README.md for HTAN Monitor

Overview

This tool is designed to monitor activity in a specified Synapse fileview. It checks for any entities modified within a set time frame and sends an update to a Slack channel. This is particularly useful for teams using Synapse for collaborative projects, as it keeps everyone informed about the latest changes.

Features

• Synapse Integration: Connects to Synapse to access fileview data.
• Slack Notifications: Sends daily updates to a designated Slack channel.
• Customizable Time Frames: Allows for setting specific intervals for monitoring changes.
• User-Friendly Updates: Formats Slack messages with Markdown for easy reading.

Requirements

• Python 3.x
• Synapse account with access to the desired fileview.
• Slack webhook URL for sending notifications.

Environment Variables

• FILEVIEW: Synapse Fileview ID to monitor.
• WEBHOOK: Slack webhook URL for sending notifications.
• SCHEDULED_JOB_SECRETS: JSON containing Synapse authentication token.

Usage

Local

1. Install Python 3.x if not already installed.
2. Clone or download this repository.
3. Install required packages: pip install -r requirements.txt.
4. Run the script: python monitor.py {fileview_synid} {slack_webhook_url}

Docker

A docker container is automatically built and pushed to GCHR when changes are made to this repo.

1. Pull the Docker image:

   docker pull ghcr.io/ncihtan/htan-monitor:latest
   

2. Run the Docker container

   docker run \
       -e FILEVIEW={fileview_synid} \
       -e WEBHOOK={slack_webhook_url} \
       -e SYNAPSE_AUTH_TOKEN={synapse_auth_token} \
       ghcr.io/ncihtan/htan-monitor:latest
   

AWS Scheduled Job

Set up an AWS Scheduled Job with the following parameters

1. Image: ghcr.io/ncihtan/htan-monitor:latest
2. Command: python ./monitor.py ${FILEVIEW} ${WEBHOOK}
3. Secrets: SYNAPSE_AUTH_TOKEN={synapse_auth_token}
4. EnvVars: FILEVIEW={fileview_synid},WEBHOOK={slack_webhook_url}
5. Schedule: (to run daily at 0800 UTC): cron(0 8 * * ? *)

Functions

• synapse_login(): Authenticates and connects to Synapse.
• find_modified_entities_fileview(): Retrieves entities modified within a specified time frame.
• enrich_count(): Enriches data with additional details from Synapse.
• dataframe_to_slack_block_with_md_links(): Formats the data into Slack message blocks with Markdown links.
• send_message_to_slack_blocks(): Sends the formatted message to Slack.

Contributing

Contributions are welcome. Please fork the repository and submit a pull request with your changes.

License

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

Support

For support, please open an issue in the GitHub repository or contact the maintainers directly.