sejalv / voucher-segmenter-airflow

Geek Repo:Geek Repo

Github PK Tool:Github PK Tool

Voucher Segmenter Airflow

Overview

A pipeline & API for voucher selection built with Airflow, Postgres, Flask, and Docker

The task is to create a Voucher Selection API for the country: Peru There are 3 steps that should be done: 0. Conduct data analysis to explore and prepare the data.

  1. Create a data pipeline to generate customer segments, including data cleaning, optimization.
  2. Create a REST API that will expose the most used voucher value for a particular customer segment.

This is a sandbox project to set up an environment with Airflow and Docker in order to schedule and monitor pipelines.

Structure

Containers

docker-compose is used to launch:

  • postgres or voucher-segmenter-airflow_postgres_1: Postgres Database instance
  • airflow or voucher-segmenter-airflow_webserver_1: LocalExecutor Airflow setup
  • api or voucher-segmenter-airflow_api_1: Local API using Flask

Database

  • Version: postgres:9.6
  • Schema: voucher_customer
  • Config: docker-compose.yml

Data pipeline:

Version: Airflow v1.10.9, with Python 3.7 (using puckel/docker-airflow) Config: dags dir, root dir files

Process

  1. Generates voucher_customer.customer_segments table by loading data from customer_segments.sql
  2. Fetches voucher data from the S3 parquet
  3. Cleanses, filters, and maps the voucher data to customer segments.
  4. Updates the voucher_customer.voucher_segments table daily, with the count of vouchers used for a particular segment_type

Final Output

$ docker-compose exec postgres psql -U airflow
psql (9.6.20)
Type "help" for help.

airflow=# select * from voucher_customer.voucher_segments;
 index | min_range | max_range |   segment_name   | voucher_amount | count 
-------+-----------+-----------+------------------+----------------+-------
     0 |       180 |  99999999 | recency_segment  |              0 | 13950
     1 |       180 |  99999999 | recency_segment  |           2640 | 49102
     2 |       180 |  99999999 | recency_segment  |           3520 | 22037
     3 |       180 |  99999999 | recency_segment  |           4400 | 21458
     0 |         0 |         4 | frequent_segment |              0 |  4543
     1 |         0 |         4 | frequent_segment |           2640 | 16496
     2 |         0 |         4 | frequent_segment |           3520 |  7758
     3 |         0 |         4 | frequent_segment |           4400 |  7402
     4 |         5 |        13 | frequent_segment |              0 |   253
     5 |         5 |        13 | frequent_segment |           2640 |  4112
     6 |         5 |        13 | frequent_segment |           3520 |  1374
     7 |         5 |        13 | frequent_segment |           4400 |  1272
     8 |        14 |        37 | frequent_segment |              0 |  1501
     9 |        14 |        37 | frequent_segment |           2640 | 11813
    10 |        14 |        37 | frequent_segment |           3520 |  4391
    11 |        14 |        37 | frequent_segment |           4400 |  4225
    12 |        38 |  99999999 | frequent_segment |              0 |  7653
    13 |        38 |  99999999 | frequent_segment |           2640 | 16681
    14 |        38 |  99999999 | frequent_segment |           3520 |  8514
    15 |        38 |  99999999 | frequent_segment |           4400 |  8559
(20 rows)

API

The Flask API (http://localhost:5000) which queries from voucher_customer.voucher_segments Config: api dir, docker-compose.yml

Setup

Prerequisites

To run this locally, you would need a few things:

  • Docker installed
  • S3 bucket and access details (Dockerfile, .env)

Clone respository

$ git clone https://github.com/sejalv/voucher-segmenter-airflow.git

Move into new directory

$ cd voucher-segmenter-airflow

Generate a fernet key for your environment and pipe into env file

$ echo $(echo "FERNET_KEY='")$(openssl rand -base64 32)$(echo "'") >> airflow.env

Execution

Launch docker containers in detached session

$ docker-compose up --build

In a new tab, initialise database for webserver

$ docker-compose exec webserver airflow initdb

Trigger pipeline

Trigger from command line

$ docker-compose exec webserver airflow trigger_dag voucher_segmenter

Or trigger from web UI

  • Open browser to http://127.0.0.1:8080/

Call API

$ curl -X GET -H "Content-type: application/json" -d '{"customer_id": 123, "country_code": "Peru", "last_order_ts": "2018-05-03 00:00:00", "first_order_ts": "2017-05-03 00:00:00", "total_orders": 15, "segment_name": "recency_segment"}' "http://localhost:5000/voucher_amount"

{"voucher_amount":[2640.0]}

Test

(TBD: Config error)

$ docker-compose exec webserver python -m unittest -v

End

Close docker session

$ docker-compose down

Caveats

Future Enhancements

  • Airflow tasks run on same machine as scheduler
  • Parallelisation of tasks (workers) possible, use of CeleryExecutor
  • Breaking down of utility functions into tasks for the pipeline, in prepare_data.py
  • ORM and security in Flask API
ezoic increase your site revenue

About


Languages

Language:Python 94.5%Language:Dockerfile 5.5%