bicimadrid

Quick implementation of a project to find the closest bikes given an address in Madrid, Spain. Built to help IronHack data science bootcamp students get familiar with Python.

Environment

Python3.8

Prepping

For ease of use, leverage python virtual env Install: pip-sync requirements.txt

How to run in command line

Shortest distance to all

CSV

python run_pipeline.py --action closest-bike-all --output-format csv --organization-name

Print

python run_pipeline.py --action closest-bike-all --output-format print

Get shortest distance to a specific location

Replace "Zapadores Ciudad del Arte" with your desired location

CSV

python run_pipeline.py --action closest-bike-location --output-format csv --organization-name "Zapadores Ciudad del Arte"

Print

python run_pipeline.py --action closest-bike-location --output-format print --organization-name "Zapadores Ciudad del Arte"

Get shortest distance to a location using fuzzy matching

We've implemented the option to search for a location using fuzzy matching (Token Sort Ratio) on its name. The score threshold has been set to 80, can be change as needed. Use the below example to see it at work

CSV

python run_pipeline.py --action closest-bike-location --output-format csv --organization-name "Monasterio de la encarnacion" --fuzzy

Print

python run_pipeline.py --action closest-bike-location --output-format print --organization-name "Monasterio de la encarnacion" --fuzzy

Optional TODOs:

• Cleanup/move modules to a package folder (optional)