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Bridgy Bridgy Circle CI Coverage Status

Bridgy connects your web site to social media. Likes, retweets, mentions, cross-posting, and more. See the user docs for more details, or the developer docs if you want to contribute.

Bridgy is part of the IndieWeb ecosystem. In IndieWeb terminology, Bridgy offers backfeed, POSSE, and webmention support as a service.

License: This project is placed in the public domain.


You'll need the Google Cloud SDK (aka gcloud) with the gcloud-appengine-python, gcloud-appengine-python-extras and google-cloud-sdk-datastore-emulator components. Then, create a Python 3 virtualenv and install the dependencies with:

python3 -m venv local
source local/bin/activate
pip install -r requirements.txt
# needed to serve static file handlers locally
ln -s local/lib/python3*/site-packages/oauth_dropins/static oauth_dropins_static
gcloud config set project brid-gy

Now, you can fire up the gcloud emulator and run the tests:

gcloud beta emulators datastore start --no-store-on-disk --consistency=1.0 --host-port=localhost:8089 --quiet
python3 -m unittest discover -s tests -t .
kill %1

If you send a pull request, please include or update a test for your new code!

To test a poll or propagate task, find the relevant Would add task line in the logs, eg:

INFO:root:Would add task: projects//locations/us-central1/queues/poll {'app_engine_http_request': {'http_method': 'POST', 'relative_uri': '/_ah/queue/poll', 'app_engine_routing': {'service': 'background'}, 'body': b'source_key=agNhcHByFgsSB1R3aXR0ZXIiCXNjaG5hcmZlZAw&last_polled=1970-01-01-00-00-00', 'headers': {'Content-Type': 'application/x-www-form-urlencoded'}}, 'schedule_time': seconds: 1591176072

...pull out the relative_uri and body, and then put them together in a curl command against the background service, which usually runs on http://localhost:8081/, eg:

curl -d 'source_key=agNhcHByFgsSB1R3aXR0ZXIiCXNjaG5hcmZlZAw&last_polled=1970-01-01-00-00-00' \

To run the app locally, use flask run:

gcloud beta emulators datastore start --no-store-on-disk --consistency=1.0 --host-port=localhost:8089 --quiet
GAE_ENV=localdev FLASK_ENV=development flask run -p 8080

Open localhost:8080 and you should see the Bridgy home page!

If you hit an error during setup, check out the oauth-dropins Troubleshooting/FAQ section. For searchability, here are a handful of error messages that have solutions there:

bash: ./bin/easy_install: ...bad interpreter: No such file or directory

ImportError: cannot import name certs

ImportError: cannot import name tweepy

File ".../site-packages/tweepy/", line 68, in _get_request_token
  raise TweepError(e)
TweepError: must be _socket.socket, not socket

error: option --home not recognized

There's a good chance you'll need to make changes to granary or oauth-dropins at the same time as bridgy. To do that, clone their repos elsewhere, then install them in "source" mode with:

pip uninstall -y oauth-dropins
pip install -e <path-to-oauth-dropins-repo>
ln -sf <path-to-oauth-dropins-repo>/oauth_dropins/static oauth_dropins_static

pip uninstall -y granary
pip install -e <path to granary>

To deploy to App Engine, run scripts/

remote_api_shell is a useful interactive Python shell that can interact with the production app's datastore, memcache, etc. To use it, create a service account and download its JSON credentials, put it somewhere safe, and put its path in your GOOGLE_APPLICATION_CREDENTIALS environment variable.

Deploying to your own app-engine project can be useful for testing, but is not recommended for production. To deploy to your own app-engine project, create a project on gcloud console and activate the Tasks API. Initialize the project on the command line using gcloud config set project <project-name> followed by gcloud app create. You will need to update TASKS_LOCATION in to match your project's location. Finally, you will need to add your "background" domain (eg to OTHER_DOMAINS in and set host_url in to your base app url (eg Finally, deploy (after testing) with gcloud -q beta app deploy --no-cache --project YOUR-APP-NAME *.yaml

To work on the browser extension:

cd browser-extension
npm install
npm run test

You need to be logged into Instagram in your browser. The extension doesn't have a UI, but you can see what it's doing on your Bridgy user page, eg[username]. Note that it doesn't work with Firefox's Facebook Container tabs add-on. If you have that enabled, you'll need to disable it to use Bridgy's browser extension.

Extension logs in the JavaScript console

If you're working on the browser extension, or you're sending in a bug report for it,, its JavaScript console logs are invaluable for debugging. Here's how to get them in Firefox:

Thanks for trying! And for offering to send logs, those would definitely be helpful. Here's how to get them:

  1. Open about:debugging
  2. Click This Firefox on the left
  3. Scroll down to Bridgy
  4. Click Inspect
  5. Click on the Console tab

Here's how to send them in with a bug report:

  1. Right click, Export Visible Messages To, File, save the file.
  2. Email the file to bridgy @ Do not post or attach it to a GitHub issue, or anywhere else public, because it contains sensitive tokens and cookies.

Adding a new silo

So you want to add a new silo? Maybe MySpace, or Friendster, or even Tinder? Great! Here are the steps to do it. It looks like a lot, but it's not that bad, honest.

