epstein-files 1.0.9

Tools for working with the Jeffrey Epstein documents released in November 2025.

I Made Epstein's Text Messages Great Again

• The Epstein text messages (and selected emails and other files) generated by this code can be viewed here.
• All of His Emails along with descriptions of the 496 files that were neither emails nor text messages can be read at another page also generated by this code.
• Word counts for all of the communications.
• Metadata containing what I have figured out about who sent or received the communications in a given file (and a brief explanation for how I figured it out for each file) is deployed here
• I Made Epstein's Text Messages Great Again (And You Should Read Them) post on Substack

Usage

Installation

1. Requires you have a local copy of the OCR text files from the House Oversight document release in a directory /path/to/epstein/ocr_txt_files. You can download those OCR text files from the Congressional Google Drive folder (make sure you grab both the 001/ and 002/ folders).
2. Use poetry install for easiest time installing. pip install epstein-files should also work, though pipx install epstein-files is usually better.

You need to set the EPSTEIN_DOCS_DIR environment variable with the path to the folder of files you just downloaded when running. You can either create a .env file modeled on .env.example (which will set it permanently) or you can run with:

EPSTEIN_DOCS_DIR=/path/to/epstein/ocr_txt_files epstein_generate --help

All the tools that come with the package require EPSTEIN_DOCS_DIR to be set. These are the available tools:

# Generate color highlighted texts/emails/other files
epstein_generate

# Search for a string:
epstein_search Bannon
# Or a regex:
epstein_search '\bSteve\s*Bannon\b'

# Show a file with color highlighting of keywords:
epstein_show 030999
# Show both the highlighted and raw versions of the file:
epstein_show --raw 030999
# The full filename is also accepted:
epstein_show HOUSE_OVERSIGHT_030999

# Count words used by Epstein and Bannon
epstein_word_count --name 'Jeffrey Epstein' --name 'Steve Bannon'

# Diff two epstein files after all the cleanup (stripping BOMs, matching newline chars, etc):
epstein_diff 030999 020442

The first time you run anything it will take a few minutes to fix all the janky OCR text, attribute the redacted emails, etc. After that things will be quick. Run epstein_generate --help for command line option assistance.

As A Library

from epstein_files.epstein_files import EpsteinFiles
epstein_files = EpsteinFiles.get_files()

# All files
for document in epstein_files.all_documents():
    do_stuff(document)

# Emails
for email in epstein_files.emails:
    do_stuff(email)

# iMessage Logs
for imessage_log in epstein_files.imessage_logs:
    do_stuff(imessage_log)

# JSON files
for json_file in epstein_files.json_files:
    do_stuff(json_file)

# Other Files
for file in epstein_files.other_files:
    do_stuff(file)