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CSC494

Disclaimer

The endpoints being queried in this project, as well as any usages of the data collected, commercial or otherwise, have been permitted as per City of Toronto's open data license at https://www.toronto.ca/city-government/data-research-maps/open-data/open-data-licence/

Overview

The project currently has 3 workflows, as illustrated under .github/workflows:

  1. cut_branch.yml: This workflow cuts a daily branch where the data collection will occur.
  2. fetch_data.yml: This workflow queries data about uoft bike stations and saves them into 2 places: a Postgres database on the cloud - currently on ElephantSQL - and as individual CSV files which are pushed onto the daily branch.
  3. clean_csv.yml: This workflow collects the above individual CSV files on a daily basis, combines them into a single CSV named as combined_daily_branch_${date_in_EST} and removes the individual files afterwards, then pushes the combined CSV file onto the daily branch, then merges the daily branch into main and deletes the daily branch afterwards. The combined CSV is saved under /collected_data.

cut_branch.yml is run on 04:23. fetch_data.yml is run with a 5 minute segment, between minutes 10-59, on hours 08:00 to 10:00 and 16:00 to 18:00. clean_csv.yml is run on 22:17. All times here are in EST - GitHub Actions currently only accepts UTC for their CRON, so the times in the actual workflow files are in UTC.

Development

Simple docker app with a NodeJS container and a PostgreSQL container. Use VSCode with dev containers and docker plugin. Recommend Rainbow CSV for highlighting csv files.

To start development, run docker compose build nodejs-app then docker compose up -d.

NodeJS

  1. Attach to the Node container
  2. Open the /app folder
  3. The image has npm and node installed, so you can just run for instance node index.js

PostgreSQL

  1. Attach to the PostgreSQL container
  2. Open the /mucp folder (TBD: Better starter location?)
  3. Currently this folder contains everything, including ridership data of all 12 months in 2022 and the first 3 months of 2023; load.sql for loading the csv files into Postgres and cleaning the resulting table(s), and query.sql to query the tables for analysis. load.sql is automatically run on container start up.
  4. cd into mucp.
  5. Run psql -U postgres to start the psql console.
  6. Run \c mucp to connect to the mucp database (can skip if don't care about organization)
  7. Run \i [sql file] to execute a .sql file.

Note: git is currently not loaded in this container, but shouldn't be a problem as all the setup are ready.

Connecting NodeJS to PostgreSQL

Because the containers already live under the same network (as it is by default), connecting the two just requires the correct configuration. In our case, it'll be

const client = new Client({
  user: "postgres",
  host: "postgres-db",
  database: "mucp",
  password: "password",
  port: "5432",
});

with Client being imported from pg.

If you'd like to connect to the ElephantSQL database instead, the configs are in project secrets, and you can also ask Jerry.