This command line tool prints, for a given regulations.gov docket ID:

• The number of unique JSON files for dockets, documents, and comments in the AWS Open Data S3 bucket (s3://mirrulations)
• The corresponding count from the regulations.gov API
• A side-by-side comparison for each type (docket, documents, comments)

The S3 bucket is part of the AWS Open Data initiative and can be accessed free of charge, without AWS credentials.

1. The setup.py works with pip to create a command mirrulations-fetch. It is recommended that you create a virtual environment and install locally:

python3 -m venv .venv
source .venv/bin/activate
pip install .

2. Create a .env file in the project root with your regulations.gov API key:

API_KEY=your_actual_api_key_here

You can use DEMO_KEY for testing, but it is rate-limited and for demo purposes only. You can obtain an API key at the Regulations.gov API documentation page.

Run the CLI tool with a docket ID:

docket-stats <DOCKET_ID>

$ docket-stats CMS-2025-0050
Gathering information (this may take a while for large dockets)...
Comments:  12%|██▍        | 120/981 [00:01<00:09, 91.23file/s]
Docket ID: CMS-2025-0050
Docket Title: Request for Information: Health Technology Ecosystem (CMS-0042-NC)
Docket JSON files (S3/API): 1/1
Documents JSON files (S3/API): 2/2
Comments JSON files (S3/API): 981/981

• The S3 count is the number of unique JSON files (ignoring duplicates with suffixes like (1), (2), etc.).
• The API count is from regulations.gov.
• The progress bar only appears for comments, and only for large dockets.

• S3 queries may take a while for large dockets.
• No AWS credentials are required; the tool uses unsigned S3 access.

This project is licensed under the MIT License. See the LICENSE file for details.