
             "url": "https://github.com/alibaba/GraphScope",
-            "html": "",
-            "class": "fa fa-solid fa-github fa-2x",
+            "html": "<svg stroke='currentColor' fill='currentColor' stroke-width='0' viewBox='0 0 16 16'><path fill-rule='evenodd' d='M8 0C3.58 0 0 3.58 0 8c0 3.54 2.29 6.53 5.47 7.59.4.07.55-.17.55-.38 0-.19-.01-.82-.01-1.49-2.01.37-2.53-.49-2.69-.94-.09-.23-.48-.94-.82-1.13-.28-.15-.68-.52-.01-.53.63-.01 1.08.58 1.23.82.72 1.21 1.87.87 2.33.66.07-.52.28-.87.51-1.07-1.78-.2-3.64-.89-3.64-3.95 0-.87.31-1.59.82-2.15-.08-.2-.36-1.02.08-2.12 0 0 .67-.21 2.2.82.64-.18 1.32-.27 2-.27.68 0 1.36.09 2 .27 1.53-1.04 2.2-.82 2.2-.82.44 1.1.16 1.92.08 2.12.51.56.82 1.27.82 2.15 0 3.07-1.87 3.75-3.65 3.95.29.25.54.73.54 1.48 0 1.07-.01 1.93-.01 2.2 0 .21.15.46.55.38A8.013 8.013 0 0 0 16 8c0-4.42-3.58-8-8-8z'></path></svg>",
+            "class": "muted-link",
         },
     ],
 }
@@ -141,14 +141,14 @@
 ]
 
 html_css_files = [
-    "css/brands.min.css",    # font-awesome
-    "css/regular.min.css",    # font-awesome
-    "css/solid.min.css",    # font-awesome
-    "css/fontawesome.min.css",    # font-awesome
+    # "css/brands.min.css",    # font-awesome
+    # "css/regular.min.css",    # font-awesome
+    # "css/solid.min.css",    # font-awesome
+    # "css/fontawesome.min.css",    # font-awesome
     "css/custom.css",
     "css/panels.css",
     "css/rst-versions.css",
-    "css/theme-toggle.css",
+    # "css/theme-toggle.css",
 ]
 
 # generate autosummary pages

docs/deployment/deploy_graphscope_on_self_managed_k8s.md

@@ -1,4 +1,4 @@
-# Deploy GraphScope on K8s cluster
+# Deploy on K8s Cluster
 
 To processing large-scale graph in a distributed environment, GraphScope is designed to be deployed on a Kubernetes(K8s) cluster. 
 

docs/deployment/deploy_graphscope_on_existing_vineyard_cluster.md → docs/deployment/deploy_with_existing_vineyard_cluster.md

@@ -1,4 +1,4 @@
-# Use an existing vineyard cluster with multiple GraphScope sessions
+# Depoly with Existing Vineyard Cluster
 
 If you have already deployed a vineyard cluster, you can easily deploy GraphScope on the existing cluster and reuse the vineyard data such as graph with several GraphScope sessions. This will allow you to load a graph to the existing vineyard cluster and then reuse it with multiple GraphScope sessions, without needing to deploy a separate vineyard cluster for each session.
 

docs/development/how_to_install_in_offline_mode.md → docs/deployment/install_in_offline_env.md

@@ -1,4 +1,4 @@
-# Install GraphScope in offline mode
+# Install GraphScope in offline environment
 
 Some users may face the problem that they need to install GraphScope on an environment that has no internet access.
 

