This tutorial was produced as a suplementary material for the short course "Computação Urbana da Teoria à Prática: Fundamentos, Aplicações e Desafios" presented at the SBRC'19. The aim is to familiarize the audience with the Urban Computing framework by usan urban mobility data to identify and analyse mobility flows.
You may use a GIT client to download this tutorial from Github. Windows OS usually do not come with GIT out of the box, so you may need to install it. Also, if you do not have Python 3 on your machine you have to install.
Some Python 3 installations may not come with support for virtual environments. Thus, you may need to install some libs:
sudo apt-get install python3.6-dev python3-venv
Download the tutorial from Github using GIT.
git clone https://github.com/diegopso/hybrid-urban-routing-tutorial-sbrc.git
Create venv:
python3 -m venv workspace
source workspace/bin/activate
Instal Jupyter with pip:
pip install --upgrade pip
pip install --upgrade ipython jupyter
Install dependencies (you may use setup.py alternativelly):
cd hybrid-urban-routing-tutorial-sbrc
pip install .
Configure API Keys:
Copy the file .env.example to .env and fill the required keys.
cp .env.example .env
nano .env
A sample file containig API Keys for use will be available for the tutorial at the hosting event. However the keys will be invalidated after its occurrence. To access this file use the following URL: https://www.dropbox.com/s/mbbvmai277giegd/env.txt?dl=0.
To create API Keys you have to visit every provider's website:
Start the notebook in the tutorial directory:
jupyter notebook