Confluence

Connect Confluence to your preprocessing pipeline, and use the Unstructured CLI or Python to batch process all your spaces and pages and store structured outputs locally on your filesystem.

You will need:

The Confluence prerequisites:

• A Confluence account.
• The URL for the target Confluence instance.
• A Confluence user with the correct permissions to access the target spaces and pages in the Confluence instance.
• A Confluence API token for the target Confluence user.
• Optionally, the names of the specific spaces in the Confluence instance to access.

The Confluence connector dependencies:

pip install "unstructured-ingest[confluence]"

You might also need to install additional dependencies, depending on your needs. Learn more.

The following environment variables:

• CONFLUENCE_URL - The URL of the Confluence instance, represented by --url (CLI) or url (Python).
• CONFLUENCE_API_TOKEN - The value of the Confluence API token for authenticating with the Confluence instance, represented by --api-token (CLI) or api_token (Python).
• CONFLUENCE_USER_EMAIL - The user’s email address for authenticating with the Confluence instance, represented by --user-email (CLI) or user_email (Python).

Additional settings include:

• --spaces (CLI) or spaces (Python): Optionally, the list of the names of the specific spaces to access, expressed as a comma-separated list of strings (CLI) or an array of strings (Python), with each string representing a space’s name. The default is no specific spaces, if not otherwise specified.
• --max-num-of-spaces (CLI) or max_num_of_spaces (Python): Optionally, the maximum number of spaces to access, expressed as an integer. The default value is 500 if not otherwise specified.
• --max-num-of-docs-from-each-space (CLI) or max_num_of_docs_from_each_space (Python): Optionally, the maximum number of documents to access from each space, expressed as an integer. The default value is 100 if not otherwise specified.

Now call the Unstructured CLI or Python. The destination connector can be any of the ones supported. This example uses the local destination connector.

This example sends data to Unstructured API services for processing by default. To process data locally instead, see the instructions at the end of this page.

For the Unstructured Ingest CLI and the Unstructured Ingest Python library, you can use the --partition-by-api option (CLI) or partition_by_api (Python) parameter to specify where files are processed:

• To do local file processing, omit --partition-by-api (CLI) or partition_by_api (Python), or explicitly specify partition_by_api=False (Python).

  Local file processing does not use an Unstructured API key or API URL, so you can also omit the following, if they appear:

  • --api-key $UNSTRUCTURED_API_KEY (CLI) or api_key=os.getenv("UNSTRUCTURED_API_KEY") (Python)
  • --partition-endpoint $UNSTRUCTURED_API_URL (CLI) or partition_endpoint=os.getenv("UNSTRUCTURED_API_URL") (Python)
  • The environment variables UNSTRUCTURED_API_KEY and UNSTRUCTURED_API_URL

• To send files to Unstructured API services for processing, specify --partition-by-api (CLI) or partition_by_api=True (Python).

  Unstructured API services also requires an Unstructured API key and API URL, by adding the following:

  • --api-key $UNSTRUCTURED_API_KEY (CLI) or api_key=os.getenv("UNSTRUCTURED_API_KEY") (Python)
  • --partition-endpoint $UNSTRUCTURED_API_URL (CLI) or partition_endpoint=os.getenv("UNSTRUCTURED_API_URL") (Python)
  • The environment variables UNSTRUCTURED_API_KEY and UNSTRUCTURED_API_URL, representing your API key and API URL, respectively.

  Get an API key and API URL.