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Danny 967c7880fc chore: prefer BOT_TOKEN env var over secrets file 
Backward-compatible reorder: env var wins, then file. This lets
multiple instances on the same host (prod + shipyard staging)
each load a distinct token via systemd EnvironmentFile, instead
of fighting over the single ~/.secrets/bigbiggerbiggestbot file.

Also documents the new two-environment workflow in README.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-10 12:44:25 +02:00
tests feat: profile/settings (rest timer toggle) 2026-04-19 15:36:06 +02:00
webapp feat(webapp): settings toggle for the +/- weight button 2026-04-24 11:28:57 +02:00
.env.example feat(tg-fitness-bot): initial Telegram workout tracker bot 2026-03-24 15:50:05 +01:00
.gitignore feat(tg-fitness-bot): initial Telegram workout tracker bot 2026-03-24 15:50:05 +01:00
bot.py chore: prefer BOT_TOKEN env var over secrets file 2026-05-10 12:44:25 +02:00
db.py feat: profile/settings (rest timer toggle) 2026-04-19 15:36:06 +02:00
flake.lock feat(tg-fitness-bot): initial Telegram workout tracker bot 2026-03-24 15:50:05 +01:00
flake.nix feat(tg-fitness-bot): add test suite with pre-commit hook 2026-04-13 20:41:03 +02:00
LICENSE docs: add LICENSE (MIT) and README 2026-04-17 14:21:12 +02:00
parser.py feat(tg-fitness-bot): multi-set format, delete, export, SQL stats 2026-04-07 22:46:10 +02:00
README.md chore: prefer BOT_TOKEN env var over secrets file 2026-05-10 12:44:25 +02:00
requirements.txt feat(tg-fitness-bot): initial Telegram workout tracker bot 2026-03-24 15:50:05 +01:00
ROADMAP.md docs: add super subtle animations item to ROADMAP 2026-04-24 11:25:24 +02:00
server.py feat: profile/settings (rest timer toggle) 2026-04-19 15:36:06 +02:00
start.py chore: prefer BOT_TOKEN env var over secrets file 2026-05-10 12:44:25 +02:00

README.md

BigBiggerBiggestBot 💪

A Telegram bot for logging gym workouts, with an embedded Mini App.

Send workouts as plain text, forward them from Saved Messages, or tap through a structured log form inside Telegram. History, stats, notes, edit & delete, JSON/CSV export — all per-user, all in SQLite.

Format

Send messages like:

Bench press: 4x8x35
Shoulder press (3032): 8x25, 5x35, 6x40
Pull-ups: 3x10
  • SETSxREPSxWEIGHT — uniform sets
  • REPSxWEIGHT, REPSxWEIGHT, ... — per-set (weight/reps vary)
  • Omit weight for bodyweight exercises
  • (machine_id) is optional (gym equipment ID)
  • Blank line separates superset groups; consecutive lines form a superset
  • Both , and . work as decimal separators

Commands

  • /start — help & open Mini App
  • /history — recent workouts
  • /stats — summary (total workouts, sets, volume)
  • /delete <id> — soft-delete a workout
  • /export — download all data as JSON
  • /feedback <text> — send feedback to the bot author

Run locally

nix run

This launches:

  • API server (port 8080)
  • cloudflared tunnel for the Mini App
  • Telegram bot (polling)

Put your bot token (from @BotFather) in ~/.secrets/bigbiggerbiggestbot or a .env file:

BOT_TOKEN=123456:your-bot-token-here

nix develop drops you into a dev shell with Python + deps.

Tests

nix develop --command pytest tests/ -v

Deployment

Two environments share one host (sunken-ship):

  • Production — fitness-bot.service, working dir /home/danny/tg_fitness_bot, watches origin/main, served behind a stable URL via the VPS Caddy.
  • Shipyard staging — fitness-bot-shipyard.service, working dir /home/danny/tg_fitness_bot_shipyard, watches origin/staging, separate bot token, ephemeral cloudflared URL each restart.

Each has its own pull timer that fetches every ~15 minutes and restarts the service when its branch has new commits.

Workflow:

# 1. land changes on a working branch (or main locally)
git push origin <branch>:staging   # → shipyard auto-deploys, test there
git push origin <branch>:main      # → production auto-deploys

Each environment keeps its own workouts.db next to its code (gitignored), so testing on shipyard never touches production data.

Architecture

  • bot.py — Telegram command handlers, polling, message parsing
  • server.py — aiohttp REST API + static file server for the Mini App
  • db.py — SQLite data layer (workouts, supersets, exercises, feedback; soft delete)
  • parser.py — workout text → structured data
  • webapp/ — Mini App (HTML/CSS/vanilla JS, Telegram WebApp SDK)
  • start.py — orchestrator: starts server + tunnel + bot, wires up the Mini App URL
  • tests/ — pytest suite for parser + db

License

MIT — see LICENSE.