docs/source/user-guide/io/table_provider.md

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(io_custom_table_provider)=

# Custom Table Provider

If you have a custom data source that you want to integrate with DataFusion, you can do so by
implementing the [TableProvider](https://datafusion.apache.org/library-user-guide/custom-table-providers.html)
interface in Rust and then exposing it in Python. To do so,
you must use DataFusion 43.0.0 or later and expose a [FFI_TableProvider](https://crates.io/crates/datafusion-ffi)
via [PyCapsule](https://pyo3.rs/main/doc/pyo3/types/struct.pycapsule).

A complete example can be found in the [examples folder](https://github.com/apache/datafusion-python/tree/main/examples).

```rust
#[pymethods]
impl MyTableProvider {

    fn __datafusion_table_provider__<'py>(
        &self,
        py: Python<'py>,
    ) -> PyResult<Bound<'py, PyCapsule>> {
        let name = cr"datafusion_table_provider".into();

        let provider = Arc::new(self.clone());
        let provider = FFI_TableProvider::new(provider, false, None);

        PyCapsule::new_bound(py, provider, Some(name.clone()))
    }
}
```

Once you have this library available, you can construct a
{py:class}`~datafusion.Table` in Python and register it with the
`SessionContext`.

```python
from datafusion import SessionContext, Table

ctx = SessionContext()
provider = MyTableProvider()

ctx.register_table("capsule_table", provider)

ctx.table("capsule_table").show()
```