Superset: Adding Python 3.12 Support

In the ever-evolving landscape of software development, staying current with programming language versions is not just a good practice; it's a necessity. For Apache Superset, a leading open-source data exploration and visualization platform, this means ensuring compatibility with the latest Python releases. As of October 2023, Python 3.12 has been released, bringing with it new features, performance improvements, and crucial updates. Currently, Superset supports Python 3.10 and 3.11. However, the absence of Python 3.12 support means that users who upgrade their Python environments might find themselves unable to use Superset, potentially blocking critical upgrades and limiting accessibility. This article delves into the importance of adding Python 3.12 compatibility to Superset, the challenges involved, and what it means for the user community.

The Critical Need for Python 3.12 Compatibility

As organizations increasingly adopt newer Python versions for their projects, Superset must keep pace to remain relevant and accessible. Python 3.12 support is crucial for several reasons. Firstly, it ensures that Superset can be deployed in modern Python environments without compatibility issues. Many companies and individual developers are eager to leverage the benefits of Python 3.12, such as its enhanced performance and new syntax features. If Superset doesn't support this version, these users will be forced to either stick with older Python versions or find alternative solutions, which is far from ideal.

Secondly, maintaining compatibility with the latest Python versions is a hallmark of a well-maintained and forward-thinking open-source project. It demonstrates a commitment to the community and ensures that Superset remains a viable choice for new projects and existing deployments that are looking to upgrade their technology stack. Ignoring newer Python versions can lead to a gradual decline in adoption and relevance. The effort to add Python 3.12 support is not merely a technical task; it's an investment in the future of Superset and its ability to serve a broader user base.

Addressing the Technical Hurdles

Supporting a new Python version like Python 3.12 often involves navigating a series of technical challenges. These challenges typically arise from breaking changes in dependencies and APIs that have been updated or deprecated between Python versions. For Superset, this means meticulously reviewing and updating its dependencies. Libraries like pandas, NumPy, and SQLAlchemy, which are core to Superset's data manipulation and database interaction capabilities, frequently introduce changes that require adjustments in the consuming code. For instance, Python 3.12 might have stricter requirements or deprecate certain functionalities that Superset currently relies upon.

Updating dependency constraints is a significant part of this process. The project needs to identify versions of these libraries that are fully compatible with Python 3.12 and adjust the requirements.txt or pyproject.toml files accordingly. This isn't just about finding compatible versions; it's about ensuring that these updated dependencies don't introduce new conflicts or break existing functionality within Superset. Furthermore, Superset's codebase might be using deprecated API patterns, particularly in libraries like pandas. A common example is the usage of pd.read_sql_query without proper connection context management, which has evolved in newer pandas versions. Adapting to these changes requires careful code refactoring to align with current best practices, ensuring stability and future maintainability. The Continuous Integration and Continuous Deployment (CI/CD) pipeline also plays a vital role. Ensuring CI/CD validation across all supported Python versions, including the newly added 3.12, is paramount. This involves configuring the test matrix to include Python 3.12, so that all automated tests (unit, integration, and pre-commit hooks) are run against it. This proactive testing approach helps catch compatibility issues early in the development cycle, guaranteeing that Superset remains robust and reliable across different Python environments. Ultimately, successfully integrating Python 3.12 support is a testament to the project's engineering rigor and commitment to providing a stable and modern platform.

Understanding the Current State of Superset

Right now, if you try to run Apache Superset in a Python 3.12 environment, you're likely to hit a roadblock. The primary reason for this incompatibility stems from the dependency versions that Superset currently specifies and the way certain APIs are used within its codebase. These factors make it impossible for the application to function correctly, or even install properly, on Python 3.12. The Superset project's testing infrastructure, its Continuous Integration and Continuous Deployment (CI/CD) workflows, are configured to validate compatibility only against the currently supported Python versions – specifically, Python 3.11 and Python 3.10. This means that any potential issues related to Python 3.12 simply go unnoticed during the development and testing phases.

Furthermore, the package metadata within Superset's configuration files, such as pyproject.toml, does not explicitly declare Python 3.12 as a supported version. This lack of declaration is a clear signal to the Python ecosystem that Superset has not yet been tested or certified for use with this latest Python release. Consequently, even if one were to manually force an installation, the underlying incompatibilities would likely surface as runtime errors, especially when performing operations that heavily rely on data manipulation libraries like pandas. The current behavior paints a clear picture: Superset, as it stands, is not ready for users who have embraced Python 3.12, presenting a barrier to adoption and upgrade.

