Relocation RecSys

Goal of the project

We offer a service based on a location recommendation system for those who decide to move from their hometown.

Target audience

In addition to people who for some reason want to move to another place, the target audience of the project are also tourists, travelers and digital nomads.

Motivation

Sometimes it is difficult for people to choose one thing from several options. Even the question of what kind of coffee to drink in the morning causes difficulties for many. Needless to say, how difficult it is to choose a place to travel or to move for a long time. Moreover, if a trip or relocation is planned with the family, then the analysis of options and the choice of the only one become much more difficult. This is where our project appears, designed to help with the choice of a place for relocation, recommending cities according to their key parameters. Using our service, it will be much easier for the user to choose a suitable city for himself, taking into account his priorities.

Main idea

description of user experience

Data used

Numbeo data

Link - https://www.numbeo.com

Site numbeo.com provides crowd-sourced information on the key parameters of life in the cities of the world. For the project, parameters such as cost of living, cost of housing, quality of life, as well as data on crime, health, pollution and traffic were parsed. A more detailed description of the data and the methodology for collecting them can be found on the website. The method of parsing the received data is given in the notebook "numbeo_parser.ipynb".

WHO data

Link - https://www.who.int/data/gho/data/themes/air-pollution/who-air-quality-database#cms

The website of the World Health Organization provides a wide range of datasets related to the health of the population of the countries of the world. The project used a dataset of air quality in cities around the world. The remaining datasets provided general information about the countries of the world, which is not enough for the task.

Run the app in development mode

1. Pull and run postgres docker image.
2. Add environment variables for src/db/app/app.py and run it. The application needs following envs:

• DB_NAME is name of DB in postgres container;
• DB_ADDRESS and DB_PORT is path and port to get DB access (for local development is localhost and 5432);
• DB_USER and DB_PASSWORD are credential to get DB access;

3. Change listening port of recsys service (src/recsys/app.py) on any value, different from 8000 (for example, 8001), because port 8000 is busy by db service. Run the application.
4. Set environment variable BOT_TOKEN for src/tg/app/app.py and run it.

Service is in air!

Useful links:

• How to set up envs in Pycharm