chore:Language changes and Fix notebook install packages

.github/workflows/ci.yml

@@ -64,5 +64,32 @@ jobs:
       - name: Build and validate
         run: make release-check
 
+      - name: Upload dist artifacts
+        uses: actions/upload-artifact@v4
+        with:
+          name: dist
+          path: dist/
+
       - name: Publish to PyPI
         uses: pypa/gh-action-pypi-publish@release/v1
+
+  release:
+    needs: publish
+    runs-on: ubuntu-latest
+    if: startsWith(github.ref, 'refs/tags/v')
+    permissions:
+      contents: write
+    steps:
+      - uses: actions/checkout@v6
+
+      - name: Download dist artifacts
+        uses: actions/download-artifact@v4
+        with:
+          name: dist
+          path: dist/
+
+      - name: Create GitHub Release
+        uses: softprops/action-gh-release@v2
+        with:
+          files: dist/*
+          generate_release_notes: true

CHANGELOG.md

@@ -34,5 +34,5 @@ Initial public release of **vowl**.
 - `THIRD_PARTY_NOTICES` and `LICENSE_AUDIT_REPORT.md`.
 - `CONTRIBUTING.md` with development setup and release workflow.
 
-[Unreleased]: https://github.com/govtech-data-practice/Vowl/compare/v0.0.1...HEAD
-[0.0.1]: https://github.com/govtech-data-practice/Vowl/releases/tag/v0.0.1
+[Unreleased]: https://github.com/govtech-data-practice/vowl/compare/v0.0.1...HEAD
+[0.0.1]: https://github.com/govtech-data-practice/vowl/releases/tag/v0.0.1

CONTRIBUTING.md

@@ -56,7 +56,7 @@ The Makefile is the canonical source for local development commands. If a README
 ```bash
 git clone https://github.com/<your-username>/vowl.git
 cd vowl
-git remote add upstream https://github.com/govtech-data-practice/Vowl.git
+git remote add upstream https://github.com/govtech-data-practice/vowl.git
 ```
 
 ### Install Development Dependencies

README.md

@@ -1,10 +1,14 @@
 <div align="center">
-  <img src="https://raw.githubusercontent.com/govtech-data-practice/Vowl/main/docs/img/vowl_logo.png" alt="vowl logo" width="400">
+  <img src="https://raw.githubusercontent.com/govtech-data-practice/vowl/main/docs/img/vowl_logo.png" alt="vowl logo" width="400">
+
+  <br/>
+
+  [![Documentation](https://img.shields.io/badge/docs-GitHub%20Pages-blue)](https://govtech-data-practice.github.io/vowl/)
 </div>
 
-# Vowl
+# vowl
 
-Vowl (vee-owl 🦉) is a validation engine for [Open Data Contract Standard (ODCS)](https://github.com/bitol-io/open-data-contract-standard) data contracts. Define your validation rules once in a declarative YAML contract and get rich, actionable reports on your data's quality.
+vowl (vee-owl 🦉) is a validation engine for [Open Data Contract Standard (ODCS)](https://github.com/bitol-io/open-data-contract-standard) data contracts. Define your validation rules once in a declarative YAML contract and get rich, actionable reports on your data's quality.
 
 ## Table of Contents
 
@@ -30,6 +34,7 @@ Vowl (vee-owl 🦉) is a validation engine for [Open Data Contract Standard (ODC
   - [Loading Contracts from Git (GitHub/GitLab)](#loading-contracts-from-git-githubgitlab)
   - [Loading Contracts from S3](#loading-contracts-from-s3)
 - [Roadmap](#roadmap)
+- [Contributing](#contributing)
 - [License](#license)
 
 ## Features
@@ -791,6 +796,12 @@ result.display_full_report()
 
 ---
 
+## Contributing
+
+We welcome contributions! Please see [CONTRIBUTING.md](CONTRIBUTING.md) for guidelines on how to get started.
+
+---
+
 ## License
 
 This project is licensed under the [MIT License](LICENSE).

