sparky

Use

sparky

to interact with a self-hosted SparkyFitness server — log food, exercise, weight, steps, and mood.

Install

• Homebrew (macOS/Linux):

  brew tap aronjanosch/tap && brew install sparky-cli

• Build from source (requires Go 1.21+):

  git clone https://github.com/aronjanosch/sparky-cli
  cd sparky-cli
  go build -o sparky .
  sudo mv sparky /usr/local/bin/
  

• Pre-built binaries: https://github.com/aronjanosch/sparky-cli/releases (Linux, macOS, Windows — amd64/arm64)

Setup (once)

• sparky config set-url <url>

  — e.g.

  sparky config set-url https://sparky.example.com

• sparky config set-key <key>

• sparky config show

• sparky ping

  — verify connection

Food

• Search:

  sparky food search "chicken breast" [-l 10]

  — local DB first, falls back to Open Food Facts; shows Brand column
• Search by barcode:

  sparky food search --barcode 4061458284547

  — exact product lookup, no ambiguity
• Log by name:

  sparky food log "chicken breast" -m lunch -q 150 -u g [-d YYYY-MM-DD]

• Log by barcode:

  sparky food log --barcode 4061458284547 -m lunch -q 113 -u g

  — most reliable, no brand guessing
• Log by ID:

  sparky food log --id <uuid> -m lunch -q 150 -u g

  — skips search, unambiguous
• Pick result:

  sparky food log "Hähnchenbrust" --pick 2

  — select Nth search result instead of prompting
• Create custom:

  sparky food create "My Meal" --calories 450 --protein 28 --carbs 42 --fat 16

  — adds a custom food to your library; defaults to 100g serving; optional: --fiber, --sugar, --sodium, --saturated-fat, --brand, --serving-size, --serving-unit
• Diary:

  sparky food diary [-d YYYY-MM-DD]

• Delete entry:

  sparky food delete <uuid>

  — removes a diary entry
• Remove from library:

  sparky food remove <uuid>

  — purge a food from your local library (get UUID via

  sparky -j food search

  )

Exercise

• Search:

  sparky exercise search "bench press" [-l 10]

  — local DB first, falls back to Free Exercise DB
• Search external only:

  sparky exercise search --external "pushup"

  — bypasses local cache
• Log by name:

  sparky exercise log "Pushups" [--duration 45] [--calories 400] [-d YYYY-MM-DD]

• Log by ID:

  sparky exercise log --id <uuid> --set 10x80@8 --set 10x80@9

  — skips search, unambiguous
• Sets format:

  REPS[xWEIGHT][@RPE]

  — e.g.

  10x80@8

  = 10 reps, 80 kg, RPE 8;

  10x80

  or

  10@8

  also valid
• Notes:

  sparky exercise log "Pushups" --notes "felt strong"

• Diary:

  sparky exercise diary [-d YYYY-MM-DD]

• Delete:

  sparky exercise delete <uuid>

Check-ins

• Weight:

  sparky checkin weight 75.5 [-u kg|lbs] [-d YYYY-MM-DD]

• Steps:

  sparky checkin steps 9500 [-d YYYY-MM-DD]

• Mood:

  sparky checkin mood 8 [-n "notes"] [-d YYYY-MM-DD]

• Diary:

  sparky checkin diary [-d YYYY-MM-DD]

  — shows biometrics + mood together

Summary & trends

• sparky summary [-s YYYY-MM-DD] [-e YYYY-MM-DD]

  — nutrition/exercise/wellbeing totals (default: last 7 days)

• sparky trends [-n 30]

  — day-by-day nutrition table

Agentic workflow (always prefer --id to avoid ambiguity)

Exercise — search first, then log by ID:

# 1. Find candidates; use --external to bypass local cache if needed
sparky -j exercise search --external "pushup"
# Each result has is_local: true/false
#   is_local: true  → id is a UUID → use --id directly
#   is_local: false → id is a source string → log by exact name to import first,
#                     then search again to get the UUID

# 2a. Local exercise
sparky -j exercise log --id <uuid> --set 3x10@8

# 2b. External exercise (import on first log, then switch to --id)
sparky -j exercise log "Pushups" --set 3x10
sparky -j exercise search "Pushups"        # now is_local: true
sparky -j exercise log --id <uuid> --set 3x10

Food — preferred agentic workflow:

# Option A: barcode (most reliable)
sparky food log --barcode 4061458284547 -q 113 -u g -m lunch

# Option B: search → inspect brand+macros → log by --id
sparky -j food search "Hähnchenbrust"
# check brand + calories in results; pick the right one
sparky food log --id <uuid> -q 400 -u g -m dinner

# Option C: search with --pick N (when brand column shows the right one)
sparky food log "Hähnchenbrust" --pick 3 -q 400 -u g -m dinner

# Remove a bad import from local library
sparky -j food search "bad product"   # get the food's id (UUID)
sparky food remove <uuid>

Custom food (when you have nutrition facts and it's not in the DB):

# Ingredients/beverages — nutrition per 100g/ml (default)
sparky -j food create "Craft Beer" --calories 43 --protein 0.5 --carbs 3.6 --fat 0 --serving-unit ml
sparky -j food log --id <uuid> -q 330 -m dinner

# Meals (Cookidoo, Chefkoch, etc.) — nutrition per serving, specify explicitly
sparky -j food create "Lasagna" --calories 450 --protein 28 --carbs 42 --fat 16 --serving-size 1 --serving-unit serving
sparky -j food log --id <uuid> -q 1 -m dinner

Notes

• -j

  /

  --json

  is a root-level flag:

  sparky -j food diary

  , not

  sparky food diary -j

• Always verify brand in search results before logging — Open Food Facts has many products with identical names

• --barcode

  is the most reliable option when the product has a scannable barcode

• --pick N

  selects the Nth result (1-based); exact local name match bypasses

  --pick

  entirely
• In JSON mode with ambiguous results, the CLI always picks

  results[0]

  — use

  --id

  in scripts to be safe
• Both search commands fall back to online providers automatically; matches are added to your library on first log
• Weight is stored in kg; lbs are auto-converted (

  166 lbs → 75.30 kg

  )
• Full UUIDs for delete:

  sparky -j food diary | jq '.[0].id'

• Meal options:

  breakfast

  ,

  lunch

  ,

  dinner

  ,

  snacks

  (default:

  snacks

  )