https://github.com/bcongdon/beeminder-to-sqlite
Export your Beeminder data to SQLite
https://github.com/bcongdon/beeminder-to-sqlite
beeminder datasette datasette-io dogsheep
Last synced: 10 months ago
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Export your Beeminder data to SQLite
- Host: GitHub
- URL: https://github.com/bcongdon/beeminder-to-sqlite
- Owner: bcongdon
- License: mit
- Created: 2020-01-11T04:48:30.000Z (about 6 years ago)
- Default Branch: master
- Last Pushed: 2020-02-02T15:45:41.000Z (almost 6 years ago)
- Last Synced: 2025-03-11T14:56:55.908Z (10 months ago)
- Topics: beeminder, datasette, datasette-io, dogsheep
- Language: Python
- Homepage:
- Size: 6.84 KB
- Stars: 2
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# beeminder-to-sqlite
[](https://pypi.org/project/beeminder-to-sqlite/)
[](https://github.com/bcongdon/beeminder-to-sqlite/blob/master/LICENSE)
Save data from [Beeminder](https://www.beeminder.com/) to a SQLite database.
Supports saving goal data and data points.
## How to install
$ pip install beeminder-to-sqlite
## Authentication
Run the following command and enter your beeminder personal auth token:
$ beeminder-to-sqlite auth
This will create a file called `auth.json` in your current directory containing
the required value. To save the file at a different path or filename, use the
`--auth=myauth.json` option.
## Usage
After you've setup your authentication, you can use the following commend to
download and save your Beeminder data:
$ beeminder-to-sqlite goals beeminder.db
More detailed help can be found by running the command with `--help`
$ beeminder-to-sqlite --help
## Attribution
This package is heavily inspired by
[goodreads-to-sqlite](https://github.com/rixx/goodreads-to-sqlite/) by
[Tobias Kunze ](https://github.com/rixx) and
[github-to-sqlite](https://github.com/dogsheep/github-to-sqlite/) by
[Simon Willison](https://simonwillison.net/2019/Oct/7/dogsheep/).
This package was designed to fit nicely in the
[dogsheep](https://dogsheep.github.io/) /
[datasette](https://github.com/simonw/datasette) ecosystems.