Data sources docs

docs/StardustDocs/d.tree

@@ -187,8 +187,23 @@
             <toc-element topic="jupyterRendering.md"/>
         </toc-element>
     </toc-element>
-    <toc-element topic="Data-Sources.md" hidden="true">
-        <toc-element topic="Integrations.md" hidden="true"/>
+    <toc-element topic="Data-Sources.md">
+        <toc-element topic="JSON.md">
+            <toc-element topic="OpenAPI.md"/>
+        </toc-element>
+        <toc-element topic="CSV-TSV.md"/>
+        <toc-element topic="Excel.md"/>
+        <toc-element topic="ApacheArrow.md"/>
+        <toc-element topic="SQL.md">
+            <toc-element topic="PostgreSQL.md"/>
+            <toc-element topic="MySQL.md"/>
+            <toc-element topic="Microsoft-SQL-Server.md"/>
+            <toc-element topic="SQLite.md"/>
+            <toc-element topic="H2.md"/>
+            <toc-element topic="MariaDB.md"/>
+            <toc-element topic="Custom-SQL-Source.md"/>
+        </toc-element>
+        <toc-element topic="Integrations.md"/>
     </toc-element>
     <toc-element topic="_shadow_resources.md" hidden="true"/>
     <toc-element topic="Support.md"/>

docs/StardustDocs/topics/Home.topic

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             <title>Featured topics</title>
             <a href="Kotlin-DataFrame-Features-in-Kotlin-Notebook.md"/>
             <a href="Compiler-Plugin.md"/>
+            <a href="Data-Sources.md"/>
             <a href="readSqlDatabases.md"/>
         </secondary>
 

docs/StardustDocs/topics/dataSources/ApacheArrow.md

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+# Apache Arrow
+
+<web-summary>
+Read and write Apache Arrow files in Kotlin — efficient binary format support with Kotlin DataFrame.
+</web-summary>
+
+<card-summary>
+Work with Arrow files in Kotlin for fast I/O — supports both streaming and random access formats.
+</card-summary>
+
+<link-summary>
+Kotlin DataFrame provides full support for reading and writing Apache Arrow files in high-performance workflows.
+</link-summary>
+
+
+Kotlin DataFrame supports reading from and writing to Apache Arrow files.
+
+Requires the [`dataframe-arrow` module](Modules.md#dataframe-arrow), which is included by 
+default in the general [`dataframe`](Modules.md#dataframe-general) artifact 
+and in [`%use dataframe`](gettingStartedKotlinNotebook.md#integrate-kotlin-dataframe) for Kotlin Notebook.
+
+> Make sure to follow the 
+> [Apache Arrow Java compatibility guide](https://arrow.apache.org/docs/java/install.html#java-compatibility) 
+> when using Java 9+.
+> {style="warning"}
+
+## Read
+
+[`DataFrame`](DataFrame.md) supports both the 
+[Arrow interprocess streaming format](https://arrow.apache.org/docs/java/ipc.html#writing-and-reading-streaming-format) 
+and the [Arrow random access format](https://arrow.apache.org/docs/java/ipc.html#writing-and-reading-random-access-files).
+
+You can read a `DataFrame` from Apache Arrow data sources 
+(via a file path, URL, or stream) using the [`readArrowFeather()`](read.md#read-apache-arrow-formats) method:
+
+```kotlin
+val df = DataFrame.readArrowFeather("example.feather")
+```
+
+```kotlin
+val df = DataFrame.readArrowFeather("https://kotlin.github.io/dataframe/resources/example.feather")
+```
+
+## Write
+
+A [`DataFrame`](DataFrame.md) can be written to Arrow format using the interprocess streaming or random access format. 
+Output targets include `WritableByteChannel`, `OutputStream`, `File`, or `ByteArray`.
+
+See [](write.md#writing-to-apache-arrow-formats) for more details.

docs/StardustDocs/topics/dataSources/CSV-TSV.md

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+# CSV / TSV
+
+<web-summary>
+Work with CSV and TSV files — read, analyze, and export tabular data using Kotlin DataFrame.
+</web-summary>
+
+<card-summary>
+Seamlessly load and write CSV or TSV files in Kotlin — perfect for common tabular data workflows.
+</card-summary>
+
+<link-summary>
+Kotlin DataFrame support for reading and writing CSV and TSV files with simple, type-safe APIs.
+</link-summary>
+
+
+Kotlin DataFrame supports reading from and writing to CSV and TSV files.
+
+Requires the [`dataframe-csv` module](Modules.md#dataframe-csv), 
+which is included by default in the general [`dataframe`](Modules.md#dataframe-general) 
+artifact and in [`%use dataframe`](gettingStartedKotlinNotebook.md#integrate-kotlin-dataframe) for Kotlin Notebook.
+
+## Read
+
+You can read a [`DataFrame`](DataFrame.md) from a CSV or TSV file (via a file path or URL) 
+using the [`readCsv()`](read.md#read-from-csv) or `readTsv()` methods:
+
+```kotlin
+val df = DataFrame.readCsv("example.csv")
+```
+
+```kotlin
+val df = DataFrame.readCsv("https://kotlin.github.io/dataframe/resources/example.csv")
+```
+
+## Write
+
+You can write a [`DataFrame`](DataFrame.md) to a CSV file using the [`writeCsv()`](write.md#writing-to-csv) method:
+
+```kotlin
+df.writeCsv("example.csv")
+```
+
+## Deephaven CSV
+
+The [`dataframe-csv`](Modules.md#dataframe-csv) module uses the high-performance
+[Deephaven CSV library](https://github.com/deephaven/deephaven-csv) under the hood
+for fast and efficient CSV reading and writing.
+
+If you're working with large CSV files, you can adjust the parser manually
+by [configuring Deephaven-specific parameters](https://kotlin.github.io/dataframe/read.html#unlocking-deephaven-csv-features)
+to get the best performance for your use case.
+

