rosaliawk/listing-analytics repository overview

I) To run locally
a. git clone https://github.com/rosaliawk/listing-analytics.git⁠
b. mkdir venv
c. cd venv
d. virtualevn venv
e. . venv/bin/activate
f. pip install Flask python numpy pandas

1) To input listings from csvs
python input-listings.py [csv1, csv2, cvs3...]

This will return a json containing new listings found in the csvs

2) To get common stats
curl -X POST -H "Content-Type: application/json" --data '{"beds":2, "city":"San Francisco", "state":"CA"}' http://127.0.0.1:5000/dataset/common_stats/⁠

This is will return a json containing mean, std, min, max, and mode

II) To run Docker image
a. pull rosaliawk/listing-analytics
b. mkdir data
c. cd data
d. cp [location of csv] .
e. cd..

1) To input new listings from csvs
a. docker run -v [absolute path of csv location]:/data rosaliawk/listing-analytics python /src/input_listings.py data/listings1.csv
e.g. docker run -v /Users/Rosie/input_listings/data:/data --name listing-analytics rosaliawk/listing-analytics python /src/input_listings.py data/listings1.csv

This will return a json containing new listings found in the csvs

2) To get common stats
a. docker run -p 80:5000 -v [absolute path of current directory/data]:/data --name listing-analytics rosaliawk/listing-analytics python /src/input_listings.py
e.g. docker run -p 80:5000 -v /Users/Rosie/input_listings/data:/data --name listing-analytics rosaliawk/listing-analytics python /src/input_listings.py

b. curl -X POST -H 'Content-Type: application/json' --data '{"city":"San Francisco", "beds":2, "state":"CA"}' http://[mac IP found on Docker kitematic]/dataset/common_stats/
e.g. curl -X POST -H 'Content-Type: application/json' -ty":"San Francisco", "beds":2, "state":"CA"}' http://192.168.99.100/dataset/common_stats/⁠

This will return a json containing mean, std, min, max and median