paleolimbot commented on code in PR #66:
URL: https://github.com/apache/sedona-db/pull/66#discussion_r2353218364
##########
docs/programming-guide.ipynb:
##########
@@ -246,7 +246,11 @@
"source": [
"df = sd.sql(\"\"\"\n",
"SELECT name, ST_Point(lng, lat) AS location\n",
+<<<<<<< HEAD
"FROM (VALUES \n",
+=======
+ "FROM (VALUES\n",
+>>>>>>> 33072a3 (Finish applying stashed changes and resolve conflict)
Review Comment:
Bad merge conflict resolution?
##########
docs/index.md:
##########
@@ -22,13 +24,18 @@ hide:
under the License.
-->
-# SedonaDB
+SedonaDB is a high-performance, dependency-free geospatial compute engine
designed for single-node processing, making it ideal for smaller datasets on
local machines or cloud instances.
+
+The initial `0.1` release supports a core set of vector operations, with
comprehensive vector and raster computation capabilities planned for the near
future.
+
+## Run a query in SQL, Python, or Rust
-SedonaDB is a high-performance, dependency-free geospatial compute engine.
+SedonaDB offers a flexible query interface in SQL, Python, or Rust.
-You can easily run SedonaDB locally or in the cloud. The first release
supports a core set of vector operations, but the full-suite of common vector
and raster computations will be supported soon.
+Engineered for speed, SedonaDB provides blazing-fast geospatial processing on
a single machine. This makes it perfect for the rapid analysis of smaller
datasets, whether you're working locally or on a cloud server. While the
initial release focuses on core vector operations, a full suite of vector and
raster computations is on the roadmap.
Review Comment:
Optional nit:
```suggestion
Engineered for speed, SedonaDB provides performant geospatial processing on
a single machine. This makes it perfect for the rapid analysis of smaller
datasets, whether you're working locally or on a cloud server. While the
initial release focuses on core vector operations, a full suite of vector and
raster computations is on the roadmap.
```
##########
docs/quickstart-python.md:
##########
@@ -0,0 +1,156 @@
+<!---
+ Licensed to the Apache Software Foundation (ASF) under one
+ or more contributor license agreements. See the NOTICE file
+ distributed with this work for additional information
+ regarding copyright ownership. The ASF licenses this file
+ to you under the Apache License, Version 2.0 (the
+ "License"); you may not use this file except in compliance
+ with the License. You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing,
+ software distributed under the License is distributed on an
+ "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ KIND, either express or implied. See the License for the
+ specific language governing permissions and limitations
+ under the License.
+-->
+
+# Python Quickstart
+
+SedonaDB for Python can be installed from PyPI:
+
+```shell
+pip install "apache-sedona[db]"
+```
+!!!tip "Run this tutorial as in interactive notebook"
+ You can also download the `.ipynb` version of this file from the [SedonaDB
GitHub](https://github.com/apache/sedona-db/blob/main/docs/quickstart-python.ipynb)and
run it as an interactive notebook.
+
+## Import SedonaDB
+
+To get started, import the library and connect to a new session. You can run
SQL queries directly on the session object.
+
+```python
+import sedona.db
+
+sd = sedona.db.connect()
+sd.sql("SELECT ST_Point(0, 1) as geom").show()
+```
+
+**Output:**
+
+```sh
+┌────────────┐
Review Comment:
Are all of these changes reflected in `quickstart-python.ipynb`? (I am
worried they will be obliterated the next time we change the quickstart and
render the notebook)
##########
docs/reference/read-parquet-files.md:
##########
@@ -32,15 +32,25 @@ The correct process is a two-step approach:
1. **Register** the DataFrame as a temporary view using
`.createOrReplaceTempView()`.
1. **Query** the view using `sd.sql()`.
-```python
-# 1. Load the Parquet file from a URL into a DataFrame
+```python linenums="1" title="Read a parquet file with SedonaDB"
+
+import sedona.db
+sd = sedona.db.connect()
Review Comment:
Are these changes reflected in a notebook somewhere so that we can edit and
re-render easily?
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