How to automate tasks with Luigi and an AWS EC2 instance.
The idea was to create an assistant that would work in an AWS EC2 instance. This assistant would allow me to easily automate tasks that will be useful for me.
As an example I use this assistant to create reports about my personal finances and to help me book cheap flights.
I am a huge fan of automation and I wanted a bot that worked for me.
The idea was to create an assistant that allowed me to avoid repetitive tasks. It was a must that new tasks could be added easily to the assistant.
I wanted to use a cloud provider so the first thing I did was to create an AWS EC2 instance (more info).
I started working with Airflow (more info) because it has more features. But I didn't need a lot of the features that Airflow offered and it was something more complex that what I wanted.
So I switched to Luigi and a created a method that made really easy to integrate new tasks.
Since 2010 I have been recording all expenses and incomes. For the last years I have been using Money Lover to do so.
This app has a way to export the data as an Excel file. But the problem is that it does not have the format I want.
So the first task is to clean that data (
With the data cleaned the idea is to create a custom html report using Jinja2 templates.
In order to make it more flexible there are two tasks:
Extract infothat creates a
yamlwith the info
Create Reportthat creates the
htmlreport with the
With this approach is easy to modify the data or the template without needing to modify the other.
So the pipeline is as follows:
As you can see I use dropbox for storing all data this way is easy for me to access or modify it.
Here you can see some of the pages the report have:
And of course the report is responsive:
I regularly travel to Italy and I want to do it as cheap as possible. So I thought the best way to do it was to let the assistant track all the prices between the airports I wanted and store that data. Then I could use Data Analysis or Machine Learning to minimize the price I pay for the flights.
To do so I used the Rapid API Flight Search app. This API allowed me to query some pairs of airports daily for free. So right now the assistant is storing a year of data each day so that I can see prices changes and which company offers cheaper flights each day.
As you can see Rapid API is getting their data from Skyscanner.
A sample of the data:
The assistant is connected to slack so that is able to send messages of each task it completes. It will also give information about any task failure that might happen.
The idea is to extend the slack integration by creating a chatbot.
This chatbot would allow me to: