kopia lustrzana https://github.com/snarfed/bridgy-fed
129 wiersze
4.5 KiB
ReStructuredText
129 wiersze
4.5 KiB
ReStructuredText
Bridgy Fed developer documentation
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----------------------------------
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Bridgy Fed connects your web site to
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`Mastodon <https://joinmastodon.org>`__ and the
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`fediverse <https://en.wikipedia.org/wiki/Fediverse>`__ via
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`ActivityPub <https://activitypub.rocks/>`__,
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`webmentions <https://webmention.net/>`__, and
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`microformats2 <https://microformats.org/wiki/microformats2>`__. Your
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site gets its own fediverse profile, posts and avatar and header and
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all. Bridgy Fed translates likes, reposts, mentions, follows, and more
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back and forth. `See the user docs <https://fed.brid.gy/docs>`__ for
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more details.
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https://fed.brid.gy/
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Also see the
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`original <https://snarfed.org/indieweb-activitypub-bridge>`__
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`design <https://snarfed.org/indieweb-ostatus-bridge>`__ blog posts.
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License: This project is placed in the public domain.
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Development
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-----------
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Pull requests are welcome! Feel free to `ping me in
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#indieweb-dev <https://indieweb.org/discuss>`__ with any questions.
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First, fork and clone this repo. Then, install the `Google Cloud
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SDK <https://cloud.google.com/sdk/>`__ and run
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``gcloud components install beta cloud-datastore-emulator`` to install
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the `datastore
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emulator <https://cloud.google.com/datastore/docs/tools/datastore-emulator>`__.
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Once you have them, set up your environment by running these commands in
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the repo root directory:
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.. code:: sh
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gcloud config set project bridgy-federated
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python3 -m venv local
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source local/bin/activate
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pip install -r requirements.txt
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Now, run the tests to check that everything is set up ok:
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.. code:: shell
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gcloud beta emulators datastore start --use-firestore-in-datastore-mode --no-store-on-disk --host-port=localhost:8089 --quiet < /dev/null >& /dev/null &
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python3 -m unittest discover
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Finally, run this in the repo root directory to start the web app
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locally:
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.. code:: shell
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GAE_ENV=localdev FLASK_ENV=development flask run -p 8080
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If you send a pull request, please include (or update) a test for the
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new functionality!
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If you hit an error during setup, check out the `oauth-dropins
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Troubleshooting/FAQ
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section <https://github.com/snarfed/oauth-dropins#troubleshootingfaq>`__.
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You may need to change `granary <https://github.com/snarfed/granary>`__,
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`oauth-dropins <https://github.com/snarfed/oauth-dropins>`__,
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`mf2util <https://github.com/kylewm/mf2util>`__, or other dependencies
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as well as as Bridgy Fed. To do that, clone their repo locally, then
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install them in “source” mode with e.g.:
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.. code:: sh
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pip uninstall -y granary
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pip install -e <path to granary>
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To deploy to the production instance on App Engine - if @snarfed has
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added you as an owner - run:
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.. code:: sh
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gcloud -q beta app deploy --no-cache --project bridgy-federated *.yaml
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Stats
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-----
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I occasionally generate stats and graphs of usage and growth via
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BigQuery, `like I do with
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Bridgy <https://bridgy.readthedocs.io/#stats>`__. Here’s how.
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1. `Export the full datastore to Google Cloud
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Storage. <https://cloud.google.com/datastore/docs/export-import-entities>`__
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Include all entities except ``MagicKey``. Check to see if any new
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kinds have been added since the last time this command was run.
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::
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gcloud datastore export --async gs://bridgy-federated.appspot.com/stats/ --kinds Follower,Response
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Note that ``--kinds`` is required. `From the export
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docs <https://cloud.google.com/datastore/docs/export-import-entities#limitations>`__:
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> *Data exported without specifying an entity filter cannot be loaded
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into BigQuery.*
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2. Wait for it to be done with
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``gcloud datastore operations list | grep done``.
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3. `Import it into
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BigQuery <https://cloud.google.com/bigquery/docs/loading-data-cloud-datastore#loading_cloud_datastore_export_service_data>`__:
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::
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for kind in Follower Response; do
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bq load --replace --nosync --source_format=DATASTORE_BACKUP datastore.$kind gs://bridgy-federated.appspot.com/stats/all_namespaces/kind_$kind/all_namespaces_kind_$kind.export_metadata
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done
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4. Check the jobs with ``bq ls -j``, then wait for them with
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``bq wait``.
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5. `Run the full stats BigQuery
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query. <https://console.cloud.google.com/bigquery?sq=664405099227:58879d2908824a21b737eee98fff2de8>`__
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Download the results as CSV.
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6. `Open the stats
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spreadsheet. <https://docs.google.com/spreadsheets/d/1OtOZ2Rb4EqAGEp9rHziWkyJD4BaRFb_971KjOqMKePA/edit>`__
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Import the CSV, replacing the *data* sheet.
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7. Check out the graphs! Save full size images with OS or browser
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screenshots, thumbnails with the *Download Chart* button.
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