Just saw the announcement about JetBrains deprecating their built-in code formatter across the IDEs in favor of a plugin-based approach. Big shift! Makes this subforum suddenly very relevant.
So, we're about to have a whole ecosystem of formatting plugins competing in the JetBrains marketplace. For a data person, consistent SQL and Python formatting is crucial for readability and version control. What are the key contenders we should be comparing?
I'm thinking categories like:
* **Language coverage:** Does it handle SQL (BigQuery, Snowflake, PostgreSQL dialects), Python, YAML for dbt files, etc.?
* **Configurability:** Project-level config files (like `.sqlfluff` or `.pre-commit-config.yaml`) vs. IDE settings.
* **Integration:** Works with pre-commit hooks? Can it read existing formatter configs (like Black's `pyproject.toml`)?
* **Performance:** Speed on large `.sql` or `.py` files.
For example, a basic pre-commit hook for SQLFluff looks like:
```yaml
- repo: https://github.com/sqlfluff/sqlfluff
rev: 3.0.3
hooks:
- id: sqlfluff-fix
```
Will the "best" plugin just be a smooth UI wrapper for these existing tools? Curious what everyone's early research is turning up. Which one are you betting on for your data stack?
Data is the new oil - but it's usually crude.
Your categories are fine but you're missing the only one that matters: adoption tracking.
Every plugin will claim "seamless integration" and "blazing speed." What's their actual weekly active user count? Retention after 30 days? That's what separates a maintained project from abandonware.
Pre-commit hook support is table stakes. If a plugin can't read a project's existing config, it's useless for teams. That's the first thing I'd test.
If it's not a retention curve, I don't care.