Full automated data pipeline using docker images

Overview

Create postgres tables from CSV files

This first section is only relate to creating tables from CSV files using postgres container alone. Just one of my experiments. If you interest, you can just follow these steps (only if your working environment support bash):

sh scripts/prep.sh

The prep.sh will handle everything for you by doing follwing:

# Start postgres db container
docker-compose -f postgres.yaml up -d
# Sleep to make sure the container is fully up running
sleep 3 

# I have problem with mouting csv files via docker compose, so here we go
# Copy csv and setup.sql to create required tables
docker cp ./csv/ my_postgres:
docker cp ./scripts/setup.sql my_postgres:setup.sql

# Execute the script in postgres db
docker exec -it my_postgres psql -p5432 --dbname=postgres --username=postgres --file=setup.sql 

# Shutdown the container
docker-compose -f postgres.yaml down --remove-orphans

I had problem with mount volumn that I can't mount the files under csv and scripts folders. Which still can be improved with a proper mount. But let's skip it for now to save time.

Initial Setup/Start Airflow container

This section will use a separate docker-compose.yaml than the above test. It will be relate due to the fact that we want to use airflow to schedule the tasks above (create table and load data). To do so, do the following. First prepare folders. You can call a new folder specifically for this if you want.

# (optional) mkdir airflow && cd airflow
mkdir ./dags ./logs ./plugins

Next we need the airflow docker-compose.yaml in our airflow directory

curl -O https://airflow.apache.org/docs/apache-airflow/stable/docker-compose.yaml

Next make sure we will have a proper permission to initial Airflow

.env ">
echo -e "AIRFLOW_UID=$(id -u)\nAIRFLOW_GID=0" > .env

Then we must initial Airflow instance

docker-compose up airflow-init

Wait until the initial finished then (you can use -d to detach if you want)

docker-compose up

Now you will be able to connect to Airflow GUI via http://localhost:8080/

Create Airflow DAG task

First thing, you need to setup connection for postgres database. Go to tab Admin > Connection > +, wow you have to fill details of the connection:

Connection Id: postgres_default
Connection Type: 'Postgres'
Host: 
   
    
Schema: postgres (default)
Login: 
    
     
Password: 
     
      
Port: 
      

      
     
    
   

Click "Test" button to check your connection then save. Now click at the Airflow icon to return to home page. You should see task name "create_postgres_tables". Try to run by clicking start button select "Trigger DAG".

You might also like...
In this project, ETL pipeline is build on data warehouse hosted on AWS Redshift.

ETL Pipeline for AWS Project Description In this project, ETL pipeline is build on data warehouse hosted on AWS Redshift. The data is loaded from S3 t

Demonstrate a Dataflow pipeline that saves data from an API into BigQuery table

Overview dataflow-mvp provides a basic example pipeline that pulls data from an API and writes it to a BigQuery table using GCP's Dataflow (i.e., Apac

X-news - Pipeline data use scrapy, kafka, spark streaming, spark ML and elasticsearch, Kibana

X-news - Pipeline data use scrapy, kafka, spark streaming, spark ML and elasticsearch, Kibana

An ETL Pipeline of a large data set from a fictitious music streaming service named Sparkify.

An ETL Pipeline of a large data set from a fictitious music streaming service named Sparkify. The ETL process flows from AWS's S3 into staging tables in AWS Redshift.

Mortgage-loan-prediction - Show how to perform advanced Analytics and Machine Learning in Python using a full complement of PyData utilities

Mortgage-loan-prediction - Show how to perform advanced Analytics and Machine Learning in Python using a full complement of PyData utilities. This is aimed at those looking to get into the field of Data Science or those who are already in the field and looking to solve a real-world project with python.

Flenser is a simple, minimal, automated exploratory data analysis tool.

Flenser Have you ever been handed a dataset you've never seen before? Flenser is a simple, minimal, automated exploratory data analysis tool. It runs

Lale is a Python library for semi-automated data science.
Lale is a Python library for semi-automated data science.

Lale is a Python library for semi-automated data science. Lale makes it easy to automatically select algorithms and tune hyperparameters of pipelines that are compatible with scikit-learn, in a type-safe fashion.