docs/StardustDocs/topics/dataSources/Data-Sources.md

@@ -1,3 +1,33 @@
 # Data Sources
 
-> This topic is not ready yet.
+<web-summary>
+Discover all the data formats Kotlin DataFrame can work with — including JSON, CSV, Excel, SQL databases, and more.
+</web-summary>
+
+<card-summary>
+Explore supported data sources in Kotlin DataFrame and how to integrate them into your data processing workflow.
+</card-summary>
+
+<link-summary>
+Explore supported data sources in Kotlin DataFrame and how to integrate them into your data processing workflow.
+</link-summary>
+
+One of the key aspects of working with data is being able to read from and write to various data sources.  
+Kotlin DataFrame provides seamless support for a wide range of formats to integrate into your data workflows.  
+Below you'll find a list of supported sources along with instructions on how to read and write data using them.
+
+- [JSON](JSON.md)
+    - [OpenAPI](OpenAPI.md) 
+- [CSV / TSV](CSV-TSV.md)
+- [Excel](Excel.md)
+- [Apache Arrow](ApacheArrow.md)
+- [SQL](SQL.md):
+    - [PostgreSQL](PostgreSQL.md)
+    - [MySQL](MySQL.md)
+    - [Microsoft SQL Server](Microsoft-SQL-Server.md)
+    - [SQLite](SQLite.md)
+    - [H2](H2.md)
+    - [MariaDB](MariaDB.md)
+    - [Custom SQL Source](Custom-SQL-Source.md)
+- [Custom integrations with unsupported data sources](Integrations.md)
+

docs/StardustDocs/topics/dataSources/Excel.md

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+# Excel
+
+<web-summary>
+Read from and write to Excel files in `.xls` or `.xlsx` formats with Kotlin DataFrame for seamless spreadsheet integration.
+</web-summary>
+
+<card-summary>
+Kotlin DataFrame makes it easy to load and save data from Excel files — perfect for working with spreadsheet-based workflows.
+</card-summary>
+
+<link-summary>
+Learn how to read and write Excel files using Kotlin DataFrame with just a single line of code.
+</link-summary>
+
+
+Kotlin DataFrame supports reading from and writing to Excel files in both `.xls` and `.xlsx` formats.
+
+Requires the [`dataframe-excel` module](Modules.md#dataframe-excel), 
+which is included by default in the general [`dataframe`](Modules.md#dataframe-general) 
+artifact and in [`%use dataframe`](gettingStartedKotlinNotebook.md#integrate-kotlin-dataframe) for Kotlin Notebook.
+
+## Read
+
+You can read a [`DataFrame`](DataFrame.md) from an Excel file (via a file path or URL) 
+using the [`readExcel()`](read.md#read-from-excel) method:
+
+```kotlin
+val df = DataFrame.readExcel("example.xlsx")
+```
+
+```kotlin
+val df = DataFrame.readExcel("https://kotlin.github.io/dataframe/resources/example.xlsx")
+```
+
+## Write
+
+You can write a [`DataFrame`](DataFrame.md) to an Excel file using the 
+[`writeExcel()`](write.md#writing-to-csv) method:
+
+```kotlin
+df.writeExcel("example.xlsx")
+```

docs/StardustDocs/topics/dataSources/Integrations.md

@@ -1,3 +1,27 @@
-# Integrations
+# Custom integrations with unsupported data sources
 
