Where to eat? Settling the biggest debate ever
Pun intended
TLDR: Restaurant week ranked by Foursquare
The Battle of Cuisines
Finding a place to eat with friends is pretty hard. It’s up there with what music to listen to, what tv shows to watch and what exactly to instagram. You would think, given the number of times we’ve decided on food, the n+1th time would be pretty easy. Its not. After spending countless hours on group texts deciding where to eat especially during restaurant week, I decided to take matters into my own hands.

Foursquare
Somehow this tiny green number wields a great deal of power in group texts.
The decision making funnel usually goes like this:
Cuisine > Location > Green No.
Somtimes the funnel will be upset by a veto that restarts the process. But you get the idea.
Restaurant Week (RW)
What’s not to love about restaurant week?! Though in all fairness its closer to a month than a week. I guess restaurant month doesn’t convey the same sense of urgency to eat as restaurant week does. While RW offers delicious food at amazing prices, it adds a great deal of volatility to group texts.
Code for Food?
After exchanging 100+ texts on where to eat on the last day of restaurant week, I decided to script this decision-making process. Well at least reduce the back & forth spent on the tiny green number.
Here’s how:
- Goto the NYC Restaurant week’s website.

2. Scroll down to get the entire page loaded! (Props for pagination)

3. Inspect the page and type this in the console. PS: A rule of thumb in scraping is to find a common element/tag in the DOM.

4. Grab the string and format it into a file so that each restaurant is on a new line. Just like this! (Sorry no hacks here, for now…)

5. Now get a Oauth Token from Foursquare to access their API!

6. Grab a copy of my program here and paste in your Token. Run it by typing — python feedMe.py

7. Voila! You now hold the key 🔑 to settle all group text debates!

My Dinner Plans
So where am I going for dinner tonight? Well that will be decided in endless stream of group texts during the day… 😋
Thanks for reading! Feel free to share/comment/discuss the article or even better the code! PS: Next up, I’m gonna explore the frequency of words used in group texts and check out Yelp + OpenTable’s API. Imagine a world where you can get personalized food recommendations/reservations based on your texts!