docs/development/dev_io_adaptor.md

@@ -0,0 +1,123 @@
+# Dev
+
+```{toctree} arguments
+---
+caption: TOC
+maxdepth: 1
+hidden: 
+---
+tutorial_run_builtin_algo
+tutorial_networkx_operations
+tutotial_networkx_algorithms
+tutorial_run_builtin_algo
+tutorial_dev_algo_cpp_pie
+tutorial_dev_algo_cpp_flash
+tutorial_dev_algo_python
+tutorial_dev_algo_java
+tutorial_run_giraph_apps
+tutorial_run_graphx_apps
+```
+
+
+This section contains a guide to the analytical engine and a number of examples.
+
+```{tip}
+We assume you has read the [getting_started](getting_started.md) section and know how to launch a GraphScope session.
+```
+
+The analytcial engine of GraphScope can handles various scenarios, .... In most cases, the built-in algorithms are sufficient for your needs.
+
+````{panels}
+:header: text-center
+:column: col-lg-12 p-2
+
+```{link-button} tutorial_run_builtin_algo.html
+:text: Tutorial
+:classes: btn-block stretched-link
+```
+^^^^^^^^^^^^^^
+Using Louvain to detect communities in a social graph.
+````
+
+If you are a scientist familiar with NetworkX, you may find GraphScope works well for your known APIs to manipulate graph, to invoke an analysis algorithm, and it works well with other modules in PyData eco-system.
+
+````{panels}
+:header: text-center
+:column: col-lg-12 p-2
+
+```{link-button} tutorial_networkx_operations.html
+:text: Toturial
+:classes: btn-block stretched-link 
+```
+^^^^^^^^^^^^^^
+Using NetworkX to manipulate graph and run algorithms.
+---- 
+
+```{link-button} tutorial_networkx_algorithms.html
+:text: Toturial
+:classes: btn-block stretched-link 
+```
+^^^^^^^^^^^^^^
+Running NetworkX Algorithms on GraphScope
+````
+
+If the built-in algorithms are not sufficient for your needs, you can implement your own algorithms in PIE or FLASH model, in Java、C++ or Python, and run them on GraphScope.
+
+````{panels}
+:header: text-center
+:column: col-lg-12 p-2
+
+```{link-button} tutorial_dev_algo_cpp_pie.html
+:text: Tutorial
+:classes: btn-block stretched-link 
+```
+^^^^^^^^^^^^^^
+Write and run customized PageRank in C++ with PIE model
+---- 
+
+```{link-button} tutorial_dev_algo_cpp_flash.html
+:text: Tutorial
+:classes: btn-block stretched-link 
+```
+^^^^^^^^^^^^^^
+Write and run SSSP in C++ with FLASH model
+---- 
+
+```{link-button} tutorial_dev_algo_python.html
+:text: Tutorial
+:classes: btn-block stretched-link 
+```
+^^^^^^^^^^^^^^
+Write and run algorithms in Python
+---- 
+
+```{link-button} tutorial_dev_algo_java.html
+:text: Tutorial
+:classes: btn-block stretched-link 
+```
+^^^^^^^^^^^^^^
+Write and run algorithms in Java with PIE and Pregel model
+````
+
+Better still, if you already have your application running on Giraph or GraphX, the packaged `jar` can directly run on GraphScope. The migration is totally transparent, you even don't need to have the sourcecode!
+
+````{panels}
+:header: text-center
+:column: col-lg-12 p-2
+
+```{link-button} tutorial_run_giraph_apps.html
+:text: Tutorial
+:classes: btn-block stretched-link 
+```
+^^^^^^^^^^^^^^
+Develop and run (existing) Giraph applications on GraphScope
+
+----
+
+```{link-button} tutorial_run_graphx_apps.html
+:text: Tutorial
+:classes: btn-block stretched-link 
+```
+^^^^^^^^^^^^^^
+Develop and run (existing) GraphX applications on GraphScope
+````

docs/index.rst

@@ -18,7 +18,7 @@ and the vineyard store that offers efficient in-memory data transfers.
 
 
 .. toctree::
-   :maxdepth: 2
+   :maxdepth: 1
    :caption: Overview
 
    overview/intro
@@ -33,17 +33,18 @@ and the vineyard store that offers efficient in-memory data transfers.
    frequently_asked_questions
 
 .. toctree::
-   :maxdepth: 2
+   :maxdepth: 1
    :caption: Installation & Deployment
 
    deployment/install_on_local
    deployment/deploy_graphscope_on_self_managed_k8s
-   deployment/deploy_graphscope_on_existing_vineyard_cluster
-   deployment/deploy_graphscope_on_clouds
+   deployment/deploy_with_existing_vineyard_cluster
+   .. deployment/deploy_graphscope_on_clouds
    deployment/deploy_graphscope_with_helm
+   deployment/install_in_offline_env
 
