Install and use plugins¶
Goal. Extend binoc with domain-specific format support by installing a plugin package.
Prerequisites. binoc working at the command line (see
Diff two snapshots).
The one-liner¶
Plugins are regular Python packages distributed on PyPI. Install one and it becomes available automatically — no configuration required:
With uvx you can run binoc plus a plugin without installing
anything permanently:
Either way, .sqlite / .db files in the snapshots now get semantic
schema and row-count diffs instead of "content changed".
How it works¶
At startup, binoc scans Python entry points in the group
binoc.plugins and loads everything it finds. An installed plugin
package declares an entry point in its pyproject.toml and exposes
either a register(registry) function (for Python plugins) or a native module
(for Rust plugins built with maturin). Either way, the host learns about the
plugin's available surfaces at startup.
You don't need to "enable" the plugin to load it; installing the package is enough. Dataset-specific semantics still belong in dataset config when a plugin documents them.
See Plugin discovery for the exact strings involved, and Plugin model for the conceptual overview.
Where do plugins come from?¶
The binoc-* namespace on PyPI is the shared ecosystem namespace
(similar to pytest-* or llm-*). Published reference plugins today
include:
binoc-sqlite— SQLite schema and row-count diffing.- (More plugins will land here as the ecosystem grows.)
For in-tree reference implementations see the model-plugins/
directory in the repository. They double as worked examples for the current
Plugin model.
List what's registered¶
Once a plugin is installed, any stable plugin surfaces it exposes are available through the host. Current diff behavior uses correspondence rule packs and renderer plugins.
For current dataset semantics, use dataset config. For the rule-family dispatch model, see Dispatch model.
Trust¶
Plugins run in-process with the host's privileges. Only install plugins from sources you trust at least as much as you trust running their code on your machine. See Security and trust for the short version and Security posture and auditing ADR for the long version.
Where to go next¶
- Plugin discovery reference — the exact entry-point strings and registry API.
- Dataset config — dataset semantics and renderer config.
- Plugin model explanation — the current rule-family plugin split and why it exists.
- Publish a plugin — if you want to build your own.