Data Competition: automated systems that can detect whether people are not wearing masks or are wearing masks incorrectly
Data Competition: automated systems that can detect whether people are not wearing masks or are wearing masks incorrectly

Table of contents Introduction Dataset Model & Metrics How to Run Quickstart Install Training Evaluation Detection DATA COMPETITION The COVID-19 pande

Pipeline and Dataset helpers for complex algorithm evaluation.

tpcp - Tiny Pipelines for Complex Problems A generic way to build object-oriented datasets and algorithm pipelines and tools to evaluate them pip inst

Releases(airflow-postgres-dag)
Mining the Stack Overflow Developer Survey

Mining the Stack Overflow Developer Survey A prototype data mining application to compare the accuracy of decision tree and random forest regression m

1 Nov 16, 2021
SparseLasso: Sparse Solutions for the Lasso

SparseLasso: Sparse Solutions for the Lasso Introduction SparseLasso provides a Scikit-Learn based estimation of the Lasso with cross-validation tunin

Gabriel Okasa 1 Nov 08, 2021
Tkinter Izhikevich Neuron Model With Python

TKINTER IZHIKEVICH NEURON MODEL WITH PYTHON Hodgkin-Huxley Model It is a mathematical model for the generation and transmission of action potentials i

Rabia KOÇ 8 Jul 16, 2022
Manage large and heterogeneous data spaces on the file system.

signac - simple data management The signac framework helps users manage and scale file-based workflows, facilitating data reuse, sharing, and reproduc

Glotzer Group 109 Dec 14, 2022
PrimaryBid - Transform application Lifecycle Data and Design and ETL pipeline architecture for ingesting data from multiple sources to redshift

Transform application Lifecycle Data and Design and ETL pipeline architecture for ingesting data from multiple sources to redshift This project is composed of two parts: Part1 and Part2

Emmanuel Boateng Sifah 1 Jan 19, 2022
Data processing with Pandas.

Processing-data-with-python This is a simple example showing how to use Pandas to create a dataframe and the processing data with python. The jupyter

1 Jan 23, 2022
Produces a summary CSV report of an Amber Electric customer's energy consumption and cost data.

Amber Electric Usage Summary This is a command line tool that produces a summary CSV report of an Amber Electric customer's energy consumption and cos

Graham Lea 12 May 26, 2022
A utility for functional piping in Python that allows you to access any function in any scope as a partial.

WithPartial Introduction WithPartial is a simple utility for functional piping in Python. The package exposes a context manager (used with with) calle

Michael Milton 1 Oct 26, 2021
DaCe is a parallel programming framework that takes code in Python/NumPy and other programming languages

aCe - Data-Centric Parallel Programming Decoupling domain science from performance optimization. DaCe is a parallel programming framework that takes c

SPCL 330 Dec 30, 2022
The Dash Enterprise App Gallery "Oil & Gas Wells" example

This app is based on the Dash Enterprise App Gallery "Oil & Gas Wells" example. For more information and more apps see: Dash App Gallery See the Dash

Austin Caudill 1 Nov 08, 2021
Python package to transfer data in a fast, reliable, and packetized form.

pySerialTransfer Python package to transfer data in a fast, reliable, and packetized form.

PB2 101 Dec 07, 2022
Data Analytics: Modeling and Studying data relating to climate change and adoption of electric vehicles

Correlation-Study-Climate-Change-EV-Adoption Data Analytics: Modeling and Studying data relating to climate change and adoption of electric vehicles I

Jonathan Feng 1 Jan 03, 2022
PyClustering is a Python, C++ data mining library.

pyclustering is a Python, C++ data mining library (clustering algorithm, oscillatory networks, neural networks). The library provides Python and C++ implementations (C++ pyclustering library) of each

Andrei Novikov 1k Jan 05, 2023
A crude Hy handle on Pandas library

Quickstart Hyenas is a curde Hy handle written on top of Pandas API to allow for more elegant access to data-scientist's powerhouse that is Pandas. In

Peter Výboch 4 Sep 05, 2022
DenseClus is a Python module for clustering mixed type data using UMAP and HDBSCAN

DenseClus is a Python module for clustering mixed type data using UMAP and HDBSCAN. Allowing for both categorical and numerical data, DenseClus makes it possible to incorporate all features in cluste

Amazon Web Services - Labs 53 Dec 08, 2022
PyNHD is a part of HyRiver software stack that is designed to aid in watershed analysis through web services.

A part of HyRiver software stack that provides access to NHD+ V2 data through NLDI and WaterData web services

Taher Chegini 23 Dec 14, 2022
Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Theano

PyMC3 is a Python package for Bayesian statistical modeling and Probabilistic Machine Learning focusing on advanced Markov chain Monte Carlo (MCMC) an

PyMC 7.2k Dec 30, 2022
An Integrated Experimental Platform for time series data anomaly detection.

Curve Sorry to tell contributors and users. We decided to archive the project temporarily due to the employee work plan of collaborators. There are no

Baidu 486 Dec 21, 2022
pyETT: Python library for Eleven VR Table Tennis data

pyETT: Python library for Eleven VR Table Tennis data Documentation Documentation for pyETT is located at https://pyett.readthedocs.io/. Installation

Tharsis Souza 5 Nov 19, 2022