docs/architecture.md

@@ -1,6 +1,6 @@
 # Architecture
 
-Vowl has a modular architecture built around **Ibis** as the universal query layer.
+vowl has a modular architecture built around **Ibis** as the universal query layer.
 
 ```
 ┌─────────────────────────────────────────────────────────────────────────────┐

docs/contracts.md

@@ -85,7 +85,7 @@ schema:
 
 ## Automatic Check References
 
-When a contract is loaded, Vowl automatically builds `CheckReference` objects for every executable check in the contract via `Contract.get_check_references_by_schema()`.
+When a contract is loaded, vowl automatically builds `CheckReference` objects for every executable check in the contract via `Contract.get_check_references_by_schema()`.
 
 This includes both user-authored checks in `quality` blocks and synthetic checks derived from column metadata. The generated references are grouped by schema, and the auto-generated ones run before explicit `quality` checks.
 
@@ -104,7 +104,7 @@ This includes both user-authored checks in `quality` blocks and synthetic checks
 
 ## Auto-Generated Checks
 
-| Generated from | What Vowl validates |
+| Generated from | What vowl validates |
 |----------------|----------------------|
 | `name` | Column declared in the contract exists in the source table |
 | `logicalType` | Values can be cast to the declared SQL type for `integer`, `number`, `boolean`, `date`, `timestamp`, and `time` |
@@ -139,11 +139,11 @@ produces three generated check references:
 | `$.schema[0].properties[...].required` | `RequiredCheckReference` |
 
 !!! note
-    Because `string` does not currently generate a SQL cast-based type check, the `logicalType` entry above contributes metadata for option checks rather than a standalone type-validation query. If you use `integer`, `number`, `boolean`, `date`, `timestamp`, or `time`, Vowl also generates a `logicalType` SQL check automatically.
+    Because `string` does not currently generate a SQL cast-based type check, the `logicalType` entry above contributes metadata for option checks rather than a standalone type-validation query. If you use `integer`, `number`, `boolean`, `date`, `timestamp`, or `time`, vowl also generates a `logicalType` SQL check automatically.
 
 ## Library Metrics (`type: library`)
 
-Instead of writing SQL by hand, you can declare common data quality metrics using `type: library` in your `quality` blocks. Vowl auto-generates the appropriate SQL at runtime.
+Instead of writing SQL by hand, you can declare common data quality metrics using `type: library` in your `quality` blocks. vowl auto-generates the appropriate SQL at runtime.
 
 ### Column-Level Metrics
 

docs/getting-started.md

@@ -13,7 +13,7 @@ Optional extras are available:
 | `vowl[spark]` | PySpark support |
 | `vowl[all]` | Everything (Spark + AWS) |
 
-For local development, testing, and release workflow, see [CONTRIBUTING.md](https://github.com/govtech-data-practice/Vowl/blob/main/CONTRIBUTING.md).
+For local development, testing, and release workflow, see [CONTRIBUTING.md](https://github.com/govtech-data-practice/vowl/blob/main/CONTRIBUTING.md).
 
 ## Validate in 3 Lines
 

docs/index.md

@@ -7,9 +7,9 @@ hide:
   <img src="img/vowl_logo.png" alt="vowl logo" width="400">
 </div>
 
-# Vowl
+# vowl
 
-Vowl (vee-owl 🦉): a validation engine for [Open Data Contract Standard (ODCS)](https://github.com/bitol-io/open-data-contract-standard) data contracts. Define your validation rules once in a declarative YAML contract and get rich, actionable reports on your data's quality.
+vowl (vee-owl 🦉): a validation engine for [Open Data Contract Standard (ODCS)](https://github.com/bitol-io/open-data-contract-standard) data contracts. Define your validation rules once in a declarative YAML contract and get rich, actionable reports on your data's quality.
 
 ## Key Features
 
@@ -42,4 +42,4 @@ Optional extras: `vowl[spark]`, `vowl[all]`.
 
 ## License
 
-This project is licensed under the [MIT License](https://github.com/govtech-data-practice/Vowl/blob/main/LICENSE).
+This project is licensed under the [MIT License](https://github.com/govtech-data-practice/vowl/blob/main/LICENSE).

docs/known-issues.md

@@ -29,13 +29,13 @@ result = validate_data("contract.yaml", adapter=IbisAdapter(con))
 Oracle has several SQL dialect differences that can cause some generated checks to `ERROR`:
 
 - **No `LIMIT` clause:** Ibis handles this via `FETCH FIRST N ROWS ONLY`, but edge cases may arise.
-- **No `!~` regex operator:** Vowl applies an AST transform to use `REGEXP_LIKE` on Oracle, but complex patterns may not translate cleanly.