Reproducing the Installation and Runtime Issues

To truly understand the current limitations, let's walk through the steps that highlight the incompatibility with Python 3.12. These steps will demonstrate where the process breaks down, from initial installation to actual application usage.

1. Set Up a Python 3.12 Environment: The first step is to create a dedicated environment using Python 3.12. This can be done using tools like venv, conda, or pyenv. It's crucial to ensure this environment is clean and isolated to accurately test Superset's dependencies.
2. Attempt Superset Dependency Installation: With the Python 3.12 environment active, the next action is to try installing Superset's dependencies. This is typically done by navigating to the Superset project directory and running a command like pip install -r requirements/base.txt or by installing directly from the pyproject.toml if you are building from source. This is where the first signs of trouble usually appear.
3. Observe Installation Failures or Warnings: Upon running the installation command, you'll likely encounter errors. These errors are often due to specific dependency versions that are not compatible with Python 3.12. Libraries such as NumPy, pandas, and tabulate are common culprits. You might see messages indicating version conflicts or outright installation failures for these packages. Even if the installation appears to complete, numerous warnings might suggest underlying problems.
4. Attempt to Run Superset and Query Data: If, by some chance, the installation succeeds without critical errors, the next step is to actually run Superset and test its core functionality. This involves starting the Superset server and attempting to execute a database query, especially one that involves complex data transformations using pandas.
5. Observe Runtime Errors: This is where issues related to deprecated API usage typically manifest. A common problem area is the use of pd.read_sql_query without the necessary connection context. Python 3.12's stricter adherence to API standards, combined with potential updates in pandas itself, can cause these calls to fail at runtime, leading to errors when charts are rendered or queries are processed. These errors are often cryptic and point towards internal library issues rather than direct Superset bugs, but they ultimately prevent the application from working as expected.
6. Examine CI/CD Workflows: To understand why these issues weren't caught earlier, it's useful to inspect the project's CI/CD configuration, typically found in .github/workflows/. Look at the matrix configurations for testing.
7. Observe Lack of Python 3.12 Testing: You'll notice that the test matrix in the CI/CD workflows only includes configurations for 'current' and 'previous' Python versions (e.g., 3.11 and 3.10). There is no entry for Python 3.12, meaning the automated testing suite never runs against this version. This absence of testing is the root cause of why these incompatibilities persist undetected. By following these steps, one can clearly see why Superset cannot run on Python 3.12 with its current setup.

Defining the Expected Behavior and Success Criteria

For Superset to be a truly accessible and robust platform, it must seamlessly integrate with modern development environments. This means that Superset should fully support Python 3.12, offering the same stability and functionality as it does for Python 3.10 and 3.11. Achieving this level of compatibility requires a clear set of expectations and measurable criteria to confirm success. When we talk about expected behavior, we mean that all components of Superset should function as intended when running on Python 3.12. This includes everything from the initial setup and dependency resolution to the execution of complex data analysis tasks and the rendering of visualizations.

Crucially, all dependencies must resolve correctly without conflicts. This involves updating pyproject.toml and requirements.txt files to specify versions of libraries like NumPy, pandas, and SQLAlchemy that are guaranteed to work with Python 3.12. The application should start without errors, and users should be able to connect to databases, run queries, and build dashboards without encountering any Python version-specific issues. The CI/CD pipeline is a cornerstone of this expected behavior. It needs to be updated to include Python 3.12 in its test matrix. This ensures that every pull request and commit is automatically validated against Python 3.12, catching potential regressions or incompatibilities before they merge into the main codebase. The goal is to achieve a state where Python 3.12 is treated with the same level of confidence as the currently supported versions.

Acceptance Criteria for Python 3.12 Support

To ensure that the implementation of Python 3.12 support is thorough and meets the project's standards, a specific set of acceptance criteria has been defined. These criteria serve as a checklist to verify that all necessary steps have been taken and that the desired outcome has been achieved. Meeting these criteria will confirm that Superset is indeed compatible and ready for use with Python 3.12.

