wwlog

wwlog unlocks the WeightWatchers data you enter in the mobile app.

It provides a CLI for exporting text, Markdown, JSON, and CSV so you can analyze your data with your own tools across a selected date range.

It also includes a TUI for browsing daily logs, comparing nutrition, and viewing insights across a selected date range.

Features

• Log tab — day-by-day food log with a points bar, meal breakdown, and per-entry kcal; filter by date and sort entries by points or calories
• Nutrition tab — nutrient bars vs. recommended daily values, per-day averages, and asciigraph trend charts for calories, protein, carbs, and fat across the selected range
• Insights tab — a calendar heatmap of daily points budget, range summary, points by meal, macro distribution, top foods by points, and a zero-point food log
• Pipeline mode — --json, --report, and --export flags for scripting and file output
• No DevTools required — one --login step stores credentials in your system keychain

Installation

Homebrew (macOS):

brew install ali5ter/tap/wwlog

Binary (macOS and Linux, no Go required):

# macOS Apple Silicon
curl -sL https://github.com/ali5ter/wwlog/releases/latest/download/wwlog_darwin_arm64.tar.gz | tar -xz
sudo mv wwlog /usr/local/bin/

# macOS Intel
curl -sL https://github.com/ali5ter/wwlog/releases/latest/download/wwlog_darwin_amd64.tar.gz | tar -xz
sudo mv wwlog /usr/local/bin/

# Linux arm64
curl -sL https://github.com/ali5ter/wwlog/releases/latest/download/wwlog_linux_arm64.tar.gz | tar -xz
sudo mv wwlog /usr/local/bin/

# Linux amd64
curl -sL https://github.com/ali5ter/wwlog/releases/latest/download/wwlog_linux_amd64.tar.gz | tar -xz
sudo mv wwlog /usr/local/bin/

Go:

go install github.com/ali5ter/wwlog@latest

First-time setup

Authenticate once — credentials are stored securely in your system keychain:

wwlog --login

Usage

# Open the TUI (defaults to the last 7 days)
wwlog

# Browse a specific date range
wwlog --start 2026-04-20 --end 2026-04-26

# Print insights report to stdout (no TUI)
wwlog --start 2026-04-20 --end 2026-04-26 --report

# Output log as JSON to stdout
wwlog --start 2026-04-20 --end 2026-04-26 --json

# Export to a file (JSON | CSV | Markdown | report)
wwlog --start 2026-04-20 --end 2026-04-26 --export markdown
wwlog --start 2026-04-20 --end 2026-04-26 --export json --output ~/Downloads/

# Clear stored credentials
wwlog --logout

Data window

The WW my-day endpoint enforces a hard ~90-day backwards retention window — any date more than 89 days before today returns HTTP 400, regardless of how long you've held your WW account. This is a server-side policy, not a wwlog limitation.

If --start is older than the window, wwlog clamps it forward and prints a one-line notice:

$ wwlog --start 2024-01-01 --end 2026-05-05 --report
note: --start clamped to 2026-02-05 (WW retains ~90 days)

If --end is also older than the window, wwlog errors out before making any API calls. There's no workaround — long-running history exports aren't possible with this API. Plan ahead if you want to keep more than ~3 months of records: pull --export json regularly and archive the files.

JSON pipeline examples

The --json flag outputs a JSON array of day logs. Each element contains the date, meals (morning / midday / evening / anytime arrays of food entries), and a points summary. Pipe it to jq for quick ad-hoc analysis.

Daily points summary:

wwlog --start 2026-04-20 --end 2026-04-26 --json \
  | jq '.[] | {date: .Date, used: .Points.DailyUsed, target: .Points.DailyTarget}'

All food names and points across the range (flat list):

wwlog --start 2026-04-20 --end 2026-04-26 --json \
  | jq '[.[].Meals | to_entries[].value[]] | map({name: .name, pts: .pointsPrecise})'

Days where you went over budget:

wwlog --start 2026-04-20 --end 2026-04-26 --json \
  | jq '.[] | select(.Points.DailyUsed > .Points.DailyTarget)
        | {date: .Date, over: (.Points.DailyUsed - .Points.DailyTarget)}'

Top foods by points for the week:

wwlog --start 2026-04-20 --end 2026-04-26 --json \
  | jq '[.[].Meals | to_entries[].value[]]
        | group_by(.name)
        | map({name: .[0].name, total_pts: (map(.pointsPrecise) | add)})
        | sort_by(-.total_pts) | .[0:10]'

Breakfast items sorted by calories:

wwlog --start 2026-04-20 --end 2026-04-26 --json \
  | jq '[.[].Meals.morning[]
        | {name: .name,
           kcal: (.defaultPortion.nutrition.calories * (.portionSize / .defaultPortion.size))}]
        | sort_by(-.kcal)'

The calorie calculation above mirrors what the app does internally — scale defaultPortion.nutrition.calories by portionSize / defaultPortion.size. Entries where WW omits calories (some protein/meat foods) will show 0; use --report for accurate totals.

Average macro distribution across the range (% of calories from protein, carbs, and fat):

wwlog --start 2026-04-20 --end 2026-04-26 --json \
  | jq '
      [.[].Meals | to_entries[].value[]]
      | map(
          (if .defaultPortion.size > 0 then .portionSize / .defaultPortion.size else 1 end) as $scale
          | { p: (.defaultPortion.nutrition.protein * $scale),
              c: (.defaultPortion.nutrition.carbs   * $scale),
              f: (.defaultPortion.nutrition.fat     * $scale) }
        )
      | (map(.p) | add) * 4 as $pkcal
      | (map(.c) | add) * 4 as $ckcal
      | (map(.f) | add) * 9 as $fkcal
      | ($pkcal + $ckcal + $fkcal) as $total
      | { protein: "\($pkcal / $total * 100 | round)%",
          carbs:   "\($ckcal / $total * 100 | round)%",
          fat:     "\($fkcal / $total * 100 | round)%" }
    '

Macros are scaled to the tracked portion size, then converted to kcal using Atwater factors (protein and carbs ×4, fat ×9) to match what the Insights tab shows.

Key bindings

Key	Action
↑ / ↓ or k / j	Navigate dates
⇧↑ / ⇧↓	Scroll detail pane
/	Filter dates (Log and Nutrition tabs)
s	Cycle sort order (logged → by points → by kcal)
r	Change date range
e	Export (opens format picker)
tab / ⇧tab	Switch tabs
q or ctrl+c	Quit

Options

Flag	Default	Description
-s, --start	7 days ago	Start date (YYYY-MM-DD)
-e, --end	today	End date (YYYY-MM-DD)
--json	—	Output log as JSON to stdout (no TUI)
-r, --report	—	Output insights report as text to stdout (no TUI)
--export	—	Export to file: json, csv, markdown, or report
-o, --output	reports/	Output file or directory for --export
--no-tty	—	Force pipeline mode even in a terminal
--login	—	Authenticate and store credentials
--logout	—	Clear stored credentials
-l, --tld	com	WW top-level domain (com, co.uk, etc.)

Configuration

Optional config at ~/.config/wwlog/config.toml:

tld       = "com"   # WW top-level domain

Credits

wwlog was inspired by wwtracked by Joshua Wright.