-- **Case-sensitive identifiers:** Oracle folds unquoted identifiers to uppercase. If your source tables were created with quoted lowercase column names, auto-generated checks may fail to match. Vowl applies quoting transforms to mitigate this, but mismatches can still occur.
-- **`TEXT`/`CLOB` types cannot be used in `REGEXP_LIKE`:** Vowl automatically casts these to `VARCHAR(4000)`, which truncates values longer than 4000 characters.
+- **No `!~` regex operator:** vowl applies an AST transform to use `REGEXP_LIKE` on Oracle, but complex patterns may not translate cleanly.
+- **Case-sensitive identifiers:** Oracle folds unquoted identifiers to uppercase. If your source tables were created with quoted lowercase column names, auto-generated checks may fail to match. vowl applies quoting transforms to mitigate this, but mismatches can still occur.
+- **`TEXT`/`CLOB` types cannot be used in `REGEXP_LIKE`:** vowl automatically casts these to `VARCHAR(4000)`, which truncates values longer than 4000 characters.
 
 ## SQLite: Regex via User-Defined Function
 
-SQLite does not natively support `REGEXP_LIKE`. Vowl rewrites regex checks to use Ibis's `_IBIS_REGEX_SEARCH` user-defined function, which Ibis registers automatically when using a DuckDB or SQLite backend. This generally works but may behave differently from server-side regex implementations in edge cases.
+SQLite does not natively support `REGEXP_LIKE`. vowl rewrites regex checks to use Ibis's `_IBIS_REGEX_SEARCH` user-defined function, which Ibis registers automatically when using a DuckDB or SQLite backend. This generally works but may behave differently from server-side regex implementations in edge cases.
 
 ## Multi-Source Adapters: Data Materialisation
 
@@ -53,9 +53,9 @@ The `MultiSourceSQLExecutor` materialises tables via Arrow instead of using Duck
 
 1. **Table namespace mismatch.** DuckDB ATTACH places tables under a qualified namespace (e.g. `pg_db.public.my_table`). User-authored contract queries use bare table names (`my_table`). `USE` or `SET search_path` resolves this for a single attached database, but cross-database joins (the core multi-source use case) require every table reference to be fully qualified. Rewriting arbitrary user SQL to inject per-table namespace prefixes is fragile and error-prone.
 
-2. **No access to connection credentials.** DuckDB ATTACH requires a connection string (`host=... port=... dbname=... user=... password=...`), not a live connection object. Vowl receives an Ibis connection from the user. Reconstructing credentials would require accessing private Ibis internals (`_con_kwargs`), would not work for connections created via `from_connection()` or environment-based auth, and would surface passwords in SQL strings.
+2. **No access to connection credentials.** DuckDB ATTACH requires a connection string (`host=... port=... dbname=... user=... password=...`), not a live connection object. vowl receives an Ibis connection from the user. Reconstructing credentials would require accessing private Ibis internals (`_con_kwargs`), would not work for connections created via `from_connection()` or environment-based auth, and would surface passwords in SQL strings.
 
-3. **Limited backend coverage.** DuckDB ATTACH only supports PostgreSQL, MySQL, and SQLite. Vowl supports 12+ Ibis backends (Snowflake, Spark, BigQuery, Trino, ClickHouse, Oracle, MSSQL, DataFusion, etc.). The materialisation path would still be needed for every unsupported backend, so ATTACH would only serve as a partial optimisation.
+3. **Limited backend coverage.** DuckDB ATTACH only supports PostgreSQL, MySQL, and SQLite. vowl supports 12+ Ibis backends (Snowflake, Spark, BigQuery, Trino, ClickHouse, Oracle, MSSQL, DataFusion, etc.). The materialisation path would still be needed for every unsupported backend, so ATTACH would only serve as a partial optimisation.
 
 4. **Filter conditions cannot be pushed through ATTACH.** When an adapter has filter conditions, `export_table_as_arrow()` applies them at the source before export. With ATTACH, the remote table is exposed raw, and pushing per-adapter filters into cross-database joins would require deep query rewriting.
 
@@ -97,7 +97,7 @@ quality:
     mustBe: 0
 ```
 
-will happily query `audit_log` even if it is not declared anywhere in the contract. Vowl extracts and reports the tables involved via `tables_in_query` in the results, but it does **not** block execution against undeclared tables.
+will happily query `audit_log` even if it is not declared anywhere in the contract. vowl extracts and reports the tables involved via `tables_in_query` in the results, but it does **not** block execution against undeclared tables.
 
