A Slack integrated Python app to analyze Facebook pages
TopBook is a simple Python Bottle application which can be called from an Outgoing Slack Webhook. It allows you to ask for the most liked or commented posts for a Facebook page or collection of Facebook pages.
TopBook lets you quickly determine what the most popular content is on a Facebook page or group of Facebook pages. You can get a list of things it knows how to do with:
topbook help
You can get a list of pages it knows about with:
topbook pages
You can for page metrics with like, which returns the most liked article on the Vox Facebook page in the last 24 hours.
topbook likes vox
You can also create collections, say for all the local news sites in your area, pages for a specific company, or the sites that follow a specific niche, and ask all of them in one go.
topbook comments VoxMedia
The main query has a whole set of options.
top X likes/comments/shares page/page1, page2, .../page_group in last X days
(top) X - return the top X results (default: 1)
relative - rank results as percentage compared to page average (optional)
likes/comments/shares - what metric the results are sorted on
(for) page/pages1, page2, .../page_group
- specific FB page, manual list of FB pages, or a page group from the config
(in the last) X days - return results from the last X days (default: 1)
Example complex query: top 3 relative likes for vox, sbnation, eater in the last 2 days
TopBook requires two configuration tokens and a list of pages to monitor. First, you need a Slack Token from your team's Slack Integrations page. Second, you need a Facebook API Token, which you get by creating a new Facebook App and then requesting it in the Graph API Explorer. Here are some instructions for getting a Facebook Token, specifically getting a non-expiring facebook token. Then, optionally, add some pages and page collections to the config.json file. The syntax is "nickname": "facebook_page_name", or "nickname": ["List","of","Facebook","page","names"]. Name this file config.json, and drop it in the same directory as run.py. You can also add multiple accounts to the json file and have different Facebook and Slack credentials for each.
Install the dependencies listed in the requirements.txt file, possibly in a python virtualenv.
Start the bottle server with ./run.py. This will by default create a server on port 8000 on your machine. Then you need to figure out a way to get requests from Slack to that port, or just use the included slack-test.py client to post requests to bottle and verify the output.
./slack-test.py "help"
The app is ready for easy Heroku deployment, and uses gevent to serve multiple requests at once. To deploy into Heroku you need to set SLACK_TOKEN and FB_TOKEN in your Heroku config. You can also commit a config.json file with page groups setup, but don't commit tokens.
heroku config:set FB_TOKEN=abcdefghijklmnopqrstuvwxyz
heroku config:set SLACK_TOKEN=1234567890
You can test your Heroku installation with the slack-test.py script.
export BOT_HOST=https://myherokuapp.heroku.com/slack
export SLACK_TOKEN=1234567890
./slack-test.py "help"