 .. toctree::
-   :maxdepth: 2
+   :maxdepth: 1
    :caption: Graph Analytical Engine
 
    analytical_engine/getting_started
@@ -52,11 +53,11 @@ and the vineyard store that offers efficient in-memory data transfers.
    analytical_engine/guide_and_examples
    analytical_engine/dev_and_test
    analytical_engine/apis
-   analytical_engine/faqs
+   .. analytical_engine/faqs
 
 
 .. toctree::
-   :maxdepth: 2
+   :maxdepth: 1
    :caption: Graph Interactive Engine
 
    interactive_engine/getting_started
@@ -68,7 +69,7 @@ and the vineyard store that offers efficient in-memory data transfers.
    interactive_engine/faq.md
 
 .. toctree::
-   :maxdepth: 2
+   :maxdepth: 1
    :caption: Graph Learning Engine
 
    learning_engine/getting_started
@@ -78,38 +79,38 @@ and the vineyard store that offers efficient in-memory data transfers.
    learning_engine/dev_and_test
 
 .. toctree::
-   :maxdepth: 2
+   :maxdepth: 1
    :caption: Storage Engine
 
-   storage_engine/getting_started
+   .. storage_engine/getting_started
    storage_engine/grin
    storage_engine/groot
    storage_engine/vineyard
    storage_engine/graphar
    storage_engine/gart
 
 .. toctree::
-   :maxdepth: 2
-   :caption: troubleshooting & utilities
+   :maxdepth: 1
+   :caption: Troubleshooting & Utilities
 
    utilities/how_to_find_logs
-   utilities/monitoring
+   .. utilities/monitoring
    utilities/gs
    utilities/error_codes
 
 .. toctree::
-   :maxdepth: 2
+   :maxdepth: 1
    :caption: Development
 
    development/dev_guide
    development/code_style_guide
    development/how_to_test
+   .. development/how_to_debug
    development/how_to_contribute
-   development/how_to_debugging
-   development/how_to_install_in_offline_mode
+
 
 .. toctree::
-   :maxdepth: 2
+   :maxdepth: 1
    :caption: Reference
 
    reference/python_index

docs/overview/getting_started.md

@@ -203,7 +203,7 @@ train_gcn(lg, node_type="paper", edge_type="cites",
 ````
 
 
-## Graph Interactive Query Quick Start
+## Graph Analytical Task Quick Start
 
 
 The installed `graphscope` package includes everything you need to analyze a graph on your local machine. If you have a graph analytical job that needs to run iterative algorithms, it works well with `graphscope`.
@@ -236,8 +236,12 @@ print(ret.to_dataframe(selector={'id': 'v.id', 'distance': 'r'})
 ```
 ````
 
+## Graph Interactive Query Quick Start
+
+TODO(Robin):
+
 ## Graph Learning Quick Start
 
-TBF
+TODO(LiSu):
 
 

docs/utilities/how_to_find_logs.md

@@ -1,6 +1,7 @@
 # How to Find logs
 
-By default, GraphScope is usually running in a silent mode following the convention of Python applications. To enable verbose logging, turn on by:
+By default, GraphScope is running in a silent mode following the convention of Python applications. 
+To enable verbose logging, turn it on by this command after importing `graphscope`.
 
 ```python
 >>> import graphscope
@@ -26,9 +27,9 @@ $ kubectl describe pod <pod_name>
 $ kubectl logs -f <pod_name>
 ```
 
-### Find logs for Graph Analytical Engine (GAE)
+### Find logs for GraphScope Analytical Engine (GAE)
 
-Within the k8s environment, all logs for Graph Analytical Engine (GAE) are consolidated into the coordinator pod. Therefore, you can view GAE logs by using the command:
+Within the k8s environment, all logs for the analytical engine (GAE) are consolidated into the coordinator pod. Therefore, you can view GAE logs by using the command:
 
 ```shell
 $ kubectl logs -f coordinator-syoove-79b44f7b58-ctmqb