Implementing and Debugging Python Scheduling Scripts

• Day: 2024-12-17
• Time: 21:40 to 22:20
• Project: Dev
• Workspace: WP 2: Operational
• Status: Completed
• Priority: MEDIUM
• Assignee: Matías Nehuen Iglesias
• Tags: Python, Scheduling, Apscheduler, Email Automation, Ai Model

Description

Session Goal

The session aimed to enhance email automation with Markdown support, explore AI model upgrade options, and refine Python scheduling scripts for task automation.

Key Activities

• Developed a Python script to send emails with Markdown content, converting it to HTML to ensure proper rendering across email clients.
• Evaluated AI model upgrade options for a staff manager agent, comparing GPT-3.5 Turbo, GPT-4 Turbo, and GPT-4o based on cost, performance, and task suitability.
• Implemented Python scripts for scheduling morning and evening briefings, detailing the necessary code adjustments.
• Addressed and debugged cron job scheduling errors, providing corrected code examples and testing instructions.
• Explored methods to check current system time using Python and terminal commands, including UTC and timezone-specific options.
• Resolved APScheduler ValueError and timezone mismatches by validating and setting explicit timezone configurations for cron jobs.
• Corrected the usage of the day_of_week parameter in APScheduler to ensure accurate task scheduling.

Achievements

• Successfully implemented email automation with Markdown support.
• Clarified AI model upgrade options for future decision-making.
• Debugged and refined scheduling scripts, ensuring accurate task execution in local timezones.

Pending Tasks

• Further testing of scheduling scripts in diverse environments to ensure robustness.
• Continuous monitoring of AI model performance post-upgrade to validate cost-effectiveness.

Evidence

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• event_ids: []