# markwk/qs_ledger

Quantified Self Personal Data Aggregator and Data Analysis

Repository: https://github.com/markwk/qs_ledger
Canonical: https://ross.abutalabs.com/products/qs_ledger
Language: Jupyter Notebook
License: MIT
License Family: permissive
Topics: quantified-self, personal-data, data-analysis, data-visualization, apple-health, lastfm, fitbit, rescuetime, todoist, toggl, self-tracking, strava, instapaper, pocket, habitica, kindle, kindle-highlights
Last push: 2022-08-18T07:50:56+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3024, "days_push": 1476, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1073, forks 197 (observed 2026-08-28T04:03:28.887226+00:00)

## What it is
A personal data aggregator and analysis toolkit for quantified self enthusiasts, written in Python and distributed as Jupyter Notebooks. It downloads data from tracking services like Apple Health, Fitbit, Last.fm, RescueTime, and Todoist, then provides analysis and visualization notebooks for each.

## Use cases
- download my fitbit and apple health data locally
- analyze my kindle highlights and reading stats
- build a personal data dashboard from rescue time and toggl
- visualize my sleep and heart rate trends
- aggregate data from multiple self-tracking services
- analyze my goodreads reading history
- export and analyze my lastfm listening data

## When to choose
- you want to own and analyze your personal tracking data locally
- you're comfortable with Python and Jupyter notebooks
- you use several of the supported services like Fitbit, RescueTime, or Kindle
- you want a starting point for personal data science and visualization

## When to avoid
- you need a polished turnkey dashboard app with no coding
- you need a service not on the integration list
- you want actively developed features - the project is in maintenance mode
- you need a web or mobile interface

## Facets
- artifact type: application
- maturity: maintenance
- function: data-science, data-visualization, etl, analytics, charts
- domain: data-science, data-visualization, developer-tools, healthcare, self-hosted
- platform: python, cross-platform, cli
- tags: quantified-self, personal-data, self-tracking, jupyter-notebooks, wearables, life-logging, data-aggregation

## Member repositories
- markwk/qs_ledger (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:28.887226+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T06:53:37.714462+00:00, confidence not recorded.
  - readme: https://github.com/markwk/qs_ledger (fetched 2026-08-28T04:03:28.887226+00:00, sha 2510da059ba5)
- Data as of 2026-08-30T08:39:29.467469+00:00.