  1. Find the silo's API docs and check that it can do what Bridgy needs. At minimum, it should be able to get a user's posts and their comments, likes, and reposts, depending on which of those the silo supports. If you want publish support, it should also be able to create posts, comments, likes, reposts, and/or RSVPs.
  2. Fork and clone this repo.
  3. Create an app (aka client) in the silo's developer console, grab your app's id (aka key) and secret, put them into new local files in the repo root dir, following this pattern. You'll eventually want to send them to @snarfed too, but no hurry.
  4. Add the silo to oauth-dropins if it's not already there:
    1. Add a new .py file for your silo with an auth model and handler classes. Follow the existing examples.
    2. Add a 100 pixel tall button image named [NAME]_2x.png, where [NAME] is your start handler class's NAME constant, eg 'twitter'.
    3. Add it to the app front page and the README.
  5. Add the silo to granary:
    1. Add a new .py file for your silo. Follow the existing examples. At minimum, you'll need to implement get_activities_response and convert your silo's API data to ActivityStreams.
    2. Add a new unit test file and write some tests!
    3. Add it to (specifically Handler.get),, index.html, and the README.
  6. Add the silo to Bridgy:
    1. Add a new .py file for your silo with a model class. Follow the existing examples.
    2. Add it to and (just import the module).
    3. Add a 48x48 PNG icon to static/.
    4. Add a new [SILO]_user.html file in templates/ and add the silo to index.html. Follow the existing examples.
    5. Add the silo to about.html and this README.
    6. If users' profile picture URLs can change, add a cron job that updates them to
  7. Optionally add publish support:
    1. Implement create and preview_create for the silo in granary.
    2. Add the silo to import its module, add it to SOURCES, and update this error message.

Good luck, and happy hacking!


App Engine's built in dashboard and log browser are pretty good for interactive monitoring and debugging.

For alerting, we've set up Google Cloud Monitoring (nΓ©e Stackdriver). Background in issue 377. It sends alerts by email and SMS when HTTP 4xx responses average >.1qps or 5xx >.05qps, latency averages >15s, or instance count averages >5 over the last 15m window.


I occasionally generate stats and graphs of usage and growth from the BigQuery dataset (#715). Here's how.

  1. Export the full datastore to Google Cloud Storage. Include all entities except *Auth and other internal details. Check to see if any new kinds have been added since the last time this command was run.

    gcloud datastore export --async gs:// --kinds Activity, Blogger,BlogPost,BlogWebmention,Facebook,FacebookPage,Flickr,GitHub,GooglePlusPage,Instagram,Mastodon,Medium,Meetup,Publish,PublishedPage,Reddit,Response,SyndicatedPost,Tumblr,Twitter,WordPress

    Note that --kinds is required. From the export docs, Data exported without specifying an entity filter cannot be loaded into BigQuery.

  2. Wait for it to be done with gcloud datastore operations list | grep done.

  3. Import it into BigQuery:

    for kind in Activity BlogPost BlogWebmention Publish Response SyndicatedPost; do
      bq load --replace --nosync --source_format=DATASTORE_BACKUP datastore.$kind gs://$kind/all_namespaces_kind_$kind.export_metadata
    for kind in Blogger Facebook FacebookPage Flickr GitHub GooglePlusPage Instagram Mastodon Medium Meetup Reddit Tumblr Twitter WordPress; do
      bq load --replace --nosync --source_format=DATASTORE_BACKUP sources.$kind gs://$kind/all_namespaces_kind_$kind.export_metadata
  4. Check the jobs with bq ls -j, then wait for them with bq wait.

  5. Run the full stats BigQuery query. Download the results as CSV.

  6. Open the stats spreadsheet. Import the CSV, replacing the data sheet.

  7. Check out the graphs! Save full size images with OS or browser screenshots, thumbnails with the Download Chart button. Then post them!

Delete old responses

Bridgy only keeps responses that are over a year or two old. I garbage collect (ie delete) older responses manually, generally just once a year when I generate statistics (above).

I use the Datastore Bulk Delete Dataflow template with this GQL query:

SELECT * FROM `Response` WHERE updated < DATETIME('2020-11-01T00:00:00Z')

I either use the interactive web UI or this command line:

gcloud dataflow jobs run 'Delete Response datastore entities over 1y old'
  --gcs-location gs://dataflow-templates-us-central1/latest/Datastore_to_Datastore_Delete
  --region us-central1
  --staging-location gs://
  --parameters datastoreReadGqlQuery="SELECT * FROM `Response` WHERE updated < DATETIME('2020-11-01T00:00:00Z'),datastoreReadProjectId=brid-gy,datastoreDeleteProjectId=brid-gy"


The datastore is exported to BigQuery (#715) twice a year.

We use this command to set a Cloud Storage lifecycle policy on our buckets to prune older backups and other files:

gsutil lifecycle set cloud_storage_lifecycle.json gs://
gsutil lifecycle set cloud_storage_lifecycle.json gs://brid-gy_cloudbuild
gsutil lifecycle set cloud_storage_lifecycle.json gs://
gsutil lifecycle set cloud_storage_lifecycle.json gs://

See how much space we're currently using in this dashboard. Run this to download a single complete backup:

gsutil -m cp -r gs://\* .


πŸ“£ Connects your web site to social media. Likes, retweets, mentions, cross-posting, and more...