gosentry/docs/ARCHITECTURE.md

PySentry Architecture

This document shows the current component interaction model. PySentry is still a single desktop process: the GUI, scheduler, storage, and command runner live in one application and communicate through Go function calls and shared in-memory job state.

Component Diagram

flowchart LR
    user["Desktop user"]
    gui["src/gui - Fyne windows, tabs, dialogs"]
    store["src/core Store - YAML config and jobs"]
    scheduler["src/core Scheduler - @every and cron timing"]
    runner["src/core Runner - shell command execution"]
    autostart["src/core Autostart - Windows Startup shortcut / Linux desktop startup"]
    config["pysentry.yaml - application settings"]
    jobs["jobs.yaml - job definitions"]
    logs["logs_dir - per-run command output logs"]
    shell["Platform shell - cmd.exe /C or sh -c"]

    user -->|"edits jobs, settings, runs commands"| gui
    gui -->|"OpenStore, SaveConfig, SaveJobs"| store
    store -->|"read/write"| config
    store -->|"read/write"| jobs

    gui -->|"Start, Pause, RunNow, RefreshSchedule"| scheduler
    scheduler -->|"SaveJobs after state changes"| store
    scheduler -->|"RunJob(trigger)"| runner
    runner -->|"execute command"| shell
    runner -->|"write stdout/stderr log"| logs
    runner -->|"RunRecord with status, duration, log path"| scheduler
    scheduler -->|"onChange RunRecord"| gui
    gui -->|"display History, command output, job state"| user

    gui -->|"SetAutostart, AutostartStatus"| autostart
    autostart -->|"use executable path from resolved Paths"| config

Main Flows

1. Startup: The executable starts cmd/pysentry, which calls the GUI package. The GUI opens the store, loads pysentry.yaml and jobs.yaml, creates the main tabs, then starts the scheduler with the loaded job slice.

2. Editing settings or jobs: The GUI updates the in-memory job/config state and asks Store to write YAML back to disk. Job definitions stay in one jobs.yaml; runtime command output is not stored there.

3. Scheduled run: Scheduler checks due jobs on a one-second ticker. When a job is due, it marks the job as running, saves state, and starts Runner asynchronously.

4. Manual run: Run now calls the same scheduler path as scheduled execution, but the resulting history record uses the Manual trigger.

5. Command execution: Runner executes the command through the platform shell, captures stdout and stderr, writes one timestamped .log file, and returns a RunRecord.

6. History update: The scheduler receives the RunRecord, updates the matching job, saves YAML, runs log cleanup, and calls the GUI callback so the History tab refreshes.

7. Autostart: The Settings tab calls the platform autostart implementation. Windows uses a shortcut in the current user's Startup folder. Linux uses a desktop-session startup entry.