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Exporting a Base from the Command Line

SeaTable provides two ways to export a base using the command line. You can perform a simple export to a single .dtable file or an advanced export that includes all data, including big data content. Both methods bypass the limits of the web interface.

Simple Export: Create a .dtable File

The simple export generates a ready-to-use .dtable file that can be imported into another SeaTable instance.

Advantages

  • Easy to run and import
  • Produces a single .dtable file

Limitations

  • Maximum export size: 100 MB
  • Does not include big data content from the SeaTable Big Data backend

Export command

Use the following command to export a base by its base_uuid. The .dtable file will be saved to your current directory. In this example, the /shared folder is used because it is accessible from the SeaTable host.

docker exec -it seatable-server bash
cd /shared
seatable.sh python-env /opt/seatable/seatable-server-latest/dtable-web/manage.py export_dtable <base_uuid>

Replace <base_uuid> with your actual base UUID.

Excluding Attached Files and Images

To export only the structured base data and omit all assets (images, files), use the --ignore-asset option:

seatable.sh python-env /opt/seatable/seatable-server-latest/dtable-web/manage.py export_dtable <base_uuid> --ignore-asset true

If the Export Fails Due to Size Limits

If your base contains many attached files/images, you might encounter the max_download_dir_size limitation. You can increase this limit (default is 100 MB) in seafile.conf: 

[fileserver]
max_download_dir_size=1000

Then restart SeaTable

This setting determines the maximum export size for .dtable files. For example, with max_download_dir_size=1000, exports up to 1 GB are allowed. You can set this value to any size you require.

Advanced Export: Export to a Folder with All Data

6.0

The advanced export uses the export_dtable_folder command. It creates a local folder that contains all base data, assets, and big data content. This approach is ideal for complete backups or when moving large datasets.

Advantages

  • Includes data from the Big Data backend
  • No size limitation (overcomes the 100 MB default limit)

Limitations

  • The export produces a folder structure, not a single .dtable file
  • Requires manual handling when re-importing or transferring

Export Command

Run the following command to export all content, including big data, to your current folder. In this example, the /shared folder is used because it is accessible from the SeaTable host.

docker exec -it seatable-server bash
cd /shared
seatable.sh python-env /opt/seatable/seatable-server-latest/dtable-web/manage.py export_dtable_folder <base_uuid>

This command creates:

  • a folder with the name of the base
  • inside this folder:
    • a content.json file with the base’s structure and data
    • one or more subfolders for assets and big data files

Optional parameters

  • --ignore-archive-backup true: Skips the export of archived backup data. Use this if archived backups are not required in the exported result.

Importing an Advanced Export

6.0

To import an exported base folder into another group/workspace, use the following command. 

seatable.sh python-env /opt/seatable/seatable-server-latest/dtable-web/manage.py import_dtable_folder --workspace-id="<workspace id>" --path="<path to folder>"

Replace <workspace id> with the ID of the target workspace/group and provide the path to the folder containing the export.

After running the command, check that the output indicates a successful import.