City Score

City Score is a command-line application for scoring cities based on your personal preferences. Here's an example:

Technologies

• Python 3

Features

• Ranks all 29,880 cities and towns in the United States
• Includes multiple built-in data providers
• Designed to allow users to easily add and remix data
• Outputs prettified to the console or to CSV, HTML, JSON, JSONL

Design

City Score uses a three-step process:

1. Qualification: criteria identify cities that meet your minimum standard.
2. Scoring: scorers score facets of your choosing at various weights.
3. Generation: dimensions appear in the final output.

Quick start

1. Download City Score from PyPI:

   $ python3 -m pip install city_score

2. Create a script (myscore.py) like this:

   from city_score import run
   from city_score.sources.core import *
   from city_score.sources.peopleforbikes import *
   from city_score.sources.zillow import *
   
   sources = (
       PeopleForBikes,
       Zillow,
   )
   
   criteria = (
       minimum_bike_score(25),
       minimum_population(60000),
       maximum_median_home_price(1000000),
       prohibited_states(('TX', 'FL', 'CO', )),
   )
   
   scorers = (
       median_home_price_scorer(lower=350000, upper=800000),
       bike_score_scorer(lower=40, upper=80, weight=2),
   )
   
   dimensions = (
       population,
       median_home_price,
       median_rent,
       bike_score,
   )
   
   run(sources, criteria, scorers, dimensions)

3. Run your script:

   $ python3 myscore.py --sort=score --scale-scores

Data sources

• 🚲 PeopleForBikes provides a score for biking infrastructure.
• 🏂 Snowpak provides the name and location of most ski resorts.
• 🏃🏻 TrailLink provides the number of nearby trail miles.
• 🍕 Yelp provides data on many points of interest, including businesses.
• 🏡 Zillow provides estimates for home and rent prices.

License

MIT License