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/
  

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 defaulting to results[0]
• Diary:

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

• Delete entry:

  sparky food delete <uuid>

• Remove from library:

  sparky food remove <external_id>

  — purge a wrongly imported product from local library

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
• 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 food remove <external_id>   # external_id from search results

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 match bypasses

  --pick

  entirely
• 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

  )