 **Why this matters:**
 

docs/usage-patterns.md

@@ -1,7 +1,7 @@
 # Usage Patterns
 
 !!! tip "Interactive Demo"
-    Try the [usage patterns notebook](https://github.com/govtech-data-practice/Vowl/blob/main/examples/vowl_usage_patterns_demo.ipynb) for a hands-on walkthrough of the examples below.
+    Try the [usage patterns notebook](https://github.com/govtech-data-practice/vowl/blob/main/examples/vowl_usage_patterns_demo.ipynb) for a hands-on walkthrough of the examples below.
 
 ## Local DataFrame (Pandas/Polars)
 
@@ -49,7 +49,7 @@ result.display_full_report()
 Ibis supports: Amazon Athena, BigQuery, ClickHouse, Dask, Databricks, DataFusion, Druid, DuckDB, Exasol, Flink, Impala, MSSQL, MySQL, Oracle, pandas, Polars, PostgreSQL, PySpark, RisingWave, SingleStoreDB, Snowflake, SQLite, Trino, and more. See [ibis-project/ibis](https://github.com/ibis-project/ibis).
 
 !!! info "MySQL"
-    Select the database when you create the connection, for example via `ibis.mysql.connect(..., database="my_db")` or a connection URI that already includes the database name. Vowl does not issue `USE database` during validation; it runs read-only `SELECT` queries against the active database on the existing connection.
+    Select the database when you create the connection, for example via `ibis.mysql.connect(..., database="my_db")` or a connection URI that already includes the database name. vowl does not issue `USE database` during validation; it runs read-only `SELECT` queries against the active database on the existing connection.
 
 ## Compatibility Mode (DuckDB ATTACH)
 

examples/vowl_usage_patterns_demo.ipynb

@@ -5,7 +5,7 @@
    "id": "5179d529",
    "metadata": {},
    "source": [
-    "# Vowl Usage Patterns Demo\n",
+    "# vowl Usage Patterns Demo\n",
     "\n",
     "This notebook demonstrates the different methods of using the **vowl** library for data quality validation using [ODCS](https://github.com/bitol-io/open-data-contract-standard) data contracts.\n",
     "\n",
@@ -33,13 +33,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": null,
    "id": "20da0e86",
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Install the package\n",
-    "#!pip install vowl[all]"
+    "# Install the package and additional packages used in the notebook\n",
+    "#!pip install \"vowl[all]\" polars"
    ]
   },
   {

mkdocs.yml

@@ -1,8 +1,8 @@
-site_name: Vowl
+site_name: vowl
 site_description: A SQL-powered data quality validation library for pandas and spark DataFrames.
-site_url: https://govtech-data-practice.github.io/Vowl/
-repo_url: https://github.com/govtech-data-practice/Vowl
-repo_name: govtech-data-practice/Vowl
+site_url: https://govtech-data-practice.github.io/vowl/
+repo_url: https://github.com/govtech-data-practice/vowl
+repo_name: govtech-data-practice/vowl
 
 theme:
   name: material

pyproject.toml

@@ -51,9 +51,9 @@ all = [
 ]
 
 [project.urls]
-Homepage = "https://github.com/govtech-data-practice/Vowl"
-Repository = "https://github.com/govtech-data-practice/Vowl"
-Issues = "https://github.com/govtech-data-practice/Vowl/issues"
+Homepage = "https://github.com/govtech-data-practice/vowl"
+Repository = "https://github.com/govtech-data-practice/vowl"
+Issues = "https://github.com/govtech-data-practice/vowl/issues"
 Documentation = "https://pypi.org/project/vowl/"
 
 [tool.setuptools.packages.find]