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Docs: Add SeaweedFS REST catalog and FileIO configuration examples #3778

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Docs: Add SeaweedFS REST catalog and FileIO configuration examples
chrislusf Aug 11, 2026
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Rename catalog example heading to avoid duplicate
chrislusf Aug 11, 2026
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Expand Up @@ -242,6 +242,21 @@ Tencent Cloud Object Storage (COS) is S3-compatible and can be used with PyIcebe

<!-- markdown-link-check-enable -->

### SeaweedFS

<!-- markdown-link-check-disable -->

[SeaweedFS](https://github.com/seaweedfs/seaweedfs) is S3-compatible and can be used with PyIceberg using the existing S3FileIO / PyArrowFileIO implementation.

| Key | Example | Description |
| -------------------- | ----------------------- | --------------------------------- |
| s3.endpoint | <http://localhost:8333> | SeaweedFS S3 gateway endpoint |
| s3.access-key-id | admin | Configured S3 access key |
| s3.secret-access-key | password | Configured S3 secret key |
| s3.path-style-access | true | SeaweedFS serves path-style URLs |

<!-- markdown-link-check-enable -->

### Hugging Face

<!-- markdown-link-check-disable -->
Expand Down Expand Up @@ -653,6 +668,23 @@ catalog:
Use the `entra` auth type for Entra ID (Azure AD) authentication via [DefaultAzureCredential](https://learn.microsoft.com/en-us/azure/developer/python/sdk/authentication/credential-chains?tabs=dac#defaultazurecredential-overview), which supports environment variables, managed identity, Azure CLI, and more. Install with `pip install pyiceberg[entra-auth]`.
<!-- prettier-ignore-end -->

##### SeaweedFS Table Buckets

[SeaweedFS](https://github.com/seaweedfs/seaweedfs) table buckets serve an Iceberg REST catalog for table metadata and store the table data as Parquet files behind the same S3 gateway:

```yaml
catalog:
seaweedfs_catalog:
type: rest
uri: http://<seaweedfs-host>:8181
warehouse: s3://<table-bucket-name>
credential: <access-key>:<secret-key>
s3.endpoint: http://<seaweedfs-host>:8333
s3.access-key-id: <access-key>
s3.secret-access-key: <secret-key>
s3.path-style-access: true
```

### SQL Catalog

The SQL catalog requires a database for its backend. PyIceberg supports PostgreSQL and SQLite through psycopg2. The database connection has to be configured using the `uri` property. The init_catalog_tables is optional and defaults to True. If it is set to False, the catalog tables will not be created when the SQLCatalog is initialized. See SQLAlchemy's [documentation for URL format](https://docs.sqlalchemy.org/en/20/core/engines.html#backend-specific-urls):
Expand Down