Convert Outlook for Mac (.olm) archive files to individual .eml files for AI analysis

• Extracts emails from OLM (Outlook for Mac) archive files
• Converts each email to standard EML format
• Handles both XML and binary message formats
• Preserves email headers (From, To, Subject, Date)
• Extracts email body content

• Python 3.6+
• No external dependencies (uses only standard library)

python olm_to_eml_converter.py path/to/your/file.olm output_directory

python olm_to_eml_converter.py ~/Documents/MyEmails.olm ./converted_emails

from olm_to_eml_converter import OLMToEMLConverter

converter = OLMToEMLConverter("path/to/file.olm", "output_directory")
converter.convert()

The script creates individual .eml files with names like:

• message_00001.eml
• message_00002.eml
• etc.

Each .eml file contains:

• Standard email headers (From, To, Subject, Date)
• Email body content
• Compatible with email clients and AI tools

1. Extraction: OLM files are ZIP archives containing email data
2. Processing: Looks for message files (.olk15Message or .olk14Message)
3. Conversion: Extracts email content from XML or binary format
4. Output: Creates standard EML files for each email

• OLM files are specific to Outlook for Mac
• The script handles various message formats within OLM files
• Some complex formatting may be simplified during conversion
• Large OLM files may take time to process

• "Invalid OLM file": Ensure the file is a valid OLM archive
• "No Local directory found": The OLM structure may be different
• Encoding issues: Some special characters may not display correctly

After conversion, you can:

1. Upload the .eml files to Notion AI or similar tools
2. Use the provided CSV conversion script to create a spreadsheet
3. Process emails programmatically for analysis