https://github.com/bcongdon/feedly-to-sqlite
Export your Feedly data to SQLite
https://github.com/bcongdon/feedly-to-sqlite
datasette datasette-io dogsheep feedly
Last synced: 10 months ago
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Export your Feedly data to SQLite
- Host: GitHub
- URL: https://github.com/bcongdon/feedly-to-sqlite
- Owner: bcongdon
- License: mit
- Created: 2020-05-16T20:28:56.000Z (over 5 years ago)
- Default Branch: master
- Last Pushed: 2020-05-16T20:30:55.000Z (over 5 years ago)
- Last Synced: 2025-03-08T23:35:59.332Z (10 months ago)
- Topics: datasette, datasette-io, dogsheep, feedly
- Language: Python
- Size: 5.86 KB
- Stars: 1
- Watchers: 2
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# feedly-to-sqlite
[](https://pypi.org/project/feedly-to-sqlite/)
[](https://github.com/bcongdon/feedly-to-sqlite/blob/master/LICENSE)
Save data from [feedly](https://www.feedly.com/) to a SQLite database. Supports
saving subscription and collection data.
## How to install
$ pip install feedly-to-sqlite
## Authentication
Obtain a personal developer token [here](https://feedly.com/v3/auth/dev). Run
the following command and enter your Feedly developer auth token :
$ feedly-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 feedly data:
$ feedly-to-sqlite subscriptions feedly.db
More detailed help can be found by running the command with `--help`
$ feedly-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.