• Python 3.12 Declaration: The pyproject.toml file must be updated to explicitly declare Python 3.12 as a supported Python version using classifiers. This formally communicates compatibility to the wider Python ecosystem.
• Dependency Compatibility: All direct and transitive dependency constraints within requirements/base.txt and pyproject.toml must be updated to versions that are known to be compatible with Python 3.12. This includes ensuring that core libraries like NumPy, pandas, and tabulate have compatible versions specified, and that these updates do not introduce new conflicts.
• Code Modernization: Any code within the Superset project that utilizes deprecated APIs, particularly within pandas (e.g., pd.read_sql_query usage), must be refactored to adopt current best practices. This involves ensuring proper context management for database connections and using the latest recommended methods for data manipulation.
• CI/CD Pipeline Integration: The project's CI/CD workflows, located in .github/workflows/, must be updated to include Python 3.12 in their test matrix. This means that automated checks, including pre-commit hooks, unit tests, and integration tests, will be executed against Python 3.12.
• Test Suite Validation: All existing tests within the Superset project must pass successfully when run in a Python 3.12 environment. The success rate should be comparable to that observed on Python 3.11, with no errors or warnings specifically related to Python version incompatibility. This comprehensive approach ensures that the addition of Python 3.12 support is not just a superficial change but a deep integration that maintains the integrity and reliability of the Superset platform.

Verifying Python 3.12 Compatibility in Superset

Once the necessary code changes and dependency updates have been implemented to enable Python 3.12 support in Apache Superset, thorough verification is essential. This process ensures that the application not only installs correctly but also functions reliably across various use cases. Verification involves a combination of manual testing, automated checks, and specific dependency validation, all performed within a Python 3.12 environment.

Manual Testing Procedures

Manual testing provides a hands-on approach to confirm that Superset behaves as expected in a real-world scenario. The process begins with setting up a clean environment:

1. Create a Fresh Python 3.12 Virtual Environment: Utilize tools like venv or conda to create an isolated environment specifically for Python 3.12. This ensures that no pre-existing packages interfere with the Superset installation.
2. Install Superset from Updated Requirements: Navigate to the Superset project directory and install the application using the modified requirements files (e.g., pip install -r requirements/base.txt or equivalent based on pyproject.toml). This step verifies that the dependency resolution works correctly for Python 3.12.
3. Verify Installation Success: Confirm that the pip install command completes without any errors or critical warnings. Any persistent issues at this stage indicate that dependency compatibility is still not fully resolved.
4. Start Superset and Test Key Features: Launch the Superset application and perform essential actions. This includes navigating to existing charts, creating new ones, and executing database queries. Pay close attention to any charts that rely heavily on pandas for data processing.
5. Validate Chart Rendering and Query Execution: Ensure that all charts render successfully and that database queries execute without any errors, particularly those that might stem from deprecated pandas or SQLAlchemy usage. The application should feel responsive and stable.
6. Confirm Database Operations: Test connectivity to various databases and verify that data retrieval and manipulation operations complete without runtime failures attributable to the Python 3.12 environment.

Automated Testing and CI/CD Pipeline Checks

Automated testing is crucial for ensuring consistency and catching regressions efficiently. The goal is to confirm that Superset's extensive test suite passes on Python 3.12 just as it does on other supported versions.

1. Run Pre-Commit Hooks: Execute the pre-commit workflow within the Python 3.12 environment. This checks for code style and basic syntax errors, ensuring adherence to project standards.
2. Execute Unit Tests: Run the unit test suite using a command like pytest tests/unit_tests/ within the Python 3.12 environment. Verify that all tests pass and that there are no unexpected failures.
3. Execute Integration Tests: Similarly, run the integration test suite (e.g., pytest tests/integration_tests/). These tests simulate more complex interactions and are vital for catching issues that might arise in a production-like environment.
4. Compare Test Success Rates: The success rate of tests on Python 3.12 should be equivalent to that on Python 3.11. Any significant drop in performance or increase in failures indicates unresolved compatibility problems.
5. Monitor CI/CD Pipeline Runs: Check the project's CI/CD pipeline (e.g., GitHub Actions) to confirm that Python 3.12 is included in the test matrix and that all stages of the pipeline pass successfully for this version. This automated validation is key to maintaining ongoing compatibility.

Dependency Verification

Finally, specific checks on dependencies can uncover subtle issues missed by general testing.

1. Run pip check: Execute pip check within the Python 3.12 environment. This command verifies that all installed packages have compatible dependencies among themselves, flagging any conflicts.
2. Verify Core Library Versions: Confirm that the versions of NumPy, pandas, and tabulate (and any other critical libraries) are indeed compatible with Python 3.12 and are the versions intended by the project.
3. Scan for Deprecation Warnings: During test execution or application runtime, monitor for any deprecation warnings, especially those related to pandas or SQLAlchemy usage. The absence of such warnings indicates that the code has been successfully updated to use current, supported APIs.

By diligently performing these manual, automated, and dependency-focused verifications, the project can confidently confirm that Superset's compatibility with Python 3.12 is robust and reliable. For more information on Python best practices and dependency management, you can refer to the official Python documentation or resources from organizations like the Python Software Foundation.