-> This topic is not ready yet.
+<web-summary>
+Examples of how to integrate Kotlin DataFrame with other data frameworks like Exposed, Spark, or Multik.
+</web-summary>
+
+<card-summary>
+Integrate Kotlin DataFrame with unsupported sources — see practical examples with Exposed, Spark, and more.
+</card-summary>
+
+<link-summary>
+How to connect Kotlin DataFrame with data sources like Exposed, Apache Spark, or Multik.
+</link-summary>
+
+Some data sources are not officially supported in the Kotlin DataFrame API yet —
+but you can still integrate them easily using custom code.
+
+Below is a list of example integrations with other data frameworks.
+These examples demonstrate how to bridge Kotlin DataFrame with external libraries or APIs.
+
+- [Kotlin Exposed](https://github.com/Kotlin/dataframe/tree/master/examples/idea-examples/unsupported-data-sources/src/main/kotlin/org/jetbrains/kotlinx/dataframe/examples/exposed)
+- [Apache Spark](https://github.com/Kotlin/dataframe/tree/master/examples/idea-examples/unsupported-data-sources/src/main/kotlin/org/jetbrains/kotlinx/dataframe/examples/spark)
+- [Apache Spark (with Kotlin Spark API)](https://github.com/Kotlin/dataframe/tree/master/examples/idea-examples/unsupported-data-sources/src/main/kotlin/org/jetbrains/kotlinx/dataframe/examples/kotlinSpark)
+- [Multik](https://github.com/Kotlin/dataframe/tree/master/examples/idea-examples/unsupported-data-sources/src/main/kotlin/org/jetbrains/kotlinx/dataframe/examples/multik)
+
+You can use these examples as templates to create your own integrations
+with any data processing library that produces structured tabular data.

docs/StardustDocs/topics/dataSources/JSON.md

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+# JSON
+
+<web-summary>
+Support for working with JSON data — load, explore, and save structured JSON using Kotlin DataFrame.
+</web-summary>
+
+<card-summary>
+Easily handle JSON data in Kotlin — read from files or URLs, and export your data back to JSON format.
+</card-summary>
+
+<link-summary>
+Kotlin DataFrame support for reading and writing JSON files in a structured and type-safe way.
+</link-summary>
+
+Kotlin DataFrame supports reading from and writing to JSON files.
+
+Requires the [`dataframe-json` module](Modules.md#dataframe-json), 
+which is included by default in the general [`dataframe`](Modules.md#dataframe-general) 
+artifact and in [`%use dataframe`](gettingStartedKotlinNotebook.md#integrate-kotlin-dataframe) 
+for Kotlin Notebook.
+
+> Kotlin DataFrame is suitable only for working with table-like structured JSON — 
+> a list of objects where each object represents a row and all objects share the same structure.
+>
+> Experimental support for [OpenAPI JSON schemas](OpenAPI.md) is also available.  
+> {style="note"}
+
+## Read
+
+You can read a [`DataFrame`](DataFrame.md) or [`DataRow`](DataRow.md) 
+from a JSON file (via a file path or URL) using the [`readJson()`](read.md#read-from-json) method:
+
+```kotlin
+val df = DataFrame.readJson("example.json")
+```
+
+```kotlin
+val df = DataFrame.readJson("https://kotlin.github.io/dataframe/resources/example.json")
+```
+
+## Write
+
+You can write a [`DataFrame`](DataFrame.md) to a JSON file using the [`writeJson()`](write.md#writing-to-json) method:
+
+```kotlin
+df.writeJson("example.json")
+```

docs/StardustDocs/topics/dataSources/OpenAPI.md

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+# OpenAPI
+
+<web-summary>
+Work with JSON data based on OpenAPI 3.0 schemas using Kotlin DataFrame — helpful for consuming structured API responses.
+</web-summary>
+
+<card-summary>
+Use Kotlin DataFrame to read and write data that conforms to OpenAPI specifications. Great for API-driven data workflows.
+</card-summary>
+
+<link-summary>
+Learn how to use OpenAPI 3.0 JSON schemas with Kotlin DataFrame to load and manipulate API-defined data.
+</link-summary>
+
+
+> **Experimental**: Support for OpenAPI 3.0.0 schemas is currently experimental 
+> and may change or be removed in future releases.  
+> {style="warning"}
+
+Kotlin DataFrame provides support for reading and writing JSON data
+that conforms to [OpenAPI 3.0 specifications](https://www.openapis.org).
+This feature is useful when working with APIs that expose structured data defined via OpenAPI schemas.
+
+Requires the [`dataframe-openapi` module](Modules.md#dataframe-openapi),
+which **is not included** in the general [`dataframe`](Modules.md#dataframe-general) artifact.
+
+To enable it in Kotlin Notebook, use:
+
+```kotlin
+%use dataframe(enableExperimentalOpenApi=true)
+```
+
+See [the OpenAPI guide notebook](https://github.com/Kotlin/dataframe/blob/master/examples/notebooks/json/KeyValueAndOpenApi.ipynb)
+for details on how to work with OpenAPI-based data.

docs/StardustDocs/topics/dataSources/sql/Custom-SQL-Source.md

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+# Custom SQL Source
+
+<web-summary>
+Connect Kotlin DataFrame to any JDBC-compatible database using a custom SQL source configuration.
+</web-summary>
+
+<card-summary>
+Easily integrate unsupported SQL databases in Kotlin DataFrame using a flexible custom source setup.
+</card-summary>
+
+<link-summary>
+Define a custom SQL source in Kotlin DataFrame to work with any JDBC-based database.
+</link-summary>
+
+
+If your SQL database is not officially supported, you can either
+[create an issue](https://github.com/Kotlin/dataframe/issues)
+or define a simple, configurable custom SQL source.
+
+See the [How to Extend DataFrame Library for Custom SQL Database Support guide](readSqlFromCustomDatabase.md)
+for detailed instructions and an example with HSQLDB.
+