---
title: "Release highlights: 1.12.3 - 1.14.1"
description:  Release highlights provide a concise overview of the most important new features, improvements, and fixes in a software update, helping users quickly understand what's changed and how it impacts their workflow.
keywords: [dlt, data-pipelines, etl, release-notes, data-engineering]
---


# Release highlights: 1.12.3 & 1.13.0 & 1.14.1

## Breaking change: Ibis dataset/relation functionality + new non-Ibis relation features

**What changed**

Accessing Ibis relations using `dataset["table_name"]` or `dataset.table_name` no longer works.

**Migration required**

To get an Ibis table relation, explicitly set the table type to get the *table expression first*, then convert it to a *table relation:*

```py
# Previously: dataset["customers"]  # now returns a regular relation
customers_expression = dataset.table("customers", table_type="ibis")
customers_relation = dataset(customers_expression)

df = customers_relation.df()  # fetch as DataFrame
```

Check out the [updated docs](../general-usage/dataset-access/dataset#modifying-queries-with-ibis-expressions) and [migration guide](../general-usage/dataset-access/dataset#migrating-from-the-previous-dlt--ibis-implementation) for full details and examples.

:::note
If you were using `dataset` without having Ibis installed, or without using any Ibis features, no changes are needed.
:::
---

**New: non-Ibis relation enhancements**

You can now use a more SQL-like interface on regular relations:

```py
customers = dataset.table("customers")

# Sort
customers.order_by("created_at").fetchall()

# Filter
customers.filter("id = 1").fetchall()

# Aggregation
customers.select("id").max().scalar()
```

---

## Marimo playground: Try dlt in your browser

**PR: #2832**

**Overview**

We now host an interactive **Marimo notebook playground** on GitHub Pages:

🔗 https://dlt-hub.github.io/dlt/playground/

This lets you test dlt code **directly in your browser** using Pyodide/WASM, no installation needed.

**What’s included**

The first notebook walks through a **simple example of loading a Python data structure into DuckDB** using dlt. It’s a quick and friendly way to understand how dlt pipelines work without setting up any environment.

**Docs integration**

We’ve also embedded the notebook directly into our docs:

[Playground tutorial page →](../tutorial/playground.mdx)

This makes it easier to **read and run** the code side by side.

![marimo-playground](https://storage.googleapis.com/dlt-blog-images/marimo-playground.png)

---

## REST API: New paginator for header-based cursors

**PR: #2798**

**Overview**

The new `header_cursor` paginator enables pagination for APIs that return the next page cursor in the **response headers**, such as those using custom headers like `NextPageToken`.

**Use case**

Some REST APIs respond like this:

```text
# response header
Content-Type: application/json
NextPageToken: 123456
```

```text
# response JSON
[
  {"id": 1, "name": "item1"},
  {"id": 2, "name": "item2"}
]
```

To fetch the next page:

```text
https://api.example.com/items?page=123456
```

**Example configuration**

```py
{
  "path": "items",
  "paginator": {
    "type": "header_cursor",
    "cursor_key": "NextPageToken",  # name of the response header
    "cursor_param": "page"          # query parameter used to pass the token
  }
}
```

You can now extract cursors from headers just like from JSON paths in the response body.

---

## Autocompletion in Notebooks: Dataset and relation

**PR: #2891**

**Overview**

Working in notebooks just got smoother. We’ve added **tab autocompletion** for `dlt.Dataset` and `dlt.Relation` objects.

Now you can:

- Use `dataset.<TAB>` to see available tables
- Use `relation.<TAB>` to explore available columns

**How it works**

The feature overrides `_ipython_key_completions_` to inspect dataset/relation structure and return available names.

**Example**

```py
dataset  # <TAB> will suggest all table names
dataset.customers  # <TAB> will suggest column names like id, email, created_at
```

---

## DuckLake setup guide for MotherDuck

**PR: #2842**

**Overview**

We’ve added a dedicated section in the docs for setting up **DuckLake**, a powerful way to persist **MotherDuck** databases on external storage like S3.

**The guide includes:**

1. Creating a DuckLake-managed database on S3
2. Storing S3 credentials securely in MotherDuck
3. Connecting dlt to DuckLake via `secrets.toml`

**Why use DuckLake?**

- Offload MotherDuck data to **S3**
- Control over **storage location** and **retention**
- Load data via dlt like with any DuckDB destination

[DuckLake setup in docs →](../dlt-ecosystem/destinations/motherduck#ducklake-setup)

---

## Athena + Iceberg + Lake Formation tags and table properties

**PR: #2808**

**Overview**

You can now apply **Lake Formation tags** to the Glue database used by the Athena destination. All tables created by dlt will inherit these tags.

**Example configuration**

```toml
[destination.athena.lakeformation_config]
enabled = true

[destination.athena.lakeformation_config.tags]
Environment = "prod"
Team = "analytics"
```

---

## Add post-create SQL statements

**PR: #2791**

You can now run **custom SQL statements** *after* tables are created or altered during schema migration. Useful for foreign keys, constraints, etc.

**Example usage**

Override `_get_table_post_update_sql` in your `SqlJobClientBase`:

```py
def _get_table_post_update_sql(self, partial_table):
    if partial_table["name"] == "orders":
        return [
            "ALTER TABLE orders ADD CONSTRAINT fk_user FOREIGN KEY (user_id) REFERENCES users(id)"
        ]
    return []
```

These run **after all tables are updated**, allowing dependency-safe logic.

---

## CLI: Friendly `drop` command 🐕‍🦺

**PR: #2720**

**Overview**

The `dlt drop` command now includes smarter validation and warnings to avoid accidental misconfigurations.

**Warning types**

1. **Run directory validation**
    ```text
    You should run this from the same directory as the pipeline script...
    ```

2. **Misaligned config context detection**
    ```text
    WARNING: Active pipeline `my_pipeline` used `/home/user/project/.dlt`...
    ```

3. **Pipeline script vs. run dir mismatch**
    ```text
    WARNING: Your run dir (/home/user/tmp) is different from the pipeline script...
    ```

4. **Credential visibility notice**
    ```text
    WARNING: When accessing data from the command line, dlt does not execute your pipeline code...
    ```

5. **Table drop preview**
    Lists tables that will be deleted before performing the drop.

---

## Shout-out to new contributors

Big thanks to our newest contributors:

- @AyushPatel101 (#2803)
- @nicob3y (#2755)
- @kaliole (#2849)
- @franloza (#2869)

---

**Full release notes**

[View the complete list of changes →](https://github.com/dlt-hub/dlt/releases)